diff --git a/.gitignore b/.gitignore index c3c431c8..7547fecf 100644 --- a/.gitignore +++ b/.gitignore @@ -8,6 +8,8 @@ __pycache__/* # MLflow output /mlruns/* +/examples/jupyter-notebooks/mlruns/* # Jupyter notebook cache files .ipynb_checkpoints/ +/.pytest_cache/ diff --git a/README.md b/README.md index e3d9f5e3..ef64c73a 100644 --- a/README.md +++ b/README.md @@ -55,7 +55,7 @@ With `pip` installed, run the following in the root directory: [Poetry](https://python-poetry.org/). To use, rename `pyproject-poetry.toml` to `pyproject.toml` (overwriting the existing file) and use Poetry as normal. Note that the Poetry build is not actively supported-- if it fails, check that the -dependencies are up to date with the setuptools `pyproject.toml`.)* +dependencies are up-to-date with the setuptools `pyproject.toml`.)* #### System Some graphing code uses cartopy, which requires [GEOS](https://libgeos.org/). To @@ -63,7 +63,7 @@ install on Ubuntu: sudo apt install libgeos-dev -On MacOS, via Homebrew: +On macOS, via Homebrew: brew install geos @@ -100,16 +100,18 @@ with `--no-conda` In order to make sure that data in- and output locations are well-defined, the environment variable `MLFLOW_TRACKING_URI` must be set to the intended data location: -> export MLFLOW_TRACKING_URI="/path/to/data/dir" + export MLFLOW_TRACKING_URI="/path/to/data/dir" in Linux, or -> %env MLFLOW_TRACKING_URI /path/to/data/dir +``` +%env MLFLOW_TRACKING_URI /path/to/data/dir +``` in a Jupyter Notebook, or ``` import os -os.environ['MLFLOW_TRACKING_URI] = '/path/to/data/dir' +os.environ['MLFLOW_TRACKING_URI'] = '/path/to/data/dir' ``` in Python. @@ -161,7 +163,7 @@ MLflow call example: ``` mlflow run . --experiment-name -e train --env-manager=local \ --P exp_id=692154129919725696 -P run_id=c57b36da385e4fc4a967e7790192ecb2 \ +-P run_id= \ -P learning_rate=0/5e-4/15/5e-5/30/5e-6 -P n_epochs=200 -P weight_decay=0.00 -P train_split=0.8 \ -P test_split=0.85 -P model_module_name=models.models1 -P model_cls_name=FullyCNN -P batchsize=4 \ -P transformation_cls_name=SoftPlusTransform -P submodel=transform3 \ @@ -175,7 +177,7 @@ Relevant parameters: * `run_id`: id of the run that generated the forcing data that will be used for training. * `loss_cls_name`: name of the class that defines the loss. This class should be - defined in train/losses.py in order for the script to find it. Currently the + defined in train/losses.py in order for the script to find it. Currently, the main available options are: * `HeteroskedasticGaussianLossV2`: this corresponds to the loss used in the 2021 paper @@ -212,17 +214,16 @@ In this step it is particularly important to set the environment variable `MLFLO in order for the data to be found and stored in a sensible place. One can run the inference step by interactively -running the following project root directory: +running the following in the project root directory: ->python3 -m gz21_ocean_momentum.inference.main --n_splits=40 + python3 -m gz21_ocean_momentum.inference.main --n_splits=40 with `n_splits` being the number of subsets which the dataset is split into for the processing, before being put back together for the final output. This is done in order to avoid memory issues for large datasets. Other useful arguments for this call would be -- `to_experiment`: the name of the mlflow experiment used for this run -n_splits: the number of splits applied to the data -- `batch_size`: the batch size used in running the neural network on the data +- `to_experiment`: the name of the mlflow experiment used for this run (default is "test"). +- `batch_size`: the batch size used in running the neural network on the data. After the script has started running, it will first require diff --git a/examples/jupyter-notebooks/Laure_maps_and_implementation-Copy1.ipynb b/examples/jupyter-notebooks/Laure_maps_and_implementation-Copy1.ipynb deleted file mode 100644 index a4800113..00000000 --- a/examples/jupyter-notebooks/Laure_maps_and_implementation-Copy1.ipynb +++ /dev/null @@ -1,2172 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "fifth-annual", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "env: GOOGLE_APPLICATION_CREDENTIALS=/home/ag7531/access_key.json\n" - ] - } - ], - "source": [ - "import xarray as xr\n", - "from analysis.utils import GlobalPlotter\n", - "import os.path\n", - "import os\n", - "import matplotlib\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import cmocean\n", - "from cartopy.crs import PlateCarree, EqualEarth\n", - "%env GOOGLE_APPLICATION_CREDENTIALS /home/ag7531/access_key.json\n", - "%matplotlib notebook\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "editorial-formula", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], - "source": [ - "path_to_data = '/scratch/ag7531/paper_plots_data'" - ] - }, - { - "cell_type": "markdown", - "id": "dutch-platform", - "metadata": {}, - "source": [ - "This is the class used for map plots. If you just want to change args passed to plots, you don't need to modify this directly, but rather modify the arg lists (see further on)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "grand-highlight", - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import mlflow\n", - "from mlflow.tracking import client\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib import colors\n", - "import matplotlib.animation as animation\n", - "from matplotlib.patches import Rectangle\n", - "import pandas as pd\n", - "from analysis.analysis import TimeSeriesForPoint\n", - "import xarray as xr\n", - "from scipy.ndimage import gaussian_filter\n", - "from data.pangeo_catalog import get_patch, get_whole_data\n", - "from cartopy.crs import PlateCarree, EqualEarth\n", - "\n", - "\n", - "from enum import Enum\n", - "\n", - "CATALOG_URL = 'https://raw.githubusercontent.com/pangeo-data/pangeo-datastore\\\n", - "/master/intake-catalogs/master.yaml'\n", - "\n", - "class GlobalPlotter:\n", - " \"\"\"General class to make plots for global data. Handles masking of\n", - " continental data + showing a band near coastlines.\"\"\"\n", - "\n", - " def __init__(self, margin: int = 2, cbar: bool = True, ice: bool = True):\n", - " self.mask = self._get_global_u_mask()\n", - " self.margin = margin\n", - " self.cbar = cbar\n", - " self.ticks = dict(x=None, y=None)\n", - " self.ice = ice\n", - "\n", - " @property\n", - " def mask(self):\n", - " return self._mask\n", - "\n", - " @mask.setter\n", - " def mask(self, value):\n", - " self._mask = value\n", - "\n", - " @property\n", - " def borders(self):\n", - " return self._borders\n", - "\n", - " @borders.setter\n", - " def borders(self, value):\n", - " self._borders = value\n", - "\n", - " @property\n", - " def margin(self):\n", - " return self._margin\n", - "\n", - " @margin.setter\n", - " def margin(self, margin):\n", - " self._margin = margin\n", - " self.borders = self._get_continent_borders(self.mask, self.margin)\n", - "\n", - " @property\n", - " def x_ticks(self):\n", - " return self.ticks['x']\n", - "\n", - " @x_ticks.setter\n", - " def x_ticks(self, value):\n", - " self.ticks['x'] = value\n", - "\n", - " @property\n", - " def y_ticks(self):\n", - " return self.ticks['y']\n", - "\n", - " @y_ticks.setter\n", - " def y_ticks(self, value):\n", - " self.ticks['y'] = value\n", - "\n", - " def plot(self, u: xr.DataArray = None, projection_cls=PlateCarree,\n", - " lon: float = -100.0, lat: float = None, ax=None, animated=False,\n", - " borders_color='grey', borders_alpha=1.,\n", - " colorbar_label='', **plot_func_kw):\n", - " \"\"\"\n", - " Plots the passed velocity component on a map, using the specified\n", - " projection. Uses the instance's mask to set as nan some values.\n", - " Parameters\n", - " ----------\n", - " u : xr.DataArray\n", - " Velocity array. The default is None.\n", - " projection : Projection\n", - " Projection used for the 2D plot.\n", - " lon : float, optional\n", - " Central longitude. The default is -100.0.\n", - " lat : float, optional\n", - " Central latitude. The default is None.\n", - " Returns\n", - " -------\n", - " None.\n", - " \"\"\"\n", - " fig = plt.figure()\n", - " projection = projection_cls(lon)\n", - " if ax is None:\n", - " ax = plt.axes(projection=projection)\n", - " plt.rc('axes',facecolor='black')\n", - " plt.rc('axes',edgecolor='k')\n", - " mesh_x, mesh_y = np.meshgrid(u['longitude'], u['latitude'])\n", - " if u is not None:\n", - " extra = self.mask.isel(longitude=slice(0, 10))\n", - " extra['longitude'] = extra['longitude'] + 360\n", - " mask = xr.concat((self.mask, extra), dim='longitude')\n", - " mask = mask.interp({k: u.coords[k] for k in ('longitude',\n", - " 'latitude')})\n", - " u = u * mask\n", - " im = ax.pcolormesh(mesh_x, mesh_y, u.values,\n", - " transform=PlateCarree(),\n", - " animated=animated, **plot_func_kw)\n", - " if self.x_ticks is not None:\n", - " ax.set_xticks(self.x_ticks)\n", - " if self.y_ticks is not None:\n", - " ax.set_yticks(self.y_ticks)\n", - " ax.set_global()\n", - " ax.coastlines()\n", - " # \"Gray-out\" near continental locations\n", - " if self.margin > 0:\n", - " extra = self.borders.isel(longitude=slice(0, 10))\n", - " extra['longitude'] = extra['longitude'] + 360\n", - " borders = xr.concat((self.borders, extra), dim='longitude')\n", - " borders = borders.interp({k: u.coords[k]\n", - " for k in ('longitude', 'latitude')})\n", - " borders_cmap = colors.ListedColormap([borders_color, ])\n", - " ax.pcolormesh(mesh_x, mesh_y, borders, animated=animated,\n", - " transform=PlateCarree(), alpha=borders_alpha,\n", - " cmap=borders_cmap)\n", - "\n", - " # Add locations of ice\n", - " if self.ice:\n", - " ice = self._get_ice_border()\n", - " ice = xr.where(ice, 1., 0.)\n", - " ice = ice.interp({k: u.coords[k] for k in ('longitude',\n", - " 'latitude')})\n", - " ice = xr.where(ice != 0, 1., 0.)\n", - " ice = abs(ice.diff(dim='longitude')) + abs(ice.diff(dim='latitude'))\n", - " ice = xr.where(ice != 0., 1, np.nan)\n", - " ice_cmap = colors.ListedColormap(['black', ])\n", - " ax.pcolormesh(mesh_x, mesh_y, ice, animated=animated,\n", - " transform=PlateCarree(), alpha=0.5,\n", - " cmap=ice_cmap)\n", - " if u is not None and self.cbar:\n", - " cbar = plt.colorbar(im, shrink=0.6)\n", - " cbar.ax.tick_params(length=0)\n", - " if colorbar_label:\n", - " cbar.set_label(colorbar_label)\n", - " cbar.ax.tick_params(length=0, which='both')\n", - " return ax\n", - "\n", - " @staticmethod\n", - " def _get_global_u_mask(factor: int = 4, base_mask: xr.DataArray = None):\n", - " \"\"\"\n", - " Return the global mask of the low-resolution surface velocities for\n", - " plots. While the coarse-grained velocities might be defined on\n", - " continental points due to the coarse-graining procedures, these are\n", - " not shown as we do not use them -- the mask for the forcing is even\n", - " more restrictive, as it removes any point within some margin of the\n", - " velocities mask.\n", - " Parameters\n", - " ----------\n", - " factor : int, optional\n", - " Coarse-graining factor. The default is 4.\n", - " base_mask: xr.DataArray, optional\n", - " # TODO\n", - " Not implemented for now.\n", - " Returns\n", - " -------\n", - " None.\n", - " \"\"\"\n", - " if base_mask is not None:\n", - " mask = base_mask\n", - " else:\n", - " _, grid_info = get_whole_data(CATALOG_URL, 0)\n", - " mask = grid_info['wet']\n", - " mask = mask.coarsen(dict(xt_ocean=factor, yt_ocean=factor))\n", - " mask_ = mask.max()\n", - " mask_ = mask_.where(mask_ > 0.1)\n", - " mask_ = mask_.rename(dict(xt_ocean='longitude', yt_ocean='latitude'))\n", - " return mask_.compute()\n", - "\n", - " @staticmethod\n", - " def _get_ice_border():\n", - " \"\"\"Return an xarray.DataArray that indicates the locations of ice\n", - " in the oceans. \"\"\"\n", - " temperature, _ = get_patch(CATALOG_URL, 1, None, 0,\n", - " 'surface_temp')\n", - " temperature = temperature.rename(dict(xt_ocean='longitude',\n", - " yt_ocean='latitude'))\n", - " temperature = temperature['surface_temp'].isel(time=0)\n", - " ice = xr.where(temperature <= 0., True, False)\n", - " return ice\n", - "\n", - " @staticmethod\n", - " def _get_continent_borders(base_mask: xr.DataArray, margin: int):\n", - " \"\"\"\n", - " Returns a boolean xarray DataArray corresponding to a mask of the\n", - " continents' coasts, which we do not process.\n", - " Hence margin should be set according to the model.\n", - " Parameters\n", - " ----------\n", - " mask : xr.DataArray\n", - " Mask taking value 1 where coarse velocities are defined and used\n", - " as input and nan elsewhere.\n", - " margin : int\n", - " Margin imposed by the model used, i.e. number of points lost on\n", - " one side of a square.\n", - " Returns\n", - " -------\n", - " mask : xr.DataArray\n", - " Boolean DataArray taking value True for continents.\n", - " \"\"\"\n", - " assert margin >= 0, 'The margin parameter should be a non-negative' \\\n", - " ' integer'\n", - " assert base_mask.ndim <= 2, 'Velocity array should have two'\\\n", - " ' dims'\n", - " # Small trick using the guassian filter function\n", - " mask = xr.apply_ufunc(lambda x: gaussian_filter(x, 1., truncate=margin),\n", - " base_mask)\n", - " mask = np.logical_and(np.isnan(mask), ~np.isnan(base_mask))\n", - " mask = mask.where(mask)\n", - " return mask.compute()\n", - "\n", - "\n", - "uv_plotter = GlobalPlotter()\n", - "uv_plotter.margin = 0" - ] - }, - { - "cell_type": "markdown", - "id": "photographic-pickup", - "metadata": {}, - "source": [ - "These functions are used for the implementation plots" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "quality-terrorism", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], - "source": [ - "def plot_implementation_1(ds):\n", - " \"\"\"Plots the figure showing the std of eta for the high-rez, low-rez no param,\n", - " low-rez with param\"\"\"\n", - " func = 'std'\n", - " cmaps = dict(mean=cmocean.cm.delta, std=cmocean.cm.matter)\n", - " args = dict(mean=dict(), std=dict(norm=matplotlib.colors.LogNorm()))\n", - " vmins=dict(mean=-1.96, std=0.5)\n", - " vmaxs=dict(mean=1.96, std=3)\n", - " vmins2=dict(mean=0, std=0.0001)\n", - " extent = (0, 3840, 0, 3840)\n", - "\n", - " fig = plt.figure()\n", - " # Determine limits.\n", - " std_h = getattr(ds['high_rez'], func)(dim='time').std()\n", - " for i, var in enumerate(ds):\n", - " if i > 2:\n", - " break\n", - " plt.subplot(1, 3, i + 1)\n", - " if i > 0:\n", - " im = plt.imshow(getattr(ds[var], func)(dim='time'), cmap=cmaps[func], **args[func], \n", - " vmin=std_h*vmins[func] + vmins2[func],\n", - " vmax=std_h*vmaxs[func], origin='lower',\n", - " extent=extent)\n", - " else:\n", - " im = plt.imshow(getattr(ds[var], func)(dim='time'), cmap=cmaps[func], **args[func],\n", - " vmin=std_h*vmins[func] + vmins2[func],\n", - " vmax=std_h*vmaxs[func], origin='lower',\n", - " extent=extent)\n", - " if i > 0:\n", - " im.axes.set_yticks([])\n", - " if i == 0:\n", - " im.axes.set_xlabel('km')\n", - " im.axes.set_ylabel('km')\n", - " fig.subplots_adjust(right=0.8)\n", - " cbar_ax = fig.add_axes([0.85, 0.3, 0.025, 0.4])\n", - " fig.colorbar(im, cax=cbar_ax, label='m')\n", - "\n", - "def plot_implementation_2(ds):\n", - " \"\"\"Plot the kE time series\"\"\"\n", - " plt.figure()\n", - " for var_name, var_values in ds.items():\n", - " plt.plot(var_values.mean(dim=('x', 'y')))\n", - " plt.ylabel(r'$m^2/s^2$')\n", - " plt.xlabel('day')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "critical-filter", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['corr_X_control', 'eta_std_l', 'mse1pct', 'mse_control', 'online_kE', 'r2_1pctC02_month', 'r2_control_month', 'rel_diff_forcing', 'rel_diff_uvnorm', 'variance_forcing_control', 'variance_forcing_control_pred', 'velocities_std_control', 'z_r2_control_month_x', 'z_r2_control_month_y']\n" - ] - } - ], - "source": [ - "print(sorted(os.listdir(path_to_data)))" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "refined-maine", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Plot n°0: corr_X_control\n", - "Plot n°1: eta_std_l\n", - "Plot n°2: mse1pct\n", - "Plot n°3: mse_control\n", - "Plot n°4: online_kE\n", - "Plot n°5: r2_1pctC02_month\n", - "Plot n°6: r2_control_month\n", - "Plot n°7: rel_diff_forcing\n", - "Plot n°8: rel_diff_uvnorm\n", - "Plot n°9: variance_forcing_control\n", - "Plot n°10: variance_forcing_control_pred\n", - "Plot n°11: velocities_std_control\n", - "Plot n°12: z_r2_control_month_x\n", - "Plot n°13: z_r2_control_month_y\n" - ] - } - ], - "source": [ - "# These define the plot args used for each plot in the list above, in the same order\n", - "plot_args=[\n", - " dict(vmin=0.7, vmax=1., lon=0., cmap=cmocean.cm.diff),\n", - " dict(),\n", - " dict(vmin=0.01, vmax=10, lon=0., cmap=cmocean.cm.thermal,\n", - " colorbar_label=r'$1e^{-14}m^2/s^4$', norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=0.01, vmax=10, cmap=cmocean.cm.thermal, lon=0., \n", - " colorbar_label=r'$1e^{-14}m^2s^{-4}$', norm=matplotlib.colors.LogNorm()),\n", - " dict(),\n", - " dict(vmin=0.5, vmax=1, cmap=cmocean.cm.diff, lon=0., norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=0.5, vmax=1, cmap=cmocean.cm.diff, lon=0., norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=-50, vmax=50, lon=0., cmap=cmocean.cm.diff, colorbar_label='%'),\n", - " dict(vmin=-50, vmax=50, lon=0., cmap=cmocean.cm.diff, colorbar_label='%'),\n", - " dict(vmin=0.01, vmax=10, cmap=cmocean.cm.thermal, lon=0., colorbar_label=r'$1e^{-14}m^2/s^4$',\n", - " norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=0.01, vmax=10, lon=0., cmap=cmocean.cm.thermal, colorbar_label=r'$1e^{-14}m^2/s^4$', \n", - " norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=0.01, vmax=1, lon=0., cmap=cmocean.cm.thermal,\n", - " colorbar_label=r'$m/s$', norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=0.5, vmax=1, cmap=cmocean.cm.diff, lon=0., norm=matplotlib.colors.LogNorm()),\n", - " dict(vmin=0.5, vmax=1, cmap=cmocean.cm.diff, lon=0., norm=matplotlib.colors.LogNorm())\n", - "]\n", - "\n", - "# These define the functions called for plotting\n", - "plot_funcs = [\n", - " uv_plotter.plot,\n", - " plot_implementation_1,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " plot_implementation_2,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot,\n", - " uv_plotter.plot\n", - "]\n", - "\n", - "list_of_plots = list(zip(sorted(os.listdir(path_to_data)), plot_funcs, plot_args))\n", - "\n", - "# If you want to change the projection cls for all plots use this\n", - "projection_cls = EqualEarth\n", - "for i, args in enumerate(plot_args):\n", - " # This only applies to map plots\n", - " if list_of_plots[i][1] == uv_plotter.plot:\n", - " args['projection_cls'] = projection_cls\n", - "\n", - "\n", - "for i, plot in enumerate(list_of_plots):\n", - " print(f'Plot n°{i}: {plot[0]}')" - ] - }, - { - "cell_type": "markdown", - "id": "bright-manchester", - "metadata": {}, - "source": [ - "Specify which plot to do" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "constitutional-quantum", - "metadata": {}, - "outputs": [], - "source": [ - "choice = 1" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "raising-costa", - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":25: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " im = plt.imshow(getattr(ds[var], func)(dim='time'), cmap=cmaps[func], **args[func],\n", - ":20: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " im = plt.imshow(getattr(ds[var], func)(dim='time'), cmap=cmaps[func], **args[func],\n", - ":20: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " im = plt.imshow(getattr(ds[var], func)(dim='time'), cmap=cmaps[func], **args[func],\n" - ] - } - ], - "source": [ - "if choice == 14:\n", - " ds1 = xr.open_zarr(os.path.join(path_to_data, list_of_plots[5][0]))\n", - " ds2 = xr.open_zarr(os.path.join(path_to_data, list_of_plots[6][0]))\n", - " ds1 = ds1.rename(dict(r2_1pctC02_month='r2_control_month'))\n", - " ds = ds1 - ds2\n", - " func = list_of_plots[7][1]\n", - " plot_args = list_of_plots[7][2]\n", - " plot_args['vmin'] = -0.1\n", - " plot_args['vmax'] = 0.1\n", - "else:\n", - " ds = xr.open_zarr(os.path.join(path_to_data, list_of_plots[choice][0]))\n", - " func = list_of_plots[choice][1]\n", - " plot_args = list_of_plots[choice][2]\n", - "\n", - "# For the kE time series re-order as in paper\n", - "if choice == 4:\n", - " ds = ds[['low_rez_0', 'low_rez_1', 'low_rez_2', 'low_rez_3', 'high_rez']]\n", - "\n", - "# Change the sign for dataset 6, as I changed the sign by mistake when saving...\n", - "if choice == 7:\n", - " ds = -ds\n", - "\n", - "#plt.style.use(\"seaborn-dark\")\n", - "uv_plotter.margin = 10\n", - "if func == uv_plotter.plot:\n", - " print('ok')\n", - " for key in ds:\n", - " print(key)\n", - " ax = func(ds[key], borders_color='black', **plot_args)\n", - " ax.coastlines(color='white')\n", - "else:\n", - " func(ds.load())" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "brave-zambia", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], - "source": [ - "plt.savefig(list_of_plots[choice][0] + '_Laure.jpg', dpi=400)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "joint-failing", - "metadata": {}, - "outputs": [], - "source": [ - "plt.savefig('r2_control_month_y.jpg', dpi=400)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "funded-lunch", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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-       "    low_rez_1  (time, y, x) float64 0.002879 0.0006572 ... 0.01557 0.01781\n",
-       "    low_rez_2  (time, y, x) float64 0.003269 -0.0004145 ... -0.2851 -0.2859\n",
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" - ], - "text/plain": [ - "\n", - "Dimensions: (time: 3599, x: 96, y: 96)\n", - "Coordinates:\n", - " * time (time) float64 8.584e+04 1.722e+05 ... 3.107e+08 3.108e+08\n", - " * x (x) float64 2e+04 6e+04 1e+05 ... 3.74e+06 3.78e+06 3.82e+06\n", - " * y (y) float64 2e+04 6e+04 1e+05 ... 3.74e+06 3.78e+06 3.82e+06\n", - "Data variables:\n", - " high_rez (y, x, time) float64 -0.02526 -0.0269 -0.02708 ... 0.1493 0.2022\n", - " low_rez_0 (time, y, x) float64 0.004493 0.002024 ... 0.1798 0.1783\n", - " low_rez_1 (time, y, x) float64 0.002879 0.0006572 ... 0.01557 0.01781\n", - " low_rez_2 (time, y, x) float64 0.003269 -0.0004145 ... -0.2851 -0.2859\n", - " low_rez_3 (time, y, x) float64 0.005626 0.002861 ... -0.4476 -0.4495" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ds" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "protecting-radius", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/jupyter-notebooks/README.md b/examples/jupyter-notebooks/README.md index 70020561..bd8d5678 100644 --- a/examples/jupyter-notebooks/README.md +++ b/examples/jupyter-notebooks/README.md @@ -1,10 +1,36 @@ # Jupyter notebooks +[gz21-paper-code-zenodo]: https://zenodo.org/record/5076046#.ZF4ulezMLy8 +[gz21-paper-agupubs]: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021MS002534 These Jupyter notebooks were created & used during original development of the -code and associated paper. They may not function properly, but provide example -usage and applications. - -See the main repository readme for more notes, links to that paper etc. +code and associated paper: [Arthur P. Guillaumin, Laure Zanna (2021). +Stochastic-deep learning parameterization of ocean momentum +forcing][gz21-paper-agupubs]. The exact version of the code used to produce said +paper can be found on [Zenodo][gz21-paper-code-zenodo]. ## 2021 paper figures -The `generate-paper-figure-X.ipynb` notebooks were used to generate the stated -number figure in the 2021 paper. +There are several notebooks which were used to generate the figures in the 2021 paper. + +The data for `generate-paper-figure-1.ipynb` can be generated by running + +``` +mlflow run . --experiment-name --env-manager=local \ +-P lat_min=-80 -P lat_max=80 -P long_min=-280 -P long_max=80 \ +-P factor=4 \ +-P CO2=1 -P global=0 \ +-P ntimes=4000 \ +-P chunk_size=1 +``` +. The notebook generates figure 1b. + +For `generate-paper-figure-6.ipynb`, which generates figure 6b, +the same call has to be run with again with `CO2=1`. +The notebook is then asking for the data set with `CO2=0` first and the one with `CO2=1` second. + +`test-global-control.ipynb` generates figures 4, 5 and 7, as well as D4 and D5. For this, the inference step with +the trained neural network has to be run both on the data with `CO2=0` and with `CO2=1`, and then the notebook needs to +be run once with each set. The paper figures referring to _piControl_ are those with `CO2=0` (the control simulation +with pre-industrial CO2 levels), and the figures referring to _1pctCO2_ are those with `CO2=1` (a 1% increase per +year in CO2 levels for the first 70 years, after which they remain constant). +The notebook needs to be handed the experiment and run ID of the inference run, which is linked to the data and training +runs through `params.data_run_id` (run ID of data run) and `params.model_run_id` (run ID of training run), +respectively. \ No newline at end of file diff --git a/examples/jupyter-notebooks/experiment-assorted-01.ipynb b/examples/jupyter-notebooks/experiment-assorted-01.ipynb deleted file mode 100644 index 3214bc3d..00000000 --- a/examples/jupyter-notebooks/experiment-assorted-01.ipynb +++ /dev/null @@ -1,10865 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/intake/source/discovery.py:285: UserWarning: Plugin name collision for \"netcdf\" from\n", - " /home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/intake_iris/netcdf.py\n", - "and\n", - " /home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/intake_xarray/netcdf.py\n", - "Keeping plugin from first location.\n", - " % (plugin_name, orig_path, new_path))\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - } - ], - "source": [ - "import mlflow\n", - "from mlflow.tracking import client\n", - "import xarray as xr\n", - "import numpy as np\n", - "import dask.array as da\n", - "import matplotlib.pyplot as plt\n", - "from analysis.utils import select_experiment, select_run, plot_dataset, GlobalPlotter, anomalies\n", - "from data.pangeo_catalog import get_whole_data\n", - "from data.xrtransforms import SeasonalStdizer, TargetedTransform, ScalingTransform\n", - "from dask.diagnostics import ProgressBar\n", - "from models.submodels import transform3\n", - "\n", - "import cartopy.crs as ccrs\n", - "import cmocean\n", - "\n", - "cmap = cmocean.cm.balance\n", - "cmap_balance = cmocean.cm.balance\n", - "cmap_balance_r=cmocean.cm.balance_r\n", - "\n", - "cmap_amp = cmocean.cm.amp\n", - "\n", - "plt.rcParams[\"figure.figsize\"] = (4, 4 / 1.618)\n", - "\n", - "uv_plotter = GlobalPlotter() \n", - "uv_plotter.x_ticks = np.arange(-150., 151., 50)\n", - "uv_plotter.y_ticks = np.arange(-80., 81., 20)\n", - "\n", - "\n", - "%matplotlib notebook\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - } - ], - "source": [ - "CATALOG_URL = 'https://raw.githubusercontent.com/pangeo-data/pangeo-datastore\\\n", - "/master/intake-catalogs/master.yaml'\n", - "data = get_whole_data(CATALOG_URL, 0)\n", - "grid_info = data[1]\n", - "# mask = grid_info['wet'].coarsen(dict(xt_ocean=4, yt_ocean=4))\n", - "# mask_ = mask.max()\n", - "# mask_ = mask_.where(mask_ > 0.1)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6 : multiregion\n", - "17 : meeting22july\n", - "15 : datacm21\n", - "21 : modelsv1\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "2 : training\n", - "4 : default\n", - "7 : Unet\n", - "18 : forcing-data-global\n", - "12 : test\n", - "9 : forcingdata1pct\n", - "5 : regionsfortraining\n", - "20 : test_global\n", - "8 : arctan\n", - "16 : meeting15july\n", - "13 : forcingdatav2\n", - "Select the id of an experiment: 4\n", - " run_id experiment_id status \\\n", - "0 9fa14fcb81054084b45634770278789b 4 RUNNING \n", - "1 08d1c3445ffe4de2b50944cab1220140 4 RUNNING \n", - "2 23cac34c4c654189adb5011067725ee1 4 RUNNING \n", - "3 4340ea02b2d74f1db37da26dcb04197f 4 FINISHED \n", - "4 dfc61b690a3e4831bddd709fb91f42ed 4 RUNNING \n", - "5 b730ea7738a743d88d90a469eae72970 4 RUNNING \n", - "6 ab4d237496e6450383d74ed2da243c22 4 RUNNING \n", - "7 1687a9a7d1f74866a9803897226b0b19 4 FINISHED \n", - "8 8b70fb93ea484452913f61b1ddad373f 4 RUNNING \n", - "9 b2f3efd050df4016b19ecead1d89f7cc 4 FINISHED \n", - "10 faf3ebb169de43bd83b3f5cc80d74009 4 FINISHED \n", - "\n", - " start_time params.CO2 params.factor params.submodel \n", - "0 2021-01-18 07:34:39.706000+00:00 0 4 None \n", - "1 2021-01-18 06:50:11.871000+00:00 0 4 None \n", - "2 2021-01-17 06:57:38.764000+00:00 0 4 None \n", - "3 2021-01-17 05:54:19.310000+00:00 0 4 None \n", - "4 2021-01-17 04:44:59.960000+00:00 0 4 None \n", - "5 2021-01-17 04:34:34.173000+00:00 0 4 None \n", - "6 2021-01-17 03:23:18.345000+00:00 0 4 None \n", - "7 2021-01-16 22:07:01.681000+00:00 0 4 None \n", - "8 2021-01-16 22:01:43.112000+00:00 0 4 None \n", - "9 2021-01-16 21:58:09.899000+00:00 0 4 None \n", - "10 2021-01-16 21:43:39.021000+00:00 0 4 None \n", - "Run id?3\n", - "Data path: /scratch/ag7531/mlruns/19/743777154cb745cf8a4272dcbd3fa189/artifacts/forcing\n" - ] - } - ], - "source": [ - "test_exp_name = select_experiment()\n", - "test_exp = mlflow.get_experiment_by_name(test_exp_name)\n", - "test_exp_id = test_exp.experiment_id\n", - "run = select_run(experiment_ids=test_exp_id, cols=['status', 'start_time', 'params.CO2', 'params.factor',\n", - " 'params.submodel'],\n", - " merge=[('data-global', 'params.data_run_id', 'run_id'),\n", - " ('modelsv1', 'params.model_run_id', 'run_id')])\n", - "client_ = client.MlflowClient()\n", - "data_file_name = client_.download_artifacts(run['params.data_run_id'], 'forcing')\n", - "print('Data path:', data_file_name)\n", - "data = xr.open_zarr(data_file_name)\n", - "data = data.rename({'xu_ocean': 'longitude', 'yu_ocean': 'latitude'})\n", - "data = data * 1e7\n", - "pred_file_name = client_.download_artifacts(run.run_id, 'test_output_0')\n", - "pred = xr.open_zarr(pred_file_name)\n", - "data = data.sel(time=slice(pred.time[0], pred.time[-1])).sel(latitude=slice(pred.latitude[0], pred.latitude[-1]))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "lon = slice(None, None, 1)\n", - "lat= slice(-80, 80, 1)\n", - "time_slice = slice(None, None, 1)\n", - "\n", - "p0 = pred['0'].sel(longitude=lon, latitude=lat).isel(time=time_slice)\n", - "p1 = pred['1'].sel(longitude=lon, latitude=lat).isel(time=time_slice)\n", - "p0 = np.exp(p0) / (np.exp(p0) + np.exp(p1))\n", - "p1 = 1 - p0\n", - "# Means\n", - "mu0 = pred['4'].sel(longitude=lon, latitude=lat).isel(time=time_slice)\n", - "mu1 = pred['8'].sel(longitude=lon, latitude=lat).isel(time=time_slice)\n", - "true = data['S_x'].sel(longitude=lon, latitude=lat).isel(time=time_slice)\n", - "# precisions\n", - "beta0 = pred['6'].sel(longitude=lon, latitude=lat).isel(time=time_slice)\n", - "beta1 = pred['10'].sel(longitude=lon, latitude=lat).isel(time=time_slice)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def apply_complete_mask(array):\n", - " mask = uv_plotter.borders\n", - " mask2 = uv_plotter.mask\n", - " mask = mask.interp({k: array.coords[k] for k in ['longitude', 'latitude']})\n", - " mask2 = mask2.interp({k: array.coords[k] for k in ['longitude', 'latitude']})\n", - " array = array.where(np.isnan(mask) & (~np.isnan(mask2)))\n", - " array = array.sel(latitude=slice(pred['latitude'][0], pred['latitude'][-1]))\n", - " return array" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Time series analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; 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We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - 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" return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "lon = -129\n", - "lat= -55\n", - "\n", - "p0_ = p0.sel(longitude=lon, latitude=lat, method='nearest')\n", - "mu0_ = mu0.sel(longitude=lon, latitude=lat, method='nearest')\n", - "mu1_ = mu1.sel(longitude=lon, latitude=lat, method='nearest')\n", - "beta0_ = beta0.sel(longitude=lon, latitude=lat, method='nearest')\n", - "beta1_ = beta1.sel(longitude=lon, latitude=lat, method='nearest')\n", - "true_ = true.sel(longitude=lon, latitude=lat, method='nearest')\n", - "\n", - "plt.figure()\n", - "plt.plot(p0_)\n", - "plt.plot(true_, '-x')\n", - "plt.plot(mu0_, 'r')\n", - "plt.plot(mu1_, 'k')\n", - "plt.plot(mu0_ -1.96 * 1 / beta0_, '--r')\n", - "plt.plot(mu0_ + 1.96 * 1 / beta0_, '--r')\n", - "plt.plot(mu1_ - 1.96 * 1 / beta1_, '--k')\n", - "plt.plot(mu1_ + 1.96 * 1 / beta1_, '--k')" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "time = 796\n", - "n_samples = 1000000\n", - "sel = np.random.rand(n_samples) > float(p0_.isel(time=time))\n", - "sel = np.arange(n_samples) + sel * n_samples\n", - "samples0 = np.random.randn(n_samples) / float(beta0_.isel(time=time)) + float(mu0_.isel(time=time))\n", - "samples1 = np.random.randn(n_samples) / float(beta1_.isel(time=time)) + float(mu1_.isel(time=time))\n", - "samples = np.concatenate((samples0, samples1))\n", - "final_samples = samples[sel]" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21.315623418120033\n" - ] - } - ], - "source": [ - "plt.figure()\n", - "print(float(true_.isel(time=time)))\n", - "_ = plt.hist(final_samples, bins=200)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Global distribution of true and simulated forcing" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We assess the goodness of fit" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Likelihood map" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "from scipy.stats import norm" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def pdf(x, p0, mu0, beta0, mu1, beta1):\n", - " return p0 * norm.pdf((x - mu0) * beta0) + (1 - p0) * norm.pdf((x - mu1) * beta1)\n", - "\n", - "lkh = pdf(true, p0, mu0, beta0, mu1, beta1)" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plt.figure()\n", - "plt.imshow(lkh.mean(dim='time'), origin='lower', vmin=0, vmax=0.5)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Mean likelihood" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[################# ] | 42% Completed | 14.4s\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mlat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m40\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m40\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mProgressBar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmean_lkh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mapply_complete_mask\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlkh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlatitude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m~/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/xarray/core/dataarray.py\u001b[0m in \u001b[0;36mcompute\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 838\u001b[0m \"\"\"\n\u001b[1;32m 839\u001b[0m \u001b[0mnew\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 840\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mnew\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 841\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 842\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpersist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;34m\"DataArray\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - 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"\u001b[0;32m~/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/threaded.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(dsk, result, cache, num_workers, pool, **kwargs)\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[0mget_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_thread_get_id\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 80\u001b[0m \u001b[0mpack_exception\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpack_exception\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 81\u001b[0;31m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 82\u001b[0m )\n\u001b[1;32m 83\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/local.py\u001b[0m in \u001b[0;36mget_async\u001b[0;34m(apply_async, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, **kwargs)\u001b[0m\n\u001b[1;32m 473\u001b[0m \u001b[0;31m# Main loop, wait on tasks to finish, insert new ones\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 474\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"waiting\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"ready\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"running\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 475\u001b[0;31m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mres_info\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfailed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mqueue_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mqueue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 476\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfailed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 477\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mres_info\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/local.py\u001b[0m in \u001b[0;36mqueue_get\u001b[0;34m(q)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mqueue_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 135\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/queue.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, block, timeout)\u001b[0m\n\u001b[1;32m 168\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 169\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_qsize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 170\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnot_empty\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 171\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 172\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"'timeout' must be a non-negative number\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/threading.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 294\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# restore state no matter what (e.g., KeyboardInterrupt)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 295\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 296\u001b[0;31m \u001b[0mwaiter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0macquire\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 297\u001b[0m \u001b[0mgotit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 298\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "lat = slice(-40, 40)\n", - "with ProgressBar():\n", - " mean_lkh = apply_complete_mask(lkh.sel(latitude=lat)).mean().compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.DataArray ()>\n",
-       "array(0.24976554)
" - ], - "text/plain": [ - "\n", - "array(0.24976554)" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mean_lkh" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Goodness of fit" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from scipy.stats import norm\n", - "def my_transform(x ,p0, mu0, beta0, mu1, beta1):\n", - " cdf = lambda x: p0 * norm.cdf((x - mu0) * beta0) + (1 - p0) * norm.cdf((x - mu1) * beta1)\n", - " return cdf(x)\n", - "\n", - "v = my_transform(true, p0, mu0, beta0, mu1, beta1)\n", - "v = v.sel(latitude=slice(-40, 40))\n", - "v = apply_complete_mask(v)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.DataArray (time: 1000, latitude: 218, longitude: 900)>\n",
-       "dask.array<where, shape=(1000, 218, 900), dtype=float64, chunksize=(32, 218, 900), chunktype=numpy.ndarray>\n",
-       "Coordinates:\n",
-       "  * latitude   (latitude) float64 -39.8 -39.49 -39.18 ... 39.1 39.41 39.72\n",
-       "  * longitude  (longitude) float64 -279.7 -279.3 -278.9 ... 79.05 79.45 79.85\n",
-       "  * time       (time) object 0181-01-05 12:00:00 ... 0183-10-01 12:00:00
" - ], - "text/plain": [ - "\n", - "dask.array\n", - "Coordinates:\n", - " * latitude (latitude) float64 -39.8 -39.49 -39.18 ... 39.1 39.41 39.72\n", - " * longitude (longitude) float64 -279.7 -279.3 -278.9 ... 79.05 79.45 79.85\n", - " * time (time) object 0181-01-05 12:00:00 ... 0183-10-01 12:00:00" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "v" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. 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" on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure()\n", - "_ = plt.hist(v.values.flatten(), bins=200, density=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(1000, 218, 900)" - ] - }, - "execution_count": 80, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "v.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "quantiles = np.exp(np.linspace(-10, 10, 100)) / (1 + np.exp(np.linspace(-10, 10, 100)))\n", - "\n", - "q = np.nanquantile(v, quantiles)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; 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' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(-4.305352916492039, 4.305352916492273, -18.0, 9.217679542913634)" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from scipy.stats import norm\n", - "s = norm.ppf(q)\n", - "plt.figure()\n", - "plt.plot(norm.ppf(quantiles), s, 'x')\n", - "plt.plot(norm.ppf(quantiles), norm.ppf(quantiles))\n", - "plt.axis([None, None, -18, None])\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Distribution of simulated vs true forcing" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [], - "source": [ - "saved_true = true" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [], - "source": [ - "def apply_complete_mask(array):\n", - " mask = uv_plotter.borders\n", - " mask2 = uv_plotter.mask\n", - " mask = mask.interp({k: array.coords[k] for k in ['longitude', 'latitude']})\n", - " mask2 = mask2.interp({k: array.coords[k] for k in ['longitude', 'latitude']})\n", - " array = array.where(np.isnan(mask) & (~np.isnan(mask2)))\n", - " array = array.sel(latitude=slice(pred['latitude'][0], pred['latitude'][-1]))\n", - " return array\n", - "\n", - "true = apply_complete_mask(saved_true)\n", - "\n", - "epsilon = np.random.randn(*true.shape)\n", - "epsilon2 = np.random.randn(*true.shape)\n", - "bernouilli = np.random.rand(*true.shape) > p0\n", - "simulated = bernouilli * (mu0 + epsilon / beta0) + (1 - bernouilli) * (mu1 + epsilon / beta1)\n", - "\n", - "simulated = apply_complete_mask(simulated)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure()\n", - "_ = plt.hist(true.values.ravel(), log=True, bins=np.arange(-20, 21, 0.5), density=True)\n", - "_ = plt.hist(simulated.values.ravel(), log=True, bins=np.arange(-20, 21, 0.5), density=True)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0.04742587, 0.05024018, 0.05321217, 0.05634954, 0.05966022,\n", - " 0.0631524 , 0.06683447, 0.07071501, 0.0748028 , 0.07910678,\n", - " 0.08363602, 0.08839968, 0.093407 , 0.09866727, 0.10418972,\n", - " 0.10998355, 0.11605783, 0.12242144, 0.12908302, 0.13605089,\n", - " 0.14333299, 0.15093676, 0.1588691 , 0.16713627, 0.17574374,\n", - " 0.1846962 , 0.19399737, 0.20364993, 0.21365546, 0.22401429,\n", - " 0.23472544, 0.24578652, 0.25719365, 0.26894142, 0.28102278,\n", - " 0.29342902, 0.30614975, 0.31917283, 0.33248443, 0.34606901,\n", - " 0.35990936, 0.37398667, 0.38828059, 0.40276933, 0.41742979,\n", - " 0.43223768, 0.44716765, 0.46219351, 0.47728837, 0.49242482,\n", - " 0.50757518, 0.52271163, 0.53780649, 0.55283235, 0.56776232,\n", - " 0.58257021, 0.59723067, 0.61171941, 0.62601333, 0.64009064,\n", - " 0.65393099, 0.66751557, 0.68082717, 0.69385025, 0.70657098,\n", - " 0.71897722, 0.73105858, 0.74280635, 0.75421348, 0.76527456,\n", - " 0.77598571, 0.78634454, 0.79635007, 0.80600263, 0.8153038 ,\n", - " 0.82425626, 0.83286373, 0.8411309 , 0.84906324, 0.85666701,\n", - " 0.86394911, 0.87091698, 0.87757856, 0.88394217, 0.89001645,\n", - " 0.89581028, 0.90133273, 0.906593 , 0.91160032, 0.91636398,\n", - " 0.92089322, 0.9251972 , 0.92928499, 0.93316553, 0.9368476 ,\n", - " 0.94033978, 0.94365046, 0.94678783, 0.94975982, 0.95257413])" - ] - }, - "execution_count": 92, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "quantiles = np.exp(np.linspace(-3, 3, 100)) / (1 + np.exp(np.linspace(-3, 3, 100)))\n", - "quantiles" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 95, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "q_true = np.nanquantile(true.values.ravel(), quantiles)\n", - "q_simu = np.nanquantile(simulated.values.ravel(), quantiles)\n", - "plt.figure()\n", - "plt.plot(q_true, q_simu, 'x')\n", - "plt.plot(q_true, q_true)" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; 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' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/ipykernel_launcher.py:6: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " \n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 249, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import matplotlib\n", - "import cmocean\n", - "mean_pred = p0 * mu0 + p1 * mu1\n", - "plt.figure()\n", - "plt.imshow(np.abs((mean_pred.mean(dim='time') - true.mean(dim='time'))) / true.std(dim='time'), vmin=0.01, vmax=1, norm=matplotlib.colors.LogNorm()\n", - ", origin='lower', cmap=cmocean.cm.delta)\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/jupyter-notebooks/experiment-assorted-02.ipynb b/examples/jupyter-notebooks/experiment-assorted-02.ipynb deleted file mode 100644 index 0e76b184..00000000 --- a/examples/jupyter-notebooks/experiment-assorted-02.ipynb +++ /dev/null @@ -1,22978 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/intake/source/discovery.py:285: UserWarning: Plugin name collision for \"netcdf\" from\n", - " /home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/intake_iris/netcdf.py\n", - "and\n", - " /home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/intake_xarray/netcdf.py\n", - "Keeping plugin from first location.\n", - " % (plugin_name, orig_path, new_path))\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - } - ], - "source": [ - "from analysis.utils import select_experiment, select_run, GlobalPlotter\n", - "import mlflow.tracking\n", - "import xarray as xr\n", - "import cmocean\n", - "import matplotlib.pyplot as plt\n", - "from dask.diagnostics import ProgressBar\n", - "from data.xrtransforms import SeasonalStdizer\n", - "import cartopy\n", - "\n", - "cmap_balance = cmocean.cm.balance\n", - "proj_robinson = cartopy.crs.Robinson\n", - "plotter = GlobalPlotter()\n", - "%matplotlib notebook\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " run_id experiment_id params.CO2 params.factor\n", - "0 359a13e63c9744d18336a7b04380569f 19 1 8\n", - "1 7a60369c9d5b48058366adef1df59728 19 1 7\n", - "2 b85d663b7a1f4e59b09b0d3813cbcab8 19 1 6\n", - "3 0c1de3ebefec40748311812a482a8024 19 1 5\n", - "4 a5049bd09c7e409791944731e5631a10 19 0 8\n", - "5 8f038ef65bdb4667a815029ccf8be3c4 19 0 7\n", - "6 2ebecb60c35642fbb1b60d1f6d33df2d 19 0 6\n", - "7 1dad89889fae43e798d8fbb171627ad0 19 0 5\n", - "8 743777154cb745cf8a4272dcbd3fa189 19 0 4\n", - "9 e5e4964d11aa4be1b70143f2289ccfb0 19 1 10\n", - "10 f4df0dbb52924d649224c4507cd160aa 19 0 10\n", - "11 29399585cd654ffbbac18531738ce984 19 1 10\n", - "12 4feb4b3a4ca340ed9e87b75e9e0706f6 19 0 10\n", - "13 b681d3b8e4e149a7a9ff3193a62be3d4 19 1 4\n", - "14 324a91cc5d64485da4109288a6222090 19 1 4\n", - "15 233450fe93354d86bdae6268cc284832 19 1 4\n", - "16 dfa9c1bbc76249c994beacea5fa70b90 19 1 4\n", - "17 0cc065fcdcea4a2c83c30c8ed66d0b81 19 1 4\n", - "18 5a86a3dbda6c4208949f0a0edbce5356 19 1 4\n", - "19 ffe4682876504d89892f2ae7571a675c 19 1 4\n", - "20 52162444c2b94caa828ef3ccc12693ba 19 1 4\n", - "21 45cf9545dfe24adfb235105781bfe852 19 1 4\n", - "22 6930f1d7501447f7aac4719474b87896 19 1 4\n", - "23 34008ec087d840e6a81407c5d95d12e2 19 1 4\n", - "24 11170a3a29684216ac32a0f54db62ccd 19 0 4\n", - "25 143e8895afd7453ba0aa7b0b02858702 19 1 4\n", - "26 72b9f00c3bfa405e865f3fd6d07edad1 19 0 4\n", - "Run id?8\n" - ] - } - ], - "source": [ - "run = select_run(cols = ['params.CO2', 'params.factor'], experiment_ids=('19',))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "client = mlflow.tracking.MlflowClient()\n", - "data_file = client.download_artifacts(run.run_id, 'forcing')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "data = xr.open_zarr(data_file)\n", - "data = data.rename(dict(xu_ocean='longitude', yu_ocean='latitude'))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset>\n",
-       "Dimensions:    (latitude: 645, longitude: 900, time: 7300)\n",
-       "Coordinates:\n",
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-       "    vsurf      (time, latitude, longitude) float64 dask.array<chunksize=(32, 645, 900), meta=np.ndarray>
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-       "Dimensions:  ()\n",
-       "Data variables:\n",
-       "    S_x      float64 6.252e-06\n",
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-       "    usurf    float64 1.617\n",
-       "    vsurf    float64 1.663
" - ], - "text/plain": [ - "\n", - "Dimensions: ()\n", - "Data variables:\n", - " S_x float64 6.252e-06\n", - " S_y float64 9.148e-06\n", - " usurf float64 1.617\n", - " vsurf float64 1.663" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.isel(time=slice(1, 10)).max().compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "from scipy.stats import norm\n", - "quantiles = data['usurf'].isel(time=slice(0, 10)).quantile(np.arange(1e-5, 1+1e-5, 1e-5)).compute()\n", - "quantiles = np.concatenate((np.array([-5,]), quantiles, np.array([5, ])))\n", - "normal_quantiles = norm.ppf(np.arange(1e-5, 1+1e-5, 1e-5))\n", - "normal_quantiles = np.concatenate((np.array([-20,]), normal_quantiles, np.array([20, ])))\n", - "\n", - "\n", - "def _transform(value):\n", - " value[np.isnan(value)] = 0\n", - " quantile_index = np.searchsorted(quantiles, value) - 1\n", - " v1 = quantiles[quantile_index]\n", - " v2 = quantiles[quantile_index + 1]\n", - " r = (value - v1) / (v2 - v1)\n", - " v1 = normal_quantiles[quantile_index]\n", - " v2 = normal_quantiles[quantile_index + 1]\n", - " result = v1 + r * (v2 - v1)\n", - " result[np.isnan(value)] = np.nan\n", - " return result\n", - "\n", - "from sklearn.preprocessing import QuantileTransformer\n", - "t = QuantileTransformer(output_distribution='normal')\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "100002" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(quantiles)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "new = t.fit_transform(data['usurf'].isel(time=slice(0, 100)).compute().data.reshape((-1, 1)))" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%matplotlib notebook\n", - "plt.figure()\n", - "plt.imshow(new[600, ...], origin='lower', vmin=-1.96, vmax=1.96, cmap=cmocean.cm.delta)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure()\n", - "_ = plt.hist(new.ravel(), bins=np.arange(-10, 10, 0.1), density=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%matplotlib notebook\n", - "plt.figure()\n", - "plt.plot(norm.ppf(np.arange(0.01, 1, 0.01)), quantiles['usurf'])" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plotter.plot(data['vsurf'].isel(time=0), lon=0, projection_cls=proj_robinson, cmap=cmap_balance, vmin=-0.5, vmax=0.5)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'chunks': (32, 609, 900),\n", - " 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n", - " 'filters': None,\n", - " '_FillValue': nan,\n", - " 'dtype': dtype('float64')}" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data['usurf'].encoding" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'chunks': (32, 609, 900),\n", - " 'compressor': Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0),\n", - " 'filters': None,\n", - " '_FillValue': nan,\n", - " 'dtype': dtype('float64')}" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data['S_x'].encoding" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.739256928\n" - ] - } - ], - "source": [ - "from dask.diagnostics import ProgressBar, ResourceProfiler\n", - "import dask\n", - "\n", - "d1 = data.sel(longitude=slice(-40, -20), latitude=slice(30, 50))\n", - "d2 = data.sel(longitude=slice(-70, -40), latitude=slice(30, 50))\n", - "\n", - "print(d1.nbytes / 1e9)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset>\n",
-       "Dimensions:    (latitude: 66, longitude: 50, time: 7000)\n",
-       "Coordinates:\n",
-       "  * time       (time) object 0181-01-01 12:00:00 ... 0200-03-01 12:00:00\n",
-       "  * longitude  (longitude) float64 -39.75 -39.35 -38.95 ... -20.95 -20.55 -20.15\n",
-       "  * latitude   (latitude) float64 30.24 30.58 30.93 31.27 ... 49.38 49.64 49.9\n",
-       "Data variables:\n",
-       "    S_x        (time, latitude, longitude) float64 dask.array<chunksize=(32, 66, 50), meta=np.ndarray>\n",
-       "    S_y        (time, latitude, longitude) float64 dask.array<chunksize=(32, 66, 50), meta=np.ndarray>\n",
-       "    usurf      (time, latitude, longitude) float64 dask.array<chunksize=(32, 66, 50), meta=np.ndarray>\n",
-       "    vsurf      (time, latitude, longitude) float64 dask.array<chunksize=(32, 66, 50), meta=np.ndarray>
" - ], - "text/plain": [ - "\n", - "Dimensions: (latitude: 66, longitude: 50, time: 7000)\n", - "Coordinates:\n", - " * time (time) object 0181-01-01 12:00:00 ... 0200-03-01 12:00:00\n", - " * longitude (longitude) float64 -39.75 -39.35 -38.95 ... -20.95 -20.55 -20.15\n", - " * latitude (latitude) float64 30.24 30.58 30.93 31.27 ... 49.38 49.64 49.9\n", - "Data variables:\n", - " S_x (time, latitude, longitude) float64 dask.array\n", - " S_y (time, latitude, longitude) float64 dask.array\n", - " usurf (time, latitude, longitude) float64 dask.array\n", - " vsurf (time, latitude, longitude) float64 dask.array" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "d1" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dask.array.core.Array" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "type(d1['usurf'].data)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'2.23.0'" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dask.__version__" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 5min 4.5s\n" - ] - } - ], - "source": [ - "with ProgressBar(), ResourceProfiler() as prof:\n", - " d1_val = d1.compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "'2.23.0'" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dask.__version__" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[ResourceData(time=1235464.319442389, mem=502.6816, cpu=0.0),\n", - " ResourceData(time=1235465.329093405, mem=506.044416, cpu=67.4),\n", - " ResourceData(time=1235466.330103216, mem=508.616704, cpu=65.9),\n", - " ResourceData(time=1235467.331098757, mem=699.260928, cpu=67.9),\n", - " ResourceData(time=1235468.332098474, mem=641.937408, cpu=69.9),\n", - " ResourceData(time=1235469.333101442, mem=609.189888, cpu=72.9),\n", - " ResourceData(time=1235470.334096437, mem=545.222656, cpu=68.9),\n", - 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Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plotter.plot(d1_val.isel(time=5000)['usurf'], cmap=cmap_balance, vmin=-1, vmax=1, projection_cls=proj_robinson, lon=0.)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plotter.plot(data.vsurf.isel(time=0), lon=0., cmap=cmap_balance, vmin=-1, vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'SeasonalStdizer' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSeasonalStdizer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstd\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mProgressBar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'SeasonalStdizer' is not defined" - ] - } - ], - "source": [ - "t = SeasonalStdizer(std=True)\n", - "with ProgressBar():\n", - " t.fit(data)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "data_n = t(data)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], - "source": [ - "data_v = data.chunk(dict(time=-1, longitude=28, latitude=17))" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "data_v = data.chunk(dict(time=100, longitude=450, latitude=275))\n", - "data_v = data_v.chunk(dict(time=400, longitude=225, latitude=137))\n", - "data_v = data_v.chunk(dict(time=1600, longitude=112, latitude=68))\n", - "data_v = data_v.chunk(dict(time=3200, longitude=56, latitude=34))\n", - "data_v = data_v.chunk(dict(time=-1, longitude=28, latitude=17))" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "import dask.array as da" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "v = da.random.randint(0, 10, (100, 1000), chunks=(10, -1))" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "
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" - ], - "text/plain": [ - "dask.array" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "d" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [], - "source": [ - "from dask import delayed\n", - "import numpy as np\n", - "def func(x):\n", - " return 2*x\n", - "delayed_func = delayed(func)\n", - "new_v = da.concatenate([da.from_delayed(delayed_func(v[start:min(start+5, 100), :]), shape=(5, 1000), dtype=np.int64)\n", - " for start in range(0, 100, 5)])" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "import dask\n", - "z = dask.delayed(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "z.compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[#### ] | 11% Completed | 26.5s\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mProgressBar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata_v\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlongitude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlatitude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36mcompute\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 812\u001b[0m \"\"\"\n\u001b[1;32m 813\u001b[0m \u001b[0mnew\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 814\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mnew\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 815\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 816\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_persist_inplace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;34m\"Dataset\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 656\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 657\u001b[0m \u001b[0;31m# evaluate all the dask arrays simultaneously\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 658\u001b[0;31m \u001b[0mevaluated_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mlazy_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 659\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 660\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlazy_data\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevaluated_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/base.py\u001b[0m in \u001b[0;36mcompute\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 445\u001b[0m \u001b[0mpostcomputes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__dask_postcompute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 446\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 447\u001b[0;31m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mschedule\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeys\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 448\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mrepack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresults\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpostcomputes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 449\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/threaded.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(dsk, result, cache, num_workers, pool, **kwargs)\u001b[0m\n\u001b[1;32m 82\u001b[0m \u001b[0mget_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_thread_get_id\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 83\u001b[0m \u001b[0mpack_exception\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpack_exception\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 84\u001b[0;31m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 85\u001b[0m )\n\u001b[1;32m 86\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/local.py\u001b[0m in \u001b[0;36mget_async\u001b[0;34m(apply_async, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, **kwargs)\u001b[0m\n\u001b[1;32m 487\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mworker_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mres_info\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 488\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"cache\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 489\u001b[0;31m \u001b[0mfinish_task\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresults\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeyorder\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 490\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mposttask_cbs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 491\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdsk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mworker_id\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/local.py\u001b[0m in \u001b[0;36mfinish_task\u001b[0;34m(dsk, key, state, results, sortkey, delete, release_data)\u001b[0m\n\u001b[1;32m 273\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"cache\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m1e6\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 274\u001b[0m )\n\u001b[0;32m--> 275\u001b[0;31m \u001b[0mrelease_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdelete\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 276\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mdelete\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mdep\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mresults\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 277\u001b[0m \u001b[0mrelease_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdelete\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/local.py\u001b[0m in \u001b[0;36mrelease_data\u001b[0;34m(key, state, delete)\u001b[0m\n\u001b[1;32m 243\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 244\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mdelete\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 245\u001b[0;31m \u001b[0;32mdel\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"cache\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 246\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 247\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "with ProgressBar():\n", - " test = data_v.isel(longitude=slice(0, 50), latitude=slice(0, 50)).compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], - "source": [ - "plt.savefig('histtemp.jpg', dpi=300)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/array/numpy_compat.py:41: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/array/numpy_compat.py:41: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - } - ], - "source": [ - "t = SeasonalStdizer()\n", - "test = t.fit_transform(data)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], - "source": [ - "u = t.transform(data)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/html": [ - "
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-       "Dimensions:    (latitude: 550, longitude: 900, time: 9)\n",
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Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ ] | 2% Completed | 1.2s" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/array/numpy_compat.py:41: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 35.8s\n" - ] - } - ], - "source": [ - "months = data['time'].dt.month\n", - "months\n", - "months_means = monthly_means.sel(month=months)\n", - "v = data - months_means\n", - "with ProgressBar():\n", - " v = v.compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "7920015600" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.nbytes" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Frozen(SortedKeysDict({'time': 500, 'latitude': 550, 'longitude': 900}))" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.dims" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. 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position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - 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" event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - 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" 339,\n", - " 340,\n", - " 341,\n", - " 342,\n", - " 343,\n", - " 344,\n", - " 345,\n", - " 346,\n", - " 347,\n", - " 348,\n", - " 349,\n", - " 350,\n", - " 351,\n", - " 352,\n", - " 353,\n", - " 354,\n", - " 355,\n", - " 356,\n", - " 357,\n", - " 358,\n", - " 359,\n", - " 360,\n", - " 361,\n", - " 362,\n", - " 363,\n", - " 364]}" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "monthly_grouped.groups" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "ename": "AttributeError", - "evalue": "'DatasetGroupBy' object has no attribute 'compute'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mProgressBar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mrr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmonthly_grouped\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m: 'DatasetGroupBy' object has no attribute 'compute'" - ] - } - ], - "source": [ - "with ProgressBar():\n", - " rr = monthly_grouped.compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. 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text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; 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" on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plt.figure()\n", - "plt.plot(monthly_means['usurf'].sel(longitude=-161, latitude=0, method='nearest'))" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plotter.plot(monthly_stds['usurf'].sel(month=10), lon=0., cmap=cmap_balance, vmax=0.5)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plotter.plot(data['usurf'].isel(time=0) - monthly_means['usurf'].sel(month=1), lon=0, cmap=cmap_balance)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - 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" // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plotter.plot(data_n['usurf'].isel(time=100), lon=0., cmap=cmap_balance)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "GroupBy objects only support binary ops when the other argument is a Dataset or DataArray", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/groupby.py\u001b[0m in \u001b[0;36m_yield_binary_applied\u001b[0;34m(self, func, other)\u001b[0m\n\u001b[1;32m 483\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 484\u001b[0;31m \u001b[0mother_sel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_group\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mgroup_value\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 485\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'sel'", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mvar\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m~/code/subgrid/data/xrtransforms.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 28\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/code/subgrid/data/xrtransforms.py\u001b[0m in \u001b[0;36mtransform\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 118\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mtransform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[0;31m# TODO unefficient\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 120\u001b[0;31m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeans\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 121\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstds\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 122\u001b[0m \u001b[0;32mdel\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'month'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/groupby.py\u001b[0m in \u001b[0;36mfunc\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 472\u001b[0m \u001b[0mg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mreflexive\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 473\u001b[0m \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_yield_binary_applied\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 474\u001b[0;31m \u001b[0mcombined\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_combine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapplied\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 475\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mcombined\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/groupby.py\u001b[0m in \u001b[0;36m_combine\u001b[0;34m(self, applied)\u001b[0m\n\u001b[1;32m 941\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_combine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mapplied\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 942\u001b[0m \u001b[0;34m\"\"\"Recombine the applied objects like the original.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 943\u001b[0;31m \u001b[0mapplied_example\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpeek_at\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapplied\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 944\u001b[0m \u001b[0mcoord\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpositions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_infer_concat_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapplied_example\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 945\u001b[0m \u001b[0mcombined\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconcat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapplied\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/utils.py\u001b[0m in \u001b[0;36mpeek_at\u001b[0;34m(iterable)\u001b[0m\n\u001b[1;32m 181\u001b[0m \"\"\"\n\u001b[1;32m 182\u001b[0m \u001b[0mgen\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0miter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miterable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 183\u001b[0;31m \u001b[0mpeek\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 184\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mpeek\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mitertools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpeek\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 185\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/analysis/lib/python3.7/site-packages/xarray/core/groupby.py\u001b[0m in \u001b[0;36m_yield_binary_applied\u001b[0;34m(self, func, other)\u001b[0m\n\u001b[1;32m 485\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 486\u001b[0m raise TypeError(\n\u001b[0;32m--> 487\u001b[0;31m \u001b[0;34m\"GroupBy objects only support binary ops \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 488\u001b[0m \u001b[0;34m\"when the other argument is a Dataset or \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 489\u001b[0m \u001b[0;34m\"DataArray\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mTypeError\u001b[0m: GroupBy objects only support binary ops when the other argument is a Dataset or DataArray" - ] - } - ], - "source": [ - "var = t.apply(data)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/jupyter-notebooks/generate-paper-figure-1.ipynb b/examples/jupyter-notebooks/generate-paper-figure-1.ipynb index 146508e7..7e223da9 100644 --- a/examples/jupyter-notebooks/generate-paper-figure-1.ipynb +++ b/examples/jupyter-notebooks/generate-paper-figure-1.ipynb @@ -4,16 +4,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Code to generate Figure 2 " + "# Code to generate Figure 1 " ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "from analysis.utils import select_experiment, select_run, GlobalPlotter, plot_training_subdomains\n", + "%cd ../../src/gz21_ocean_momentum\n", + "import os\n", + "from utils import select_experiment, select_run\n", + "from analysis.utils import plot_dataset, GlobalPlotter, plot_training_subdomains\n", + "from data.utils import load_training_datasets\n", "import mlflow\n", "from mlflow.tracking import MlflowClient\n", "import xarray as xr\n", @@ -25,1116 +29,87 @@ "cmap_solar = cmocean.cm.solar\n", "cmap_balance = cmocean.cm.balance\n", "\n", + "mlruns_path=os.path.join(os.getcwd(), '../../mlruns')\n", + "%env MLFLOW_TRACKING_URI $mlruns_path\n", + "\n", "plt.rcParams[\"figure.figsize\"] = (4, 4 / 1.618)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Select an experiment by experiment ID, and get the associated run" + ] + }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6 : multiregion\n", - "17 : meeting22july\n", - "15 : datacm21\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "2 : training\n", - "4 : default\n", - "7 : Unet\n", - "18 : forcing-data-global\n", - "12 : test\n", - "9 : forcingdata1pct\n", - "5 : regionsfortraining\n", - "20 : test_global\n", - "8 : arctan\n", - "16 : meeting15july\n", - "13 : forcingdatav2\n", - "Select the id of an experiment: 19\n" - ] - } - ], + "outputs": [], "source": [ - "exp_name = select_experiment()" + "exp_id, exp_name = select_experiment()" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " run_id experiment_id params.CO2\n", - "0 873b7eea20934f4cb141a35167400bcc 19 1\n", - "1 e98db6311efb4892aaeff61840386c1a 19 0\n", - "2 a9f2228e10c945df8f7829f4ebf09271 19 1\n", - "3 38491825c56c4c8c8afbf5286ce59c7c 19 0\n", - "Run id?3\n" - ] - } - ], + "outputs": [], "source": [ "experiment_id = mlflow.get_experiment_by_name(exp_name).experiment_id\n", "cols = ['params.CO2', ]\n", "run = select_run(cols=cols, experiment_ids=(experiment_id,))" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get the data set of the selected run " + ] + }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], + "outputs": [], "source": [ "ml_client = MlflowClient()\n", "data_fname = ml_client.download_artifacts(run.run_id, 'forcing')\n", "data = xr.open_zarr(data_fname)\n", - "data = data.rename(dict(xu_ocean='longitude', yu_ocean='latitude'))\n" + "#data = data.rename(dict(xu_ocean='longitude', yu_ocean='latitude'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Define a plotter which plots the dataset as a map, and the areas for the training, and execute the plotting" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " run_id experiment_id\n", - "0 a32ab882fab84d26b07e767846f6c702 17\n", - "1 d4d29e1686904f4fafefcb5f7b0b0e63 17\n", - "2 29a43a58e38f47cdbd8acd77e6101adc 17\n", - "3 410cb79eb81d4df1b015d2a440093f8d 17\n", - "4 738c4a3c73a04499af30bc4b16d719f9 17\n", - "5 0eb015bab85241089fe8584e9b7f4a30 17\n", - "6 8a0843c1aa8540f99629e829223573ba 17\n", - "7 896f639a1cf345948d141ad37c9faaf3 17\n", - "8 63e8b9b7424f4e938f596235acdac30d 17\n", - "9 01853b8a98c84839b01ef62d42785134 17\n", - "10 d7ea697fcc2e43faa2753231b88f1dd4 17\n", - "11 adf99c6514c04689b7e3e7331e75ed99 17\n", - "12 25ad18f498f44e278cd6d2434d9e697d 17\n", - "13 e79fc14d53314f59895625c4e331ccd5 17\n", - "14 648757da89fc4cde97357baa3bd28a97 17\n", - "15 c36e01c3c47d49259d828c1a12eb02ff 17\n", - "16 7f5c0bd8a50446c3b72523db33c47a71 17\n", - "17 989207c9b27843debea15ee4dec12712 17\n", - "18 d92172911d0745af836df9a3f21162a5 17\n", - "19 3c36ecae70f044838978a1183f18b5d7 17\n", - "20 2370107146564198b9f7351036632770 17\n", - "Run id?20\n", - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. 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We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n", - "\\begin{table}[]\n", - "\\begin{tabular}{lcccc}\n", - "subdomain & latitude range & longitude range & training & validation \\\\ \n", - "A & 35.0\\degree, 50.0\\degree & -50.0\\degree, -20.0\\degree & X & X \\\\\n", - "B & -40.0\\degree, -25.0\\degree & -180.0\\degree, -162.0\\degree & X & X \\\\\n", - "C & -20.0\\degree, -5.0\\degree & -110.0\\degree, -92.0\\degree & X & X \\\\\n", - "D & 0.0\\degree, 15.0\\degree & -48.0\\degree, -30.0\\degree & X & X \\\\\n", - "\\end{tabular}\n", - "\\end{table}\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from data.pangeo_catalog import get_patch\n", "\n", - "%matplotlib notebook\n", - "run = select_run(experiment_ids=('17'))\n", + "#run = select_run(experiment_ids=('497746281881301089'))\n", "run_id = run.run_id\n", "\n", "from cartopy.crs import PlateCarree\n", "from data.pangeo_catalog import get_patch, get_whole_data\n", "from scipy.ndimage import gaussian_filter\n", "from matplotlib import colors\n", + "import matplotlib.pyplot as plt\n", "\n", + "from importlib import reload\n", + "reload(plt)\n", + "\n", + "%matplotlib widget\n", + "#%matplotlib inline #this option does not work with jupyterlab\n", "\n", "CATALOG_URL = 'https://raw.githubusercontent.com/pangeo-data/pangeo-datastore\\\n", "/master/intake-catalogs/master.yaml'\n", @@ -1215,17 +190,18 @@ " None.\n", "\n", " \"\"\"\n", + "\n", " fig = plt.figure()\n", " projection = projection_cls(lon)\n", " if ax is None:\n", " ax = plt.axes(projection=projection)\n", - " mesh_x, mesh_y = np.meshgrid(u['longitude'], u['latitude'])\n", + " mesh_x, mesh_y = np.meshgrid(u['xu_ocean'], u['yu_ocean'])\n", " if u is not None:\n", - " extra = self.mask.isel(longitude=slice(0, 10))\n", - " extra['longitude'] = extra['longitude'] + 360\n", - " mask = xr.concat((self.mask, extra), dim='longitude')\n", - " mask = mask.interp({k: u.coords[k] for k in ('longitude',\n", - " 'latitude')})\n", + " extra = self.mask.isel(xu_ocean=slice(0, 10))\n", + " extra['xu_ocean'] = extra['xu_ocean'] + 360\n", + " mask = xr.concat((self.mask, extra), dim='xu_ocean')\n", + " mask = mask.interp({k: u.coords[k] for k in ('xu_ocean',\n", + " 'yu_ocean')})\n", " u = u * mask\n", " im = ax.pcolormesh(mesh_x, mesh_y, u.values,\n", " transform=PlateCarree(),\n", @@ -1239,10 +215,10 @@ " # \"Gray-out\" near continental locations\n", " if self.margin > 0:\n", " extra = self.borders.isel(longitude=slice(0, 10))\n", - " extra['longitude'] = extra['longitude'] + 360\n", - " borders = xr.concat((self.borders, extra), dim='longitude')\n", + " extra['xu_ocean'] = extra['xu_ocean'] + 360\n", + " borders = xr.concat((self.borders, extra), dim='xu_ocean')\n", " borders = borders.interp({k: u.coords[k]\n", - " for k in ('longitude', 'latitude')})\n", + " for k in ('xu_ocean', 'yu_ocean')})\n", " borders_cmap = colors.ListedColormap([borders_color, ])\n", " ax.pcolormesh(mesh_x, mesh_y, borders, animated=animated,\n", " transform=PlateCarree(), alpha=borders_alpha,\n", @@ -1251,10 +227,10 @@ " if self.ice:\n", " ice = self._get_ice_border()\n", " ice = xr.where(ice, 1., 0.)\n", - " ice = ice.interp({k: u.coords[k] for k in ('longitude',\n", - " 'latitude')})\n", + " ice = ice.interp({k: u.coords[k] for k in ('xu_ocean',\n", + " 'yu_ocean')})\n", " ice = xr.where(ice != 0, 1., 0.)\n", - " ice = abs(ice.diff(dim='longitude')) + abs(ice.diff(dim='latitude'))\n", + " ice = abs(ice.diff(dim='xu_ocean')) + abs(ice.diff(dim='yu_ocean'))\n", " ice = xr.where(ice != 0., 1, np.nan)\n", " ice_cmap = colors.ListedColormap(['black', ])\n", " ax.pcolormesh(mesh_x, mesh_y, ice, animated=animated,\n", @@ -1297,7 +273,7 @@ " mask = mask.coarsen(dict(xt_ocean=factor, yt_ocean=factor))\n", " mask_ = mask.max()\n", " mask_ = mask_.where(mask_ > 0.1)\n", - " mask_ = mask_.rename(dict(xt_ocean='longitude', yt_ocean='latitude'))\n", + " mask_ = mask_.rename(dict(xt_ocean='xu_ocean', yt_ocean='yu_ocean'))\n", " return mask_.compute()\n", "\n", " @staticmethod\n", @@ -1306,8 +282,8 @@ " in the oceans. \"\"\"\n", " temperature, _ = get_patch(CATALOG_URL, 1, None, 0,\n", " 'surface_temp')\n", - " temperature = temperature.rename(dict(xt_ocean='longitude',\n", - " yt_ocean='latitude'))\n", + " temperature = temperature.rename(dict(xt_ocean='xu_ocean',\n", + " yt_ocean='yu_ocean'))\n", " temperature = temperature['surface_temp'].isel(time=0)\n", " ice = xr.where(temperature <= 0., True, False)\n", " return ice\n", @@ -1348,25 +324,16 @@ "plotter = GlobalPlotter(cbar=True, margin=0)\n", "plotter.x_ticks = np.arange(-150., 151., 50)\n", "plotter.y_ticks = np.arange(-80., 81., 20)\n", - "plot_training_subdomains(run_id, plotter, bg_variable=data['usurf'].isel(time=0), facecolor='green', edgecolor='black', linewidth=2, fill=False, vmin=-0.5, vmax=0.5, lon=0., cmap=cmap_balance)\n" + "plot_training_subdomains(plotter, bg_variable=data['usurf'].isel(time=0), facecolor='green', edgecolor='black', linewidth=2, fill=False, vmin=-0.5, vmax=0.5, lon=0., cmap=cmap_balance)\n" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], + "outputs": [], "source": [ - "plt.savefig('figure2.jpg', dpi=250)" + "plt.savefig('figure1b.jpg', dpi=250)" ] }, { @@ -1379,7 +346,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1393,7 +360,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.7" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/examples/jupyter-notebooks/generate-paper-figure-6.ipynb b/examples/jupyter-notebooks/generate-paper-figure-6.ipynb index f656a7ec..c094c212 100644 --- a/examples/jupyter-notebooks/generate-paper-figure-6.ipynb +++ b/examples/jupyter-notebooks/generate-paper-figure-6.ipynb @@ -4,16 +4,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Code to generate Figure 1 " + "# Code to generate Figure 6 " ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "from analysis.utils import select_experiment, select_run, GlobalPlotter\n", + "%cd ../../src/gz21_ocean_momentum\n", + "import os\n", + "from utils import select_experiment, select_run\n", + "from analysis.utils import plot_dataset, GlobalPlotter\n", "import mlflow\n", "from mlflow.tracking import MlflowClient\n", "import xarray as xr\n", @@ -26,6 +29,9 @@ "cmap_solar = cmocean.cm.solar\n", "cmap_balance = cmocean.cm.balance\n", "\n", + "mlruns_path=os.path.join(os.getcwd(), '../../mlruns')\n", + "%env MLFLOW_TRACKING_URI $mlruns_path\n", + "\n", "plt.rcParams[\"figure.figsize\"] = (4, 4 / 1.618)" ] }, @@ -38,12 +44,10 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "# run_control_id = 'a06e42d44402481eb3a8f9e705770950'\n", - "# run_1pct_id = '32ebeb9bdec9441ca761e91b8777acd1'\n", "run_control_id = None\n", "run_1pct_id = None\n", "var_name = 'vsurf'\n", @@ -52,138 +56,30 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], + "outputs": [], "source": [ "def select_run_id():\n", - " exp_name = select_experiment()\n", - " experiment_id = mlflow.get_experiment_by_name(exp_name).experiment_id\n", + " exp_id, exp_name = select_experiment()\n", + " #experiment_id = mlflow.get_experiment_by_name(exp_name).experiment_id\n", " cols = ['params.CO2', 'params.factor']\n", - " run = select_run(cols=cols, experiment_ids=(experiment_id,))\n", + " run = select_run(cols=cols, experiment_ids=(exp_id,))\n", " return run.run_id" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6 : multiregion\n", - "17 : meeting22july\n", - "15 : datacm21\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "2 : training\n", - "4 : default\n", - "7 : Unet\n", - "18 : forcing-data-global\n", - "12 : test\n", - "9 : forcingdata1pct\n", - "5 : regionsfortraining\n", - "20 : test_global\n", - "8 : arctan\n", - "16 : meeting15july\n", - "13 : forcingdatav2\n", - "Select the id of an experiment: 19\n", - " run_id experiment_id params.CO2 params.factor\n", - "0 359a13e63c9744d18336a7b04380569f 19 1 8\n", - "1 7a60369c9d5b48058366adef1df59728 19 1 7\n", - "2 b85d663b7a1f4e59b09b0d3813cbcab8 19 1 6\n", - "3 0c1de3ebefec40748311812a482a8024 19 1 5\n", - "4 a5049bd09c7e409791944731e5631a10 19 0 8\n", - "5 8f038ef65bdb4667a815029ccf8be3c4 19 0 7\n", - "6 2ebecb60c35642fbb1b60d1f6d33df2d 19 0 6\n", - "7 1dad89889fae43e798d8fbb171627ad0 19 0 5\n", - "8 743777154cb745cf8a4272dcbd3fa189 19 0 4\n", - "9 e5e4964d11aa4be1b70143f2289ccfb0 19 1 10\n", - "10 f4df0dbb52924d649224c4507cd160aa 19 0 10\n", - "11 29399585cd654ffbbac18531738ce984 19 1 10\n", - "12 4feb4b3a4ca340ed9e87b75e9e0706f6 19 0 10\n", - "13 b681d3b8e4e149a7a9ff3193a62be3d4 19 1 4\n", - "14 324a91cc5d64485da4109288a6222090 19 1 4\n", - "15 233450fe93354d86bdae6268cc284832 19 1 4\n", - "16 dfa9c1bbc76249c994beacea5fa70b90 19 1 4\n", - "17 0cc065fcdcea4a2c83c30c8ed66d0b81 19 1 4\n", - "18 5a86a3dbda6c4208949f0a0edbce5356 19 1 4\n", - "19 ffe4682876504d89892f2ae7571a675c 19 1 4\n", - "20 52162444c2b94caa828ef3ccc12693ba 19 1 4\n", - "21 45cf9545dfe24adfb235105781bfe852 19 1 4\n", - "22 6930f1d7501447f7aac4719474b87896 19 1 4\n", - "23 34008ec087d840e6a81407c5d95d12e2 19 1 4\n", - "24 11170a3a29684216ac32a0f54db62ccd 19 0 4\n", - "25 143e8895afd7453ba0aa7b0b02858702 19 1 4\n", - "26 72b9f00c3bfa405e865f3fd6d07edad1 19 0 4\n", - "Run id?8\n", - "6 : multiregion\n", - "17 : meeting22july\n", - "15 : datacm21\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "2 : training\n", - "4 : default\n", - "7 : Unet\n", - "18 : forcing-data-global\n", - "12 : test\n", - "9 : forcingdata1pct\n", - "5 : regionsfortraining\n", - "20 : test_global\n", - "8 : arctan\n", - "16 : meeting15july\n", - "13 : forcingdatav2\n", - "Select the id of an experiment: 19\n", - " run_id experiment_id params.CO2 params.factor\n", - "0 359a13e63c9744d18336a7b04380569f 19 1 8\n", - "1 7a60369c9d5b48058366adef1df59728 19 1 7\n", - "2 b85d663b7a1f4e59b09b0d3813cbcab8 19 1 6\n", - "3 0c1de3ebefec40748311812a482a8024 19 1 5\n", - "4 a5049bd09c7e409791944731e5631a10 19 0 8\n", - "5 8f038ef65bdb4667a815029ccf8be3c4 19 0 7\n", - "6 2ebecb60c35642fbb1b60d1f6d33df2d 19 0 6\n", - "7 1dad89889fae43e798d8fbb171627ad0 19 0 5\n", - "8 743777154cb745cf8a4272dcbd3fa189 19 0 4\n", - "9 e5e4964d11aa4be1b70143f2289ccfb0 19 1 10\n", - "10 f4df0dbb52924d649224c4507cd160aa 19 0 10\n", - "11 29399585cd654ffbbac18531738ce984 19 1 10\n", - "12 4feb4b3a4ca340ed9e87b75e9e0706f6 19 0 10\n", - "13 b681d3b8e4e149a7a9ff3193a62be3d4 19 1 4\n", - "14 324a91cc5d64485da4109288a6222090 19 1 4\n", - "15 233450fe93354d86bdae6268cc284832 19 1 4\n", - "16 dfa9c1bbc76249c994beacea5fa70b90 19 1 4\n", - "17 0cc065fcdcea4a2c83c30c8ed66d0b81 19 1 4\n", - "18 5a86a3dbda6c4208949f0a0edbce5356 19 1 4\n", - "19 ffe4682876504d89892f2ae7571a675c 19 1 4\n", - "20 52162444c2b94caa828ef3ccc12693ba 19 1 4\n", - "21 45cf9545dfe24adfb235105781bfe852 19 1 4\n", - "22 6930f1d7501447f7aac4719474b87896 19 1 4\n", - "23 34008ec087d840e6a81407c5d95d12e2 19 1 4\n", - "24 11170a3a29684216ac32a0f54db62ccd 19 0 4\n", - "25 143e8895afd7453ba0aa7b0b02858702 19 1 4\n", - "26 72b9f00c3bfa405e865f3fd6d07edad1 19 0 4\n", - "Run id?13\n" - ] - } - ], + "outputs": [], "source": [ "ml_client = MlflowClient()\n", "if not run_control_id:\n", + " print(\"Please select run with CO2=0.\")\n", " run_control_id = select_run_id()\n", "if not run_1pct_id:\n", + " print(\"Please select run with CO2=1.\")\n", " run_1pct_id = select_run_id()\n", "\n", "run_control = mlflow.get_run(run_control_id)\n", @@ -209,48 +105,9 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[### ] | 8% Completed | 30.9s" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/array/numpy_compat.py:41: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 6min 1.1s\n", - "[### ] | 8% Completed | 25.5s" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/dask/array/numpy_compat.py:41: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 5min 21.6s\n" - ] - } - ], + "outputs": [], "source": [ "var_control = data_control[var_name].std(dim='time')\n", "var_1pct = data_1pct[var_name].std(dim='time')\n", @@ -261,18 +118,9 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], + "outputs": [], "source": [ "diff = var_1pct - var_control\n", "r_diff = diff / var_control" @@ -280,971 +128,12 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - } - ], + "outputs": [], "source": [ - "%matplotlib notebook\n", + "#%matplotlib notebook #this option does not work with jupyterlab\n", + "%matplotlib widget\n", "from cartopy.crs import PlateCarree\n", "from data.pangeo_catalog import get_patch, get_whole_data\n", "from scipy.ndimage import gaussian_filter\n", @@ -1264,401 +153,18 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], + "outputs": [], "source": [ "plt.savefig('r_diff_' + var_name + '.jpg', dpi=400)" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - "\n", - "array(0.04863561)" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "uv_plotter = plotter\n", "def apply_complete_mask(array):\n", @@ -1682,7 +188,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1696,7 +202,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/examples/jupyter-notebooks/multi-region-analysis-01.ipynb b/examples/jupyter-notebooks/multi-region-analysis-01.ipynb deleted file mode 100644 index b158d8b2..00000000 --- a/examples/jupyter-notebooks/multi-region-analysis-01.ipynb +++ /dev/null @@ -1,1077 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "###### Multi-region analysis " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this notebook we analyse the ability of a model trained on a region A to infer the subgrid forcing to achieve the same task on a different region, say region B. " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "import mlflow\n", - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "from analysis.utils import select_run" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "plt.rcParams[\"figure.figsize\"] = (20, 15)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_dataset(dataset : xr.Dataset, plot_type = None, *args, **kargs):\n", - " \"\"\"Calls the plot function of each variable in the dataset\"\"\"\n", - " plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " kargs_ = [dict() for i in range(len(dataset))]\n", - " def process_list_of_args(name: str):\n", - " if name in kargs:\n", - " if isinstance(kargs[name], list):\n", - " for i, arg_value in enumerate(kargs[name]):\n", - " kargs_[i][name] = arg_value\n", - " else:\n", - " for i in range(len(dataset)):\n", - " kargs_[i][name] = kargs[name]\n", - " kargs.pop(name)\n", - " process_list_of_args('vmin')\n", - " process_list_of_args('vmax')\n", - " for i, variable in enumerate(dataset):\n", - " plt.subplot(int(len(dataset) / 2), 2, i + 1)\n", - " if plot_type is None:\n", - " try:\n", - " # By default we set the cmap to coolwarm\n", - " kargs.setdefault('cmap', 'coolwarm')\n", - " dataset[variable].plot(*args, **kargs_[i], **kargs)\n", - " except AttributeError as e:\n", - " kargs.pop('cmap', None)\n", - " dataset[variable].plot(*args, **kargs)\n", - " else:\n", - " plt_func = getattr(dataset[variable].plot, plot_type)\n", - " plt_func(*args, **kargs)\n", - "import matplotlib.animation as animation\n", - "\n", - "def dataset_to_movie(dataset : xr.Dataset, interval : int = 50,\n", - " *args, **kargs):\n", - " \"\"\"Generates animations for all the variables in the dataset\"\"\"\n", - " fig = plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " axes = list()\n", - " ims = list()\n", - " for i, variable in enumerate(dataset.keys()):\n", - " axes.append(fig.add_subplot(int(len(dataset) / 2), 2, i + 1))\n", - " for i, t in enumerate(dataset['time']):\n", - " im = list()\n", - " for axis, variable in zip(axes, dataset.keys()):\n", - " plt.sca(axis)\n", - " img = dataset[variable].isel(time=i).plot(vmin=-2, vmax=2,\n", - " cmap='coolwarm')\n", - " cb = img.colorbar\n", - " cb.remove()\n", - " im.append(img)\n", - " ims.append(im)\n", - " ani = animation.ArtistAnimation(fig, ims, \n", - " interval=interval, blit=True,\n", - " repeat_delay=1000)\n", - " return ani" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "client = mlflow.tracking.MlflowClient()" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "def select_run(limit=1000, sort_by=None, cols=None, merge=None, *args, **kargs):\n", - " \"\"\"Allows to select a run from the tracking store interactively\"\"\"\n", - " mlflow_runs = mlflow.search_runs(*args, **kargs)\n", - " if cols is None:\n", - " cols = list()\n", - " cols = ['run_id', 'experiment_id' ] + cols\n", - " mlflow_runs = mlflow_runs.iloc[:limit]\n", - " # Remove possible duplicate columns\n", - " new_cols = list()\n", - " for e in cols:\n", - " if e not in new_cols:\n", - " new_cols.append(e)\n", - " cols = new_cols\n", - " print(len(mlflow_runs))\n", - " if merge is not None:\n", - " cols[cols.index('run_id')] = 'run_id_x'\n", - " cols[cols.index('experiment_id')] = 'experiment_id_x'\n", - " for name, key_left, key_right in merge:\n", - " experiment = mlflow.get_experiment_by_name(name)\n", - " df2 = mlflow.search_runs(experiment_ids=experiment.experiment_id)\n", - " mlflow_runs = pd.merge(mlflow_runs, df2, left_on=key_left,\n", - " right_on=key_right)\n", - " print(len(mlflow_runs))\n", - " if len(mlflow_runs) == 0:\n", - " raise Exception('No data found. Check that you correctly set \\\n", - " the store')\n", - " if sort_by is not None:\n", - " mlflow_runs = mlflow_runs.sort_values(by=sort_by, ascending=False)\n", - " cols.append(sort_by)\n", - " print(mlflow_runs[cols])\n", - " id_ = int(input('Run id?'))\n", - " if id_ < 0:\n", - " sys.exit()\n", - " return mlflow_runs.loc[id_, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:Malformed run 'a4da4cad3ecc4412af086e7bad8eb8bd'. Detailed error Yaml file '/scratch/ag7531/mlruns/12/a4da4cad3ecc4412af086e7bad8eb8bd/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/mlflow/store/tracking/file_store.py\", line 585, in _list_run_infos\n", - " run_info = self._get_run_info_from_dir(r_dir)\n", - " File \"/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/mlflow/store/tracking/file_store.py\", line 423, in _get_run_info_from_dir\n", - " meta = read_yaml(run_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/mlflow/utils/file_utils.py\", line 160, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/scratch/ag7531/mlruns/12/a4da4cad3ecc4412af086e7bad8eb8bd/meta.yaml' does not exist.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "24\n", - "3\n", - " run_id_x experiment_id_x \\\n", - "0 235204ea3a15413f8113e0271dbba24a 12 \n", - "1 7606981f52144e0c8472e199785d60ac 12 \n", - "2 5a14d68dbd6746638258558cfbb4ffa9 12 \n", - "\n", - " start_time_x params.model_cls_name metrics.test loss \\\n", - "0 2020-07-24 14:06:48.826000+00:00 FullyCNN -1.760762 \n", - "1 2020-07-24 10:01:32.841000+00:00 FullyCNN -1.760762 \n", - "2 2020-07-22 08:59:03.065000+00:00 FullyCNN -1.760762 \n", - "\n", - " params.lat_min params.lat_max params.long_min params.long_max \\\n", - "0 -60 0 60 110 \n", - "1 -60 0 60 110 \n", - "2 20 35 -30 -18 \n", - "\n", - " params.n_epochs_x params.model_run_id \\\n", - "0 0 2370107146564198b9f7351036632770 \n", - "1 0 2370107146564198b9f7351036632770 \n", - "2 0 2370107146564198b9f7351036632770 \n", - "\n", - " start_time_x \n", - "0 2020-07-24 14:06:48.826000+00:00 \n", - "1 2020-07-24 10:01:32.841000+00:00 \n", - "2 2020-07-22 08:59:03.065000+00:00 \n", - "Run id?2\n" - ] - } - ], - "source": [ - "cols = ['start_time_x','params.model_cls_name', 'metrics.test loss', 'params.lat_min', \n", - " 'params.lat_max', 'params.long_min', 'params.long_max', 'params.n_epochs_x', 'params.model_run_id']\n", - "run = select_run(sort_by='start_time_x', cols=cols, merge=[('meeting22july', 'params.model_run_id', 'run_id'),\n", - " ('forcingdatav3', 'params.data_run_id', 'run_id')], experiment_ids = ['12',])" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "run_id_x: 5a14d68dbd6746638258558cfbb4ffa9\n", - "experiment_id_x: 12\n", - "status_x: FINISHED\n", - "artifact_uri_x: /scratch/ag7531/mlruns/12/5a14d68dbd6746638258558cfbb4ffa9/artifacts\n", - "start_time_x: 2020-07-22 08:59:03.065000+00:00\n", - "end_time_x: 2020-07-22 09:09:30.380000+00:00\n", - "metrics.validation loss: 0.0\n", - "metrics.Inf Norm_x: 2.750422538611019e-07\n", - "metrics.mse_x: 0.20767951424627448\n", - "params.model_run_id: 2370107146564198b9f7351036632770\n", - "params.data_run_id: 08db5f2f1c8b45c1879fa235f6eaad3a\n", - "params.n_epochs_x: 0\n", - "tags.mlflow.source.git.commit_x: fbed3c214941cd805e93a485154228434aaa19d6\n", - "tags.mlflow.source.type_x: LOCAL\n", - "tags.mlflow.user_x: ag7531\n", - "tags.mlflow.source.name_x: /home/ag7531/code/subgrid/testing/main.py\n", - "run_id_y: 2370107146564198b9f7351036632770\n", - "experiment_id_y: 17\n", - "status_y: FINISHED\n", - "artifact_uri_y: /scratch/ag7531/mlruns/17/2370107146564198b9f7351036632770/artifacts\n", - "start_time_y: 2020-07-22 08:04:01.181000+00:00\n", - "end_time_y: 2020-07-22 08:57:35.031000+00:00\n", - "metrics.Inf Norm_y: 1.7761233266355703e-06\n", - "metrics.mse_y: 0.06447393229143253\n", - "metrics.test loss: -1.7607615370455085\n", - "metrics.train loss: -1.8989318599755114\n", - "params.source.run_id: 95dfe34c555b4fdbbb8afb9a6e568c93/5ac900b6d97d46d9830d24e492954625/9185f0305de848718159f913d7bbcffd/a5307020cffe4640bc87bb21d72c7a7c\n", - "params.model_module_name: models.models1\n", - "params.weight_decay: 0.00\n", - "params.print_every: 20\n", - "params.train_split: 0.6\n", - "params.batchsize: 4\n", - "params.transformation_cls_name: SoftPlusTransform\n", - "params.time_indices: 0\n", - "params.test_split: 0.7\n", - "params.learning_rate: 0/5e-4/10/5e-5/20/5e-6\n", - "params.loss_cls_name: HeteroskedasticGaussianLossV2\n", - "params.exp_id: 14\n", - "params.run_id: 95dfe34c555b4fdbbb8afb9a6e568c93/5ac900b6d97d46d9830d24e492954625/9185f0305de848718159f913d7bbcffd/a5307020cffe4640bc87bb21d72c7a7c\n", - "params.model_cls_name: FullyCNN\n", - "params.source.experiment_id: 14\n", - "params.targets_transform_cls_name: FixedForcingNormalizer\n", - "params.features_transform_cls_name: FixedVelocityNormalizer\n", - "params.n_epochs_y: 28\n", - "tags.mlflow.project.env_x: conda\n", - "tags.mlflow.source.git.repoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.gitRepoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.name_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.entryPoint_x: train\n", - "tags.mlflow.project.backend_x: local\n", - "tags.mlflow.source.git.commit_y: fbed3c214941cd805e93a485154228434aaa19d6\n", - "tags.mlflow.user_y: ag7531\n", - "tags.mlflow.source.type_y: PROJECT\n", - "run_id: 08db5f2f1c8b45c1879fa235f6eaad3a\n", - "experiment_id: 14\n", - "status: FINISHED\n", - "artifact_uri: /scratch/ag7531/mlruns/14/08db5f2f1c8b45c1879fa235f6eaad3a/artifacts\n", - "start_time: 2020-07-22 06:57:51.077000+00:00\n", - "end_time: 2020-07-22 07:14:08.007000+00:00\n", - "params.scale: 32.6\n", - "params.long_min: -30\n", - "params.lat_max: 35\n", - "params.CO2: 0\n", - "params.lat_min: 20\n", - "params.factor: 4\n", - "params.ntimes: 4400\n", - "params.chunk_size: None\n", - "params.long_max: -18\n", - "tags.mlflow.project.env_y: conda\n", - "tags.mlflow.source.git.repoURL_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.gitRepoURL_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.name: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.entryPoint_y: main\n", - "tags.mlflow.project.backend_y: local\n", - "tags.mlflow.source.git.commit: 213819428f7ef410bb5ddaf1fabf63e48c1659dc\n", - "tags.mlflow.user: ag7531\n", - "tags.mlflow.source.type: PROJECT\n" - ] - } - ], - "source": [ - "for k,v in run.items():\n", - " print(f'{k}: {v}')" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "data_run_id = run['params.data_run_id']\n", - "data_run = client.get_run(data_run_id)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "data_file = client.download_artifacts(data_run_id, 'forcing')\n", - "data = xr.open_zarr(data_file)\n", - "data['time_index'] = xr.DataArray(np.arange(len(data.coords['time'])),\n", - " dims = ('time',),\n", - " coords = {'time' : data['time']})\n", - "data = data.swap_dims({'time' : 'time_index'})" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2349: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " if isinstance(obj, collections.Iterator):\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2366: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " return list(data) if isinstance(data, collections.MappingView) else data\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from random import randint\n", - "plot_dataset(data[['usurf', 'vsurf']].isel(xu_ocean=randint(0, len(data['xu_ocean'])),\n", - " yu_ocean=randint(0, len(data['yu_ocean']))))" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_dataset(data[['usurf', 'vsurf']].mean(dim='time_index'), cmap='coolwarm', vmin=-1, vmax=1)\n", - "_ = plt.suptitle('Mean flow')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_dataset(data[['S_x', 'S_y']].mean(dim='time_index'), cmap='coolwarm', vmin=-1e-7, vmax=1e-7)\n", - "_ = plt.suptitle('Average forcing')" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_dataset(data[['S_x', 'S_y']].std(dim='time_index'), cmap='coolwarm', vmin=0, vmax=2e-7)\n", - "_ = plt.suptitle('forcing std')" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
<xarray.Dataset>\n",
-       "Dimensions:  ()\n",
-       "Data variables:\n",
-       "    usurf    float64 0.1183\n",
-       "    vsurf    float64 0.07184\n",
-       "    S_x      float64 5.169e-08\n",
-       "    S_y      float64 5.19e-08
" - ], - "text/plain": [ - "\n", - "Dimensions: ()\n", - "Data variables:\n", - " usurf float64 0.1183\n", - " vsurf float64 0.07184\n", - " S_x float64 5.169e-08\n", - " S_y float64 5.19e-08" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data[['usurf', 'vsurf', 'S_x', 'S_y']].std().compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "eddy_data = data[['usurf', 'vsurf']] - data[['usurf', 'vsurf']].mean(dim='time_index')\n", - "eddy_data['usurf'].attrs['units'] = r'$m \\ s^{-1}$'\n", - "eddy_data['vsurf'].attrs['units'] = r'$m \\ s^{-1}$'\n", - "eddy_data['usurf'].attrs['long_name'] = 'eddy usurf'\n", - "eddy_data['vsurf'].attrs['long_name'] = 'eddy vsurf'" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "random_time = randint(0, len(eddy_data['time_index']))\n", - "fig = plt.figure(figsize=(20, 10))\n", - "plot_dataset(data[['usurf', 'vsurf']].isel(time_index=random_time))\n", - "_ = plt.suptitle('Velocities at day {}'.format(random_time))\n", - "plot_dataset(eddy_data[['usurf', 'vsurf']].isel(time_index=random_time))\n", - "_ = plt.suptitle('Eddy velocities at day {}'.format(random_time))" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "data['kinetic energy'] = 1/2*1e4*(data['usurf']**2 + data['vsurf']**2)\n", - "data['kinetic energy'].attrs['units'] = r'$(cm/s)^2$'\n", - "eddy_data['eddy kinetic energy'] = 1/2*1e4*(eddy_data['usurf']**2 + eddy_data['vsurf']**2)\n", - "eddy_data['eddy kinetic energy'].attrs['units'] = r'$(cm/s)^2$'" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "mean_kinetic_energy = data['kinetic energy'].mean(dim='time_index')\n", - "mean_kinetic_energy.attrs['units'] = r'$(cm/s)^2$'\n", - "mean_eddy_kinetic_energy = eddy_data['eddy kinetic energy'].mean(dim='time_index')\n", - "mean_eddy_kinetic_energy.attrs['units'] = r'$(cm/s)^2$'" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "mean_kinetic_energy.plot()\n", - "_ = plt.title('Time-averaged total kinetic energy')" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "mean_eddy_kinetic_energy.plot()\n", - "_ = plt.title('Time-averaged eddy kinetic energy')" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - ". test_output_0 .\n", - "loading\n", - ". test_output_1 .\n", - "loading\n", - ". test_output_2 .\n", - "loading\n", - ". test_output_3 .\n", - "loading\n", - ". test_output_4 .\n", - "loading\n", - ". test_output_5 .\n", - "loading\n", - ". test_output_6 .\n", - "loading\n", - ". test_output_7 .\n", - "loading\n", - ". test_output_8 .\n", - "loading\n", - ". test_output_9 .\n", - "loading\n" - ] - } - ], - "source": [ - "from analysis.base import get_test_datasets\n", - "test_datasets = get_test_datasets(run['run_id_x'])" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "lat = np.arange(-80, 80, 1)\n", - "lon = np.arange(-279.9, 80.1, 1)\n", - "interp_dss = []\n", - "for ds in test_datasets:\n", - " ds = ds.ds\n", - " ds = ds.chunk(dict(time=1, latitude=None, longitude=None))\n", - " interp_dss.append(ds.interp(dict(latitude=lat, longitude=lon),\n", - " method='nearest', kwargs=dict(bounds_error=False, fill_value=0.)))\n", - " interp_dss[-1] = interp_dss[-1].chunk(dict(latitude=None, longitude=None))" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "final_ds = sum(interp_dss)" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in greater\n", - " return func(*args2)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "([,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ],\n", - " )" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import cartopy.crs as ccrs\n", - "final_ds = final_ds.where(abs(final_ds) > 0)\n", - "ax = plt.axes(projection=ccrs.PlateCarree())\n", - "squared_error = ((final_ds['S_xpred'] - final_ds['S_x']))**2\n", - "(np.sqrt(squared_error.mean(dim='time'))).plot(ax=ax, transform = ccrs.PlateCarree(), vmin=0, vmax=3, cmap='coolwarm')\n", - "ax.set_global()\n", - "ax.coastlines()\n", - "plt.xticks(final_ds.longitude[::30] + 99.9)\n", - "plt.yticks(final_ds.latitude[::30])" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
<xarray.Dataset>\n",
-       "Dimensions:    (latitude: 45, longitude: 45, time: 1320)\n",
-       "Coordinates:\n",
-       "  * latitude   (latitude) float64 -39.95 -39.65 -39.34 ... -25.92 -25.56 -25.2\n",
-       "  * longitude  (longitude) float64 -179.9 -179.5 -179.1 ... -163.1 -162.7 -162.3\n",
-       "  * time       (time) object 0189-06-08 12:00:00 ... 0193-01-17 12:00:00\n",
-       "Data variables:\n",
-       "    S_x        (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_xpred    (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_xscale   (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_y        (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_ypred    (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_yscale   (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    u_surf     (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    v_surf     (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_datasets[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "id = 0\n", - "error = (test_datasets[id]['S_xpred'] - test_datasets[id]['S_x']) \n", - "error0 = test_datasets[id]['S_x']" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2349: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " if isinstance(obj, collections.Iterator):\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "((error**2).mean(dim='time') / (error0**2).mean(dim='time')).plot(vmin=0., vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "model_output = test_datasets[id]\n", - "model_output['S_xscale'] = 1/(model_output['S_xscale'])\n", - "model_output['S_yscale'] = 1/(model_output['S_yscale'])\n", - "model_output['err_S_x'] = (model_output['S_x'] - model_output['S_xpred'])**2\n", - "model_output['err_S_y'] = (model_output['S_y'] - model_output['S_ypred'])**2" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "model_output['time_index'] = xr.DataArray(np.arange(len(model_output.coords['time'])),\n", - " dims = ('time',),\n", - " coords = {'time' : model_output['time']})\n", - "model_output = model_output.swap_dims({'time' : 'time_index'})" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Random time index: 1102\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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KOlVpulrS8RFxgqRbJL1Vkmx3S/q0pHMj4jhlA8eGO9RGAAAAAOhMpSkivt3w9FpJL8sfP1fS+oj4ab7f1uluGwAAAHCwc7flHipNZTkQxjS9TtK38sePlRS2r7L9E9t/M1HI9jm2r7d9/ebNm6eloQAAAABmnrZVmmxfI+mwJpvOj4iv5/ucr+x+wlc0tOd3JZ2kbK7279i+ISK+M/4gEbFW0lpJWrNmTZT/CgAAAICDk7sY01SmtnWaIuLUou22z5b0Qkmn5HO0S9IGSd+PiC35PldKepKkR3SaAAAAAGA6dGr2vNMkvVnSMyNib8OmqyT9je3ZymbWe6ak93egiQAAAMBBy91iTFOJOnVz23+S1CfpatuSdG1EnBsRD9p+n6TrJIWkKyPimx1qIwAAAAB0bPa8owq2fVrZtOMAAAAAEtQY01SqA2H2PAAAAAA4YHXq8jwAAAAA7dJluYtKU1moNAEAAABAASpNAAAAQMXUalaNSlNpqDQBAAAAQAEqTQAAAEDFuGa5RqWpLFSaAAAAAKAAlSYAAACgYtxluYv6SFl4JwEAAACgAJUmAAAAoGLM7HmlotMEAAAAVAwTQZSLy/MAAAAAoACVJgAAAKBiuLltuag0AQAAAEABKk0AAABAxWRTjlNpKguVJgAAAAAoQKUJAAAAqBjbco36SFl4JwEAAACgAJUmAAAAoGq4T1OpqDQBAAAAQAEqTQAAAEDFcJ+mclFpAgAAAIACVJoAAACAijFjmkpFpQkAAAAAClBpAgAAAComqzRRHykL7yQAAAAAFKDSBAAAAFSNGdNUJipNAAAAAFCAShMAAABQMbUu7tNUJipNAAAAAFCAShMAAABQMWZMU6moNAEAAABAASpNAAAAQMW4VuM+TSXinQQAAACAAlSaAAAAgIpxTYxpKhGVJgAAAAAoQKUJAAAAqBpmzysVnSYAAACgYlyj01QmLs8DAAAAgAJUmgAAAICKYcrxcvFOAgAAAEABKk0AAABAxdRqUq2LMU1lodIEAAAAoHS2T7P9K9u32X5Lk+3vt31jvtxie3vDttGGbeumt+WPRKUJAAAAqJhOz55nu0vSByU9R9IGSdfZXhcRvxjbJyL+smH/P5P0xIZDDETEidPV3slQaQIAAABQtpMl3RYRd0TEkKTPSTqjYP8zJX12WlqWgEoTAAAAUDVu++x5S21f3/B8bUSsbXi+XNK9Dc83SHpKswPZfpSk1ZK+27C6Pz/+iKRLIuJr5TQ7DZ0mAAAAAPtrS0SsKdje7NrAmGDfV0j6UkSMNqxbGREbbT9a0ndt/ywibk9t7FTRaQIAAAAqptNjmpRVlo5seL5C0sYJ9n2FpDc2roiIjfm/d9j+nrLxTh3rNDGmCQAAAEDZrpN0tO3VtnuVdYweMQue7WMkLZL0Hw3rFtnuyx8vlfQ0Sb8Yn51OVJoAAACAiul0pSkiRmyfJ+kqSV2SLouIm2xfKOn6iBjrQJ0p6XMR0Xjp3uMkfcR2XVmR55LGWfc6gU4TAAAAgNJFxJWSrhy37oJxz9/RJPdjSY9va+P2E50mAAAAoGJst3v2vBmFdxIAAAAAClBpAgAAACqm02OaqoZKEwAAAAAUoNIEAAAAVE2txpimEvFOAgAAAEABKk0AAABA5VgyY5rKQqUJAAAAAApQaQIAAAAqxjUxe16JqDQBAAAAQAEqTQAAAEDFmNnzSsU7CQAAAAAFOtJpsn2p7Zttr7f9VdsL8/U9ti+3/TPbv7T91k60DwAAADiY2ZZr7Vtmmk5Vmq6WdHxEnCDpFkljnaOXS+qLiMdLerKkP7a9qiMtBAAAAA5SWeem1rZlpunIK46Ib0fESP70WkkrxjZJmmO7W9IsSUOSdnagiQAAAAAg6cCYCOJ1kj6fP/6SpDMkbZI0W9JfRsS2ZiHb50g6R5JWrlw5Dc0EAAAADg4z9TK6dmlbp8n2NZIOa7Lp/Ij4er7P+ZJGJF2RbztZ0qikIyQtkvRD29dExB3jDxIRayWtlaQ1a9ZE+a8AAAAAANrYaYqIU4u22z5b0gslnRIRY52eV0r614gYlvSA7R9JWiPpEZ0mAAAAABMwlaYydWr2vNMkvVnS6RGxt2HTPZKe7cwcSU+VdHMn2ggAAAAAUufGNP2TpD5JV9uWpGsj4lxJH5T0cUk/l2RJH4+I9R1qIwAAAHBwqtWyBaXoSKcpIo6aYP1uZdOOAwAAAMAB4UCYPQ8AAABAiWwrv6ILJaBmBwAAAAAFqDQBAAAAFWNbZkxTaXgnAQAAAKAAlSYAAACgYlzjPk1lotIEAAAAAAWoNAEAAABVw32aSsU7CQAAAAAFqDQBAAAAFZPNnseYprJQaQIAAACAAlSaAAAAgIqxLZv6SFl4JwEAAACgAJUmAAAAoGpqzhaUgkoTAAAAABSg0gQ0cfPLn5ucXXne65Jy2w87Nvmc27oOSc4OjvYlZ5d0b03O7lN/cnbn8Lzk7N6R3uTsjXektfkxy0eTz3n43F3J2UNrm5Kz3aNDydmBnil8PjEnOTsSXcnZvlra6108dF/yOR2RnB3sSX+fhrvSf+Y3DR6anP3hz9N/5lctn9rfeM98Gn9txwxUq8ncp6k0vJMAAAAAUIBKEwAAAFAxtrhPU4moNAEAAABAASpNAAAAQNW4li0oBe8kAAAAABSg0gQAAABUjGtmTFOJ6DQBAAAAVeOaxJTjpeGdBAAAAIACVJoAAACAirElm8vzykKlCQAAAAAKUGkCAAAAqqbGmKYy8U4CAAAAQAEqTQAAAEDF2Ew5XiY6TUAT9fd8Ijk7OHBHUm5P94Lkc0ak/0ex5npydm/MSc52eyQ5O7d7T3J2cc+25OwRx3Ul5bqm8Fq76unZEfd25LxLd6T9DEjSrrmHpWe7FiVn+2NvUm5bb3p759R3JmdHaumf7VT+e7G4d0dy9sVP3p6c7ddAcjZz1BTzAGY6Ok0AAABA1biWLSgF7yQAAAAAFKDTBAAAAFRNTVLN7VtaYPs027+yfZvttzTZ/ke2N9u+MV/e0LDtbNu35svZ5b0xabg8DwAAAECpbHdJ+qCk50jaIOk62+si4hfjdv18RJw3LrtY0tslrZEUkm7Isw9OQ9ObotIEAAAAVI1rchuXFpws6baIuCMihiR9TtIZLbb+eZKujohteUfpakmnJb0PJaHTBAAAAGB/LbV9fcNyzrjtyyXd2/B8Q75uvJfaXm/7S7aP3M/stOHyPAAAAKBq3PrYo0RbImJNUQuarItxz/9F0mcjYp/tcyVdLunZLWanFZUmAAAAAGXbIOnIhucrJG1s3CEitkbEvvzpP0t6cqvZ6UanCQAAAKgY1yzXam1bWnCdpKNtr7bdK+kVktY9rI324Q1PT5f0y/zxVZKea3uR7UWSnpuv6xguzwMAAABQqogYsX2ess5Ol6TLIuIm2xdKuj4i1kn6c9unSxqRtE3SH+XZbbYvUtbxkqQLI2LbtL+IBnSaAAAAgKqxs6WDIuJKSVeOW3dBw+O3SnrrBNnLJF3W1gbuBzpNQBOLR+5Pzm6ZvTIp163h5HMeMrwhObul54jkrKcwJrNHQ8nZPo0mZ+vqmvZs7+hg8jkXPnhncna0Z1ZyVq1NJ9vUvr75ydmhrim0eQruGzk0KTc40pt8zvm9/cnZWUr/Tu2rp7c5mo7Nbk33FH5uBzQ7OQsAZaDTBAAAAFSNa1JrY4/QAt5JAAAAAChApQkAAAComgNgTFOVUGkCAAAAgAJUmgAAAICKGbtPE8rBOwkAAAAABag0AQAAAFXj2pRuH4GHo9MEAAAAVI0t1ZgIoix0PwEAAACgAJUmAAAAoGLsmszleaXhnQQAAACAAlSaAAAAgKqpiTFNJaLTBDTRt29ncna7Hp2Um9U9mHzOwzbfkJydPXtzcnbLoqOSs8PqnUJ2dnJ26+D85Gx/10hSbnYt/fs00jc3PdszKzm7p3dhcnbYfcnZoZjC9yLS/5e2rHdrUm6Wdyefc1fXouRst4eTs/21geTslpGlydnervQ2Lx65PzmbOWKKeQAzHZ0mAAAAoGqYcrxUvJMAAAAAUIBKEwAAAFA1dragFFSaAAAAAKAAlSYAAACgamypRn2kLLyTAAAAAFCAShMAAABQNcyeVyreSQAAAAAoQKUJAAAAqJqaswWl6FilyfZFttfbvtH2t20fka+37X+0fVu+/UmdaiMAAAAAdPLyvEsj4oSIOFHSNyRdkK9/vqSj8+UcSR/uUPsAAACAg1TtoXFN7VhmmI694ojY2fB0jqTIH58h6ZORuVbSQtuHT3sDAQAAAEAdHtNk+2JJZ0naIelZ+erlku5t2G1Dvm7TuOw5yipRWrlyZdvbipnl/rmPSc4u1Zak3Nx9Dyafc/MRT0jOLtu0PjnbvWAoOTtS60nO9ng4OXtY/9bkbG8MJuX21WYnn3No7qzk7LB6k7N7RtPbPLtrIDnb7ZHkbGj6r92fs+eB5OysrvSf+V2zD0nO+jd/o9x/87t3JWe7p/Bz2z2S9rMHzGhWdq8mlKKtlSbb19j+eZPlDEmKiPMj4khJV0g6byzW5FCP+C98RKyNiDURsWbZsmXtexEAAAAAZrS2Vpoi4tQWd/2MpG9KeruyytKRDdtWSNpYctMAAACA6qrVsgWl6OTseUc3PD1d0s3543WSzspn0XuqpB0RsekRBwAAAACAadDJMU2X2D5GUl3S3ZLOzddfKekFkm6TtFfSazvTPAAAAOAgZTOmqUQd6zRFxEsnWB+S3jjNzQEAAACApjo6ex4AAACANpih91NqF95JAAAAAChApQkAAACoGpvZ80pEpwkAAACoGiaCKBXdTwAAAAAoQKUJAAAAqBomgigVnSagiaF6b3J26b57k3JR60o+51TUe/uTs131keTs6BReb5dGk7O9MZicHXba92KgPjv5nLuHZyVnF/TsTs7O6kp/n7o1nH7e0fQ2D3bPSc6ORtr/Dof65iWfs15L/19wLdJ/BmpRT87OUvrn0xXp/70Y6FuQnAWAMtBpAgAAAKrGYkxTiajZAQAAAEABKk0AAABA1bjGlOMl4p0EAAAAgAJUmgAAAICKCVvBmKbSUGkCAAAAgAJUmgAAAICq4T5NpeKdBAAAAIACVJoAAACAqrGpNJWIdxIAAAAAClBpAgAAACqG2fPKRacJaOL2B5ckZ3fNnZ2UO6LvvuRz1qdQfh/un5+cHeyek5zdM5r2PknSoq4Hk7NTMaKepNyu4fTXev+u9OyhSzYnZ+cMbU/Obu5Znpzd5XnJ2fpI+s9Bj0eScjtnLUs+52B9VnJ253D6z96Cnt3J2anorqW9xwBwIKDTBAAAAFQOs+eViXcSAAAAAArQaQIAAACqxm7v0lITfJrtX9m+zfZbmmz/K9u/sL3e9ndsP6ph26jtG/NlXYnvTBIuzwMAAABQKttdkj4o6TmSNki6zva6iPhFw27/LWlNROy1/SeS/l7SH+bbBiLixGltdAE6TQAAAEDV1CzVOnpR2cmSbouIOyTJ9ucknSHpN52miPi3hv2vlfTqaW3hfuDyPAAAAAD7a6nt6xuWc8ZtXy7p3obnG/J1E3m9pG81PO/Pj3ut7ReX1OZkVJoAAACAipmG+zRtiYg1BdubnTya7mi/WtIaSc9sWL0yIjbafrSk79r+WUTcnt7cqaHSBAAAAKBsGyQd2fB8haSN43eyfaqk8yWdHhH7xtZHxMb83zskfU/SE9vZ2MnQaQIAAACqxrX2LpO7TtLRtlfb7pX0CkkPmwXP9hMlfURZh+mBhvWLbPflj5dKepoaxkJ1ApfnAQAAAChVRIzYPk/SVZK6JF0WETfZvlDS9RGxTtKlkuZK+qKzSwnviYjTJT1O0kds15UVeS4ZN+vetKPTBAAAAFSOFa1VhNomIq6UdOW4dRc0PD51gtyPJT2+va3bP1yeBwAAAAAFqDQBTXzjqm3J2VecPj8pN9LXk3zOBwaXJGdH56b/Z6A3BpOzh+nXydnuoaHk7M7epcnZeqT9namvazj5nMcuecSY2ZYt3JOe7R5J/2x7e5clZ1PfY0nqro0mZ3ud9p2qR1fyOQfrfcnZLXtnJ2frs9Lf44W9u9LPO4W/0w7Ve5OzwIxlZwtKQacJAADUCm+qAAAgAElEQVQAqJhwreOX51UJ7yQAAAAAFKDSBAAAAFQNl+eVikoTAAAAABSg0gQAAABUjd3qTWjRAt5JAAAAAChApQkAAAComLAVjGkqDZUmAAAAAChApQkAAAConBpjmkrEOwkAAAAABag0AQAAABUTskKMaSoLnSagiTUnLZtCel9SauNg+jkHhtN/lA/pi+Tsg7E4OTu/e2dydtG+HcnZ/u49ydl6bV5Sbn7XruRz9tX3JmfrtfTvxa65hyVnrfTvVJdHk7PdHknODtT7k3KzaoPJ56y5npyd1zecnO3vHkrO9jn99U5Fby3tv6sPOaSUdgCYueg0AQAAABWTzZ7HSJyy8E4CAAAAQAEqTQAAAEDVmNnzysQ7CQAAAAAFqDQBAAAAVWMrzOx5ZaHSBAAAAAAFqDQBAAAAFcPseeXinQQAAACAAlSaAAAAgMqxxJim0lBpAgAAAIACVJoAAACAignXGNNUIjpNQBNrVm9PzlqRlBuJ9P+wzeoaTs7+bOuR6dlbRpOzLzw5/fUurt+bnK1Fepu3DS1IyvV3DyWfcyrXAwzOmpOcTf0eS9Jg9KdnR/uSs4u6H0zO9ngkKdcXA8nn7Pfe5OysWYPJ2aF6b3J2dAq/NvRqX3I2xCVGADqLThMAAABQMSHzB4cSUbMDAAAAgAJUmgAAAICK4T5N5aLTBAAAAFSNmXK8THQ/AQAAAKAAlSYAAACgYkI1BfWR0vBOAgAAAECBjnSabF9ke73tG21/2/YR+fpX5evX2/6x7Sd0on0AAADAQc3OJ4NozzLTdKrSdGlEnBARJ0r6hqQL8vV3SnpmRJwg6SJJazvUPgAAAACQ1KExTRGxs+HpHCm79XxE/Lhh/bWSVkxnuwAAAIAqYMrxcnVsIgjbF0s6S9IOSc9qssvrJX2rIH+OpHMkaeXKle1oIgAAAAC07/I829fY/nmT5QxJiojzI+JISVdIOm9c9lnKOk1vnuj4EbE2ItZExJply5a162UAAAAAB52Q27rMNG2rNEXEqS3u+hlJ35T0dkmyfYKkj0p6fkRsbVPzgEL7RnuSszXXk3IDI+nn7O8aSc7etSn9P3yrj5z+90mS9sxakpwdqfUmZ+fWBtJy3pV8zlqMJmc79T+1Lqd/H2td6d+Lqehy2vt8z+Dy5HMe0f9AcnbJvo3J2c296Ve+92goOds7mvbzI0lDXbOSswBQho5cnmf76Ii4NX96uqSb8/UrJX1F0msi4pZOtA0AAAA42IVqjGkqUUudJtuPlfRhSYdGxPF5Nej0iHhX4nkvsX2MpLqkuyWdm6+/QNISSR9yNpXhSESsSTwHAAAAAExZq5Wmf5b015I+IkkRsd72ZyQldZoi4qUTrH+DpDekHBMAAABAJqwZeT+ldmm1Zjc7Iv5r3Lr0i9YBAAAA4CDRaqVpi+3HKL+fku2XSdrUtlYBAAAASDZTZ7lrl1Y7TW+UtFbSb9n+taQ7Jb26ba0CAAAAgANES52miLhD0qm250iqRUT6/LkAAAAA2svMnlemwk6T7b+aYL0kKSLe14Y2AQAAAMABY7JK07z832MknSRpXf78RZJ+0K5GAQAAAEjHmKZyFXaaIuKdkmT725KeNHZZnu13SPpi21sHAAAAAB3W6kQQKyUNNTwfkrSq9NYAAAAAmLKwGdNUolY7TZ+S9F+2v6ps2vGXSPpk21oFdFh3Lf02ZIf0bEnK9XYNJJ9zqGtWcvYFx/clZ3u1Lzk7op7k7MBvrhzef90aTs72JGb7RvYmn7Ornt7ePb0Lk7PO7jCRZP7AA8nZ/p45ydmhrv7k7IOji5Jyv/x1ent7Vy5Ozi4e/XVy9rC9tydn9/Wm/+zt7Z2fnHWkfx8BoAwtdT8j4mJJr5X0oKTtkl4bEe9uZ8MAAAAApBkb09Su5WBk+/XjnnfZfnsr2ZY6TbZXStoi6av5sjVfBwAAAAAHg1NsX2n7cNvHS7pWau3ylVYvz/um9JtrNWZJWi3pV5KO29+WAgAAAGivOADu02T7NEkfkNQl6aMRccm47X3Khvw8WdJWSX8YEXfl294q6fWSRiX9eURcNdX2RMQrbf+hpJ9J2ivpzIj4USvZVi/Pe3xEnJAvR0s6WdK/J7cYAAAAQGXZ7pL0QUnPl3SspDNtHztut9dLejAijpL0fknvzbPHSnqFsgLNaZI+lB9vqm06WtKbJH1Z0l2SXmN7divZpO5nRPxE2X2bAAAAABxwOj6m6WRJt0XEHRExJOlzks4Yt88Zki7PH39J2eVzztd/LiL2RcSdkm7LjzdV/yLp7yLijyU9U9Ktkq5rJdjS5Xm2/6rhaU3SkyRt3s9GAgAAAJgG2ZTjbZ2wYant6xuer42ItQ3Pl0u6t+H5BklPGXeM3+wTESO2d0hakq+/dlx2eQltPjkidubnC0n/x/a6sY22nxMRVzcLtjqmqXGA1IiyMU5fTmwsAAAAgIPblohYU7C9WY9t/P0DJtqnlex+G+swjVt3a8PT90qaUqfpFxHxxcYVtl8u6YsT7A8AAACgQyKkiI5ODb5B0pENz1dI2jjBPhtsd0taIGlbi9l2mPANa3VM01tbXAcAAAAA10k62vZq273KJnZYN26fdZLOzh+/TNJ388vm1kl6he0+26slHS3pv6ahzRNWsworTbafL+kFkpbb/seGTfOVXaYHAAAA4AATqinS5nwr5/zZGKXzJF2lbMrxyyLiJtsXSro+ItZJ+pikT9m+TVmF6RV59ibbX5D0C2V9jjdGxGhHXkhussvzNkq6XtLpkm5oWL9L0l+2q1EAAAAADm4RcaWkK8etu6Dh8aCkl0+QvVjSxWW0w/ZJku6NiPvy52dJeqmkuyW9IyK25bveNdExCjtNEfFTST+1fUVEUFkCWtA/sicpN3tg2+Q7TWDLvEclZ0cj/bYHg5qVnJ0KO30s6MLB+5Kzhz1wW1Ju77LVyed01JOzc5KTUzPY29LN1Zvqqqf/r6ZvZG/6eWtpf8CMKQxLvvWBBcnZw444JDm7afiw5OzWvS3dzqSpZz/wleTswPeuSc5Kki5YO/k+QMXsx9TgM8FHJJ0qSbafIekSSX8m6URJa5VdGqiI+B8THWCyy/O+EBF/IOm/3eS3lIg4IbnpAAAAANB+XQ3VpD9UNj36lyV92faNrRxgssvz3pT/+8LEBgIAAACYZlSaHqbLdnd+5dwpks5p2NbSbOKFo8MiYlP+8E8j4u7GRdKfJjUZAAAAAKbPZyV93/bXJQ1I+qEk2T5K0o5WDtDqlBrPabLu+S1mAQAAAEyzsWpTO5aDST6pxP+S9AlJv5tPay5lfaE/a+UYk41p+hNlFaVH217fsGmepB/tb4MBAAAAYLpFxLVN1t3San6ya/g+I+lbkt4j6S0N63c1DKYCAAAAcAA5GCtCB7LJphzfoew6vzMlyfYhkvolzbU9NyLuaX8TAQAAAKBzWpotwvaLJL1P0hGSHpD0KEm/lHRc+5oGAAAAIEWEFUGlqSytTgTxLklPlXRLRKxWNlUfY5oAAAAAVF6rnabhiNgqqWa7FhH/puwOugAAAAAOMO2cOW8mjpVq6fI8Sdttz5X0A0lX2H5A0kj7mgUAAAAAB4ZWO01nSBqU9JeSXiVpgaQL29UooNMe2D03Odszf0VS7jGxJfmcc4e3J2fVszA5OqKe5Ox9A0uSs+9+783J2ee+5KTk7BsHv5uU27r2U8nndK3VCwIeacVpv5OcjVXHJGfrvf3J2aFZ6d/H7uG9ydnD5qa9zyevTj6ldg+nv0+v/stNk+80oalk0/3uRYckZ6+96PtTOvfvXzClOHBQmqkVoXZpqdMUEXsanl7eprYAAAAAwAFnspvb7pIUzTZJioiY35ZWAQAAAEhGpalck92nad50NQQAAAAADkStjmkCAAAAcLAIcZ+mEqWPMAYAAACAGYBKEwAAAFAxdVl1xjSVhkoTAAAAABSg0gQAAABUDLPnlYtKEwAAAAAUoNIEAAAAVEyEmT2vRHSaAAAAgMrh8rwy0WkCmujvGU3O3r877Z7QCxasTj5n/+ie5OyIepKzA/X+5Oz7P3hPcnbv9p3J2f/84d3J2Ree95qk3Kr+2cnnvPWyryVnBzdsTM7OWnZYcnZk9vzk7M7ZhyZn5+x7MDnbv29HUm7ZrPT/jX79hqOTs53yP97wjOTslnl3JWdP+dy5yVkAKAOdJgAAAKBiuDyvXEwEAQAAAAAFqDQBAAAAFRMSY5pKRKUJAAAAAApQaQIAAAAqJsSYpjJRaQIAAACAAlSaAAAAgIqp5wvKQaUJAAAAAApQaQIAAACqhvs0lYpKEwAAAAAUoNIEAAAAVEzI3KepRHSagCZOjh8nZ+9f8JgSW9KavpG9ydmRWm9y9mdbj0jObt1wU3J2Kt70Pw9JzvbqvqTcHSe8PPmccz/w+8nZ3fWh5OzeGE3OdtVHkrMDnpOc/drtRydnf3DN7Um5l7zsqORzfueL30/OTsUzX/LU5Ozpx9+VnK2rKzl714npP0OS9FtTSgMAnSYAAACgcoIxTaViTBMAAAAAFKDSBAAAAFRMSIxpKhGVJgAAAAAoQKUJAAAAqJh6ZAvKQaUJAAAAAAp0rNNk+yLb623faPvbto8Yt/0k26O2X9apNgIAAAAHJ//mXk3tWGaaTlaaLo2IEyLiREnfkHTB2AbbXZLeK+mqTjUOAAAAAKQOjmmKiJ0NT+com+RjzJ9J+rKkk6a1UQAAAEAFcJ+mcnV0IgjbF0s6S9IOSc/K1y2X9BJJz1ZBp8n2OZLOkaSVK1e2va0AAAAAZqa2Xp5n+xrbP2+ynCFJEXF+RBwp6QpJ5+Wxf5D05ogYLTp2RKyNiDURsWbZsmXtfBkAAADAQSWivctM09ZKU0Sc2uKun5H0TUlvl7RG0udsS9JSSS+wPRIRX2tPK4FH2vPxDydnZw+PJOV6/vxtyees1dPOKUnzBrckZz9w8abk7FS86fynJ2cX9d6fnN2079Ck3OK+HcnnHFFPcvan21cnZ2f3Fv7dqtDi/j3JWaV/lXXvhr3J2Qfu/HVS7iOXpuWm6hkvfmpy9vd/eyg5OxCzk7NTcdjQ3VM8wopS2gFg5urY5Xm2j46IW/Onp0u6WZIiYnXDPp+Q9A06TAAAAEDr6rLqM3CWu3bp5JimS2wfI6ku6W5J53awLQAAAECFMBFEmTo5e95LW9jnj6ahKQAAAAAwoY7OngcAAACgfDN1woZ26eTNbQEAAADMQLYX277a9q35v4ua7HOi7f+wfZPt9bb/sGHbJ2zfafvGfDmxne2l0wQAAABUTMhtXUrwFknfiYijJX0nfz7eXklnRcRxkk6T9A+2FzZs/+uIODFfbiyjUROh0wQAAABgup0h6fL88eWSXjx+h4i4ZWy27YjYKOkBSR25QSudJgAAAKBi6tHeRdJS29c3LOfsZxMPjYhNkpT/e0jRzrZPltQr6faG1Rfnl+2933bffp5/vzARBAAAAID9tSUi1hTtYPsaSYc12XT+/pzI9uGSPiXp7Iio56vfKuk+ZR2ptZLeLOnC/Tnu/qDTBAAAAFRMNnteZ+/TFBGnTrTN9v22D4+ITXmn6IEJ9psv6ZuS3hYR1zYce1P+cJ/tj0v63yU2/RG4PA8AAADAdFsn6ez88dmSvj5+B9u9kr4q6ZMR8cVx2w7P/7Wy8VA/b2djqTQBTezdsis5e8sXbp98pyZO/Iv0H8d7e45Nzv7w5gXJWekHU8imW7VoZ3J26775ydk5PfuScvVI//vUQMxKzk7l/hz37+hNzu7el/5dPn7JhuTs449dmZz9z2+l5d74lmckn/O3DtmanN20K/07tXso/bL/btcn32kCC3rSf27r7krOAjPWgX+fpkskfcH26yXdI+nlkmR7jaRzI+INkv5A0jMkLbH9R3nuj/KZ8q6wvUySJd0o6dx2NpZOEwAAAIBpFRFbJZ3SZP31kt6QP/60pE9PkH92Wxs4Dp0mAAAAoGLqsurl3E8JYkwTAAAAABSi0gQAAABUTOiAH9N0UKHSBAAAAAAFqDQBAAAAFRPhjt+nqUqoNAEAAABAASpNAAAAQMVESHXGNJWGShMAAAAAFKDSBAAAAFRMBLPnlYlKEwAAAAAUoNIENHHLF26f9nPGFO7aPVzvSs5+5aM/SM5OxZ+++RnJ2aHRPcnZuT2DydnZXQNJuUN3p3+fuofTzilJ+xY8NTl7V31+cnbz9vS/x+1cMC85e9KKTcnZr644LCn37MU/ST6nh9P/BLy957jkbK2Wft653ek/e0sGNiRne4d2J2eBmSrkKf1ugYej0gQAAAAABag0AQAAABVTZ/a8UlFpAgAAAIACVJoAAACAqmH2vFJRaQIAAACAAlSaAAAAgIoJUWkqE50mAAAAoGLqYdWDKcfLwuV5AAAAAFCAShMAAABQMcFEEKWi0gQAAAAABag0AQAAABVDpalcdJqAkv3OO56dlBsa3Zd8zmW925Kzb7vot5Oz83qHkrMn7L4yOXtnz0nJ2a2D85KzD4ymZRf33pd8zq7R9Pf4mD3XJWd/q5Z+3l+u/N3k7Ge/05ucfdwxi5Kzf3vji5Nyt7+mnnzOx3/4ncnZwxYfnpytR/pFJnO0Kzm7t29hcnbbrOXJWUmaP6U0ANBpAgAAAConQqpTaSoNY5oAAAAAoACVJgAAAKBiIqzgPk2lodIEAAAAAAWoNAEAAAAVE2L2vDJRaQIAAACAAlSaAAAAgIqpM3teqag0AQAAAEABKk0AAABA1QRjmspEpQkAAAAAClBpAppY/qxDkrP9K5cn5Xp2bkw+546ly5Kzj553X3J25R3fTc5+5wXvSc6ecsX/TM7e+eQzk7PdGknK1QaGk8+5r29+erZnTnK2u57e5kU925OzL33W4uTs0OhAcnb17x2TlJv/tN9OPuc9i49PzvZoKDk7q747OTvUNSs5W6/1JGf76umfLTBTBZWmUlFpAgAAAIACVJoAAACAimH2vHJRaQIAAACAAlSaAAAAgIoJMaapTFSaAAAAAKAAlSYAAACgYqIu1eudbkV1UGkCAAAAgAJUmgAAAICK4T5N5aLSBAAAAAAFqDQBAAAAFUOlqVx0mgAAAICK4ea25aLTBDQxvHc4Ofvd130qKbdo/ZuSz/k3f/GT5OxUvPVf39OR89YPXZGcjXBy9tAdNyflts9fmXzOcPpV1AOek5ydVduTnK1P4crvhT27krPuTf/t4JbXfDg5m2q5NiVnh9SXnu2alZwNpf/8bB9ZmJztraX/NxkAykCnCQAAAKicUHB9XmmYCAIAAAAAClBpAgAAACqGiSDKRaUJAAAAAApQaQIAAAAqpl7PFpSDShMAAAAAFKDSBAAAAFQMY5rK1ZFKk+2LbK+3faPtb9s+omHb7+Xrb7L9/U60DwAAAED72F5s+2rbt+b/Lppgv9G8b3Cj7XUN61fb/s88/3nbve1sb6cuz7s0Ik6IiBMlfUPSBZJke6GkD0k6PSKOk/TyDrUPAAAAOGhFSPU2LiV4i6TvRMTRkr6TP29mICJOzJfTG9a/V9L78/yDkl5fSqsm0JFOU0TsbHg6R9LYW/9KSV+JiHvy/R6Y7rYBAAAAaLszJF2eP75c0otbDdq2pGdL+lJKPkXHJoKwfbHteyW9SnmlSdJjJS2y/T3bN9g+qyB/ju3rbV+/efPm6WgyAAAAcFAIPTSuqR2LpKVjv4vnyzn72cRDI2KTJOX/HjLBfv358a+1PdYxWiJpe0SM5M83SFq+n+ffL22bCML2NZIOa7Lp/Ij4ekScL+l822+VdJ6kt+ftebKkUyTNkvQftq+NiFvGHyQi1kpaK0lr1qxhmBtKdd8H/j05+5wtl0++U7PcW25MPmenPOufX5mc3fq09Ktv76nNT87uHZmVnL1p9m8n5eZ6IPmcs7w3Odut4eRs30j6eWtdo8nZfbX0z6em9Ll1D++/P+2ckX7OkJOz/ZH++czetz05W6+l/9pwv5YlZyPS3ysAbbMlItYU7VDUH9iP86yMiI22Hy3pu7Z/Jmlnk/3a2h9oW6cpIk5tcdfPSPqmsk7TBmUfwB5Je2z/QNITJD2i0wQAAACguaiHoqTBR8ltKOgP2L7f9uERscn24ZKaDsuJiI35v3fY/p6kJ0r6sqSFtrvzatMKSRtLfwENOjV73tENT0+XdHP++OuSnm672/ZsSU+R9Mvpbh8AAACAtlon6ez88dnK+gEPY3uR7b788VJJT5P0i4gISf8m6WVF+TJ16j5Nl9g+RlJd0t2SzpWkiPil7X+VtD7f9tGI+HmH2ggAAAAclEqc5a5dLpH0Bduvl3SP8lmzba+RdG5EvEHS4yR9xHZdWbHnkoj4RZ5/s6TP2X6XpP+W9LF2NrYjnaaIeGnBtkslXTqNzQEAAAAwjSJiq7J5DMavv17SG/LHP5b0+Anyd0g6uZ1tbNSpShMAAACAdnloljuUoGNTjgMAAADAwYBKEwAAAFAx9QjVD/BBTQcTKk0AAAAAUIBKEwAAAFAxwZimUlFpAgAAAIACVJqAJt77jh+lZ3VUUu5Vb3x68jkXzU//U9JxhzS9AXdLbhp9QnK2FvXk7HztSs4u6N6ZnB2OnqRcfQp/nxpR2jklqVvDydm9PfOTs32je5OzU2Gl/xzUI+0z2hNzk8/Z74HkrN2VnB3oTf9sR2vp38e5kf56F8S25Gxm0RTzwMGHSlO5qDQBAAAAQAEqTQAAAEDFRITqlJpKQ6cJAAAAqJgIaQpXwmMcLs8DAAAAgAJUmgAAAICKiQgFl+eVhkoTAAAAABSg0gQAAABUTL2eLSgHlSYAAAAAKEClCQAAAKiY7Oa2jGkqC5UmAAAAAChApQkAAAComAipTqGpNHSagJL91d89PSl3/JJ7ks+5ed/i5Ozu4VnJ2eN3/3tytt7Vm5zdO3tpcnZf9+zk7LyRbUm5uTs2JJ9z58JHJWen8loHlf692FJP/3wWdu1Izh667ZfJ2V3zVyTlRrp7ks/ZVx9Izm4aXZ6c3TXcl5xd1Lfn/7d398G21XUdx98fud4UebC4KPLUNcIHSrzqzbAcRURTmoBIQ3rQLLuj5R/FJGo0PQjOYNrQEI0T1hTNGKTMMKKQFOYjaXqjy+UiKNcrXIgHgVKeCoX97Y+9rmwO+yz2PWfts89Z5/2aWcNev/Wwf/vLvb9zf+ez1toLPnbvPe5b8LEPZeHjhSR1wUmTJEmS1DNVRRk1dcZ7miRJkiSphUmTJEmS1DPDp+fNuhf9YdIkSZIkSS1MmiRJkqSeqUEx8J6mzpg0SZIkSVILkyZJkiSpZ4qivKmpMyZNkiRJktTCpEmSJEnqmRoMF3XDpEmSJEmSWpg0SZIkST0zqGLgPU2dcdIkjfGFj798Bu966IKPfFaHvdg9x83kXfedybsuxgsWfOReHfZiZVjE/93DFv53aO8FHnfggt9xcQ6Z0fvCkxZx7H6d9UKSlpqTJkmSJKlnqnx6Xpe8p0mSJEmSWpg0SZIkST1TBYOBSVNXTJokSZIkqYVJkyRJktQzVcNF3TBpkiRJkqQWJk2SJElSz9SgKO9p6oyTJkmSJKln/HLbbnl5niRJkiS1MGmSJEmS+qa8PK9LJk2SJEmS1MKkSZIkSeoZHwTRLZMmSZIkSWph0iRJkiT1zKCGi7ph0iRJkiRJLUyaJEmSpJ6pwnuaOmTSJEmSJEktTJokSZKkvqmiyqSpKyZNkiRJktTCpEmSJEnqmcGgGHhPU2dMmiRJkiSphZMmSZIkqWequadpWstiJfmhJP+S5Ibmvz84Zp9XJNkysvxfkhObbX+X5Jsj2zYsulMtnDRJkiRJWmrvAj5VVYcDn2rWH6WqPl1VG6pqA3AM8ADwzyO7vGPX9qraMs3Oek+TJEmS1DNVtdy/p+kE4Ojm9fnAZ4B3tuz/OuCfquqB6XZrPJMmSZIkSbtrXZLNI8um3Tz+6VV1G0Dz36c9zv5vAC6Y0/beJFuTnJ3kB3bz/XeLSZMkSZLUMzWYetJ0V1VtbNshyRXAAWM2nb47b5TkGcDzgMtHmt8N3A6sBc5jmFK9Z3fOuzucNEmSJEnqXFUdO9+2JHckeUZV3dZMir7VcqpfBC6uqu+NnPu25uWDSf4W+L1OOj0PL8+TJEmSeqYKBlVTWzpwCfCm5vWbgI+17HsKcy7NayZaJAlwIrCti07Nx0mTJEmSpKV2FvCqJDcAr2rWSbIxyV/v2inJeuAQ4LNzjv9wkmuAa4B1wJnT7KyX50mSJEk9swT3NC1KVd0NvHJM+2bgLSPrNwIHjdnvmGn2by6TJkmSJElqYdIkSZIk9UxRVDf3HokZJk1Jzmieq74lyT8nObBp3zfJx5NcneTaJG+eVR8lSZIkaZaX572/qo6sqg3AJ4A/bNp/G/hqVT2f4bcE/1mStTPqoyRJkrTiDAY11WW1mdnleVV1z8jqU4Bd1S9g7+bxgXsB/w08tMTdkyRJklauZf4giJVmpvc0JXkv8EbgO8ArmuZzGT63/VZgb+DkqhqMOXYTsAng0EMPXZL+SpIkSVp9pnp5XpIrkmwbs5wAUFWnV9UhwIeBtzeH/QywBTgQ2ACcm2SfueeuqvOqamNVbdx///2n+TEkSZKkFWXXgyCmtaw2U02aqurYCXf9B+BS4I+ANwNn1fD/xvYk3wSeA3x5Or2UJEmSpPnN7PK8JIdX1Q3N6vHA9c3rnQy/6OrzSZ4OPBvYMYMuSpIkSSvS8MttH3OHixZolvc0nZXk2cAAuAl4a9N+BvB3Sa4BAryzqu6aUR8lSZIkrXKzfHreL8zTfivw6iXujiRJktQbq/XR4NMyy+9pkiRJkqRlb6aPHJckSZI0Bav0KXfTYtIkSZIkSS1MmiRJkqSeqSrKe5o6Y9IkSZIkSS1MmiRJkqSeqQEmTR0yaZIkSZKkFiZNkiRJUs8MasCgBrPuRm+YNEmSJElSC9OCrV0AAA2BSURBVJMmSZIkqWd8el63TJokSZIkqYVJkyRJktQ3A5OmLpk0SZIkSVILkyZJkiSpZ6qKKpOmrpg0SZIkSVILkyZJkiSpZwZVDAZ+T1NXTJokSZIkqYVJkyRJktQz5dPzOmXSJEmSJEktTJokSZKknqkaUOU9TV1x0iRJkiT1jZfndcrL8yRJkiSphUmTJEmS1DNVmDR1yKRJkiRJklqYNEmSJEk9M6gBAx8E0RmTJkmSJElqYdIkSZIk9YxfbtstkyZJkiRJamHSJEmSJPVNFTXwnqaumDRJkiRJUguTJkmSJKlnvKepWyZNkiRJktTCpEmSJEnqmaoB5fc0dcakSZIkSZJamDRJkiRJPTOoYuA9TZ0xaZIkSZKkFiZNkiRJUs8Mn57nPU1dMWmSJEmSpBYmTZIkSVLf+D1NnTJpkiRJkqQWJk2SJElSz/g9Td0yaZIkSZKkFk6aJEmSpJ6pquYJetNZFivJ65Ncm2SQZGPLfq9J8rUk25O8a6T9mUn+PckNSf4xydpFd6qFkyZJkiRJS20bcBLwufl2SLIH8JfAa4EjgFOSHNFsfh9wdlUdDvwP8BvT7KyTJkmSJKlndn1P07QWIIvqX9V1VfW1x9ntxcD2qtpRVd8FLgROSBLgGOCiZr/zgRMX05/H46RJkiRJ6pevfufuLVM7+f337ABYm2TzyLJpCm91EHDzyPotTdt+wLer6qE57VPj0/MkSZKkfvngHTsvfd8Bh/4sT9jjBzo/+c03nA/w1qq6sm2/JFcAB4zZdHpVfWyCtxqXZlVL+9Q4aZIkSZJ6pKruXf/cTdy+81IOfOZJnZ77/nt28PBDD/B4E6amH8cu8u1uAQ4ZWT8YuBW4C3hqkjVN2rSrfWq8PE+SJEnqmZuu/9A+d+y8lMHDD3Z63ptvOJ9DDn9jp+ds8RXg8OZJeWuBNwCXVFUBnwZe1+z3JmCS5GrBnDRJkiRJPVNV9+5/0DHcvvPSzs65K2XaeuXbF/UQCIAkP5/kFuAlwKVJLm/aD0xyGUCTIr0duBy4DvhIVV3bnOKdwKlJtjO8x+lvFtunNl6eJ0mSJPXQTdd/aJ899z7snq7ubeoyZaqqi4GLx7TfChw3sn4ZcNmY/XYwfLrekjBpkiRJknqoy7Spy5RpJXLSJEmSJPVUV/c2LfG9TMuOkyZJkiSpp7pIm1Z7ygROmiRJkqReW2zatNpTJnDSJEmSJPXaYtImU6YhJ02SJElSzy00bTJlGnLSJEmSJPXcQtImU6ZHOGmSJEmSVoHdTZtMmR7hpEmSJElaBXYnbTJlejQnTZIkSdIqMWnaZMr0aE6aJEmSpFVikrTJlOmxnDRJkiRJq8jjpU2mTI8180lTkt9LUknWNetJck6S7Um2JnnhrPsoSZIk9UVb2mTKNN5MJ01JDgFeBewcaX4tcHizbAI+OIOuSZIkSb01X9pkyjTerJOms4HTgBppOwH4+xr6EvDUJM+YSe8kSZKkHhqXNpkyzW9mk6YkxwP/VVVXz9l0EHDzyPotTdvc4zcl2Zxk85133jnFnkqSJEn9MzdtMmWa35ppnjzJFcABYzadDvw+8Opxh41pq8c0VJ0HnAewcePGx2yXJEmSNL+qunf9czdx+85L2Xe/DaZMLaY6aaqqY8e1J3ke8Ezg6iQABwNXJXkxw2TpkJHdDwZunWY/JUmSpNXopus/tM+eex92z7fv2mzK1GIml+dV1TVV9bSqWl9V6xlOlF5YVbcDlwBvbJ6idxTwnaq6bRb9lCRJkvpseG/TK6nB90yZWqRq9le2JbkR2FhVd2UYPZ0LvAZ4AHhzVW1+nOPvBG4as2kdcFfH3e0j6zQ5azUZ6zQ5azUZ6zQZ6zQ5azUZ6/RYP1xV+8+6E1pay2LSNC1JNlfVxln3Y7mzTpOzVpOxTpOzVpOxTpOxTpOzVpOxTtLQrB85LkmSJEnLmpMmSZIkSWrR90nTebPuwAphnSZnrSZjnSZnrSZjnSZjnSZnrSZjnSR6fk+TJEmSJC1W35MmSZIkSVoUJ02SJEmS1KIXk6Ykr09ybZJBko0j7U9Mcn6Sa5Jcl+TdI9tek+RrSbYneddser70Wmr1y0m2jCyDJBuabac0Ndya5JNJ1s3uEyyNBdZpbZLzknw9yfVJfmF2n2DpLKRWI/tckmTb0vd66e1unZLsmeTS5s/StUnOmmX/l8oC/+69qBmjtic5p/m+v96br1bNtiOTfLHZfk2SJzXtjueP3jZfnRzPJ6zVyPZVM55rlaqqFb8AzwWeDXyG4Zfk7mr/JeDC5vWewI3AemAP4BvAjwBrgauBI2b9OWZZqzn7PA/Y0bxeA3wLWNes/ynwx7P+HMutTs36nwBnNq+fsKtmfV8WUqum7STgH4Bts/4My7FOzZj1iub1WuDzwGtn/TmWW52a9S8DLwEC/NNqqFNbrZpxeyvw/GZ9v+bnnuP5BHVqXjueT1irZn1Vjecuq3NZQw9U1XUAY365WMBTkqwBngx8F7gHeDGwvap2NMddCJwAfHWp+jwrLbUadQpwQfM6zfKUJHcD+wDbp9nH5WABdQL4deA5zfEDVsk3qC+kVkn2Ak4FNgEfmWb/lovdrVNVPQB8unn93SRXAQdPuZszt7t1SvIMYJ+q+mKz/vfAiQwnT73WUqtXA1ur6upmv7ub/Z6I4/mosXVqOJ4/2ry1Wo3juVanXlye1+Ii4H7gNmAn8IGq+m/gIODmkf1uado0dDKP/MPte8DbgGuAW4EjgL+ZXdeWle/XKclTm7YzklyV5KNJnj67ri07369V4wzgz4AHZtOdZWtunYDv//n6OeBTS96j5Wm0TgcxHMN3cTyHZwGV5PJmPDoNHM/HGFsnx/Oxxtaq4XiuVWHFJE1JrgAOGLPp9Kr62DyHvRh4GDgQ+EHg8815xv0KszfPXl9grXYd+5PAA1W1rVl/IsMfsi8AdgB/AbwbOLPTTs9Al3Vi+HfpYODKqjo1yanAB4Bf7bLPs9Lxn6kNwI9W1e8mWd91X2ep4z9Tu9rXMJwgnLMrHV/pOq6T4/ljrQFeCvwEw3/IfirJfwCfw/F81Hx1uhrH87nmq9Xd9HQ8l+ZaMZOmqjp2AYf9EvDJ5rdr30pyJbCRYcp0yMh+BzP8rVsvLLBWu7yBR/+me0Nzzm8AJPkI0IsHZ3Rcp7sZ/iC5uFn/KPAbizj/stJxrV4CvCjJjQzHoKcl+UxVHb2I91gWOq7TLucBN1TVny/i3MtKx3W6hUdftuh4PqzJZ6vqLoAklwEvZHh5uuP5I+ar07/ieD7XfLW6j56O59Jcfb88bydwTIaeAhwFXA98BTg8yTOTrGX4Q/iSGfZzWUjyBOD1wIUjzf8FHJFk/2b9VcB1S9235WRcnaqqgI8DRzdNr2QV3CP3eOap1Qer6sCqWs/wN5dfX+0/YOf5u0eSM4F9gd+ZRb+Wm3n+PN0G3JvkqAxvxHgj0JpWrQKXA0dm+ATGNcDLGY5HjuePNrZOjudjzVcrx3OtHrN+EkUXC/DzDH8L8iBwB3B5074Xw98QXctwwHvHyDHHAV9n+BS902f9GWZdq2bb0cCXxhzzVoY/WLcy/EGy36w/xzKt0w8zvPxlK8N7Tw6d9edYrrUa2b6eVfK0pd2tE8PEpJq/e1ua5S2z/hzLrU5N+0ZgWzOenwtk1p9jGdTqV5qffduAPx1pdzyfrE6O5xPWamT7qhnPXVbnkqreXPotSZIkSZ3r++V5kiRJkrQoTpokSZIkqYWTJkmSJElq4aRJkiRJklo4aZIkSZKkFk6aJGmZS3LfFM55fJJ3Na9PTHLEAs7xmSQbu+6bJEnLjZMmSVqFquqSqjqrWT0R2O1JkyRJq4WTJklaITL0/iTbklyT5OSm/egm9bkoyfVJPpwkzbbjmrYvJDknySea9l9Lcm6SnwKOB96fZEuSw0YTpCTrktzYvH5ykguTbE3yj8CTR/r26iRfTHJVko8m2WtpqyNJ0vSsmXUHJEkTOwnYADwfWAd8Jcnnmm0vAH4MuBW4EvjpJJuBvwJeVlXfTHLB3BNW1b8luQT4RFVdBNDMt8Z5G/BAVR2Z5Ejgqmb/dcAfAMdW1f1J3gmcCryniw8tSdKsOWmSpJXjpcAFVfUwcEeSzwI/AdwDfLmqbgFIsgVYD9wH7KiqbzbHXwBsWsT7vww4B6CqtibZ2rQfxfDyviubCdda4IuLeB9JkpYVJ02StHLMGwEBD468fpjh+N62f5uHeOTy7SfN2Vbz9OtfquqUBb6fJEnLmvc0SdLK8Tng5CR7JNmfYfLz5Zb9rwd+JMn6Zv3kefa7F9h7ZP1G4EXN69fNef9fBkjy48CRTfuXGF4O+KPNtj2TPGuCzyNJ0orgpEmSVo6Lga3A1cC/AqdV1e3z7VxV/wv8FvDJJF8A7gC+M2bXC4F3JPnPJIcBHwDeluTfGN47tcsHgb2ay/JOo5mwVdWdwK8BFzTbvgQ8ZzEfVJKk5SRV4660kCT1QZK9quq+5ml6fwncUFVnz7pfkiStJCZNktRvv9k8GOJaYF+GT9OTJEm7waRJkiRJklqYNEmSJElSCydNkiRJktTCSZMkSZIktXDSJEmSJEktnDRJkiRJUov/Bw90m+fBqKAaAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Random snapshot of the forcing for Laure\n", - "from random import randint\n", - "n_times = len(model_output['time'])\n", - "random_time = randint(0, n_times)\n", - "print('Random time index: ', random_time)\n", - "(model_output['S_x'].isel(time_index=random_time)).plot(vmin=-1., vmax=1., cmap='coolwarm')\n", - "plt.legend(r'S_x ($m^4s^{-3})')" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "377\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from random import randint\n", - "random_time = randint(0, n_times)\n", - "print(random_time)\n", - "plot_dataset(model_output.isel(time_index=random_time)[['u_surf', 'v_surf', 'S_x', 'S_y', 'S_xpred', 'S_ypred',\n", - " 'S_xscale', 'S_yscale', 'err_S_x', 'err_S_y']],\n", - " vmin = [-2]*6 + [0., 0., 0., 0.], vmax = [2]*6 + [2, 2,2,2])" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(30, 30))\n", - "long = -172\n", - "lat = -32\n", - "plt.subplot(2, 1, 1)\n", - "time = slice(0, 500)\n", - "model_output['S_y'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "model_output['S_ypred'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "uB = model_output['S_ypred'] + 1.96 * model_output['S_yscale']\n", - "lB = model_output['S_ypred'] - 1.96 * model_output['S_yscale']\n", - "uB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "lB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "plt.legend(('Sy', 'Sy_pred'))" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "correlations = (model_output['S_y'] * model_output['S_ypred']).mean(dim='time_index') / np.sqrt((model_output['S_y']**2).mean(dim='time_index') * (model_output['S_ypred']**2).mean(dim='time_index'))" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "correlations.plot(vmin=0., vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/jupyter-notebooks/multi-region-analysis-02.ipynb b/examples/jupyter-notebooks/multi-region-analysis-02.ipynb deleted file mode 100644 index 9674c550..00000000 --- a/examples/jupyter-notebooks/multi-region-analysis-02.ipynb +++ /dev/null @@ -1,1090 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "###### Multi-region analysis " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this notebook we analyse the ability of a model trained on a region A to infer the subgrid forcing to achieve the same task on a different region, say region B. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/__init__.py:107: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import MutableMapping\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/rcsetup.py:20: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import Iterable, Mapping\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/colors.py:53: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import Sized\n" - ] - } - ], - "source": [ - "import mlflow\n", - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "from analysis.utils import select_run" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "plt.rcParams[\"figure.figsize\"] = (20, 15)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_dataset(dataset : xr.Dataset, plot_type = None, *args, **kargs):\n", - " \"\"\"Calls the plot function of each variable in the dataset\"\"\"\n", - " plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " kargs_ = [dict() for i in range(len(dataset))]\n", - " def process_list_of_args(name: str):\n", - " if name in kargs:\n", - " if isinstance(kargs[name], list):\n", - " for i, arg_value in enumerate(kargs[name]):\n", - " kargs_[i][name] = arg_value\n", - " else:\n", - " for i in range(len(dataset)):\n", - " kargs_[i][name] = kargs[name]\n", - " kargs.pop(name)\n", - " process_list_of_args('vmin')\n", - " process_list_of_args('vmax')\n", - " for i, variable in enumerate(dataset):\n", - " plt.subplot(int(len(dataset) / 2), 2, i + 1)\n", - " if plot_type is None:\n", - " try:\n", - " # By default we set the cmap to coolwarm\n", - " kargs.setdefault('cmap', 'coolwarm')\n", - " dataset[variable].plot(*args, **kargs_[i], **kargs)\n", - " except AttributeError as e:\n", - " kargs.pop('cmap', None)\n", - " dataset[variable].plot(*args, **kargs)\n", - " else:\n", - " plt_func = getattr(dataset[variable].plot, plot_type)\n", - " plt_func(*args, **kargs)\n", - "import matplotlib.animation as animation\n", - "\n", - "def dataset_to_movie(dataset : xr.Dataset, interval : int = 50,\n", - " *args, **kargs):\n", - " \"\"\"Generates animations for all the variables in the dataset\"\"\"\n", - " fig = plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " axes = list()\n", - " ims = list()\n", - " for i, variable in enumerate(dataset.keys()):\n", - " axes.append(fig.add_subplot(int(len(dataset) / 2), 2, i + 1))\n", - " for i, t in enumerate(dataset['time']):\n", - " im = list()\n", - " for axis, variable in zip(axes, dataset.keys()):\n", - " plt.sca(axis)\n", - " img = dataset[variable].isel(time=i).plot(vmin=-2, vmax=2,\n", - " cmap='coolwarm')\n", - " cb = img.colorbar\n", - " cb.remove()\n", - " im.append(img)\n", - " ims.append(im)\n", - " ani = animation.ArtistAnimation(fig, ims, \n", - " interval=interval, blit=True,\n", - " repeat_delay=1000)\n", - " return ani" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "client = mlflow.tracking.MlflowClient()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "def select_run(limit=1000, sort_by=None, cols=None, merge=None, *args, **kargs):\n", - " \"\"\"Allows to select a run from the tracking store interactively\"\"\"\n", - " mlflow_runs = mlflow.search_runs(*args, **kargs)\n", - " if cols is None:\n", - " cols = list()\n", - " cols = ['run_id', 'experiment_id' ] + cols\n", - " mlflow_runs = mlflow_runs.iloc[:limit]\n", - " # Remove possible duplicate columns\n", - " new_cols = list()\n", - " for e in cols:\n", - " if e not in new_cols:\n", - " new_cols.append(e)\n", - " cols = new_cols\n", - " print(len(mlflow_runs))\n", - " if merge is not None:\n", - " cols[cols.index('run_id')] = 'run_id_x'\n", - " cols[cols.index('experiment_id')] = 'experiment_id_x'\n", - " for name, key_left, key_right in merge:\n", - " experiment = mlflow.get_experiment_by_name(name)\n", - " df2 = mlflow.search_runs(experiment_ids=experiment.experiment_id)\n", - " mlflow_runs = pd.merge(mlflow_runs, df2, left_on=key_left,\n", - " right_on=key_right)\n", - " print(len(mlflow_runs))\n", - " if len(mlflow_runs) == 0:\n", - " raise Exception('No data found. Check that you correctly set \\\n", - " the store')\n", - " if sort_by is not None:\n", - " mlflow_runs = mlflow_runs.sort_values(by=sort_by, ascending=False)\n", - " cols.append(sort_by)\n", - " print(mlflow_runs[cols])\n", - " id_ = int(input('Run id?'))\n", - " if id_ < 0:\n", - " sys.exit()\n", - " return mlflow_runs.loc[id_, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:Malformed run 'a4da4cad3ecc4412af086e7bad8eb8bd'. Detailed error Yaml file '/scratch/ag7531/mlruns/12/a4da4cad3ecc4412af086e7bad8eb8bd/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/mlflow/store/tracking/file_store.py\", line 585, in _list_run_infos\n", - " run_info = self._get_run_info_from_dir(r_dir)\n", - " File \"/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/mlflow/store/tracking/file_store.py\", line 423, in _get_run_info_from_dir\n", - " meta = read_yaml(run_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/mlflow/utils/file_utils.py\", line 160, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/scratch/ag7531/mlruns/12/a4da4cad3ecc4412af086e7bad8eb8bd/meta.yaml' does not exist.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "24\n", - "3\n", - " run_id_x experiment_id_x \\\n", - "0 235204ea3a15413f8113e0271dbba24a 12 \n", - "1 7606981f52144e0c8472e199785d60ac 12 \n", - "2 5a14d68dbd6746638258558cfbb4ffa9 12 \n", - "\n", - " start_time_x params.model_cls_name metrics.test loss \\\n", - "0 2020-07-24 14:06:48.826000+00:00 FullyCNN -1.760762 \n", - "1 2020-07-24 10:01:32.841000+00:00 FullyCNN -1.760762 \n", - "2 2020-07-22 08:59:03.065000+00:00 FullyCNN -1.760762 \n", - "\n", - " params.lat_min params.lat_max params.long_min params.long_max \\\n", - "0 -60 0 60 110 \n", - "1 -60 0 60 110 \n", - "2 20 35 -30 -18 \n", - "\n", - " params.n_epochs_x params.model_run_id \\\n", - "0 0 2370107146564198b9f7351036632770 \n", - "1 0 2370107146564198b9f7351036632770 \n", - "2 0 2370107146564198b9f7351036632770 \n", - "\n", - " start_time_x \n", - "0 2020-07-24 14:06:48.826000+00:00 \n", - "1 2020-07-24 10:01:32.841000+00:00 \n", - "2 2020-07-22 08:59:03.065000+00:00 \n", - "Run id?2\n" - ] - } - ], - "source": [ - "cols = ['start_time_x','params.model_cls_name', 'metrics.test loss', 'params.lat_min', \n", - " 'params.lat_max', 'params.long_min', 'params.long_max', 'params.n_epochs_x', 'params.model_run_id']\n", - "run = select_run(sort_by='start_time_x', cols=cols, merge=[('meeting22july', 'params.model_run_id', 'run_id'),\n", - " ('forcingdatav3', 'params.data_run_id', 'run_id')], experiment_ids = ['12',])" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "run_id_x: 5a14d68dbd6746638258558cfbb4ffa9\n", - "experiment_id_x: 12\n", - "status_x: FINISHED\n", - "artifact_uri_x: /scratch/ag7531/mlruns/12/5a14d68dbd6746638258558cfbb4ffa9/artifacts\n", - "start_time_x: 2020-07-22 08:59:03.065000+00:00\n", - "end_time_x: 2020-07-22 09:09:30.380000+00:00\n", - "metrics.mse_x: 0.20767951424627448\n", - "metrics.Inf Norm_x: 2.750422538611019e-07\n", - "metrics.validation loss: 0.0\n", - "params.model_run_id: 2370107146564198b9f7351036632770\n", - "params.data_run_id: 08db5f2f1c8b45c1879fa235f6eaad3a\n", - "params.n_epochs_x: 0\n", - "tags.mlflow.user_x: ag7531\n", - "tags.mlflow.source.type_x: LOCAL\n", - "tags.mlflow.source.name_x: /home/ag7531/code/subgrid/testing/main.py\n", - "tags.mlflow.source.git.commit_x: fbed3c214941cd805e93a485154228434aaa19d6\n", - "run_id_y: 2370107146564198b9f7351036632770\n", - "experiment_id_y: 17\n", - "status_y: FINISHED\n", - "artifact_uri_y: /scratch/ag7531/mlruns/17/2370107146564198b9f7351036632770/artifacts\n", - "start_time_y: 2020-07-22 08:04:01.181000+00:00\n", - "end_time_y: 2020-07-22 08:57:35.031000+00:00\n", - "metrics.test loss: -1.7607615370455085\n", - "metrics.Inf Norm_y: 1.7761233266355703e-06\n", - "metrics.train loss: -1.8989318599755114\n", - "metrics.mse_y: 0.06447393229143253\n", - "params.time_indices: 0\n", - "params.model_cls_name: FullyCNN\n", - "params.exp_id: 14\n", - "params.targets_transform_cls_name: FixedForcingNormalizer\n", - "params.train_split: 0.6\n", - "params.batchsize: 4\n", - "params.source.run_id: 95dfe34c555b4fdbbb8afb9a6e568c93/5ac900b6d97d46d9830d24e492954625/9185f0305de848718159f913d7bbcffd/a5307020cffe4640bc87bb21d72c7a7c\n", - "params.features_transform_cls_name: FixedVelocityNormalizer\n", - "params.n_epochs_y: 28\n", - "params.model_module_name: models.models1\n", - "params.print_every: 20\n", - "params.learning_rate: 0/5e-4/10/5e-5/20/5e-6\n", - "params.run_id: 95dfe34c555b4fdbbb8afb9a6e568c93/5ac900b6d97d46d9830d24e492954625/9185f0305de848718159f913d7bbcffd/a5307020cffe4640bc87bb21d72c7a7c\n", - "params.loss_cls_name: HeteroskedasticGaussianLossV2\n", - "params.weight_decay: 0.00\n", - "params.test_split: 0.7\n", - "params.transformation_cls_name: SoftPlusTransform\n", - "params.source.experiment_id: 14\n", - "tags.mlflow.user_y: ag7531\n", - "tags.mlflow.source.type_y: PROJECT\n", - "tags.mlflow.source.name_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.env_x: conda\n", - "tags.mlflow.project.entryPoint_x: train\n", - "tags.mlflow.gitRepoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.git.commit_y: fbed3c214941cd805e93a485154228434aaa19d6\n", - "tags.mlflow.project.backend_x: local\n", - "tags.mlflow.source.git.repoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "run_id: 08db5f2f1c8b45c1879fa235f6eaad3a\n", - "experiment_id: 14\n", - "status: FINISHED\n", - "artifact_uri: /scratch/ag7531/mlruns/14/08db5f2f1c8b45c1879fa235f6eaad3a/artifacts\n", - "start_time: 2020-07-22 06:57:51.077000+00:00\n", - "end_time: 2020-07-22 07:14:08.007000+00:00\n", - "params.factor: 4\n", - "params.ntimes: 4400\n", - "params.scale: 32.6\n", - "params.CO2: 0\n", - "params.chunk_size: None\n", - "params.long_max: -18\n", - "params.lat_min: 20\n", - "params.long_min: -30\n", - "params.lat_max: 35\n", - "tags.mlflow.user: ag7531\n", - "tags.mlflow.source.type: PROJECT\n", - "tags.mlflow.source.name: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.env_y: conda\n", - "tags.mlflow.project.entryPoint_y: main\n", - "tags.mlflow.gitRepoURL_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.git.commit: 213819428f7ef410bb5ddaf1fabf63e48c1659dc\n", - "tags.mlflow.project.backend_y: local\n", - "tags.mlflow.source.git.repoURL_y: git@github.com:arthurBarthe/subgrid.git\n" - ] - } - ], - "source": [ - "for k,v in run.items():\n", - " print(f'{k}: {v}')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "data_run_id = run['params.data_run_id']\n", - "data_run = client.get_run(data_run_id)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "data_file = client.download_artifacts(data_run_id, 'forcing')\n", - "data = xr.open_zarr(data_file)\n", - "data['time_index'] = xr.DataArray(np.arange(len(data.coords['time'])),\n", - " dims = ('time',),\n", - " coords = {'time' : data['time']})\n", - "data = data.swap_dims({'time' : 'time_index'})" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2349: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " if isinstance(obj, collections.Iterator):\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2366: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " return list(data) if isinstance(data, collections.MappingView) else data\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from random import randint\n", - "plot_dataset(data[['usurf', 'vsurf']].isel(xu_ocean=randint(0, len(data['xu_ocean'])),\n", - " yu_ocean=randint(0, len(data['yu_ocean']))))" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_dataset(data[['usurf', 'vsurf']].mean(dim='time_index'), cmap='coolwarm', vmin=-1, vmax=1)\n", - "_ = plt.suptitle('Mean flow')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_dataset(data[['S_x', 'S_y']].mean(dim='time_index'), cmap='coolwarm', vmin=-1e-7, vmax=1e-7)\n", - "_ = plt.suptitle('Average forcing')" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot_dataset(data[['S_x', 'S_y']].std(dim='time_index'), cmap='coolwarm', vmin=0, vmax=2e-7)\n", - "_ = plt.suptitle('forcing std')" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
<xarray.Dataset>\n",
-       "Dimensions:  ()\n",
-       "Data variables:\n",
-       "    usurf    float64 0.1183\n",
-       "    vsurf    float64 0.07184\n",
-       "    S_x      float64 5.169e-08\n",
-       "    S_y      float64 5.19e-08
" - ], - "text/plain": [ - "\n", - "Dimensions: ()\n", - "Data variables:\n", - " usurf float64 0.1183\n", - " vsurf float64 0.07184\n", - " S_x float64 5.169e-08\n", - " S_y float64 5.19e-08" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data[['usurf', 'vsurf', 'S_x', 'S_y']].std().compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "eddy_data = data[['usurf', 'vsurf']] - data[['usurf', 'vsurf']].mean(dim='time_index')\n", - "eddy_data['usurf'].attrs['units'] = r'$m \\ s^{-1}$'\n", - "eddy_data['vsurf'].attrs['units'] = r'$m \\ s^{-1}$'\n", - "eddy_data['usurf'].attrs['long_name'] = 'eddy usurf'\n", - "eddy_data['vsurf'].attrs['long_name'] = 'eddy vsurf'" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "random_time = randint(0, len(eddy_data['time_index']))\n", - "fig = plt.figure(figsize=(20, 10))\n", - "plot_dataset(data[['usurf', 'vsurf']].isel(time_index=random_time))\n", - "_ = plt.suptitle('Velocities at day {}'.format(random_time))\n", - "plot_dataset(eddy_data[['usurf', 'vsurf']].isel(time_index=random_time))\n", - "_ = plt.suptitle('Eddy velocities at day {}'.format(random_time))" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "data['kinetic energy'] = 1/2*1e4*(data['usurf']**2 + data['vsurf']**2)\n", - "data['kinetic energy'].attrs['units'] = r'$(cm/s)^2$'\n", - "eddy_data['eddy kinetic energy'] = 1/2*1e4*(eddy_data['usurf']**2 + eddy_data['vsurf']**2)\n", - "eddy_data['eddy kinetic energy'].attrs['units'] = r'$(cm/s)^2$'" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "mean_kinetic_energy = data['kinetic energy'].mean(dim='time_index')\n", - "mean_kinetic_energy.attrs['units'] = r'$(cm/s)^2$'\n", - "mean_eddy_kinetic_energy = eddy_data['eddy kinetic energy'].mean(dim='time_index')\n", - "mean_eddy_kinetic_energy.attrs['units'] = r'$(cm/s)^2$'" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "mean_kinetic_energy.plot()\n", - "_ = plt.title('Time-averaged total kinetic energy')" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "mean_eddy_kinetic_energy.plot()\n", - "_ = plt.title('Time-averaged eddy kinetic energy')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - ". test_output_0 .\n", - "loading\n", - ". test_output_1 .\n", - "loading\n", - ". test_output_2 .\n", - "loading\n", - ". test_output_3 .\n", - "loading\n", - ". test_output_4 .\n", - "loading\n", - ". test_output_5 .\n", - "loading\n", - ". test_output_6 .\n", - "loading\n", - ". test_output_7 .\n", - "loading\n", - ". test_output_8 .\n", - "loading\n", - ". test_output_9 .\n", - "loading\n" - ] - } - ], - "source": [ - "from analysis.base import get_test_datasets\n", - "test_datasets = get_test_datasets(run['run_id_x'])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "lat = np.arange(-80, 80, 1)\n", - "lon = np.arange(-279.9, 80.1, 1)\n", - "interp_dss = []\n", - "for ds in test_datasets:\n", - " ds = ds.ds\n", - " ds = ds.chunk(dict(time=1, latitude=None, longitude=None))\n", - " interp_dss.append(ds.interp(dict(latitude=lat, longitude=lon),\n", - " method='nearest', kwargs=dict(bounds_error=False, fill_value=0.)))\n", - " interp_dss[-1] = interp_dss[-1].chunk(dict(latitude=None, longitude=None))" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "final_ds = sum(interp_dss)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in greater\n", - " return func(*args2)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "([,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ],\n", - " )" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import cartopy.crs as ccrs\n", - "final_ds = final_ds.where(abs(final_ds) > 0)\n", - "ax = plt.axes(projection=ccrs.PlateCarree())\n", - "squared_error = ((final_ds['S_xpred'] - final_ds['S_x']))**2\n", - "(squared_error.mean(dim='time') / (final_ds['S_x']**2).mean(dim='time')).plot(ax=ax, transform = ccrs.PlateCarree(), vmin=0, vmax=1, cmap='coolwarm')\n", - "ax.set_global()\n", - "ax.coastlines()\n", - "plt.xticks(final_ds.longitude[::30] + 99.9)\n", - "plt.yticks(final_ds.latitude[::30])" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
<xarray.Dataset>\n",
-       "Dimensions:    (latitude: 45, longitude: 45, time: 1320)\n",
-       "Coordinates:\n",
-       "  * latitude   (latitude) float64 -39.95 -39.65 -39.34 ... -25.92 -25.56 -25.2\n",
-       "  * longitude  (longitude) float64 -179.9 -179.5 -179.1 ... -163.1 -162.7 -162.3\n",
-       "  * time       (time) object 0189-06-08 12:00:00 ... 0193-01-17 12:00:00\n",
-       "Data variables:\n",
-       "    S_x        (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_xpred    (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_xscale   (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_y        (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_ypred    (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    S_yscale   (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    u_surf     (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>\n",
-       "    v_surf     (time, latitude, longitude) float64 dask.array<chunksize=(330, 12, 23), meta=np.ndarray>
" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test_datasets[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "id = 0\n", - "error = (test_datasets[id]['S_xpred'] - test_datasets[id]['S_x']) \n", - "error0 = test_datasets[id]['S_x']" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2349: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " if isinstance(obj, collections.Iterator):\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "((error**2).mean(dim='time') / (error0**2).mean(dim='time')).plot(vmin=0., vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "model_output = test_datasets[id]\n", - "model_output['S_xscale'] = 1/(model_output['S_xscale'])\n", - "model_output['S_yscale'] = 1/(model_output['S_yscale'])\n", - "model_output['err_S_x'] = (model_output['S_x'] - model_output['S_xpred'])**2\n", - "model_output['err_S_y'] = (model_output['S_y'] - model_output['S_ypred'])**2" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "model_output['time_index'] = xr.DataArray(np.arange(len(model_output.coords['time'])),\n", - " dims = ('time',),\n", - " coords = {'time' : model_output['time']})\n", - "model_output = model_output.swap_dims({'time' : 'time_index'})" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Random time index: 1102\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Random snapshot of the forcing for Laure\n", - "from random import randint\n", - "n_times = len(model_output['time'])\n", - "random_time = randint(0, n_times)\n", - "print('Random time index: ', random_time)\n", - "(model_output['S_x'].isel(time_index=random_time)).plot(vmin=-1., vmax=1., cmap='coolwarm')\n", - "plt.legend(r'S_x ($m^4s^{-3})')" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "377\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from random import randint\n", - "random_time = randint(0, n_times)\n", - "print(random_time)\n", - "plot_dataset(model_output.isel(time_index=random_time)[['u_surf', 'v_surf', 'S_x', 'S_y', 'S_xpred', 'S_ypred',\n", - " 'S_xscale', 'S_yscale', 'err_S_x', 'err_S_y']],\n", - " vmin = [-2]*6 + [0., 0., 0., 0.], vmax = [2]*6 + [2, 2,2,2])" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(30, 30))\n", - "long = -172\n", - "lat = -32\n", - "plt.subplot(2, 1, 1)\n", - "time = slice(0, 500)\n", - "model_output['S_y'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "model_output['S_ypred'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "uB = model_output['S_ypred'] + 1.96 * model_output['S_yscale']\n", - "lB = model_output['S_ypred'] - 1.96 * model_output['S_yscale']\n", - "uB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "lB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "plt.legend(('Sy', 'Sy_pred'))" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "correlations = (model_output['S_y'] * model_output['S_ypred']).mean(dim='time_index') / np.sqrt((model_output['S_y']**2).mean(dim='time_index') * (model_output['S_ypred']**2).mean(dim='time_index'))" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "correlations.plot(vmin=0., vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/jupyter-notebooks/multi-region-analysis-testUnet1pctCO2.ipynb b/examples/jupyter-notebooks/multi-region-analysis-testUnet1pctCO2.ipynb deleted file mode 100644 index 14601461..00000000 --- a/examples/jupyter-notebooks/multi-region-analysis-testUnet1pctCO2.ipynb +++ /dev/null @@ -1,629 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "###### Multi-region analysis " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this notebook we analyse the ability of a model trained on a region A to infer the subgrid forcing to achieve the same task on a different region, say region B. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/__init__.py:107: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import MutableMapping\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/rcsetup.py:20: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import Iterable, Mapping\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/colors.py:53: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import Sized\n" - ] - } - ], - "source": [ - "import mlflow\n", - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "from analysis.utils import select_run" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "plt.rcParams[\"figure.figsize\"] = (15, 10)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_dataset(dataset : xr.Dataset, plot_type = None, *args, **kargs):\n", - " \"\"\"Calls the plot function of each variable in the dataset\"\"\"\n", - " plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " kargs_ = [dict() for i in range(len(dataset))]\n", - " def process_list_of_args(name: str):\n", - " if name in kargs:\n", - " if isinstance(kargs[name], list):\n", - " for i, arg_value in enumerate(kargs[name]):\n", - " kargs_[i][name] = arg_value\n", - " else:\n", - " for i in range(len(dataset)):\n", - " kargs_[i][name] = kargs[name]\n", - " kargs.pop(name)\n", - " process_list_of_args('vmin')\n", - " process_list_of_args('vmax')\n", - " for i, variable in enumerate(dataset):\n", - " plt.subplot(int(len(dataset) / 2), 2, i + 1)\n", - " if plot_type is None:\n", - " try:\n", - " # By default we set the cmap to coolwarm\n", - " kargs.setdefault('cmap', 'coolwarm')\n", - " dataset[variable].plot(*args, **kargs_[i], **kargs)\n", - " except AttributeError as e:\n", - " kargs.pop('cmap', None)\n", - " dataset[variable].plot(*args, **kargs)\n", - " else:\n", - " plt_func = getattr(dataset[variable].plot, plot_type)\n", - " plt_func(*args, **kargs)\n", - "import matplotlib.animation as animation\n", - "\n", - "def dataset_to_movie(dataset : xr.Dataset, interval : int = 50,\n", - " *args, **kargs):\n", - " \"\"\"Generates animations for all the variables in the dataset\"\"\"\n", - " fig = plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " axes = list()\n", - " ims = list()\n", - " for i, variable in enumerate(dataset.keys()):\n", - " axes.append(fig.add_subplot(int(len(dataset) / 2), 2, i + 1))\n", - " for i, t in enumerate(dataset['time']):\n", - " im = list()\n", - " for axis, variable in zip(axes, dataset.keys()):\n", - " plt.sca(axis)\n", - " img = dataset[variable].isel(time=i).plot(vmin=-2, vmax=2,\n", - " cmap='coolwarm')\n", - " cb = img.colorbar\n", - " cb.remove()\n", - " im.append(img)\n", - " ims.append(im)\n", - " ani = animation.ArtistAnimation(fig, ims, \n", - " interval=interval, blit=True,\n", - " repeat_delay=1000)\n", - " return ani" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client = mlflow.tracking.MlflowClient()\n", - "client.list_experiments()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "def select_run(limit=1000, sort_by=None, cols=None, merge=None, *args, **kargs):\n", - " \"\"\"Allows to select a run from the tracking store interactively\"\"\"\n", - " mlflow_runs = mlflow.search_runs(*args, **kargs)\n", - " if cols is None:\n", - " cols = list()\n", - " cols = ['run_id', 'experiment_id' ] + cols\n", - " mlflow_runs = mlflow_runs.iloc[:limit]\n", - " # Remove possible duplicate columns\n", - " new_cols = list()\n", - " for e in cols:\n", - " if e not in new_cols:\n", - " new_cols.append(e)\n", - " cols = new_cols\n", - " print(len(mlflow_runs))\n", - " if merge is not None:\n", - " cols[cols.index('run_id')] = 'run_id_x'\n", - " cols[cols.index('experiment_id')] = 'experiment_id_x'\n", - " for name, key_left, key_right in merge:\n", - " experiment = mlflow.get_experiment_by_name(name)\n", - " df2 = mlflow.search_runs(experiment_ids=experiment.experiment_id)\n", - " mlflow_runs = pd.merge(mlflow_runs, df2, left_on=key_left,\n", - " right_on=key_right)\n", - " print(len(mlflow_runs))\n", - " if len(mlflow_runs) == 0:\n", - " raise Exception('No data found. Check that you correctly set \\\n", - " the store')\n", - " if sort_by is not None:\n", - " mlflow_runs = mlflow_runs.sort_values(by=sort_by, ascending=False)\n", - " cols.append(sort_by)\n", - " print(mlflow_runs[cols])\n", - " id_ = int(input('Run id?'))\n", - " if id_ < 0:\n", - " sys.exit()\n", - " return mlflow_runs.loc[id_, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7\n", - "2\n", - " run_id_x experiment_id_x \\\n", - "0 08c1c58ef8dd4669999bf355b8459aea 11 \n", - "1 c55c0b2985244decbc7e20cc1a5d35c0 11 \n", - "\n", - " start_time_x params.model_cls_name metrics.test loss \\\n", - "0 2020-06-25 12:31:17.256000+00:00 Unet32 -1.515098 \n", - "1 2020-06-25 11:16:35.717000+00:00 Unet32 -1.347764 \n", - "\n", - " params.lat_min params.lat_max params.long_min params.long_max \\\n", - "0 35 50 -50 -20 \n", - "1 35 50 -50 -20 \n", - "\n", - " params.n_epochs_x params.model_run_id \\\n", - "0 0 8351e0c188d14be5a28abdce1cf01f5d \n", - "1 0 e663efdb6c40493d8e06b80647f7acdf \n", - "\n", - " start_time_x \n", - "0 2020-06-25 12:31:17.256000+00:00 \n", - "1 2020-06-25 11:16:35.717000+00:00 \n", - "Run id?0\n" - ] - } - ], - "source": [ - "cols = ['start_time_x','params.model_cls_name', 'metrics.test loss', 'params.lat_min', \n", - " 'params.lat_max', 'params.long_min', 'params.long_max', 'params.n_epochs_x', 'params.model_run_id']\n", - "run = select_run(sort_by='start_time_x', cols=cols, merge=[('Unet', 'params.model_run_id', 'run_id'),\n", - " ('forcingdata1pct', 'params.data_run_id', 'run_id')], experiment_ids = ['11',])" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "run_id_x: 08c1c58ef8dd4669999bf355b8459aea\n", - "experiment_id_x: 11\n", - "status_x: FINISHED\n", - "artifact_uri_x: /scratch/ag7531/mlruns/11/08c1c58ef8dd4669999bf355b8459aea/artifacts\n", - "start_time_x: 2020-06-25 12:31:17.256000+00:00\n", - "end_time_x: 2020-06-25 12:33:03.144000+00:00\n", - "metrics.validation loss: 0.0\n", - "metrics.Inf Norm_x: 1.7839448673839797e-06\n", - "metrics.mse_x: 0.06976134034679163\n", - "params.model_run_id: 8351e0c188d14be5a28abdce1cf01f5d\n", - "params.data_run_id: a47e3597568146b088f1f17b17111e29\n", - "params.n_epochs_x: 0\n", - "tags.mlflow.source.type_x: LOCAL\n", - "tags.mlflow.source.name_x: /home/ag7531/code/subgrid/testing/main.py\n", - "tags.mlflow.source.git.commit_x: 7aafd1426a54f64359f715b4aede609401ea9ab1\n", - "tags.mlflow.user_x: ag7531\n", - "run_id_y: 8351e0c188d14be5a28abdce1cf01f5d\n", - "experiment_id_y: 7\n", - "status_y: FINISHED\n", - "artifact_uri_y: /scratch/ag7531/mlruns/7/8351e0c188d14be5a28abdce1cf01f5d/artifacts\n", - "start_time_y: 2020-06-24 08:36:30.211000+00:00\n", - "end_time_y: 2020-06-24 10:16:51.655000+00:00\n", - "metrics.train loss: -1.6850772797158255\n", - "metrics.test loss: -1.5150982925386145\n", - "metrics.mse_y: 0.08592168752411718\n", - "metrics.Inf Norm_y: 26.135334014892578\n", - "params.time_indices: 0\n", - "params.test_split: 0.7\n", - "params.exp_id: 1\n", - "params.print_every: 20\n", - "params.weight_decay: 0.00\n", - "params.learning_rate: 0/5e-4/10/5e-5/90/5e-6\n", - "params.source.run_id: d8544c4ed65744e2ab25efd076231a9f/77b601955b3d4b5b97b811c3518b2fd6/72f3866845684663b02172e571d1dba8/03e55c986efd465487dfab63a3179597\n", - "params.transformation_cls_name: SoftPlusTransform\n", - "params.source.experiment_id: 1\n", - "params.model_cls_name: Unet32\n", - "params.train_split: 0.6\n", - "params.targets_transform_cls_name: FixedForcingNormalizer\n", - "params.model_module_name: models.Unet\n", - "params.batchsize: 16\n", - "params.features_transform_cls_name: FixedVelocityNormalizer\n", - "params.n_epochs_y: 52\n", - "params.run_id: d8544c4ed65744e2ab25efd076231a9f/77b601955b3d4b5b97b811c3518b2fd6/72f3866845684663b02172e571d1dba8/03e55c986efd465487dfab63a3179597\n", - "params.loss_cls_name: HeteroskedasticGaussianLossV2\n", - "tags.mlflow.project.backend_x: local\n", - "tags.mlflow.project.entryPoint_x: train\n", - "tags.mlflow.source.git.repoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.user_y: ag7531\n", - "tags.mlflow.source.type_y: PROJECT\n", - "tags.mlflow.source.name_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.git.commit_y: 1df868e6315322fc72034811eddbfcf1a281dc6f\n", - "tags.mlflow.project.env_x: conda\n", - "tags.mlflow.gitRepoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "run_id: a47e3597568146b088f1f17b17111e29\n", - "experiment_id: 9\n", - "status: FINISHED\n", - "artifact_uri: /scratch/ag7531/mlruns/9/a47e3597568146b088f1f17b17111e29/artifacts\n", - "start_time: 2020-06-25 06:19:15.326000+00:00\n", - "end_time: 2020-06-25 07:09:02.795000+00:00\n", - "params.scale: 32.6\n", - "params.lat_min: 35\n", - "params.ntimes: 7300\n", - "params.CO2: 1\n", - "params.long_max: -20\n", - "params.lat_max: 50\n", - "params.long_min: -50\n", - "tags.mlflow.project.backend_y: local\n", - "tags.mlflow.project.entryPoint_y: main\n", - "tags.mlflow.source.git.repoURL_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.user: ag7531\n", - "tags.mlflow.source.type: PROJECT\n", - "tags.mlflow.source.name: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.git.commit: 5008af2247611b7a3b5b52bc27d85d0344d66bcc\n", - "tags.mlflow.project.env_y: conda\n", - "tags.mlflow.gitRepoURL_y: git@github.com:arthurBarthe/subgrid.git\n" - ] - } - ], - "source": [ - "for k,v in run.items():\n", - " print(f'{k}: {v}')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "data_run_id = run['params.data_run_id']\n", - "data_run = client.get_run(data_run_id)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - ". test_output_0 .\n", - "loading\n" - ] - } - ], - "source": [ - "from analysis.base import get_test_datasets\n", - "test_datasets = get_test_datasets(run['run_id_x'])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "id = 0\n", - "error = (test_datasets[id]['S_xpred'] - test_datasets[id]['S_x']) \n", - "error0 = test_datasets[id]['S_x']" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2349: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " if isinstance(obj, collections.Iterator):\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "((error**2).mean(dim='time') / (error0**2).mean(dim='time')).plot(vmin=0.2, vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "model_output = test_datasets[id]\n", - "model_output['S_xscale'] = 1/(model_output['S_xscale'])\n", - "model_output['S_yscale'] = 1/(model_output['S_yscale'])\n", - "model_output['err_S_x'] = (model_output['S_x'] - model_output['S_xpred'])**2\n", - "model_output['err_S_y'] = (model_output['S_y'] - model_output['S_ypred'])**2" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "model_output['time_index'] = xr.DataArray(np.arange(len(model_output.coords['time'])),\n", - " dims = ('time',),\n", - " coords = {'time' : model_output['time']})\n", - "model_output = model_output.swap_dims({'time' : 'time_index'})" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2154\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: divide by zero encountered in true_divide\n", - " return func(*args2)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: divide by zero encountered in true_divide\n", - " return func(*args2)\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from random import randint\n", - "n_times = len(model_output['time'])\n", - "random_time = randint(0, n_times)\n", - "print(random_time)\n", - "plot_dataset(model_output.isel(time_index=random_time)[['u_surf', 'v_surf', 'S_x', 'S_y', 'S_xpred', 'S_ypred',\n", - " 'S_xscale', 'S_yscale', 'err_S_x', 'err_S_y']],\n", - " vmin = [-2]*6 + [0., 0., 0., 0.], vmax = [2]*6 + [1, 1,1,1])" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(30, 30))\n", - "long = -45\n", - "lat = 44\n", - "plt.subplot(2, 1, 1)\n", - "time = slice(0, 600)\n", - "model_output['S_x'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "model_output['S_xpred'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "uB = model_output['S_xpred'] + 1.96 * model_output['S_xscale']\n", - "lB = model_output['S_xpred'] - 1.96 * model_output['S_xscale']\n", - "uB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "lB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "plt.legend(('Sx', 'Sx_pred'))" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "correlations = (model_output['S_y'] * model_output['S_ypred']).mean(dim='time_index') / np.sqrt((model_output['S_y']**2).mean(dim='time_index') * (model_output['S_ypred']**2).mean(dim='time_index'))" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "correlations.plot(vmin=0.1, vmax=1)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/jupyter-notebooks/multi-region-analysis-testunet.ipynb b/examples/jupyter-notebooks/multi-region-analysis-testunet.ipynb deleted file mode 100644 index aa8a1b40..00000000 --- a/examples/jupyter-notebooks/multi-region-analysis-testunet.ipynb +++ /dev/null @@ -1,639 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "###### Multi-region analysis " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this notebook we analyse the ability of a model trained on a region A to infer the subgrid forcing to achieve the same task on a different region, say region B. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/__init__.py:107: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import MutableMapping\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/rcsetup.py:20: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import Iterable, Mapping\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/colors.py:53: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " from collections import Sized\n" - ] - } - ], - "source": [ - "import mlflow\n", - "import xarray as xr\n", - "import matplotlib.pyplot as plt\n", - "from analysis.utils import select_run" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "plt.rcParams[\"figure.figsize\"] = (15, 10)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_dataset(dataset : xr.Dataset, plot_type = None, *args, **kargs):\n", - " \"\"\"Calls the plot function of each variable in the dataset\"\"\"\n", - " plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " kargs_ = [dict() for i in range(len(dataset))]\n", - " def process_list_of_args(name: str):\n", - " if name in kargs:\n", - " if isinstance(kargs[name], list):\n", - " for i, arg_value in enumerate(kargs[name]):\n", - " kargs_[i][name] = arg_value\n", - " else:\n", - " for i in range(len(dataset)):\n", - " kargs_[i][name] = kargs[name]\n", - " kargs.pop(name)\n", - " process_list_of_args('vmin')\n", - " process_list_of_args('vmax')\n", - " for i, variable in enumerate(dataset):\n", - " plt.subplot(int(len(dataset) / 2), 2, i + 1)\n", - " if plot_type is None:\n", - " try:\n", - " # By default we set the cmap to coolwarm\n", - " kargs.setdefault('cmap', 'coolwarm')\n", - " dataset[variable].plot(*args, **kargs_[i], **kargs)\n", - " except AttributeError as e:\n", - " kargs.pop('cmap', None)\n", - " dataset[variable].plot(*args, **kargs)\n", - " else:\n", - " plt_func = getattr(dataset[variable].plot, plot_type)\n", - " plt_func(*args, **kargs)\n", - "import matplotlib.animation as animation\n", - "\n", - "def dataset_to_movie(dataset : xr.Dataset, interval : int = 50,\n", - " *args, **kargs):\n", - " \"\"\"Generates animations for all the variables in the dataset\"\"\"\n", - " fig = plt.figure(figsize = (20, 5 * int(len(dataset) / 2)))\n", - " axes = list()\n", - " ims = list()\n", - " for i, variable in enumerate(dataset.keys()):\n", - " axes.append(fig.add_subplot(int(len(dataset) / 2), 2, i + 1))\n", - " for i, t in enumerate(dataset['time']):\n", - " im = list()\n", - " for axis, variable in zip(axes, dataset.keys()):\n", - " plt.sca(axis)\n", - " img = dataset[variable].isel(time=i).plot(vmin=-2, vmax=2,\n", - " cmap='coolwarm')\n", - " cb = img.colorbar\n", - " cb.remove()\n", - " im.append(img)\n", - " ims.append(im)\n", - " ani = animation.ArtistAnimation(fig, ims, \n", - " interval=interval, blit=True,\n", - " repeat_delay=1000)\n", - " return ani" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ,\n", - " ]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client = mlflow.tracking.MlflowClient()\n", - "client.list_experiments()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "def select_run(limit=1000, sort_by=None, cols=None, merge=None, *args, **kargs):\n", - " \"\"\"Allows to select a run from the tracking store interactively\"\"\"\n", - " mlflow_runs = mlflow.search_runs(*args, **kargs)\n", - " if cols is None:\n", - " cols = list()\n", - " cols = ['run_id', 'experiment_id' ] + cols\n", - " mlflow_runs = mlflow_runs.iloc[:limit]\n", - " # Remove possible duplicate columns\n", - " new_cols = list()\n", - " for e in cols:\n", - " if e not in new_cols:\n", - " new_cols.append(e)\n", - " cols = new_cols\n", - " print(len(mlflow_runs))\n", - " if merge is not None:\n", - " cols[cols.index('run_id')] = 'run_id_x'\n", - " cols[cols.index('experiment_id')] = 'experiment_id_x'\n", - " for name, key_left, key_right in merge:\n", - " experiment = mlflow.get_experiment_by_name(name)\n", - " df2 = mlflow.search_runs(experiment_ids=experiment.experiment_id)\n", - " mlflow_runs = pd.merge(mlflow_runs, df2, left_on=key_left,\n", - " right_on=key_right)\n", - " print(len(mlflow_runs))\n", - " if len(mlflow_runs) == 0:\n", - " raise Exception('No data found. Check that you correctly set \\\n", - " the store')\n", - " if sort_by is not None:\n", - " mlflow_runs = mlflow_runs.sort_values(by=sort_by, ascending=False)\n", - " cols.append(sort_by)\n", - " print(mlflow_runs[cols])\n", - " id_ = int(input('Run id?'))\n", - " if id_ < 0:\n", - " sys.exit()\n", - " return mlflow_runs.loc[id_, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7\n", - "2\n", - " run_id_x experiment_id_x \\\n", - "0 fb31982e69204fa899d9027e87c28afb 11 \n", - "1 87bc21f5476640b9a56ccdf5d53a79ea 11 \n", - "\n", - " start_time_x params.model_cls_name metrics.test loss \\\n", - "0 2020-06-25 12:16:45.476000+00:00 Unet32 -1.515098 \n", - "1 2020-06-25 10:24:58.125000+00:00 Unet32 -1.347764 \n", - "\n", - " params.lat_min params.lat_max params.long_min params.long_max \\\n", - "0 20 35 -48 -30 \n", - "1 20 35 -48 -30 \n", - "\n", - " params.n_epochs_x params.model_run_id \\\n", - "0 0 8351e0c188d14be5a28abdce1cf01f5d \n", - "1 0 e663efdb6c40493d8e06b80647f7acdf \n", - "\n", - " start_time_x \n", - "0 2020-06-25 12:16:45.476000+00:00 \n", - "1 2020-06-25 10:24:58.125000+00:00 \n", - "Run id?0\n" - ] - } - ], - "source": [ - "cols = ['start_time_x','params.model_cls_name', 'metrics.test loss', 'params.lat_min', \n", - " 'params.lat_max', 'params.long_min', 'params.long_max', 'params.n_epochs_x', 'params.model_run_id']\n", - "run = select_run(sort_by='start_time_x', cols=cols, merge=[('Unet', 'params.model_run_id', 'run_id'),\n", - " ('forcingdata', 'params.data_run_id', 'run_id')], experiment_ids = ['11',])" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "run_id_x: fb31982e69204fa899d9027e87c28afb\n", - "experiment_id_x: 11\n", - "status_x: FINISHED\n", - "artifact_uri_x: /scratch/ag7531/mlruns/11/fb31982e69204fa899d9027e87c28afb/artifacts\n", - "start_time_x: 2020-06-25 12:16:45.476000+00:00\n", - "end_time_x: 2020-06-25 12:30:49.471000+00:00\n", - "metrics.mse_x: 0.22279064244940455\n", - "metrics.Inf Norm_x: 3.324599049392418e-07\n", - "metrics.validation loss: 0.0\n", - "params.n_epochs_x: 0\n", - "params.data_run_id: 729366a2d22b41599182c5f1b222ba2e\n", - "params.model_run_id: 8351e0c188d14be5a28abdce1cf01f5d\n", - "tags.mlflow.user_x: ag7531\n", - "tags.mlflow.source.git.commit_x: 7aafd1426a54f64359f715b4aede609401ea9ab1\n", - "tags.mlflow.source.type_x: LOCAL\n", - "tags.mlflow.source.name_x: /home/ag7531/code/subgrid/testing/main.py\n", - "run_id_y: 8351e0c188d14be5a28abdce1cf01f5d\n", - "experiment_id_y: 7\n", - "status_y: FINISHED\n", - "artifact_uri_y: /scratch/ag7531/mlruns/7/8351e0c188d14be5a28abdce1cf01f5d/artifacts\n", - "start_time_y: 2020-06-24 08:36:30.211000+00:00\n", - "end_time_y: 2020-06-24 10:16:51.655000+00:00\n", - "metrics.test loss: -1.5150982925386145\n", - "metrics.mse_y: 0.08592168752411718\n", - "metrics.Inf Norm_y: 26.135334014892578\n", - "metrics.train loss: -1.6850772797158255\n", - "params.features_transform_cls_name: FixedVelocityNormalizer\n", - "params.print_every: 20\n", - "params.weight_decay: 0.00\n", - "params.source.experiment_id: 1\n", - "params.transformation_cls_name: SoftPlusTransform\n", - "params.run_id: d8544c4ed65744e2ab25efd076231a9f/77b601955b3d4b5b97b811c3518b2fd6/72f3866845684663b02172e571d1dba8/03e55c986efd465487dfab63a3179597\n", - "params.source.run_id: d8544c4ed65744e2ab25efd076231a9f/77b601955b3d4b5b97b811c3518b2fd6/72f3866845684663b02172e571d1dba8/03e55c986efd465487dfab63a3179597\n", - "params.train_split: 0.6\n", - "params.batchsize: 16\n", - "params.time_indices: 0\n", - "params.model_module_name: models.Unet\n", - "params.n_epochs_y: 52\n", - "params.targets_transform_cls_name: FixedForcingNormalizer\n", - "params.loss_cls_name: HeteroskedasticGaussianLossV2\n", - "params.learning_rate: 0/5e-4/10/5e-5/90/5e-6\n", - "params.model_cls_name: Unet32\n", - "params.test_split: 0.7\n", - "params.exp_id: 1\n", - "tags.mlflow.source.git.repoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.user_y: ag7531\n", - "tags.mlflow.source.git.commit_y: 1df868e6315322fc72034811eddbfcf1a281dc6f\n", - "tags.mlflow.gitRepoURL_x: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.env_x: conda\n", - "tags.mlflow.project.backend_x: local\n", - "tags.mlflow.project.entryPoint_x: train\n", - "tags.mlflow.source.type_y: PROJECT\n", - "tags.mlflow.source.name_y: git@github.com:arthurBarthe/subgrid.git\n", - "run_id: 729366a2d22b41599182c5f1b222ba2e\n", - "experiment_id: 1\n", - "status: FINISHED\n", - "artifact_uri: /scratch/ag7531/mlruns/1/729366a2d22b41599182c5f1b222ba2e/artifacts\n", - "start_time: 2020-06-03 17:04:11.591000+00:00\n", - "end_time: 2020-06-03 17:29:04.696000+00:00\n", - "params.lat_min: 20\n", - "params.scale: 32.6\n", - "params.long_min: -48\n", - "params.long_max: -30\n", - "params.lat_max: 35\n", - "params.ntimes: 4400\n", - "params.CO2: 0\n", - "tags.mlflow.source.git.repoURL_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.user: ag7531\n", - "tags.mlflow.source.git.commit: 7f6dee3f49bc98e77e717d74fd015f05e0bee836\n", - "tags.mlflow.gitRepoURL_y: git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.env_y: conda\n", - "tags.mlflow.project.backend_y: local\n", - "tags.mlflow.project.entryPoint_y: main\n", - "tags.mlflow.source.type: PROJECT\n", - "tags.mlflow.source.name: git@github.com:arthurBarthe/subgrid.git\n" - ] - } - ], - "source": [ - "for k,v in run.items():\n", - " print(f'{k}: {v}')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "data_run_id = run['params.data_run_id']\n", - "data_run = client.get_run(data_run_id)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - ". test_output_0 .\n", - "loading\n", - ". test_output_1 .\n", - "loading\n", - ". test_output_10 .\n", - "loading\n", - ". test_output_2 .\n", - "loading\n", - ". test_output_3 .\n", - "loading\n", - ". test_output_4 .\n", - "loading\n", - ". test_output_5 .\n", - "loading\n", - ". test_output_6 .\n", - "loading\n", - ". test_output_7 .\n", - "loading\n", - ". test_output_8 .\n", - "loading\n", - ". test_output_9 .\n", - "loading\n" - ] - } - ], - "source": [ - "from analysis.base import get_test_datasets\n", - "test_datasets = get_test_datasets(run['run_id_x'])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "id = 0\n", - "error = (test_datasets[id]['S_xpred'] - test_datasets[id]['S_x']) \n", - "error0 = test_datasets[id]['S_x']" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:2349: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working\n", - " if isinstance(obj, collections.Iterator):\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "((error**2).mean(dim='time') / (error0**2).mean(dim='time')).plot(vmin=0.2, vmax=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "model_output = test_datasets[id]\n", - "model_output['S_xscale'] = 1/(model_output['S_xscale'])\n", - "model_output['S_yscale'] = 1/(model_output['S_yscale'])\n", - "model_output['err_S_x'] = (model_output['S_x'] - model_output['S_xpred'])**2\n", - "model_output['err_S_y'] = (model_output['S_y'] - model_output['S_ypred'])**2" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "model_output['time_index'] = xr.DataArray(np.arange(len(model_output.coords['time'])),\n", - " dims = ('time',),\n", - " coords = {'time' : model_output['time']})\n", - "model_output = model_output.swap_dims({'time' : 'time_index'})" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "582\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from random import randint\n", - "n_times = len(model_output['time'])\n", - "random_time = randint(0, n_times)\n", - "print(random_time)\n", - "plot_dataset(model_output.isel(time_index=random_time)[['u_surf', 'v_surf', 'S_x', 'S_y', 'S_xpred', 'S_ypred',\n", - " 'S_xscale', 'S_yscale', 'err_S_x', 'err_S_y']],\n", - " vmin = [-2]*6 + [0., 0., 0., 0.], vmax = [2]*6 + [1, 1,1,1])" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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3wqkvIrudDSa2zMbxy8eejOwOzV2C7Ob3fhzZfeskqw8zxphRkWfOT/k2jCx+jNmC7OuwbmFN2O3t8MkdyO4jk0yMvHTn55Dd9iYThQuJ1V5JC9DObBQLA0fRjDHGbBwWP6ZW5E6F+WyXOesfPvI0ZHfkwe3IrtFmDR2+eGovsptqXYXsjiyzWqgPLDwd2T33yX+I7PY3PZtmo3jtDjYc9Y/jecjuie1jyE5ibfSNMWZUFGf/mEdj8WNqxXVHvxbZLe2+Cdl9coGl7NxxfBeya02wRgI7Z1iEowlrdz5z4lJkd89x1paue5pFfn5v31cju7fsZml2ZeB9c0xgP23sfmT3jA5LPTwyfSuyu623G9k9te20N2OMKQMWP6ZWfOLBA8juoWU22PHgFNtF/upLDiO7sSYr0H9wkUUq7jrJxMipB2E3u/vZK6sFs94eWGaOfln4bycvG9rmVz/6crTW1z3zS8juPQc/guxeMsGimX8yz8TWnf2HkN3BlqOExpjR4Dk/q2PxY2rF7BeYs/7JPUz8LFzRRnY7OmwX+WSXTQHFIuYIOy+Td7FXz9R97DW7cBFLd7z52PDiQJJu2/e3yO6JLXY+KXcuD5+2GF02pOlJU0wc5OaLS6xRwh88wKLKF42z+r6X7DiE7L5rijVFMcaYqmDxY2pF+zRzggcsC02LfSZ+aAOC+QeY89ycZQ5ti51OFbCGfXEPW3DpYpaed3SW1XH8y5t/CNk9dc8RZPdvLvk7ZLcNNJB4+rPuRGv9x72fR3aUuYJtIPzFYdYu/oH72TOrJhP0N+xhUew/3sGi0X04mfif72IpoG/acTeyM8Y8wiCd+WMejcWPqRWHfvi3kN0Ny6yW5u9hzc+R7jZk99mdrJbmLlhLs21iGdk9czebu3PpOGuRvbPFhpzeMs+iAH9395OQ3Q1fOojs7jzFrt+/e+JHh7b590/8JFrrr2Bq5Y996l8hu8Eh9gxRxmBV8Tjsr9A6znYQ7hSraZqH0dMvfyNb703Ps/gxxowGix9j1sFXjzWRXTfdhuy2TTFRcQVrvqa74CzPjy0+AdmNN5iY3NFkjRm6iV2/vdtZitAVT2Ee7R0L7AJeNMZSp142dfvQNtsaLLr4T/Osw1/3DiaadtyFzDSA9WEJRkHHTrFt2fY8U1sFDNe255ndyTtZROznDrAOjT+2h81pkiT4+jRmy5Kj21sZA0sWP6ZW/D1syLSU2C7reDBV8YwOq92hPAOmoc2ne5DdoeX9yO6eLss/vGn2CmS3t8OGv75mJ2vP/NW78s60ubM//NfWdXMsyvSX91yN7CYeYE735EOs4QHM7lJ/HKqfgKm4Y8yuD+0KlsGr8QfZCf2jD34DsnvP9NcjO0m680ewqTGmRFj8mFrxq/d8C7JrwOGhT9/G0ru+YZwNAc3NnT22V/q3J9hw1C+dYOsd/cIeZAe1q/76q56C7L55/xeQ3en+OLL71NHhGzo8eJSlk43fyo5x1+1MxLTn2MXrT7Ao4WA7c/K725gYiT4UMXSj41L2DhzsZtch5th16JxgdsZUkYFCA8GNmQpj8WPMCLl17mJk99tjLG3qayeGT2OSpJMFizR9fJalvd16fB+yO3YPS6GZuYu9/MdOM4dv8Sirc/jTnWzXejDJEhtIqtbkvczJ332IOcFjJ1iKJBUxi7uZ3ezlMIIDg7ydE8yuDxsK7riavZO+5yCLgt6+yDY6rv8iizAaY+qDxY+pFa+66FNZ1/vEaSYOPj1/ObI72mf1EUswp+XIMltv2xjLP+xezNLQ5hfZvJ4CplwN4O56o8vsChZUUQD1Mw6d7vYsi+AULSa2+pMwggPTwmAZm5rwmrdZ+Zu6LGtRL770y8juzTvvRHY3TLK5UJ/bxzacjKkiRTrzZ5SkEhb9WPyYWvGvtz2Ydb1vmmQOw0koRh4asG3dLy0zh6GYZI4infly2f7jyO62K1ik6dMnWW3SXJdVzZ+YZ2GA8SaL/Jy+b/gUtkaPiZEBFCO9CbYe7HGh9gL7Jm/BesL2HLt2zR47zv4E+9q/a57V29E6yz889s+Q3b3HYctxY0xtsPgxZoTkn97OUosub7Fak0+12BDQ+3rMQXnGOGuw8EPb70d2uujTyOzeAesSd2uXnZendlgL8F+//BuHtvnQ3V+D1movwAgObCTQnociZgGKkS5bb+w4C/1En0XSto2x2VU3fZx16/uhy1n7/e4RuBHw0AXU/LyamxqzFSmy1PyUr6bI4scYo10N5rj14Pb6vcss9+Zvi6chu+d02IDNsWARuP1NJnr3TzCHVmLr/drFNw9t8+cXPR+ttf0OZKaAfVqLNvxCzvytWHSYKCwm2YHSrm1T97LzubzAotGTw8/flSS1Wdd3Y0yNsPgxxuizXVYTcxi2nj68AMXPCbb7/IkTB5Hdt+1jkR96Xk70JpHdv9x5E7L7y1PPGtqmc5w5640enUuDzNSdpvVazK4Ja34oVBTSSFpAXd5mZXpqslFnOG3RmCqSo9tbGZ84ix9jKsStvXlk97kl1iHpgWUmmh5aZKk3J48xu7l5VoPTaTCP7/ZTTPwcu4OJwg8ssmhMe3b4L8Wpe9FSClh124DtxlMTih/YPIK2kG7BdMDOLFM/rSVaK5T3fJbSozLGlAKLH2MqxMmCOfkP9tjslgeWmN2xeSZickNFzPFjLNWH1itQQdJaHN7DbC1CpxvX0jCnm7TxPgOsTWKPHhYVUcBGEHCIK+1mN8bK0dQ5ze4XOJLNmEpSpFDBX4aVxeLHmC3IkQHLFflS9yCyO95lYuR0j3l8g4K9jDtTzAMb9JioOPYQE3eCAxrbrE+CJo7RQaDD2zWX2FqNLrNLDXavtOA1aC6zohg6H6jPMh1xTVNnlqmDyaPwHoMtztuzrBFEbxsMwRljaoPFj6kVy4k5z+1gjs3vnGKtkk8NmEc0C3NMHlpmkQq6o7Rvhom7AuYuHznFGgL055gj3Fpi2+u0roIKBLYYc56jD3fyqR2sMeq0YQMC2mChASM4cDnala41z27O1hx759Lr7nQ5Yx7BNT+rY/FjasV75y5Bdu+65+uQ3Z2HWJvXNM0KHaZ2shZJDZgrMg9raeJ+JtI6J2DdAdxd1z7muPV3sOu3tMTEVsBcprGp4ddrLbCvDVrzkzuNiTYSGD/Orvnk/UxU9GG3t6U9zG5xH7s36bBZmp7Xm4KGxpjaYPFjasX/OvIcZHfX55iImTrMvoi721nqxnyTeYqdSebkFyfYcc7cBztqwYGJtBg92swTbkC77nbmKMaAdmAb/jrg1tOwAQEWP9AO9rjA4q65yERTe57ZDeDQ2N4kHG47RmuakBm2M6aKDNTQANYxrp/y1RRZ/Jha8ambn4Dsdh5iLw9SUC5JzWX2Mik6zMvvTrNXQec4c9Zp8TQWMbBjWOtBtiBtzxwtdr8sXcI+YNEe/kCn74E1OPBZoCKGiyZmSFMPizEYGYm8DkejDyN3UEw2BrQ7YBmTcIwxObH4MbVi221MxEw9AL1nSLMHxRZsm9ufgCIGnhY8o4QNfdfYCWY3fpzOimHrLV7M7LY/gU12XNgx/IEuLsKhlUegsw7vFeo8t+BwTSqaBrDGqDfNntneVN45Rs1l2OVvCUZd4XU3pork6PZWxifO4sfUiskjsAj6FPXymVmjyxybsRNwmxUyGGeO2/J2WFTego4baxyFU5nojBn6HXX6FFOFg8XhvwKm6KOA5/UwO3qv0PV45AcKbGiH30k9KCYXaCdCdsPEwHlvxpivjMWPqRXNZZp6Q1M+oMMAa1voerijVsGKoLvTMAcZOm5d1uxN3e1sweXdcLcbpjtO3czEz/jx4e+XsVPMmaVdxui9MuhAoQzfETTiEDBNa+xU3v1WGomhLasbizDUZIx5mBzd3sqIxY+pFX1Y7Bs7YMtjOBCyAdv0UvEjWD9Az+fCRWy9hUthatEUFCPbYcioy87L5B2se97uz7HjHDs6fI5XdNmOfGrD1MrdrFVfHxbo0wgHtoPzj3ANTp+tF8vwOJehiIERnNSBoTtjTG2w+DG1os86LOO+q7RzVAM6GrjuYJy9CuYvZnazz1xGdgf2H0N2D51mdSqLD7Dhr5P3MAds4mjmNDswYybgPUZpwmeBHiedD9RcgGlaPfj5CrhBAsWrltgzKyi2KNFjG1XGVJEiNTSgfePXiWt+jNni5G6DSlNaGt28B9qbYc763AG23rc9/bPI7kmTDyK7d5z4RmS3/RYoYo6x67e4F9ZQbWMO33ZQFzN2FH6R0qAkTMlswYgKFQelSdOiImaR5eKmPhSFTUdwjDGjweLH1AranQxDd5+hw5dg56guFD/dS5jD98a9f4vsYJ8Evb33Tchu+j66K4/MNHsFVAhwvlN7fvjr3lxkQqu5BEUFjMRQMRKLMNVxACMcoN24JAk246CRGCpi1INpknQobstujTHnKNRQ4Tk/j8NvCVMr8AyIzLNGaMpO0WIvORwVbzLHdLLBPt/xAnaJm2UOO71f5i9hr9YdT2FpfbPzLJ+zuIWl9SEyz6XBYqRLWwOO2sF4DDT9kNpRsZUbet2NMbXB4sfUigbsOEU7VdFd69wDDNsL7PN1DrMC/R++7TXI7vgSK36f+SJ71TVhsTbtLgfHA6m3QBtyDH/daYE+7ihI7eBx0kJ75S60hzU/WPzAVt54Z4Wul1tkG7OFydHtrSTbIo/C4sfUCrqTTwf10d3SYpw5UkWHDkdljuLOW9hL9e6jVyI7Omhx510s9aa5yOwmH2Sv1tMf343sts0iM03dP3yUozXLakZwG3ZaoL8Ma1t6dJonbd8OHZNlGKGi6WsUeF5wzQ9o4mGMqRcWP6ZW0BkeeNglrMFJUGtRB7Nzijl8Yw+xIujtX0BmwqnLtH8E7KI2cxc7L5MPMoePivP2sfmhbWIBigoKddZpgT5Mm8LOOo00QZGWYA0OBZ8XR3CMuWAGKdztbRUsfkytSHDqex+mtNAp83SgYOck2w1uztE2ttBxg6JCdI4RBR5n4zQUoTSVic5SIfUtuWsq4DlJXXhO6DWgYck2bM2cu+bHYsQYUxEsfkytWN7ORExvgn3xD1hJjMZPsp0aKn6owzfYyWpwutthjQpMz2sfnUN2MbuA7PBsE+p4U0ECog6JhiVzk7kmhoqtoKKC2tH0PAqt3XHamzEXTKFQMfJubOXbGLH4MbWCipilPWy97jZmV3TYcU7dB9OmkJXUhfNlZi9jduMn2ZG2T8BPmHuwY+4ib7BewI57uUk4DY0KSdhCmoom+PmCdqWjoom2nqYtwHN33TPGlA6LH1MraNe26DPnshhj63W3Q5G2C85gWWAhKirSBhPITIMF2nEq80wU2i4ZOnxBU6cINGUxc4tlKg4SFaC0doeeF0pZRAxdz+l5xjzMQA0NRjznxzU/xmxxJo+wYt/2AnOkGn3Y8ABuWifomA4mmfNM1wu4uU7FK61NosXv2KGlDnSLDkcFN1rmmh+cZkfPZe40NCq2KLk/nzHGbDEsfkytGHuI1XB0jtEW0mz4ZG8apnfNwkgFdGxoQ4cGDIy0FuHMFzplPne9At2Vx+sBO+oE0xbSuYdrVr0hQO5GCTgiVpL7xZgtzCA1Rt7trYyhn00XPxHRlHSjpHtTSq+MiCslXSdpl6SbJX1vSgm6SsY8mlhkX6gNWDw9DnfJWzMsDY0OVaW0lpjTPXaarUdbcqOuZrqA+gg68DJ3ahFJl6Otp6n4yZ0WVpYITm5yiybaSTL3HCNjTOnYdPEj6c2SbpF0rjT8VyT9Rkrpuoj475J+UNJvbdbBmWqRJjvMcAE6z0twuGY777T4WGYibewoW68D0+Vax2D3NTrbhDq0ZamPILvysAkEbj1N0+xwtzCYypm70D632KLd8zLb4VRVYypIUkPFyGt+yrfxs6ltUSLiMknfKumdZ38OSd8k6Y/P/sq7JX3H5hydMcYYY4wxpkpsduTn/5H0f0qaOfvzbkknU0rntmkPS9q/GQdmqsnCfjaXpnOaRYyac2y3u4BpUwE3WRuzbDe/Nb/EFqQpUDR6kDsVhs4aoSlXtM4BpAOmZZiFTHfkM8+zoRGc7POP8OmE9yaNNMF7E0dwHPkx5mEGKTRI5YvMOWpXAAAgAElEQVTMjJpNEz8R8UpJR1JKN0XEi8799Sq/uuqbMyKukXSNJB04cGAkx2iqx9yl7JafbDOHgbU7kAYdtl5jwByN1nHoPM+y4aHYgc5cjB541kjmRglU/OSsp6HXoANTVTuw/TdMtwqor3N3FExBGxcwMyyactcYGWNqw2ZGfl4o6dsj4hU64yNu05lI0I6IaJ2N/lwm6b7VjFNK10q6VpKe97zn+W1n1sWAqhHsaMDW0+NQ/MxDD4V2Q6MRHBqJwcXomSMx1PGmYms543XIXYOT+1xSIQnvsaD7APQZotePPkM0IEZrfmiNkTEVxHN+VmfTxE9K6S2S3iJJZyM/P5VS+u6IeJ+kV+tMx7fvk/Tnm3WMpnrM3M2++CfvY+ldDdhdrrkEh5XOsfQ1LSwyO9pIgEIdsNyDHemAzRZ0oJego0iuH3XyqYjBjQtoxz065JSKA9oKuhwNCDCO/BhjRsRm1/ysxk9Lui4i3irpk5J+Z5OPx1SIbZ+F7cnm5pkddBgapAWxhHd10yKs3aFAURG5owetzF33cHvffHUOWMTkTl8rS91VbnAExxEVY8pGkRoqRj3np4Td3raE+EkpfUTSR87+/9slvWAzj8dUl3T/g8yO1gHg4ZOZa2KoYwNTiyJzRCW7I0xTi3p5rx+6P+m5zN2aOfezgFNAaWF/5ghO5oiK09eMMaNiS4gfY3JRwBkluPC9LEBRkX22Ce32RqGRHyrSqIOJ6zgyChLq5OeOqNBrAMVP7q5mpREVTl8z5oJxzc/qVNyjM+Yx4Dz5zI83dkozt6OlRdfdzAMMoSOFI1S5xTIu0h/+fokydJbbDHJ/Pto9D0busg8Pzfz5jDH1weLHmHWAv/hh9lpkbunMd5/zFmun3CIUroevH40YUUBr9ETbd2XujYGh84Fo9JQK5dzd7MBMKIm/W7CIyf0MGbOF8Zyf1bH4MWYd8IhD3ghHwIhRdlFRFmikEM+0gcX9VPSCNMIEnWAslClUxBSZUx1pcxMqDnAUFH4+Wgvld5IxZkRY/JhakdvJ5+vBfH469T13MXruWiEcaYIONI384GYC1A6EY3AL4szih+5XwOVwOiAVFbSVN70OVEyy1bJ2MDSmqhRqqBh5zU/5IksWP8asBxwByOvkl0bEZHaEqQiNRsb5OZK0zKIquKtgxmhM7o0Heu2UO0Uk8wYJBs9Ngm6G5/wYY0aExY8xW5DsIoZSltodCD5Omia5DIfU5qxzoCl9uWsx4DOEj5M+s9SOtmEvSWOG0nw+Y7YwZ2p+3ATksVj8GLMeYISjNCKmLJQkApe9MxaEOPpYHNDaFuoEU3KLkdzpcrhhBYxm0tbamWuajDH1weLHGFOaSEz2WqGqQ8QPTWPCkZHMXb9yz1rK3L49++fL3Lkyu1g2ZguTFCpGXJNTEu/hUdiTMMYYY4wxxtQCR35MrXAraDMMlU9bLMMuOY38lOGzSTydrCyfjx6nh5Uac8EMUmP0NT8lnCNk8WOMqbwoLEsXPHycGYvDE627om3Y6T2W+5pnfxYyn5fcbdid9maMGREWP6ZWlGXOT1kiDmU5TkzuGqPc69Fi9IwkWqCfGxzhgF3p6L2C34HwOuRueEBr0oypIAM1NBj5nJ/y4beEqRVVj3CUZe6OGxfUkNyti3MLO+qs03FEuef80OWouKPvXHd7M8asgcWPMevAEY6NXq7a57M0YpmQeyefgsVIZtFkcbcqiQ6p7ZckUmhMBgqFihLW5Iwaix9j1kPFIxVVFyOlgUbg4JdbznlEUfUd+dyiMLeYLEstTZU3HowxG4LFjzFbEIuRrUFpIjhUxGQU9WlAxUHuZhUwTctiZEOhNU04YmSMqQ0WP8aMkNwipjTOulmV3NcvyuAoFjQyUhJxUIKmE5JK03IcD+E1poLkaXhQknftCvyWMGYLgp3g3I0LclOS9MOyiN6cYgufE1ow32yy9XJT9XRA+PloS/WIklx3Y8ymYfFjagVvPc2+iBPdtc4sYvJHHMq3U1RJyH1GBWhJhGtp0slyiyYYoaJ1ZVFAEVMW0WtMBorUUDHqIaclxGfEGGOMMcYYUwsc+TFmlMAIjmt3zkNJ0vpwxI8vmHc983hyNzygwEgM7gxI097oer0+szOmggwUGoy4JqeM3orFjzHrwGJkY6n6+cSNBMqSGlYCEkzTwl3bSjL/iJ4X0W59VJjT9LWM7duNMeXE4scYY7YKuSM4QGyVpl4rd8SB1grldtYzixhcZykYoSpLzZYxGUhZan7K98xZ/BizFaFOcO7IQVmO02wYuZuG4FbXFKcQrkruaC2+z6i4M8bUBosfY7YiZRExZlW4QCjfDtp64c5zSdKY/AxtCVLf18GYc7jmZ3UsfowxHEdwVqU0Iianw07vFYuKVal63ZwxxowKix9jjEWM2bo4CmqMMQjP+VkdnxFjjDHGGGNMLXDkxxhTeWgaGk0tcs1PiXF63pbAz4IxF84gNTQYceQnpfI9qxY/xhizRchdx5HVwXRnwFVx7Y4xxuTF4scYwymJQ2sHc3XKcV5Yt7fckYPs57Ikz54xZvMoFCq2wByeiHiZpLdLakp6Z0rpbY/59wOS3i1px9nf+ZmU0vWjOh6LH2MMpywpQnb4akc5hN0F4HvaGFMCIqIp6R2SXirpsKQbIuL9KaVDK37tZyW9N6X0WxHxNEnXSzo4qmOy+DHGVJ+q75JXuWW1r8HqlOW8GGM2jUGK0df8rP0rL5D05ZTS7ZIUEddJepWkleInSdp29v9vl3Tfhh7kY7D4MbUid+G72WDs8G0+VS/sL8vnq7iYdNMQYyrDfkn3rPj5sKSveczv/IKkD0fEmyRNSfrmUR5QOd6CxhhjjDHGmHVTpBj5HykUEddExI0r/lyz4jBW25F47O7G6yW9K6V0maRXSPr9iNHt1DjyY8woqfjurFkdRxg3kLJEYspCxd9JfoaMyU9K6VpJ157nnw9LunzFz5fp8WltPyjpZWf/W/8UEeOS9kg6ssGHKsnix5jRUhKHAZPbMXVdRXkpS3MMszoVF03GVJGBGhqMOMlrHdsNN0i6KiKulHSvpNdJesNjfuduSS+R9K6I+CpJ45Ie2tADXYHFj6kV3hU8D3YwN5Ts91kZHEzfY/XE192YWpNS6kfEGyV9SGfaWP9uSunzEfGLkm5MKb1f0k9K+u2I+HGd0VPfn1Ia2RepxY8xo8Rf/OWmLNevDOLHGGNMVtLDdTmbfRzpep1pX73y735+xf8/JOmFuY7H4sfUi7I4s8YMg1OSjDHGmHVh8WOMMXXFmwHGGFNZCjVUjLzmZ/MjS8PibT9jjDHGGGNMLXDkxxhjjDHGmIoxSKHBFqj52WpY/BhjjDGmGriOzRizBhY/xhhjjDHGVIwiQ7e30TWkHh0WP8YYY4ypBm7iYYxZA4sfY4wxxhhjKkaRGiqSU0Efi8+IMcYYY4wxphY48mOMMcYYY0zFGCg0GPEcnjLO+bH4McYYY+qCu6EZY2qOxY8xVYI6Ni4SNqZcWMQYY9YgR7e3MmLxY4yxaDJms7CIMcaYrFj8mHpRFiffDpEx9cAbCBuL353GPIy7va2Oz4gxxhhjjDGmFjjyY8x68G7i6pQlkmaMqQd+txjzMIVCxci7vZUPix9jRkg08hYapqIkr6GSiElfv1Wwc2mGAT7r9NkrxTNkjNlULH5MrcjtzJrVKc11yCzSosGEhR0+s24yi5FotZGdmvDZ6/aYnTEVpEihwci7vZXk+3wFFj/GGAwWMSWJ/BgzcrIL7LwiprFtGtmpzdZL8wtsPWNMbbD4MfUic41KWXbkc4uYaDbZeiW5Djxlh+7KZzwvrvNanZKIGPzMdmAEZ2yM2bWYexLLXbaeMRUkR7e3VA4351F4+9UYY4wxxhhTCxz5McZg8O4ztRsws+zgiBhbLsHzQiJGOIrmVMdVKU3UldKFkZjlZWRWLC6y9YypIEU6U/djHo3FjzEjpPLdwnI7tHi9zKqJpnhldmiJaKIpduY8ZG5AQEn9PrObm2cLDmAq56AsOyTGmM3C4seYCpG9AQEtnqbOOhQxAXe+sotJfP3odQDXvepOaW7hmrvzIf18Jbl8xphH8Jyf1bH4MaZKlMQBS0U5ogfZxSQVMZ0OswMiNNE0JlqHXpImF9kpS+OJ7BsrbDljTH2w+DHGGGOMMaZiFCky1PyUr6bI4scYk792h/bGpLv5tMgbRmJK0/uT7K7Tc9mEeVP0i7tgNSoYHFGh55NGednXfu5obcA5P8YYsxYWP6ZeVH3WSFnIPXcnc4crXN9C62lgZyzBIvYygGct0doWnOqYuWsbtAsq6MtS62VMBckx56eMWPwYUyGyt56mkRH6Loaiie5aYwcTR4yYo5h68Lz08omf7IX9lJLUzeHoIo665t04Sr0eNCxJ1NUYs2lY/Jh6URbHhpK50B5DRQzcRaafLrsblbuVd8ZIKI6oUDKnctIGC7R1OBauNBKTOwWURocd3TfmYXLU/JRxu8GxMGOMMcYYY0wtcOTH1AqcxpQ7LYySPRWmHLuzuSNGueGRSdDquiw1HJnn9VB4S+68M6/yN0Vxi3NjLpQcc37KiMWPqReZh3JS8cML5vM6ptjRKMmskdyOfmnSKwG5ndLSnMvMIi232MqO096MMWtg8WPqBY3EZI7gRAM6NlSk5a5XKDIPaCyJQ5S905h5PCW5VyqPr4MxF0yhDDU/I58jtPFY/BizDnDaVO5uYbm7r5VkM5hS+WgFcDDLklbEGxCU44u8LMdJ351luc+MMeXD4scYY4wxxpiKkTJ0eysjFj+mXtDC/ty1O5kHCmbfZc3d8KAsu8iZW7Fnbz9tHk9JUhYrHwU1xtQGix9TL+gXeO6hnBXvqFUaMVJ1kONdjnuz6s6znyFjzFrkmPNTRix+TK3gXdQ29jgMo+oOLReT+RpI4ChTZmfdkYoNxtFaY0xFsPgxtaIsERXsSNEUmsyOTeUdxdy4M1b9yD3HqCTvFmPMI+SI/JRxm6IcycbGGGOMMcYYc4E48mNMlaj4Lmvu9sVOndo4ynINspP7mS1JxIjOEDPGPEKhUKHqfq9QNk38RMTlkn5P0sWSCknXppTeHhG7JP2RpIOS7pT02pTSic06TmM2g7I43WVxTH2cG0dugVb1e7M0VHxjxRhTHzYz8tOX9JMppZsjYkbSTRHxV5K+X9LfpJTeFhE/I+lnJP30Jh6nMZXHjmK5qXLEyGwNqj401pgqkqfmp3zP+KbV/KSU7k8p3Xz2/89KukXSfkmvkvTus7/2bknfsTlHaIwxxhhjjKkSW6LmJyIOSnqOpI9LuiildL90RiBFxL7z2Fwj6RpJOnDgQJ4DNcaYEZJ9lzzngM2SzITK3mmRUpI0tNJcP2MqSJY5PyVMHNl08RMR05L+RNKPpZROR6zvIqWUrpV0rSQ973nPK+GpN5tB7i9Gp5PVEztgJQYX6Od+t7j19Gr4nWuMWYtNFT8R0dYZ4fOelNKfnv3rByPikrNRn0skHdm8IzTGVAGLkfNQYUe40lE0SbknL/sZMqZ8ZIn8lJDN7PYWkn5H0i0ppV9f8U/vl/R9kt529n//fBMOz5gNwQ7DBpPdwWSUpkNZCcRP5Z8h+PkCOjQp85znaDazrufIjzFmLTYz8vNCSd8r6bMR8amzf/d/6YzoeW9E/KCkuyW9ZpOOzxhjjDHGmFKSp9tb+dg08ZNS+gfpvP3xXpLzWEyNoJGD3IMBS0L24vDcUQC6i0x384OtlwYZt/Nd2L81wNchc+jHGGO2GJve8MCYnPAUmrypG9mhjlQTFoe322y9dTZEeRxQHGQVFRIePoBToGjRfJWhXengrRK53y2ZN4A8H8iYzSOlUHLNz+Ow+DH1wrvWG0o0MoumFntlpS4yUyQYiSkyX3faoYz43SVpWU3hxwnVT8XfEfzzMVGYu8bIGFM+LH6MMcYYY4ypGIVCxXkrTDaK8kWWLH5MvcheM1LtSBONcOCrANPe6G5w6veRHQXvWrfgGQWRLZoKSOuZhFP6aLpV3shWWSJilNydD+n1M8bUB4sfY9ZDbgeFirSq13DgNDt4/WCaHRV3MdZhhuNjzK4HxN3CIlsr88ZDdHvILnVZjmQq8gplszpVF5PGDIO7va2OxY+pF/SLMXdefllEDKyJwdeB1tLQiFEbviKhaCr27UJ2S5dNI7v2qeEd/fY9x9BaGuSug1pCZjiaSZtqlMRZz97ZkVL1GipjzAVj8WPqhVtWrw49L1Sk0S5qfWgHGyzg7nJQNA22sQjO7GVsvdbu4dPstveZQGueYhGjWFxGdrjdOIwuppxNJ1SeQbq5u7a5g6ExK0gafbe3cuzfPAq/JYwxxhhjjDG1wJEfUy9gOlJpoGlomcfZ4Pk5MEIVdHud1hjB3fXmaRblGD/OIka9yeF3BJf2sbU64+watI/BiMrCArLL3VQjJsazrlcswpqtzM0/KJ4PZMwjFCnwHLgqU3FP0JhHg4dr5p7bQufL5B7KSdPl6Ms4d31E5qGqjROnkd3Mbew4u7smhrZJzcxfpPQadGDzCOjk05lQsWM7stM4+3yNYyeQXTE3j+xKU2dpjKkNFj+mXuQWB9Bxw0Myc3++3NDPR88njaRRh510X5PUOD6H7Ma6w6+XxtgGQiywLmq45qcDj3MZtkVvwQ2LaRb5KSaZ+GnOMrtowgYSNKxc8VeZMTlIKUZe81PCkh/X/BhjjDHGGGPqgSM/plbgiEpucrcFptAueHQgJI38wJkvAaMHosNKqR3tbLY8fOQn5lgEQLTWhNbp0dlHNGqHW0HTFFBmhqOZxpjSkafmp3w1RRY/xowQ3DYXz8+peDAXn5fMYpKKGFj8nsahSAOON61twdcON/GA15w2LsCpjrA+DJ8XOo+ItsO32DLGbC0sfkytoB2Ssu+WUkeqLNm3uecK5R7GSoHziGj9R396eNGUYgqt1Tk+fHMFSWocPYXsVMAoIRSgvDkG7GC4xGqo0jKzK03EqOoz2YwxF4zFjzHGGGOMMRUjpfLsW+TE4sfUCxr5ydxFjUao8Duu4pERHkmD0BShPu2Mxa5Db2r4+2zuUva1EYlFp3Z8mUViOg+yDnh4thMkFmEkJve8nuxt5h3BMcaMBosfUyuizW55/LVPHY3Mgxb5fCDaCjqzY5O5kQAWk4usmUATrjfeGf68LO1i53JpJzuXC/tYPVNznommxiJrjkGJ3EKZUpbhobk3OozZwhQKxYgbEpQxsGTxY+oF7ByFK3Cg+KFihDZYwJTFIaJF3rSLGu1mB2uhYonNwmmB+3PnYCdaq7cNDuXssnPSADOMJClwZISZqcfEVvaBxplFBX6XWfwYY9bA4scYY4wxxpiKkWPIaRlDPxY/xqwHugtJ2+ay1Xg7WpqmRdPzaAtw+PlwJA2eF/pdgK8fvT/BeWnCmUlNOjOpDe0o9FmgESPafY1C30k0dZQC6/vCtULGmDWw+DG1Ii2z9CAMdWZzzxopSzuYzI0ZUkmGzfK5UODz0XQrek/DOj0sCKkdnoMDUx1z17HRYbO5BwUbYx4mz5DT8mHxY2pFgrUR2Wtp6K4ndDRw/UAvb00T7jhF5wqVBTzcdvjzSYUWjqJRYUefIep05641oZ0PO6z2Km1n850GM2y+U2qzz9foZq6FMsaUDosfY4wxxhhjKobn/KyOxY+pF3T3OXNqCs5bp93sYF1FEmvNjKMAZUlDgxGqKEP3PJpCGPAZohEVGhnJDY0qw2c9zcAIzvZJZNebge+WFrvuja7T5YwxXxmLH2PWAU57w3bU4YNf/GMsFYY6plQc4LoKmvOMRQw8ztzF2jnTAWE2Et205K2SqRjJ2xSFPrNqwiYlMJ2sPYvMVEDxU5r2+8ZkIEe3tzIGlix+TK3Ins+f245Ch7/CGiM82DF3/J5eh8zznTBVLo+g9xgl9wYJ7WA4BwfpLsBmMfQZwh02SxLxM8ZsGhY/xhhjjDHGVIwsc37wcI7Nw+LHmFFCIxU5WxdfAMXUGLJr9lj9QNBZKhTa3pdehx6boSM4ewenHxJgOhJOX6NRXho5oOvReyx3hIO+k2idHn3WS1IXaIzZPCx+TL3InU4GwUM5aeMCWAcwmKSvEFZ03aTiALY4x/cLbTyR29EHDSvwvYnFSOahnJlFTIIbCGmMNhKgc4yYWaPLREwswuGv3cxDY43ZwhTKMOenhEU/Fj+mXtCBiRRc2E93WWERB3TyizHmKA7Gmd1YbwbZNY5Bz42eT3qfNWEROxUk5Lov53UuI3dkBNeo5K1toSIm4cgWM0sJitdu5oYVxpjaYPFjjDHGGGNMxfCcn9Wx+DG1IsbHmSGNAMDaD9z1i84jWmLpZI0uW683w149vT1sWnyHnpfT88hONP1wnNlRSFQlWqxbGK7hyN0tjK5H26L32LPeyOzRRJ9GT2n9G7xfaGqsMaY2WPyYetGi+fzQrg/TkajjRh2iRebQto/OIbsYsIYHRRum2dHGDNDhw0Nccb0JTIHqDP8V0KD3Jq3FoM5z7nbqVNwtwnuMrVaebWCa+luWz2dMBjznZ3Usfky96NDBgLRIGL4Wcu960sjIKRYZacOBicU0EzF4Nx82glAfRgHofKAmixgVQPzEBByIS6OZVPxQJ5jeK1g0lWTYEt0AwjU4NPoNlzPG1AaLH2OMMcYYY6pGljk/5cPix9SKNAkjBxQaUaHrJTpTA65HU4tgml2Drpe7yx+MVgQNAtBUNBD5IdEiSWrmTuXEbcOhXYO2Q8scqqDd8+AzRNvoB4wOK9zq2hjzlbH4MbUiwZoR0doPtlr+QYs0tSi7o5g5jTC3w05rxOB1QLVJNBUQp01lTkOj9yYV2LQ+jIoRKF4TbGtPr1/A+UANVoZoTCVJKmdNzqix+DG1Au9CwrBxgsMxqIMS1O40LS7OHImhs1RoXQWNNOWGOvrALtG5NHDjAc/5KeA1p4Keggfp5r0O9LoHfYZwnZ7n/BhjvjIWP8YYY4wxxlSMHN3eyojFj6kVxRi75RuwKCaC7cjT46Q04ayRWFxmC+J2tJlf4jQdMDewq2BjcfjugDQCQHfy0wSr0wua6kgjFbSbHU1VhcfZWII1MbnTDwfUriTPrDFm07D4MbWiP8lu+TYd8Af7ribqX9LDpJkiNO2tyJzSkrvepCSQuoqgIobWCtE0LZriCgf+8hojeJz4nQSh1z33M0RTY42pIjmKfkpYVGTxY2oFjv7SL36aJw/nxDRoBIfusuIZHhB6HWB9BOmGdkHk3iUn0FoTagcjI3SuEBYVuYdrZm5Sgp+hzOInd/M8Y0z5sPgxxhhjjDGmYuSp+SlftNXix9SK5jKdvwLt6C4yba3dh3UOdBeZpphkTqHBLc7prjWMxKDW02cMmR0At0qmkQMKnZlEgXVX2YHHSd9lON2RPnsVT1U1poxExMskvV1SU9I7U0pvW+V3XivpF3Qmke7TKaU3jOp4LH5MraAiBkOHnNKUHZr+hPPkoaig6+VOnYJiJGib5dwARzF3DQfeQKDZa3QuDVuOk7sBAWwgEf3MIsatro15mJRGn5G71n8+IpqS3iHppZIOS7ohIt6fUjq04neukvQWSS9MKZ2IiH0jO2BZ/Ji6AZ3uosOc5+xfw7nz62nnr8x1I0Ub1l7RCA69DiXw2/CcnxYUFfBcNmjXNhipoDO98DXPHZXMPSurLA0WjDFr8QJJX04p3S5JEXGdpFdJOrTid35I0jtSSickKaV0ZJQHVIKvWmOMMcYYY8wwnKv5GeUfSYqIayLixhV/rllxGPsl3bPi58Nn/24lT5b05Ij4x4j42Nk0uZHhyI8x66CgkQoaAMiculF02HqDMdiGGEYBMHS3O3cdR+6UMvL54Cmh7dubXZg6ilNO6TWnNTEwYkRrqHDaG1yPpi3SFue0vs8Yg0kpXSvp2vP882pfbI99EbUkXSXpRZIuk/T3EfH0lNLJDTvIxyxmTG2gjk3qwHQ5OF9mMMHW608yB2V5O7PrTdHzgszUgCNY2vPsureWqacPzXKnQAEaPdqGPa+QjAG8yWiWFhQVuVM5KfR80g2EBDeA6EaOMZUkxQXM+NgwDku6fMXPl0m6b5Xf+VhKqSfpjoj4gs6IoRtGcUAWP6ZW0M5DA/iF2p9gdt0ZZre0m32+pT3ITEUHOrS0HGOJfb72HLPrzDK7JhRNCdakJbjZXQC7Bixg78yyi96EEYeCRnDgyaQDhqmzTqPRFB4RY9DocJE7qmyMWYsbJF0VEVdKulfS6yQ9tpPb/5L0eknviog9OpMGd/uoDsjixxhjjDHGmIqRo9vbWpkOKaV+RLxR0od0pkXs76aUPh8RvyjpxpTS+8/+27+IiEM6M6jgP6SUjo3qkC1+TK3ozbBbvj8O08m2MbvFvchMi5fA7eddXWQWcL5M0YPpgMuwNmmSrVe0YZTjNOxQBtP6aLocCXIk2i0epuaR6JQkCUZUok+jdjS9i7aCZmY0JZO2R6LRTEdwjKkOKaXrJV3/mL/7+RX/P0n6ibN/Ro7Fj6kV3WmYvjbOvoh7M8hM3Z2wrmLfErLbPrOI7AYFrE0aMI+222WvrN5YG9ktN5gddfSb7DIoYBfiBrBrwDm6GFzPlDf1kM6ZxamO9LTQ9ahoonOTaO1V5vQ8Y7Y0SXzDo8JY/Jha0YMNAfqTcL1pZjcYZ2+rTpt5wa0G8zT6sAh6MIB1DlBsqZu3PoLeLwXVWrSGamF4Gyp+BvCz0WZo9IrTaB+df1TAZipUNNGIEW1Y0VxiN2cDdomz+DHGrIXFjzHGGGOMMRVj5Swe8wgWP6ZW0J11WndA18M1HPAlN95mxSb9gh3o3ByMGC0wu8YSPaHMjEbuaAvw1mK+KAD9HsVpTLTGiNaawBocWqNCa374dYAzr+CzgCMxtEW2/TxjzBpY/JhasbSb2RUdZtebgV/gEyx9bazNcl/gHQAAACAASURBVJKm2qzhQQ/W7tCGB815qEIH0MFs09ktsGYLNnQQSF+TWApbdhEDndkBTl9j65ViQK24iKHgNMIx5p4kuJ4xlcQ1P6ti8WNqRe8Z88hucoKJg4smWQV7E3qKky0WwaF2DRjh6O+Fc4x2sFAa7Uo3gJGt5WXYmGGWqezGEjsvA7AcFTE9uCVP59mQZg6SsjsKVMTQeUt0xhat2Qo66BmKmMGYxY8x5itj8WOMMcYYY0zFcM3P6lj8mFrxDy/8b8huBrY8PlWwiMpJ2NVsPrHjbMLt4Kvb7BXSjryvns/3WF7YB2afiew+ceJKZHfXqZ3I7niHtRUsxocP/bTmYBtv1oVdQVMWYYYkbRvehqmH7Tlm12TBaBzZCuhA0cgWbgFO50IZY2qDxY+pFfuasPc0ZKI5huwu9hf4hnJ1m/WeftLOW5DdB8YeRHaf2XYA2X15F5uKe8ep4YvgTsxPoLXoTKiJceblT8D6t+Oz7F7p3jGF7KbuhemAcCYUHlZKW2TD9Dy3rDZmA8hR81PCRzXv8AtjjDHGGGOM2SQc+THGmPMwFiyN8Jmd+5HdvuYssnv6xHZkd8/2XUPb3LW4B601R7orSNrdYflkO1usucnNp1j07aaFK5Dd4jI7L2328fguLbSjQ3EbNN3R5Q3GrCCEW2YOtUa5sPgxxpjz0EvMc9sFZ7dcAgtjljvME54tDg9tc9v4DrTWoeX9yK7AvacZ061lZDezg4m0WSgqerPs67sJZ0I1l2jNDzLDXenwesaY2mDxY4ypPLThwSwc8HR5i3lg2xqsRmw6xpHdbqArqEA70DqE7E4ndg2W4MTYsQZrUjIBOxDcv4tF7e6f24bsjh5ndY/9E+zebM0z8dqCNU0N2gjCmCriOT+r4pofY4wxxhhjTC1w5McYUxru7rOamEPLlyG7g+2jyG4GtvJuBtuPOg1bf82CtL4e3EXsirUwHA+WergXpq9NNW5Ddpe3jyG7u6ZYDdWhyUuR3WdazO7exNqwFz0WMQraUp1ddmOqiSM/q2LxY4wpDVMNJg72tk4ju13QkzoJZ5t8tsscxRsXvwrZfWHhoqFtaA3OLliXdFGbXbvJBrt2S3BW1tyApR4+sMzS3u6aG75ZhSSdmGetvIslJl7by7BWCDZKsKNnjFkLix9jTHZOFKwG52boKH5p+WJkdw+sbzk5YA7mLfOXILsvnWZzfk4sDn+cYy3mlR6YOYns5seYIKSc7jMRc98Cq8F54DSzmz3J5i3FKSbuxmZh7Q7sSkeH4tLucsZUkhRugbgK63qbRcSTI+JvIuJzZ39+ZkT87GgPzRhjjDHGGGPWJiLW1SFnvZGf35b0HyT9f5KUUvpMRPyBpLeywzPGjILFxFJ9PjC/D9ndMP8EZLc8YEHnkz222326x3bzt7XZ9vMCnGlzH+zgdWKORZqWF1gUgDAP59ks7GDHeMkES5c72WX32N3HWU3M8hF27VqnWBpaiwVdBZvZCWYfqk2Pc9l5b8acI6Uzf0a6xmj/8+clIj4i6ftTSnee/fkFOqNXnrWW7Xo9kMmU0iciHhU6c3DZmC3GoR4Lb//d6acgu08fY7Nb2o0BsptqMw9soc8c6NOwBmexxxz9UwtMpPW6TEwWy8M70LEMmzL0md09DfbV2ghmd2SBtYJeOsmu3dhxWEvDtB1uCBDskRV81NWAnTWarFO5MaZ8/LKkD0bEb0raL+nlkn5gPYbr/cY8GhFP1FmBFxGvlsRGmBtjRkYTTgbswpkoc3A3n1LASdIFzHk+vcgc2qVlJrYGAyYQGk123Sd2Dh/ZoueSbg/SXUs6B+f4aRaJacwzEUNFBYUOAaV2dEbtYIzdZ5ln4hqz9Rl1aGaTQj8ppQ9FxA9L+itJRyU9J6X0wHps1+vx/KikayU9NSLulXSHpO8hB2uMMcYYY4wxlIj4OUmvlfTPJT1T0kci4idTSn+5lu26xE9K6XZJ3xwRU5IaKSU2bMOYmlHASMwdfZbw/qUuS0M7tjyF7Ja7LMJB07QWl1ikqQkjI10awQHpZJKUBnC2yTjLQt4xPfx99tRdR9BaFNpFjXSyk6QEI1vFBLvHen0Y4Wgyuz47LYJZhIKvQJye13DamzGPkFTlbm97JL0gpbQo6Z8i4oOS3inpwsRPRPzEef5ekpRS+vWhD9WYTeRjy8xJPDZgdQC05fFswYqu711mRdctmNOyY4oN1zw2YGKruwDT7KCoEHRMBWuvGgV0vLss1+domhneZor1Lt4/eQrZtRrs3qR2nQ57Rww6TNCnFrt2cKwQ94NgOllzEc75gaLJc36MqQcppTc/5ue7JL303M8R8V9TSm9azXatt/W5b8anSHq+pPef/fnbJH0UHa0xxhhjjDFmpES6gKjtetcY7X/+Qnjh+f7hK4qflNJ/lKSI+LCk555Ld4uIX5D0vg08QGOy8Cv3vALZ0V3knR2WvjbTYi2WcTE6pFew7eDeIksna5yAdkvwvECzosO+bVILdjaDHdgKDX8+D5/cgdai0cXJFstjGp9m7dDml/cgO83B1tPz7NqlJrtXigl4b8KuewG7/A3G2cM3YEFzY0yNWG+c/oCklT1mu5IObvjRGDNido2xlJ0J2D91Giauj8Ex5YsFSwvrwxZJ84usFbRmWYpQa445RC2WnaeC+bPqsY+nAoofDHBoaf3U1dtZg9DnTN6F7HY155Ddu9r/DNn94+GnIjs6d6doU3EARcw29g4cTMPjXIIPX3XrG4wZniSngq7Cer+if1/SJyLiz3TmNH6npN8b2VEZMyKaMP57cPwYsrukfQLZLScW4aA1RoMp5jAs7GbHeTts6dwNVugQUMXgtsCwfXHQWiFoN4jhrwOd0fTybZ9Bdt8Aa1soL7ni75DdW6ceRHb/49Nfh+zSKTigdpptrOzaxTaOto2xKPYSnM115PjwdWzGmEpy3i/G9XZ7+08R8b8lfcPZv/qBlNInN+LIjDHGGGOMMRtMilpEQyNip6STKT1qMtzbz/f76xI/EXFAZwYI/dnKv0sp3U0PdB1rvkxnDrwp6Z0ppbeNai1TH2588HJkd/8Ma7dLO1xNNLtr/9Iq7GyzHJqrJ+/NavfpmQPI7uYdlyG7w2O7kV3rBMtfC9hdrjWfuTMWsDu1wIoqaIc/iUUccvOze25ldi9hdr8/y2qTPnLyKciOpv5OQrsBdNgOz7COl8aYchARPy/pvSmlWyNiTNIHJT1LUj8i3pBS+mtJSim963z/jfV+s/+lHskanJB0paQvSLoaHvtXJCKakt6hMy3rDku6ISLen1I6NIr1TH04/UX2xXiyw4q8PzfBUoTo3JapaVZj9PR9rB7ja3fcjuy+auo+ZDfWZOfln5CVdG+b3S8BU5KasDFDinwNHbrz7LP9+bHnIrvvmPp7ZFd1vnfmKLJ73fS6BqA/jt8+dRDZHVq4FNnN9li+42SLbRwZU0ly1Pzkryn6V5J+6ez//76z/7tX0pMlvVvSX6/1H1hv2tszVv4cEc+V9G/XfZjD8wJJXz47XFURcZ2kV0my+DEXxPQ9dGcdOqUN2IWryRzM/gTblf/4zu3I7mN7r0R2E1CktWCxfa/Pan4aLbZeMQ7tYG1So0s7cQ1/XzeOs6YaH/3ik5Dd6wfsWfiVy/8c2R1oVbtmpB0smrmrxSJwt8EI1V3HdiG7Ar6rJZ3xPIwxW53uivS2b5F0XUppIOmWiPW94JBnllK6WWfm/oyK/ZLuWfHz4bN/9zARcU1E3BgRNz700EMjPBRjjDHGGGNKRsrwJz/LEfH0iNgr6cWSPrzi39bV9Wm9NT8/seLHhqTnShql4lht6+ZRpzildK2kayXpec97nhv5mXUxeQTOUenBnXU8pZzO4mC7nv1JaDfBUlP648yugA2uBDtyd2DLavqFADucK1hZBRp+l5qws9xJds1vfODJyO5F+34M2V152RFk9/KLWWLC67d/Ctntb+aNUD3YY9HhE4usA+XSXN42+saY0vBmSX+sM6luv5FSukOSIuIVktbVjG29b4mVb9m+ztQA/cn6j3NoDktaWZl+mSRWJGDMCsZOQO8yt7yGDmb0mdrqnIZiq03T+pCZihZNP8w75LQsFMBPpNdg0GF2eJ7NvSw978FbWVONa3fuX/uXVuEdu16M7LbtZWlol25nTVjmukyMHD0xjewEB/fiDSdjqkgF5/yklD4u6XGD1VJK10u6/tzPEfF9KaV3r/bfWO9X36GU0vtW/kVEvEbS+87z+xfKDZKuiogrJd0r6XWS3jCitUyNaM8x8VO02BcxSyy9gLx1WPgOxx8puszTCChGaG1LYwDt6OcblMMDS83hb9Ciw27q/gSz600zpdybYPcYbLSozmn47N3BwpmpyZqwHJ5kdgM4b2mMvlvorKxyPHrGmNHzZp1pgPA41vtt9JZ1/t2GkFLqS3qjpA9JukVnWtp9flTrGWOMMcYYUynOzfkZ5Z+tCxtyGhEvl/QKSfsj4jdX/NM2nUl/GxmPDV8Zs5lEAbcv4S4kDBjhlKQCptnR9Dx6nLQWqrEIa7ZgBCdgpCl6ebetU4sU/bDPRm+xAqZWdqfZgl1YSlOwLDs1l5hde47ZTT0Arx+NusJ6yUafRnmRmTGmepz3JbJW2tt9km6U9O2Sblrx97OSfvzCj8uYvNDaj0SddQoVTTBNi9ZVYDtY89OAw0Pp5lTRhq2nYe4NFT8xYB5fFMOvFwWtxYCCkO47tFjh+wCm9fVwHRu0o80/4LPQWmIXorXA7s3GMpyRBu2MqSKR+Du0ArDIT0rp05I+HRHvOZuKZowxxhhjjDGbQkQ0JL06pfTer/Br/3i+f1gr7e29KaXXSvpkxOO1Y0rpmes+UmO2ADSFhkY4aFvggCkfdHedHicFp7TQluNw54uelwQ3nxNsrBEwFU2gO2Cjx/pqN5bY/llzkdm15lgoZvwYC6nQxgz4HUEjaTSqDJ9ZXBJAo/S0s6MxVSRHt7dNiCyllIqIeKOk84qflNIbz/dvawXc33z2f18Jjs2YLUeCxTTUQcG1LdAO1yZBaH59c5l5YI0uTe+iNT+Z3+rQcaPpeUHu637eei1c57XMRFMH3mNUbNFrjs8n7AiJgceJ6+16Tnszpib8VUT8lKQ/kvRw7/+U0vG1DNdKe7v/7P/9kZTST6/8t4j4FUk//XgrY7YuuNU1rAOg9QM0UtGANSMJOkQNOFeoAXfzcW1LZhFDIzjUDgOue4EnvzJoVIvOvCLRMElqgPopSVyMlET84OtAn3W6njGmbPzrs//7oyv+Lkl6wlqG6/2mfekqf/fyddoaY4wxxhhjzAVztubne1JKVz7mz5rCR1q75uffSfoRSU+IiM+s+KcZfYVCImO2Ks1Z1le2AdOKWnSXle4iQxL8fBTSZUwS7oKHzycejsoiWzQCR/tIp7Hh61vSGIv84BRQOrgXpk3h1EoacaARHPyKyJzKCZ+9gNch97vTmK1MVbu9na35+VVJX0fs1/oW+wNJ/1vSL0v6mRV/P7uenDpjthqxsMzsGpnTkZowbYo2LoAOZoLnhdoF9fgK6EAnKpqgwwcd4bTmq3zjwE0gYLMRWsAesDaJz2iCoonWqGSvR4N2uTcsqJg0xpSND0fEd0n605SGe/DXqvk5JemUpNdLUkTskzQuaToiplNKd8MDNmZzgJ2qcJ584A4LbDna0UHsvEQTdriitS2ZHRsaicFVFbi+BTrQIELVoOekl3cDgUZiaNQue40KFNjZa4XgRg4mc9MXY7Y0KS6g5eJ62bQOiz8haVLSICKWzh5ISiltW8twXduFEfFtkn5d0qWSjki6QtItkq6mR2yMMcYYY4wxgO2SvlvSlSmlX4yIA5IuWY/henMl3irpayX9dUrpORHxYp2NBhlTKhqZ29HmhrZ0hrvPNCuMdm2j4G5vuVNoMteIkTTQJq1nwh3wYEpf5oADJnfr6bJAz0tZ3tXG5CDHnJ/N4x06k1j7TZJ+UdKspD+R9Py1DNf7rdJLKR2LiEZENFJKf3u21bUx5YKmYNCaH/pFTGtwaEoSdfLL4mDSz5c7tYiCjxPY0XqmAdx4oM9Ciw0rpW3tNWAiDdcK4QHKJWkIgMVPWV5KxpgL5GtSSs+NiE9KUkrpRER01mO43rf1yYiYlvRRSe+JiCOSYGK0MZtI5rx13ICAfoFTR5GtxruT5fZPmvAT4iJ2+HrM3amK1KRlHsqJGwLg+TmZOx/m7vZGa2JyNyCgx0nD0cZUkWpHfnoR0dTZTxgRe7XON+N6v/leJWlR0o9L+qCk2yR92/DHaYwxxhhjjDEXxG9K+jNJ+yLiP0n6B0n/eT2G64r8pJTmV/z47qEPz5itQrfL7Pqw+xpNs2vBLmo0YkRTaNhqUr8cW1F8HhG069OIUcbzmbumAp4T2gEve1t7Wv9G7XJHYjx3xxgzAlJK74mImyS9RGfcke9IKd2yHtu1hpzOavWA2brbyRmzpZhfZHbU4cNiBIotKJrUZvURvJYms+OGU6Ay1wrlFlsEeG9mh6YeUnI3LqD3Zu56NM/rMWbTqOqQ03OklG6VdOuwdmvN+ZnBR2SMMcYYY4wxW4h8Y8GN2QIkmlZEgWlvON0q+65u5shP5hbZpSFnRMyRg9WhEbGqdyejnw+/I5xmZ8zD5Gh4UMLIksWPqRfZu2nRVteZ3yawPoKvB2fF5J4PRLqhbQIpY4eroM5l1eev0HdL7pRMugGEO2WWJE3SGFMbLH5Mvaj6Lit1wOh5wTUqmYuuIamR+fNRMkY5EhXmuYN2VGzRawfXw1FeCN1AyL4R4JofYy6care6xlTcEzTGGGOMMcaYMzjyY0yVKEn3NZymlb3eJO9y2bvgEfBg28zRRRppwjUq8FnIHGnCZB5ui6l6eqUxQ1D1bm8Uix9TLzK3ow1cBJ3Z0YAOGK7BKUtKS+4GC1RMlmCWSpTlmudOHYXgNDQ6e8wYYyqCxY+pFzQvnzoacD0sKnJ3OiqB031BZHbYsYgpgbDA9zTcsMg+rDTzxgqNnkaiTVhKMsco93Eas6UJiT7zFcZbQMYYY4wxxpha4MiPMaMEz8GhdQ5sdz132lTuXfnsaWFlmbeUk6rXYuS+5plrjHAKLyRn+3ZjKou7va2KxY+pFz04XyZ3Cg0VMZlTi3JTGhFDxUiVHb6CPkO0qUbmtKmSDOClGw+Vr+8zxtQGix9TK1LuAX+U7FPKM9e2lMUhyixicOevUpB5QG3uPHdaF0gFL1wv5R5Sm1sUlmQwsTE5yNHtrYzd5PyWMMYYY4wxxtQCR35MvShJakq1IwCbsCsPwdehyulrJSHhNDtK7ncLWy9oB8peWd5J5XjHG5MF1/ysisWPqRU4b91sKKnilyG3eKUOLaEswjwaFqCrUfVnz2lvxpi1sPgxZh2UxeEz9cT35+PxOSk3WNA76mrMw+So+Skj3iIxxhhjjDHG1AJHfkyt8G5wyfGu7urkTPUpyzVw+lOp8bvamA3ANT+rYvFjzHrI3I628pTFgS4LPp+PpyznxO8IY4zJisWPqRe5HaKqi6ayOJhm88k9B6cs+B1hjBkVjvysSknensYYY4wxxhhzYTjyY4wpD44ebD65Iw5liXCY1fH1M2bTyNLtrYSRJYsfUy/8RbyxlOV8luU4jRkxOWdCSW5cYIzZelj8GLMOcjsMubGDsjplue6+fma9+F4xxtQdb4caY4wxxhhjaoEjP6ZWRLOZd72SRA4Cnpaq7yLj+wXWGNHzGY2tX9NU+XvF6WQbCj2fVT8vxgyFu72tisWPqRXYmaWOTTA7fpwwmFsw5zkSe6smuJ7gevh8tuArcjBgdt0eMktwObYYvFdKshFQFnw+V8fnxRizFhY/xhhjjDHGVIws3d5KiMWPqRdNFhnBkYM2e8Ryp+dhYKQJ7832YYijlTny06MRHPb5IuegzJQ3HcnpT8YYYzYSix9TK4KmhVEnn4oYmC6H7ehxjo8xO3qc/T5cD153KJYp2dMdAVig0e1HKH5oHRtNWcwttnB6F30WypJOZtFrzCO45mdVLH6MWQ+wRoU6ipTIPc+Gfj4aUcn9+WCNEY4wQjGJ77MBuK9pvVYTipiMwk66EBGT91nH5I5+Z65DzP3ONcaUD4sfY4wxxhhjqoYjP6ti8WPMKCE76xJOC0uw5XEUMKUFdifDtTs06oCjFZnTFmFELOj9Ugx//bLXo2WOHODICFsNd8/LHgUtCaWplzTGbBoWP6ZeUKeUQh0w7PAxszSAIobWf1AHBaYk4VQYWm9C0/roeYF20RneJvXhM0QbHsDPhmuTkJXwM4vbvkOyp6/lrkM0xjxCjm5vJYwsWfyYepG5fiB7pKIkJBoRy35eoANGPx8lo9gK+tly+7K0QD9lnpVVFlFRlo2Air87jTEXjsWPMcYYY4wxVcM1P6ti8WNqRYyBPB8J7+Qnms/vdq2rEh14/coC7S5H0/rAeqW5p+m5LEmXsdy1LXg9Gvmhs7n87jTGrIHFj6kX7TazS11kFgWdL8PMsg/zzJ3WR8UrdYjgsFJ+XqjDDmfTECHTg7OWqBih6V25U1xzQ88nhd6b9DhpU5Tc58WYLUxkqPkpyQSwR2HxY+oFFT90uCbtQEAdPioOJsaZHa3/oI5NG76yMkZGJPH7hYqY3J+PkLlGBTdKgJEtWruTqMCmwGuO77FFz90xxmwtLH6MMcYYY4ypGq75WRWLH2PWQ1nartJ5Ly2YItSBc2l6mSMVuTefS1I3gu6XzJEYnMpJj5NGRhaX2Hq5W09TYDSTtvLGXfBoCq8xZmRExMskvV1nkvrfmVJ623l+79WS3ifp+SmlG0d1PH5LmHoB04qwA5bbQSmJSEtQpOE2y7nrFUpSdI0c78xiJPszlDsNDX4+3EIaknseUfaZbMZUkS0Q+YmIpqR3SHqppMOSboiI96eUDj3m92Yk/XtJHx/1MVn8mHpBHYbcszgo0FmPAdztpru6uYuZqcOectcYwfMZtLEGsMNzW+Ax4royWHdF701KWZx8WG8X1I7e08aYrcYLJH05pXS7JEXEdZJeJenQY37vlyT9F0k/NeoD8tvFGGOMMcaYinGu29so/6wjsrRf0j0rfj589u8eOc6I50i6PKX0gY38/OfDkR9TL2jqDY04wN3u1IRpYV24aw3bF+M9a7qbT2fM0GgFjqhkrouhkclGCaIOmVsl4zlGFFpjRKOE9N5sw46QtEMjhbZiN8ZgIuIaSdes+KtrU0rXnvvnVUwefvHFmTDvb0j6/pEd4GOw+DFmPdB89y50UHK3dF5mc4wwuWdx5HaIqBihrcrh/UJqr3DKIn2GqFCGYAEKh2nQJhc4LYxuBMB2+GmC3dPRpxski8zOmCqSqebnrNC59jz/fFjS5St+vkzSfSt+npH0dEkfiTPfSRdLen9EfPuomh5Y/JhakWDtR1BR0c1cPJ17PhCtq8CRH9rtLXMdB60xyl3/Abr8JVr+tpxZ8OZuzIDr7TJnn9N7jNrRZxY/65kjd8aYtbhB0lURcaWkeyW9TtIbzv1jSumUpD3nfo6Ij0j6KXd7M2aDSOOw+JbuWtOuX3Rg4jgc4ko7TnWh+KGRGOoQURGaO1qxtMzsYHplDIDopalyuZtc5O4SR6FiC9+bdFgpbOXdhdeB3i+5o9jGbGW2QLe3lFI/It4o6UM60+r6d1NKn4+IX5R0Y0rp/bmPyeLHGGOMMcYYMxJSStdLuv4xf/fz5/ndF436eCx+TL0oS1vZsqSmUGiNCm0EQXfXcYSKtmeGu900YpS7rTOhLKmO9DhL0g4fzz+CZil3Sq0xFSSEyxErjcWPqRXRgw4RHq5Ja4Vgo4TMXekoaYyl5xUTzI6m5zUWMqd44Zk2sLMZcGhxoT1Nl4Opo9h5pulkJZkFhjcCQH3YhUDvs2RPzxizBhY/plbELOwEREUMjRxQB4yu12END9LEGLIrYO1VorUtuXfX6S55l9Ur8F3y4e9r0iHugqCtoHNHfijwfGIR04F1gePsWcfd5WjtzsICszOmimyBmp+tSEkqQo0xxhhjjDHmwnDkx9SLRRj5KUvb1cx1BwHbCTfmkZliQOsVYGSERlToepnvl0QjjDmh9zTttJibsmxB0ggObTm+lPlZN6aCRMpQ81OSV+1KLH5Mvchc4J17WnzQjxfQYZidY8udLomYpLVQNFWL3i8ZU6dwOlnupho0RbIsLbIpuduwU+h6ue8zY0zpsPgxtSLBmorsM0OgM5satFYo8zyb3BEHev1ybyKXIRJDyR2JgZ0BcQOC3A0PaAMJakffnbkbVhhjHsE1P6tS8S0uY4wxxhhjjDmDIz+mXuSeGUJ3dfHU98yfL3eKSVnmNNEITllmxRAyt7rGZL6nA868yh2NJm3R9f+3d+7Blt1Vnf+u87jvpLtJJ4TOAxASp0DiKyIzo4KKiJYGaoYpGEHBx2RkdKamLAeGiaOjFlMq1qAWjmXKwhodJaKjQ0pRBHV0BFK8iYYBDAkhnQfd6ed933vOWfPHPUluwunuez99z+/cvff3U5VK973313vfvfc5Z31/a63vksqXqlbhtWBMKZz5GYnFj2kWtGm3tDgoXPJRuvEd91Xg5vfCs1soFSi5oqEl7hWit6C0RXbpksXCs7n4wN+ykVclTDyMMRPF4seYMVKZWSN0d53u5pemtGiigTc8Hr4LRDTRa1kV17bCJiVJMyP0tVeROU2Yqrj8GVOA0EV8PtQY9/wYY4wxxhhjGoEzP6ZZwEwMdh4qnfkJuJ9ROINT9zI7XjpFLbIL7nbTnfXSGZXKZIxoPyG08qb9hFWh8HNmzL7GPT8jsfgxzcIzIEZTvFSkcB9AVUpvaOBWgepKLEYqEszS3y/oxgO8Lll8P6b0xorf440x58fix5h9CP8Ar0AUPAl8WfaOumdwClMV0UTJgavrjZkUkVv/jfUY4/3nr1cnUwAAIABJREFUx4LFj2kUuByJlstVxfDAmB1SdzFCqXuGo/TvZ4wx48LixxhjjDHGmLpRouengvthExE/EfEWSd8taUPS5yR9f2aeHn7vTZJ+UFuFKv8uM98ziXM0NaVwBqcqu7Pezd8fVGF3ve7PWBXuQaWgZXbUvMUYYy7ApDI/75X0pszsRcTPS3qTpDdGxHMkvUrScyUdkfS+iLg+s3SLpqkrVRExpal7QFsVivd/kACzIgYEFD/To6l7b5IxtcRubyOZiPjJzD/f9tc7JL1i+OeXSbotM9cl3RsRd0t6vqQPFj5FU1Mc2Iym9teldCBVlV1rB5hmzBQXTcYYcwH2wyf0D0j60+Gfr5J0/7bvHR1+7UuIiJsj4iMR8ZHjx4+P+RSNMcYYY4ypDo+6vY3zvyoytsxPRLxP0pUjvnVLZr5r+DO3SOpJ+p1Hl434+ZGXNjNvlXSrJN14440VvfymNFUp76rKeRanKpmKwn0Olbjvzr6ZXVCJZ9oYU0nGJn4y88Xn+35EvFbSd0n61nx8AuFRSdds+7GrJT04njM0jQQHRGXbzvzBfw7o/au7aDLGGGOejHt+RjIpt7eXSnqjpBdm5sq2b90u6Xcj4r9py/DgOkkfmsApGlNNqhI8l96Vr7toqjPO4BhjjNlDJuX29jZJ05LeGxGSdEdm/nBm3hUR75T0KW2Vw/2Ind7MnlL3YNaB4mjqft+rgJ/N/YGtp41pDFXuyxknk3J7e/Z5vvdmSW8ueDrGGGOMMcaYBjCpzI8xE6HuvTSVMUpwJqa6OAOwP/BryBhzIUr0/FQwrLL4McaYpmIhU11874wxBmHxY5pFVXZLq2J5XJXraSZOVbKSpYdrOhttjBkX7vkZjcWPMcYixuyYugezdRcjlLrfd2NMc7D4McYYY4wxpm54zs9ILH6MMfXvH6h7Zqvg/XNmpJnQ++6MkTFmv2HxY4ypP1UZclp3EWqMMaYczvyMxOLHNAsHl/uCqjS/+3kx5uJwxsgYs9+w+DHGGGOMMaZm2O1tNBY/plnQMiZnAKqN7/vkKX0P6t7nRanIM+3eMmPMuLD4MWYnVCV4rsh5ViawcQA9eXwP9paKvEcYY/aAEj0/Ffk4347Fj2kWdf8Ar/vv50DYGGOMMReBxY8xpjq4BMqYyeDXkDGVIzIVOd7UTBWtSWq+TWyMMcYYY4wxWzjzY4ypDt59NsYYY8xFYPFjjPEwT2OMMaaOVNCQYNxY/BhTJ+qeGXHPjzHGGGMuAosfY8aJg+7R2G7XmC2qYodvjKkcHnI6GkcSxhhjjDHGmEbgzI9pFt71rDa+f3tLnTNpflZG49JRY5pDiSGnFcTix5hx4pIWsxsqIEaixaY65KDwJ3BVgnyXgBpjTFEsfowx5lxUJMCkgqQkFk3GGFOWIj0/FcwsWfwYM04cEJkCFBcI5kupiFD2e5IxpulY/BhjOFUJ+IzZr1iMGGPGhXt+RuLIxRhjjDHGGNMInPkxZpw4M7KnVKZvxFQXZ2KMMTXBc35GY/FjzE6wiBlJ6UZ7i5gGYjFijDFmD7H4McaY/ULpQN+i3hhj6ot7fkZi8WOahYO9SlP7src6P591n2fjDJUxxlQCix9jTO2pvWiqAlURMRTPBzLG7DPc8zOamn8aGWOMMcYYY8wWzvwYY8w+obSBBMHZsD3GGSNjzLjI3Ppv3MeoGBY/xhgMDYTtElddqiDQJkHpZyzabbSuMq+FuveIGWMmhsWPMaY4lQnAjNkhWBQWDtajxURF8dcsvC4W58Y8Tomenyq+4ix+TKOgu6WYipSmFN+1doCyL7AI3TtKP9P8ePQ9sM+WORNjjNlnWPwYY4wxxhhTNzznZyQWP6ZRlO81qUYzszMx+4TCze/kvjtbtE8onVEp7Jfr9yRjzLiw+DGNojKBmx2g9pa6l94UfF48M6niwPsXsFwu+7Bczhhz0cRg6z/zRCx+jNkBtXcnKy0O7OTUOLyTv8fgjQ7Y80NFU1bDCMIY0xwsfkyjqLsjEw1svCu/t1QmO1Lwua7MBkJFhDm2mS9tXEDXWSwbc/GU6PmpYPhg8WPMfqT4rmfh0pSK7OpWJltRMGDH16Sw02LQHhWaqaC/HxQxtJwMl6HB6xldFmYUd+Y0xjQGix/TKPhQzsK7wTTAhIFNZYL8ioimyvReofMsLGJoEFzc1Z7e8wpumxpjKkGJOT9VpCKRhDHGGGOMMcZcHM78GLMfof0KpV3i6PHaNd93wW0V7D6UtFTH2VO6/UgzOKXLpnDmpzDwNVu6DI1m0qJV8/cWY3ZD5tZ/5glY/JhGUby8qyrlTxTqAFWRAAWXMlFxVxXRxA4Gl8EgGPfgVOM1W9y8pfR7Zx8+Lw70jDEXwOLHNIuqzM+pSm9L0ACstAilvV7sPmDRRANMLGKA2sIiBmYcah7MUkOA0mCjBDtJGjM53PMzkmq86xqzV9RdxODdYJjBwc3ocF1FAmEq7XCACZ9rkj3AIoZmCfEzRq2Z6TwbWqoKnxYqmqgYKW3ogDcCqvEeYYyZHBY/plGUnqPC5/VAaAagDQO+qSl2vKkuW0cDsF5pW+DCGbGCpUy4d4cGs/BZiQ77eMuNTbaucHke/f3wM4attQu/B1bFudKYEpSY81NBLH6MGSPcWht+gNPddSpi5mfZujm4ju6uL62wdctwHQSX2dEDkutJnzEYrMf0NFoneC2D9pqgVeLPNBU/HSi2Sm8glM6kGWMag8WPMcYYY4wxNaPInJ8KZpYsfkyjoBmV4hkcakdLd9dpJgauG8zCUqaNHltHd4Pp7nNFepOKUro/rHD2tPg9p890C15PmjHqwhLX0iWnxpjGYPFjGgUu76qI/S1ugobrkvYKURGzxvoxtAnXVeS+V8E6HBsXYBEDj0cND2gZGr13VGwNoKigZYS4PM/hiTEXjef8jMTvLqZR0AwH7gMoXO/Om6BhYNOD4oA2QfeYaMLQwJTe99KQQJ9ek8JOhMWdHel1ob8ffS3QdTSAKm1A4MyPMeYCWPyYZjEDm6dhs2+UDtbx7nNFbGWpqxluti9b9obF8iZ8zkpmjOizQn83eg/oa7ZwmVZusMPxjBGdXUUdKAtnmoypIaHx9/xUcbvB7xKmWdAAjO4m0lIfSuld5NLih5bs0IAPl2rBwI0GmFAUZsHsCD1W4JJFeM9plpdaXZfOLpYW5hBcouyoxhhzAfw2YZoFDaQqU88Pg1l6XepuR1t6GCt9XrB98e7XlBRMkrCIKX2euKepKqYapV+zdEht6Q0nY/YznvMzEosf0ygSBvn4Y59+EJd2Jyvd00QpPGMGUzowpfOBErweaL8WDWYhQbNhpWPnqphqFHbrKz7E1RjTGCx+jDHGGGOMqRlF5vxUEIsf0yxo8zRttKfQXVa4i4xLhOpe9la6ybtwmSTJjqQKZypoxohaVic9XjUcIUuDM0aUqjgtGmMmhsWPMTuABig4xC9cvobXVYXSpVql7aD71NBh9+cZLTi0siqCF1K8F6oi1xNfF2ijT8sdjaklA43fmKga+zBPwOLHNAosYqhDEhYxNAiuyC4yDdzor0fd1+hbZJu6thXu9SLHq8pOPrSnx8F6YUvuyjT2U2EOyUHh8QLGmMph8WOaBW3sL+2+Vpqal69h8UqPhzM4MNAvmblrFw5m8dydsq+94uVrVXlvKU1FygGNKYLd3kZi8WMaBS9fo05HsO+g5PBJ8RklVQk08AwWejw6gJJSss+hcHaquKMgzkrS11C9RUyWngVmjDEXwOLHNAvc2E/D4GrUn1OxhQNTGhAVDhRx2Fa676DGAXTtg+eK3Luq3AecdTWmhtjtbTQWP8bsAPrBH6XL7EpDB1DiEqHC4ofedwdgjaMq4gBT3NABbsjU/T4YYy4aix9jdgL84E/oWISpitMRvZ4VCWyqcp5mH0BFBX2tVyTTZIzZAzIrU55ekopESsYYY4wxxhhzcTjzYxpF/XfkPeBvJN7tHk1VMoXmS6n7M106I2ZMDSnS81PBsMrixxhjmgoJMB1cGmOMqTAWP8aY+uP+iL3DO/J7S+lns+5OhH7NGvM4+2TOT0S8VNIvS2pL+o3M/Lknff/HJP2QpJ6k45J+IDPvG9f5WPwYY8y5qHugWJKqBOtVoSrXxRsPxjSaiGhL+lVJ3ybpqKQPR8TtmfmpbT/2cUk3ZuZKRLxe0i9IeuW4zsnixxhjzP6l7qKp7r8fxaLJmIsmMhVjd3u74L//fEl3Z+Y9khQRt0l6maTHxE9m/tW2n79D0mv2+CSfgMWPMfuQus+Jqb/xBKQKAW1VgsuqiIoq3HNjjDkPEXGzpJu3fenWzLx1+OerJN2/7XtHJX39ef65H5T0p3t7hk/E4sc0iuKiAgY2pc+ztBiJNlxY8/lAxpiLxGLSmMcZDP8bM0Ohc+s5vj0qoBn5oRwRr5F0o6QX7tGpjcTix5gdEG0YrXfYSwwfj6a3+4UtsgOKO/r7bfbg8aqR5Sgq7qpSjuQg2Bhj9gNHJV2z7e9XS3rwyT8UES+WdIukF2bm+jhPyOLHNAsaEEER05qfK3o8bWzCdRtsXQtmtujvB8l19j6ahUUTFzEVmO9UETFS+6yrS2qNaQwlen52MEfow5Kui4hnSnpA0qskfc8T/o2Ir5b065JempnHxnCaT8DixzSK6EIRMzvLDjgH19HMD8yo4ICIZnAKix+a2aJhYuLjQRGTBQPaujvgFc5sVUaMVOS+V+Z6GtMQMrMXET8q6T3asrp+e2beFRE/I+kjmXm7pLdIWpD0+7EVV3whM28a1zlZ/JhGgTMOlyygZYND82hd9NlOTVAxAkUhpnT5GgWKUFq2mDADF7S3jNx3KsyhIMTZt9KCvg+zfYVLTvlGR1nxk/SyVKRU1Zgi7JM5P5n5bknvftLXfnLbn19c8nyqUYdgjDHGGGOMMReJMz+mUQQsQ+sdOYTWLV07g9ZNnWHbnrOfh9ulU122rgMzDstr7HjLq2wdzDThTGHhrAMt59Q8yEy24Z7ZCrx3q+xZwaYh9LUwgJmfNdiPRvv0KDQjRg9H++Yq0P5mTDEyeaVFjbH4Mc3i0kvQssWnMxFz+joWKC7czwKNuXtgwDDF3gr6l7Dr0lmDxgyl6RR2+YPiPOG6/kGwDgbBnZPwmtCgG5pxaIGZlGQXlkjCjYBYXELrqNiiAVRCUYipiLGGMWZyWPyYRtE/xAKb3iwLwBJ+Drfo7iV0OhrMTaF1mwvsLaS9yHbXA4oRvGdNswcz02hZzrL7MJhnx+vNg/tAtcg6O8fWWtkMx2CaPZuDObauBbOnrR7shYI9VDjTVHjX2YYHxjxO5I7c2BrHRMVPRPy4thweLs/MR2Jri++XJX2npBVJr8vMj03yHE29WL+MZSoGXfaB2mWbs+qsQBGzwALMwRQUFfBNNWm5XBeWJFFo9qBwtmLQpevKBYoDmBlp0ZI+WuoIMxUBDQ8wrdKzwODvV9qAgG5YGGMaw8TET0RcI+nbJH1h25e/Q9J1w/++XtKvDf9vzJ6wdIQFzxusWg47ECd8ZQ5m2O/XXma7uu1ltEyxCVNbtAeHlt7QddS1jZbZCWaa2rt/QKkTIe2Dotmw2GAZDvpsVqbYCgtzuG5Q9srgXi9j6oh7fkYyyczPWyW9QdK7tn3tZZJ+KzNT0h0RcTAinpaZD03kDE3t2DjA1vXouB5aKUIDRWxAAIP8wja9uAeHqklqs9yD1wWua22y+9dZ3f3xAh6LfgAPZmE5GVoliQpzKpTxrCyYrZ1l2W/c87PJ+vuCDlCeZhsBxpjmMBHxExE3SXogMz/5pGbWqyTdv+3vR4df+xLxExE3S7pZkq699trxnaypFSVnQUpS0BElG2V3agYzsBm9X3aXlRozxAZctwQdymiJEHVSg4Fpe3n3D2hrvbBZBS09hNCyN1FRWNhFjc70immWgcMOhoX77YypIzHY+m+sVDCxNDbxExHvk3TliG/dIuk/SXrJqGUjvjbysmbmrZJulaQbb7yxgpfeTILpM2wdzeC0oaNzd5X2HcDdddjzQwMbmtmizfbtVaZC27TEizaVw74YwQ+3FsjcRa9wCSENnmkGB1pr4ywhFXe0/42KLTzwF953muWlIs0Y0xjGJn7ONa01Ip4n6ZmSHs36XC3pYxHxfG1leq7Z9uNXS3pwXOdomsfUIvsgnj7NjtddZgFYd7Hs7nrSjAOkP82O159h69rTLJCiYVRrFd4/2qRPA31wOZMG67SMCfdrQeFKxQFdR+vxBxUZaEM3Ogpn/IypJ+75GUXxsrfM/DtJVzz694j4vKQbh25vt0v60Yi4TVtGB2fc72P2ktYmexPoLkERswR3g6ll9QzNHMCyqXV2XbIFjScuZQHR5gILwKgb2tRpKNKg8QTN+CVJpQGThK2D0XOEQfA0/HijvTS0zwv3lcF1pQOh0o6JVPQaYxrDfpvz825t2VzfrS2r6++f7OmYutHqUftbdrxBh9bzl+0DoCKmtQJd4mimKZho6sE2gBbMNHVgpil6cP4RLUUjx8KZGHhA2gZFraBhNVkOYC9Njw5HRcuwEyEWI6Xt6akoNKaOpCrZkzNuJi5+MvMZ2/6ckn5kcmdj6g4VMXRYKZ6fg+2E2TJa9kaHo24cgCIGDpul970NM4U00B9M0flHcB15zmBsGfSilM5U0D42WMpJ+7xatIxwBb5JUBMPWvZGRQzNwBljGsPExY8xJcGiAvcBlBUxfRg892G5HM1srV7GzpOKn+nT7D50VsoGUr1LmCik4rwNjDXa61CAdmDWFQazuA+qMAmFa3+KWVa3qGPiWtmSTJe9GXPxRKZi7BtI1XvNWfyYRlE6mKWN/TQDQA0BejNle2LouvY6WqapRVjWt8F2uzcvYW+tS0fYuo1L0TK1gC/DzCnaNwfNRs6wDEDnDAzWK1LWR98jBl2WrW1DMUKt0XHA1ndYY4w5P36XMI2ivcYCqQHcnR3AXVYqDvrTbB3NqFDL6oAatLsCjRnWqM0yW9afYgupiFl6Jrygs7tft3yCZadmjrHs4sKD7LW3QAe/nmEKOxLeA2ogAaHvZS24LvtU3VF3QIc1xjxGFnB7q17ix+LHNIssbGNLMwcB65hoGRpdR8utWrQnmTqGwQCTPi9tOKS2s4KWKfrsPLsLu8+ObHbYM70m5jrRgWV2MyfZx1v3NJzzswGdD+kwT2qLTl9DnbI9TZTsOKwxxpwfv0uYRlHSFUuSpmhARAc79lhJC80Y9aGRU6twOwY2EihskIGBO2+Zu7/vg3UWzHZXqQBFy7Q5D8/zAOulaa+Unc0VsLcl6VtgYeMJKgqjVcFtaGPGxUClzWMrgcWPMTuA9gHQpmv6XtVdLNuD05ulGSq0DGfgqEijGRVaWtSnU1WpQDix+0B/7gEWlM6cRMtwiSSd7bQ6YDehuwTFFpwF1oJlfRS6EYCPh4e/Fj5RY0zlsPgxjaI/D+eowF3WFrXNpetgeRcd/hpwfg4VMQM6w5X2NNF5RJAuLHubux/OIwLtLXNfZMFld5mto/1TvTnqKAizhNTUDMbqnRUmmrCIoWV21O2NZulLZ12N2ceUcXurHhY/plH05lj03Ia9Oxj6ZgXX0SGntFyORiiDeXa8tUNlDR26cADl1CJ7zuaOQ3EORC81j+iehlZ9kM2DTJn3YLlc6X60/mzZXpqAmSa8Dq2SBOcfGWOag8WPaRTYYhkORce7pdScDPYYSWzdFMyIDaZZ4NabocNR0TL1WfsHNnRoP8Ku5/Qp2G9C7h8dWglpbUCr6+WyQTDdXW2vwtJYOHSUm76wZdwogTpslhWFxuxrSri9VRCLH9MosKigu5c9OtiRHY/O1KBEnwVug00mYjqX0L4Kto7MwZGkNjQMa9PyQ/i8kMxWHwpX2gfVWS4bzNIsKH2PwHNwCpu3UBEzmGav9f4cC09odt8Y0xwsfkyjoCU7tOeH7pLj3VLYFEMDKWro0IKlKZ0VOigTGhDAsr7OKixDgxbZVGQn6Keh2VOaOmhBq2tsM0/7++BrAQ9HpRkcuGER9HpCq+s+dGjcnHfZmzGP4Tk/I7H4MY2CDjmlvR+9efYSo/a+nVUWaHSWWF1frBcuvYHgjAptRl+FWQAYYNLSsMjdPy/9jbI76y2aPaU9OIVNSoLOoKIGC9SHHbqoJdzooPb0dGaZMaY5WPyYRtFeZEH+5mHWNLJ+iAWKVGzlWbpLDjM4NCCCdfn9GRgQwQCzswb7OGAGhzpV0UGS9DkjtKDrF+1tET1eRaqm6BwcPD8HZoxo9puK3jZ8zRpTSzznZyQWP6ZRRA92osP4qwfLpnrUmhlGbnQ4aqdwUzItQ6Ob3XiQJN1cp30V8D6Q8kosQGmmgvbSUIdGXNUHF8K3JFoaWxoqXttrcEB0NS6LMWaCWPyYRkF7WzrLLGM0c4oF+Rt92KAPd7sT9nFQR6YWvA9TZ6HBAiyhoeWH1L4YD9OFu+QDICZpL8YADpoddJgwp/19NOPQgkYJbVq/RrPD8Nks7fJHs5I0y2uMaQ4WP6ZZbLJt1vaZVbRuDoqR6VMsUqTBOp0WT3flKTTApLvk/RnobEbL7JbZ89laZY5hRLzSbFgMqCBEy7CIwfcAbpDQbHROsY/v/gKbf4Szi1DE9Kfd82PMxVJiyGlU0PHA4seYnUADvjUWEHVgA3txP3/aVN4p+9aD+0YgdJO8tQ6NC2DGqOTzQgaqStLUaSbsuqfYhkWswqFecGNFA+i+Ns1EDBZNs/A1S0tO4aNJzU2MMc3B4sc0C9jsSwlahkabjGjfQUWmomMHL5p1oBkxWi5HF8KAlgybpVbXAfvlcaaJzryiQpIqXqrLqXCF70l0A4iW4tLr0nLZmzGP4yGnI7H4Mc2iDYP8jbLDQzXF+hyo6xd9cyw9aBFDA6LCPT80I0bLHUlZHzaPgOIHX0so6EPU1QxeGPxaZ88KzRLS4a9UbNHtmHGX+Bhjqo/Fj2kUeBYHnf0xw3p3egdm2PHofKBl2DOCp77DIL8qu7rweaFubwn7HMhM3Bas7mrjGUYw+0aD4NLBcwduWNDXAt3ooLOk8Dootmj5oTF1xENOR2LxY5oFnaMyz8TI5lPgfKCDTDS14dBRuqtLMz/9GVimBZ3GaABNh+LGJgzcoMFCD2cBdr+GDnDtLMNZUrAPCn/gU09uGgHQDRl6noXFHe6hotn2zcJZemNM5bD4MWYHDGaZGNm4lL3ENheonTDtx4B2wlBs0fOk62hKrLVZtr+FBsLUUYs0lbfgPW9RQQihWcmA9xwH63T2GM7gwEwTNSmhw1FpiXI6rDHmMdzzMxK/S5hGkdNMxNBMBS3T6sOZKBuXsIBh7RAccroKp7BvwD6AwhUt/QF0xqKZLWjv26eiF4kfdChu/kHLu2CwHvQhw5km2DdHRUXpckAqmqj5hzHGXACLH9MoVq5ZQOvo7AiYUNHmAjveypXseP15FoB1z7BgfeYR9vvNnGIBWHeJii12XXrz7K21N0NnqaBlqOytMn1XtH8K9qPFAL7YcflaYbMRKmKoEYR3q425eAbCxj11xuLHNIrTz2IlHy1Ytk43kTfn4boj7EQvv+IMWnf8+KVoXfTYjJKZU2gZ7vmhgf7mLAv4erOwPI9WFq2XCzCxaAr2mu3De9Cagu8RNNNUOhNDM000E0PXwY0Hak5jjGkOFj+mUSw9nTZrs0BqimkKvlPTYgHRtQdOo3XrPfYWst5h4qe9VnY3eOMS2rNFM4Vle4xIK1SrBzMqwWo5E5b09ak5Bpzt1F1kzwrNLtIZVC08/4gtwxm4OWeMjLlYItP27yOw+DGNYubqJbRubRmWtIi5xHUX4eFW2Ev6C2cOonVLS+z3m11By9SBzfZ92EuDjSdgmSQVvQPYI9YHl5P2F/XhDKoBFIS0FLBFjRKo2RsUk60eOyB9NFtrTDT156BZDHS8pOYfxpjmYPFjGsWXXXYCrbtr6Qha14O9NDRymz7GAsyVz1+O1h04i5bhDM7aIRhAQ4Or0uVkNGDvrsBeqMXd/4JtmHHAhge0jImKHzyPqOwQUDqsFB8PGizg65JM/NDXujG1pMicn+pllix+TKOY67DdyzjNPog7S3RXFy0rWv4kXUTGge7mUxFDB3NCZzN6PWnmp00rmch9aLObQMu0KDgTQ8UBLF/DPTgUPEiXljuyh7q9RnuToOo1xjQGix/TKO469lS0buoU+0BtQ6MEKmLouhYMnunxNi9h69afwgLTmRMsAOsso2Xqwd+vz1qhsNrK1u6FDC23am2UNXOg5znYpMEzNDzo0Rc7LD+cpuWHbB22+4fOh7jk1Jg6knkRg5vri8WPaRRr9zF3Mtqjgoe+081gmsGB7wQ0E7NxgK3rX8ZSOP0lmKKC15O69fVZC5Xaa2ydSAscfKZpMNuj2TDqZAfrplpd2CsEj0czKnSW1Absf+tP0x4xixhjzHiw+DHNAtbC9ObZBzE1LqDiZ5NpO/Vg0E3Ps3eQNtPQHiq2jM5poqKQnieFZEe6K3D2EQy6e3PstUfXUWttmmmiDKgNO3QiXD9Q1sSDjheg/W/G1JISPT8VxOLHNIp4KtsiX59lUXBrg73EqEV2e5Wto03CtOcH2+auQjth2gsFK6A6MFNI52RuQNEb4Bec+yI7VmeVzloqm6mgWdA2LOuj/WFU3K0ybxO8ETB9kq3rrLKAbWrRgZ4x5vxY/JhGccUhloo5Hgto3cYBpiraazAiKlxmN5iiB2TLBEUMFWlY3NFME+z5WXsaKwfcBM9na4OJinlYhtbapG5oZZ/NPjX/gGVhtHR04yB1e2PHC3hB6XsSvZ7G1JKUMz8jsPgxjWK6DW2/IP1Z9qazeWnZD3Aa5GenbIAZfTrwkh2vD3fJB112XfqHmfPEZZczUX+ys3tnho1L2cXsrNGeGLRM/ZmymRgsmuizSUtVYRMVzWZSx0Tq0GiWM1SJAAAZn0lEQVSMMRfC4sc0iqsWWD3ZsUWW+enNwx35TaZGqGsbHgi5CQNMKGKoY9hgGvZ6Xcq2u2Oarbv8MBucdHie2dItLu8+gl4/RAf+wnsOn+lN9pLF84Gw6QSEirQum/Os2eNs3cwJpl67y9Tmz5kfYx6jyJyf8f7z48Dix5gx0ppiH+ADaEdLZ1wM5mCgQTM/qzAL0KOzRtAyteB5JhRpjwTzyJ7qsPt36JLdb+cfu4KJn8E0+7ihJaC4JJN+kA/gPJvCmRFq3z59momYmRNMvXbPsgsz6HrKqTHm/Fj8mEbx20//a7Tu1fkitO5D9z0drRMUI4M2jNyon3CXBUStQ8zKKQ+hZXQkCjZmyEUmEKbuYbVMD51g86suu/6RXa953rPvR8d6YJE1qZw8ytZ1TrGPtw40DcEDcQvP5KTHK32edK5Q9AsPjTVmPzNIjT81U73Uj8WPMTvgmtlTaN2H41p2QByslzVKaMHyrtk5Jn6mu2y7+8ufcgytOzTFGh3+6r7r0Lr1NZb5GRxgu+skY3R8hdWTkRI7SfyZxn1lbB0VP9TkYkBLValxAe29mmMihs6FKm05boypHhY/xoyRqSkWrLdasGEe7pZ24Xk+7SD05IYsdJlo+sZD/4DWXdk5jdY9dAXLVnwW3vfLF1gjRw9s5z/80EF0rFiEHzcwyO8dYFE+tdburJQte6NQEUOtw3uzZXu9qKW6MbUkB1v/mSdg8WPMDnjpgTvRusPXs6D0k4tXo3WfO30YrTs0yzIcV8yw3+/BFTaYptNib+IfW2Tlh4ubX47WnVqbRevmppi4O77EsjHLR3efaZr/AuwrgxmO1SNMxLQPsGvZn2IfixsrzKSktPjpwfuwwZKSSmhAQAdEd5fd82OMOT8WP8bsgBfNsB35F818Dq37zz0WPH/0gWvQugMzrNHheZccReu+BrqoUW77wo1o3UP3MjFJCWiUMHWaCZJDD+1+zfQZJkDXngKHlV7K1vVnYBDcZr/f+uXsmW5BC/CpUzDTBDMqdAAvLuujx5tj64ypJSXc3iqIxY8x+5C5Ntu1Xoe7z/f0YZB/BVv2QwdYGVpHLKB9Z3wtWjfzIDveNKwGnDlJp9rDwBv0R9DG90GHBevzD7B1m2dZ9Lx+mImf/gIss4N28QF7obLw4N6EJiwbC/A+wF4hY0xzsPgxZox8vsdqNx5eZz0jCQOiwf1su/Tt3X+M1l3zFSfRupvmd+9OJkltWC43zVp+dPAe1kM1fZxl4FrLsHYK2OD1F6BxQbIUQLZoGRN8LXRg8AxnV1GDhY1DTFTQAbxtak8P2w2ouMNmMcbUkRJubxVMLFn8mEbx7L98HVp37VNZsD7dYUHww4uswL49BXdLL2eZptX72Xm+8fQr0Lp3Xn8fWvfI4jxa14bvkJ1ldt/bx9iQ0zzL1m19MO6OziwTP50T7B5MXcn6w1avYGJr4UG0DLN8JRMVqzDrSgcF0yGu1AiCip8+1ObGmOZg8WMaRZ5gAdHpA6wH5yVXfxqte80RNkvl2i4TaSf6LDD9qbtuQuuW72GZrY/ezYwL2tNMjOS1bEvrzBn2nB0+wZ6zWIeZnzbIqnTKfmy0V1iTysxxdryAu5iDKdibNM3K87JNM1tomQIOVaU9Rp0VdiPo8FdjakmRnp/qpX4sfkyjoKUb/T5b94KFu9G6l8/DMeyQpcEJtO6X5plL3MYis0sWHB7aux5aeT/ni2jdA93L0brZR1iWY2GVZe7U2b34GcyxexA9lpWMDXbvOvB4gqIi+qyZZvoM7BUKVg64OV94bhK8DVNLLKCaewimqIwxjcHixzSKS1jVlFbWWbD+S/MvRusue9a70Lq5FguCP7ByPVrXhRMTe/MssJl+hEVg6zDjNzgE3deuYL07S0eYZfXcUZYxIjuCm4dYXVF7BZYCLrJgNrtwuOY8EzGDLuyJ2YSvBSiaOtBdrj8NM03UdG+dqab2qlM/xjyG3d5GYvFjGsWhz7LyoIUH2Cf4I+tH0LrXL34PWvfUS5nBwhfPwiEelCMsoN2AFuDz98H7d+apaF1/Djajw3fk3qVM3LU2dh9g9mbLzlFprZQVMWuXsXVwH0DtNRbkd5eh+IFDQKmLWm+arWtBUdifdVhjjDk/fpcwjWL67mNo3dQC3FkXyxgdm2I9Mfc+DTb2n2EBZk6xACWeysRPb54FbgtwMOfccfb7rcGMER142ZuHb+VgfhXtNaHDLgezTIz0YdCNrZLXoYsa3JUNYFMuSQGbmga0HBC6y9HnrD/jsMaYx3DmZyR+lzCNIk8y7+JYYWVMC4usJ2b2wUNo3dqVTKQNOkxUbM6zQHHlcmatnfAdi86m2ZyDgT5MjvSYdtXqZXAe0endZw86K3Cm0DpcB3t+Zh5mJaBTp6kjAHtWWiuwXwsGNIN5OHUUxk/YQKILryft9TLGNAaLH9MsiLuVpOzDmpYlZlzQBhbEkjSbTDStX8b6OGiAMnMKLcNN17RfAY5bwiKN2gm3N2AWAMSJdFip4IBanYG/21m28dCGZXbEPEKStAHt0KDYCtgL1YKZu9YGfO+Eoqm1Dq+nMXVkMJA05g2BCiaWLH5Ms6DpX7j7nAPocAVFWmyyQAPX88/C8i4Yn7RgkE8zOD2WoFIHmvVRhytqQ9yfAtcl2LPSBv1FEjcuEAzWBV+zdMipevTmwfeWGVZGiEUTzGzF2bKOl8aY5mDxYxpFbsKoGwYaOACDu7oDWO++foAFNusH2Xl2YZDfgakfOviwPwvPkw52hJvklN4srAcEtOBLbwAb2OMAU67Ukjs7sLGfbsjAUly6CYytytfgjV+1ZbUxF43n/IzE4sc0CypikqaN4a41FD/ZZgHYgG0GC442kWAmhtrm0lkj3UVa6sOOR93e6OwWkvnprMFeE2gFvXoF61HpXMoezjbsaaJDTrvT7Dw7J+B7BDUEoAEUzaTRYbowa26MaQ4WP6ZRRLfsB2rQD/AZFvDRmSiHPoWWaf1ydp6LV7Hr0oeme3PHWOA2dTccQAkTKmuH2HO2ericu9z8F+k1Yee49hR2MTfnYZkWzIL22exXdQ6y483SjBjsJ6S9O61VuEMCz9MYsw27vY3E4sc0CypGSr950Hp+WGLSgb1ClPVLWcC3cQnNxMDyNThLhRpBtDdg9gCW2c2c2v1zNn2SpbUGtHcn2Gt2c45dSypcO6tQYJ+FogK+Zlub7L0Fu9LR8rVNDys1xowHix/TKKiRQMKmZOoSFxu0boqWmLDr0oYB7cxpljEK6CFNm+2DzmBJatOLluHAuw1K2Gjw3F5hwry9yj6m2gdZKiahcO2eZTevc5aJg1grKw6CutKtseFVuD/TGPM4g9TYe3IqmFiy+DFmH5Iw0KDBumg5IOxN6ixS4wlYsgPXYeDhOqtQpA2gA9s6OB69B8ssCMbrYGYEGxfA84wlmBmhLnHUhIX2S/ZgVpmWvdHfzxjTGCx+TLOYZbZfAUs3cMao8K5ndFld/uYh1oTTm4e7+Wsw6wAHbNKZNvR4UyehgxcFiFca5IvOX4FmIy1abkWDbrrxQNfR2WMwO4yz2NAaHfdntso5GBqz30kNlNiwqb5Y/JhmMQ875mkZGiy3wtBACootWgJF3dfo9PaAu88t6NYXtGeL9l7R+w7ET9LhmtDVDIsRKg5oeVdpEYPd1ypYo7IbLH6MMRfA4sc0ioQfjLScjO6W0hKTFCyXgzNDOifZIMLWOsuIlRYHgxnWN4LLD3EADdcRbQf7vAYdKH5o3xUcTIyLppbYa4GWuBa3noYkdcqkYwKMMY8zSCk85+fJWPyYRhGrsPmWBihUxNASE5jeHiyvoHUtmAVorTLDA9pjJFjWh3uF6OYzHUBJA+He7tcl/dSIsjOv8LyX0nNiCpup4OsJwRtH9HgBPceNMY3B4sc0ijx7lq2jPTi01hauS9j4Tsu0kk6ZhwEfnpsEHaeCltDQAHMKBm4wQzUApWgBMwct2NhPs7Vqw3tQ2ta+sBihFH8tUKgoNKaOZAG3twpi8WOaBax3p4YAWbouH4stOC0eBsJ00GLxpvLCJUI0UMxZlklLUsIGB+HQksWg817gRgB+VqAwDzjQWHAmFBYHpTNiNGNki2xjzAWw+DHNgn7w014hOlcIBnyJm5kL29HiMi06CAcGpqUDPiwmoUgD2ZEBdO8SNDzA7ev0GaMZDugkSbN90YGue/Q1BCnd94jXGVNHBskdhnZKBRNLFj+mUeDenXZZB6GAsyqS+gHgUhE4S6UH7wMMvFvUNnduDi2LSxfY8WjZGxSh7dO77/XKKXYtSYmdJA3g3J2EZW+0zI7OFcKCtw+fTWgEIVriCo0g8EZVRcoIjTGTw+LHNApsJLDH5zEucKaJap/S8wNoL1Th+57zLDDNOZgFWGFW7KSkbDDLRMzGQVbeRY2KApg5SLwkM+FMKLopi+3bqdhCqzi0pNYYsw33/IzE4seYnUCDfFoiRO1hS5flV0Q04XJAWjoFsw69eSYs2jA7Qvpw+jPsY6M3Ry2y4aBZOGOru0wzDuwe9KbYujbs+Qk6K6t06ShdV9qwwhhTOSx+TKPAU8Nh5gBnHFrwPOkAysJldsWhFuBLS2hd6/6H0bqp9cNo3cZVB9C69aftfuhve41dy6lFVm61epgJwqUj7DXUXWZB94G7mV189yQrJ+vDLOFgGoqYBTYgOuh7IC1fc8+PMY+Rg4FyzD0/WcHMksWPaRal68FphgPXu8P+COqCV3PRRMUrFk1oldTtsIC9P3XprtfQXhpahjZ9GpZ3wdaWFjxPPLh3CQ4Yhr07CbOEGGpPT9+r4XuSMaY5WPwYswOoOMDlVrDRIVoV2fWk5YCle4wgWDTBYbPtR06iddMge7B+mGUAaDnS9DHWMD/9CHvGcGYElpPhjY7Vwv2LtAyt8GBiz/kxZhslen6ql/ix+DHNAru9le5RgW5oFXwPMtug971/8hRa11rd/eDR2Qepkx0MZumcHyi2sDNg6awyFSNYbLEhtfg8F5hpiKARhDGmOVj8mGZRkcyBMbuBZhgHq7svuaJDR4OKH2r+QY9H5/zA0kNcFkbPk4o0unFUes5P4bEExuxrBsktM2uMxY8xxuwXaDkgBIkmOqOJbjyUFj/TcNYSPV5paE8MFVtrcBgrnSs0wyzVjTHNweLHmJ2Ag1KXYJhdUInMJJwlRU01Ctu3qwfL7Og6muEobQgAfz88QPnsYtl1xtSRHEga9+dK9TJLFj/G7IRKBKXG1BBqMw97VIp7hVHxU9jVDIsYfEBoMmPDA2PMBbD4MY0Cu6/xA5Y9njFjhtuis9cCtkVfh+VWFDxDrGzmh846o8NKcwAzYpTS7/HG7GNykMpx9/xU8CVn8WMaxXv7vzfpUzDGGGOMMRPC4scYY4wxxpi6UaTnp3rYE9IYY4wxxhjTCJz5McYYY4wxpmYU6fmpIBPL/ETEv42Iz0TEXRHxC9u+/qaIuHv4vW+f1PkZY4wxxhhj6sVEMj8R8c2SXibphsxcj4grhl9/jqRXSXqupCOS3hcR12divx9jjDHGGGOah+f8jGRSZW+vl/RzmbkuSZl5bPj1l0m6bfj1eyPibknPl/TByZymMcYYY4wxlWPzM/qEWjneIq+eNsf674+DSYmf6yV9Y0S8WdKapB/PzA9LukrSHdt+7ujwa19CRNws6ebhX5ci4jNjPN9zcVjSIxM4bpPxNS+Pr3l5fM3L42teHl/z8via7w1Pn/QJ7IDvfUj3jYyh95iTBY6xp4xN/ETE+yRdOeJbtwyPe0jSCyR9naR3RsSXafRw7ZH5tMy8VdKte3O2jIj4SGbeOMlzaBq+5uXxNS+Pr3l5fM3L42teHl/z5pCZD0t6eNLnsR8Zm/jJzBef63sR8XpJf5iZKelDETHQ1m7EUUnXbPvRqyU9OK5zNMYYY4wxxjSHSbm9/W9J3yJJEXG9pCltpWFvl/SqiJiOiGdKuk7ShyZ0jsYYY4wxxpgaMamen7dLentE/L2kDUmvHWaB7oqId0r6lKSepB/Z505vEy27ayi+5uXxNS+Pr3l5fM3L42teHl9z03hiS3MYY4wxxhhjTL2Z2JBTY4wxxhhjjCmJxQ8gIn42Iu6MiE9ExJ9HxJHh1189/PqdEfGBiPjKSZ9rXTjPNY+I+JWIuHv4/a+Z9LnWhYh4S0R8enhd/ygiDg6/3o2I/xERfxcR/y8i3jTpc60L57rmw+/dEBEfjIi7htd+ZpLnWhfOd82H3782IpYi4scndY514zzvLd8WER8dPt8fjYhvmfS51oULvLe8afgZ+pmI+PZJnqcxJbD4YbwlM2/IzK+S9MeSfnL49XslvTAzb5D0s3Jt7V5yrmv+HdoyxrhOW3Offm1C51dH3ivpK4bP82clPSpy/oWk6cx8nqSvlfSvI+IZEznD+jHymkdER9L/lPTDmflcSS+SKjhZbn9yruf8Ud4q6U+Ln1W9Odc1f0TSdw/fW14r6bcndH515FzvLc+R9CpJz5X0Ukn/PSLaEztLYwpg8QPIzLPb/jqv4SyizPxAZp4afv0ObVl1mz3gXNdc0ssk/VZucYekgxHxtOInWEMy888zszf86/bnOSXNDwPyWW2Zlpwd8U+YXXKea/4SSXdm5ieHP3din5vBVIbzXHNFxMsl3SPprkmcW1051zXPzI9n5qPjLe6SNBMR05M4x7pxnuf8ZZJuy8z1zLxX0t2Snj+JczSmFBY/kIh4c0TcL+nVejwLsZ0flHcL95RzXPOrJN2/7ceODr9m9pYf0OPP8x9IWpb0kKQvSPrFzKzchOcKsP2aXy8pI+I9EfGxiHjDBM+rzjx2zSNiXtIbJf30RM+o/mx/zrfzzyV9PDPXC59PE9h+zf0ZahrHpKyu9z0R8T5JV4741i2Z+a7MvEXSLcN+hx+V9FPb1n6ztsTPNxQ52ZoAr3mM+HlbGO6QC13z4c/coi3r+d8Zfu/5kvqSjkg6JOn/RsT7MvOeAqdceeA172jr/eTrJK1I+ouI+Ghm/kWBU6488Jr/tKS3ZuZSxKi3GXM+4DV/dO1zJf28tjKeZofAa+7PUNM4LH7OQWa+eIc/+ruS/kRD8RMRN0j6DUnfkZknxnR6tQRe86OSrtn2vaslPThqkflSLnTNI+K1kr5L0rfm47743yPpzzJzU9KxiHi/pBu1VR5kLgC85kcl/XVmPjL8mXdL+hpJFj87AF7zr5f0ioj4BUkHJQ0iYi0z3zbes60H8JorIq6W9EeSvi8zPzfes6wXF/He4s9Q0yhc9gaIiOu2/fUmSZ8efv1aSX8o6Xsz87OTOLe6cq5rLul2Sd83dH17gaQzmflQ8ROsIRHxUm2V/dyUmSvbvvUFSd8yvObzkl6gx++HuQjOc83fI+mGiJgb9lq9UFvDoM1Fcq5rnpnfmJnPyMxnSPolSf/VwmdvONc1HzqQ/YmkN2Xm+yd1fnXkPO8tt0t6VURMR8QztWUe9KFJnKMxpfCQU0BE/C9JXy5pIOk+bTkwPRARv6GtOuX7hj/ay8wbJ3SateI81zwkvU1bLjUrkr4/Mz8yuTOtDxFxt6RpSY9mMO/IzB+OiAVJvynpOdoqmfjNzHzLhE6zVpzrmg+/9xptOTSlpHdnpvt+9oDzXfNtP/NfJC1l5i8WPr1acp73lp/Q1jP+D9t+/CWZeaz0OdaNC7y33KKtPqCepH+fme5XNrXG4scYY4wxxhjTCFz2ZowxxhhjjGkEFj/GGGOMMcaYRmDxY4wxxhhjjGkEFj/GGGOMMcaYRmDxY4wxxhhjjGkEFj/GGLOPiYilMfybN0XEfxz++eUR8Rzwb/yfiLCVvzHGmEph8WOMMQ0jM2/PzJ8b/vXl2prZZIwxxtQeix9jjKkAscVbIuLvI+LvIuKVw6+/aJiF+YOI+HRE/M5w+K8i4juHX/vbiPiViPjj4ddfFxFvi4h/IukmSW+JiE9ExLO2Z3Qi4nBEfH7459mIuC0i7oyI35M0u+3cXhIRH4yIj0XE7w8H4RpjjDH7js6kT8AYY8yO+GeSvkrSV0o6LOnDEfE3w+99taTnSnpQ0vsl/dOI+IikX5f0TZl5b0S848n/YGZ+ICJul/THmfkHkjTUTaN4vaSVzLwhIm6Q9LHhzx+W9BOSXpyZyxHxRkk/Juln9uKXNsYYY/YSix9jjKkG3yDpHZnZl/TFiPhrSV8n6aykD2XmUUmKiE9IeoakJUn3ZOa9w/XvkHTzRRz/myT9iiRl5p0Rcefw6y/QVtnc+4fCaUrSBy/iOMYYY8zYsPgxxphqcM6UjKT1bX/ua+u9/Xw/fz56erwkeuZJ38tznNd7M/NfwuMZY4wxxXDPjzHGVIO/kfTKiGhHxOXaysR86Dw//2lJXxYRzxj+/ZXn+LlFSZds+/vnJX3t8M+veNLxXy1JEfEVkm4Yfv0ObZXZPXv4vbmIuH4Hv48xxhhTHIsfY4ypBn8k6U5Jn5T0l5LekJkPn+uHM3NV0r+R9GcR8beSvijpzIgfvU3Sf4iIj0fEsyT9oqTXR8QHtNVb9Ci/JmlhWO72Bg2FV2Yel/Q6Se8Yfu8OSf/oYn5RY4wxZlxE5qgqBmOMMVUnIhYyc2no/varkv4hM9866fMyxhhjJoUzP8YYU1/+1dAA4S5JB7Tl/maMMcY0Fmd+jDHGGGOMMY3AmR9jjDHGGGNMI7D4McYYY4wxxjQCix9jjDHGGGNMI7D4McYYY4wxxjQCix9jjDHGGGNMI7D4McYYY4wxxjSC/w9Fc4HN2oS6WQAAAABJRU5ErkJggg==\n", 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(30, 30))\n", - "long = -26\n", - "lat = -20\n", - "plt.subplot(2, 1, 1)\n", - "time = slice(0, 600)\n", - "model_output['S_x'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "model_output['S_xpred'].isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linewidth=3)\n", - "uB = model_output['S_xpred'] + 1.96 * model_output['S_xscale']\n", - "lB = model_output['S_xpred'] - 1.96 * model_output['S_xscale']\n", - "uB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "lB.isel(time_index=time).sel(longitude=long, latitude=lat, method='nearest').plot(linestyle='--',color='gray')\n", - "plt.legend(('Sx', 'Sx_pred'))" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "correlations = (model_output['S_y'] * model_output['S_ypred']).mean(dim='time_index') / np.sqrt((model_output['S_y']**2).mean(dim='time_index') * (model_output['S_ypred']**2).mean(dim='time_index'))" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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-       "    dyu       (xu_ocean, yu_ocean) float64 1e+04 1e+04 1e+04 ... 1e+04 1e+04
" - ], - "text/plain": [ - "\n", - "Dimensions: (xu_ocean: 384, yu_ocean: 384)\n", - "Coordinates:\n", - " * xu_ocean (xu_ocean) float64 5e+03 1.5e+04 2.5e+04 ... 3.825e+06 3.835e+06\n", - " * yu_ocean (yu_ocean) float64 5e+03 1.5e+04 2.5e+04 ... 3.825e+06 3.835e+06\n", - "Data variables:\n", - " dxu (xu_ocean, yu_ocean) float64 1e+04 1e+04 1e+04 ... 1e+04 1e+04\n", - " dyu (xu_ocean, yu_ocean) float64 1e+04 1e+04 1e+04 ... 1e+04 1e+04" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "dxu = xr.DataArray(dims=('xu_ocean', 'yu_ocean'), data=np.ones((384, 384)) * 1e4,\n", " coords=dict(xu_ocean=uv_high_rez.xu_ocean, yu_ocean=uv_high_rez.yu_ocean))\n", @@ -1018,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "bizarre-beads", "metadata": {}, "outputs": [], @@ -1028,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "environmental-chancellor", "metadata": {}, "outputs": [], @@ -1041,55 +143,20 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "connected-night", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1.061418616" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "low_rez.nbytes / 1e9" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "conceptual-analysis", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[## ] | 6% Completed | 0.4sUsing factor mode\n", - "[## ] | 6% Completed | 49.4sscale factor: 4\n", - "[####### ] | 18% Completed | 53.9sUsing factor mode\n", - "[####### ] | 18% Completed | 1min 42.9sscale factor: 4\n", - "[############ ] | 31% Completed | 1min 47.4sUsing factor mode\n", - "[############ ] | 31% Completed | 2min 36.4sscale factor: 4\n", - "[################# ] | 43% Completed | 2min 40.9sUsing factor mode\n", - "[################# ] | 43% Completed | 3min 29.9sscale factor: 4\n", - "[###################### ] | 56% Completed | 3min 34.3sUsing factor mode\n", - "[###################### ] | 56% Completed | 4min 23.3sscale factor: 4\n", - "[########################### ] | 68% Completed | 4min 27.8sUsing factor mode\n", - "[########################### ] | 68% Completed | 5min 16.8sscale factor: 4\n", - "[################################ ] | 81% Completed | 5min 21.3sUsing factor mode\n", - "[################################ ] | 81% Completed | 6min 10.3sscale factor: 4\n", - "[##################################### ] | 93% Completed | 6min 14.3sUsing factor mode\n", - "[##################################### ] | 93% Completed | 6min 23.5sscale factor: 4\n", - "[########################################] | 100% Completed | 6min 24.3s\n" - ] - } - ], + "outputs": [], "source": [ "from dask.diagnostics import ProgressBar\n", "with ProgressBar():\n", @@ -1098,1573 +165,20 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "dirty-search", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
<xarray.Dataset>\n",
-       "Dimensions:   (time: 3599, xu_ocean: 96, yu_ocean: 96)\n",
-       "Coordinates:\n",
-       "  * time      (time) float64 8.627e+04 1.727e+05 ... 3.109e+08 3.11e+08\n",
-       "  * xu_ocean  (xu_ocean) float64 2e+04 6e+04 1e+05 ... 3.78e+06 3.82e+06\n",
-       "  * yu_ocean  (yu_ocean) float64 2e+04 6e+04 1e+05 ... 3.78e+06 3.82e+06\n",
-       "Data variables:\n",
-       "    usurf     (time, yu_ocean, xu_ocean) float64 -0.001499 ... 0.0009649\n",
-       "    vsurf     (time, yu_ocean, xu_ocean) float64 0.001475 ... -0.0003283\n",
-       "    S_x       (time, yu_ocean, xu_ocean) float64 nan nan ... 1.832e-10 3.368e-11\n",
-       "    S_y       (time, yu_ocean, xu_ocean) float64 nan nan ... 9.307e-10 2.972e-10
" - ], - "text/plain": [ - "\n", - "Dimensions: (time: 3599, xu_ocean: 96, yu_ocean: 96)\n", - "Coordinates:\n", - " * time (time) float64 8.627e+04 1.727e+05 ... 3.109e+08 3.11e+08\n", - " * xu_ocean (xu_ocean) float64 2e+04 6e+04 1e+05 ... 3.78e+06 3.82e+06\n", - " * yu_ocean (yu_ocean) float64 2e+04 6e+04 1e+05 ... 3.78e+06 3.82e+06\n", - "Data variables:\n", - " usurf (time, yu_ocean, xu_ocean) float64 -0.001499 ... 0.0009649\n", - " vsurf (time, yu_ocean, xu_ocean) float64 0.001475 ... -0.0003283\n", - " S_x (time, yu_ocean, xu_ocean) float64 nan nan ... 1.832e-10 3.368e-11\n", - " S_y (time, yu_ocean, xu_ocean) float64 nan nan ... 9.307e-10 2.972e-10" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "low_rez" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "touched-township", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - 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"execution_count": 16, + "execution_count": null, "id": "productive-duplicate", "metadata": {}, "outputs": [], @@ -2683,153 +197,20 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "collaborative-courage", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FullyCNN(\n", - " (0): Conv2d(2, 128, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n", - " (1): ReLU()\n", - " (2): Conv2d(128, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n", - " (3): ReLU()\n", - " (4): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (5): ReLU()\n", - " (6): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (7): ReLU()\n", - " (8): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (9): ReLU()\n", - " (10): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (11): ReLU()\n", - " (12): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (13): ReLU()\n", - " (14): Conv2d(32, 4, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - ")" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "net" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "professional-border", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7 : Unet\n", - "21 : modelsv1\n", - "6 : multiregion\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "17 : meeting22july\n", - "5 : regionsfortraining\n", - "2 : training\n", - "23 : Default\n", - "4 : default\n", - "13 : forcingdatav2\n", - "16 : meeting15july\n", - "22 : parameterized\n", - "20 : test_global\n", - "9 : forcingdata1pct\n", - "12 : test\n", - "15 : datacm21\n", - "8 : arctan\n", - "18 : forcing-data-global\n", - "Select the id of an experiment: 21\n", - " run_id experiment_id metrics.test loss \\\n", - "0 dc74cea68a7f4c7e98f9228649a97135 21 -1.978643 \n", - "1 ec38e81123804b318c65b2c055667cbe 21 NaN \n", - "2 d5089bb089004bdf8c7de3831fc745ed 21 -1.905384 \n", - "3 2c646c84f25b46e69fa2b323ef9eb132 21 -1.897243 \n", - "4 7b828ab254a24c5b92557e78f601bd4f 21 -1.907832 \n", - "5 454771c464a145dcaf75a786632976ef 21 -1.887052 \n", - "6 4e8e899e198a4ea5b50f27555d19b97e 21 -1.910706 \n", - "7 3d858e5733cb4de99c8fdba1ca8f6b08 21 NaN \n", - "8 a36074fb07a14d778478ed64c1ab5c25 21 NaN \n", - "9 61f5b08d8d794bd58109d1ec6545d1cf 21 -1.898471 \n", - "10 0df152f9ce994f5e8f0176cb7cb6ca51 21 NaN \n", - "11 ed3011fdbb624c39be804b20b057a314 21 -1.011060 \n", - "12 40322e6a00e444daa5a218418f6064f5 21 -0.967294 \n", - "13 0939d22b367f4c9fa298441fa2fe06fa 21 -1.037308 \n", - "14 8375d0b9a5bd45aa8fbe1d837838c857 21 NaN \n", - "15 e3bea2e766f145249c8cafb9bde1ab49 21 NaN \n", - "16 6ec7560d89144e4d8e79906cf83578bf 21 NaN \n", - "17 8476b5a1150b4cebbaa497ef2b2f44d4 21 -0.849705 \n", - "18 d5eed3c5b21948c280fe2e1676875efd 21 -1.065311 \n", - "19 20505560597c440fa4bf25ef661c072b 21 NaN \n", - "20 bc739ec14cfb403f9be6c7ab3b2faa8a 21 NaN \n", - "21 4a5ac38ef8054aabbb8d0b684ba60065 21 NaN \n", - "22 dc0870fb027c4aac802c8df435260b3a 21 -1.974147 \n", - "23 dacde66589874c27a0967e6cbf357fe1 21 -2.056109 \n", - "\n", - " start_time params.time_indices params.model_cls_name \\\n", - "0 2021-01-31 16:57:19.290000+00:00 0 FullyCNN \n", - "1 2021-01-31 16:50:02.232000+00:00 None None \n", - "2 2021-01-30 23:44:10.091000+00:00 0 FullyCNN \n", - "3 2021-01-30 20:02:11.502000+00:00 0 FullyCNN \n", - "4 2021-01-30 17:01:11.783000+00:00 0 FullyCNN \n", - "5 2021-01-30 14:32:13.660000+00:00 0 FullyCNN \n", - "6 2021-01-30 07:46:27.612000+00:00 0 FullyCNN \n", - "7 2021-01-30 07:45:06.625000+00:00 0 FullyCNN \n", - "8 2021-01-30 07:42:40.833000+00:00 0 FullyCNN \n", - "9 2021-01-30 01:57:29.262000+00:00 0 FullyCNN \n", - "10 2021-01-30 00:14:30.253000+00:00 0 FullyCNN \n", - "11 2021-01-15 04:54:15.042000+00:00 0 FullyCNN \n", - "12 2021-01-14 21:49:55.067000+00:00 0 FullyCNN \n", - "13 2021-01-14 20:39:12.895000+00:00 0 FullyCNN \n", - "14 2021-01-14 19:54:05.802000+00:00 0 FullyCNN \n", - "15 2021-01-14 19:25:50.042000+00:00 0 FullyCNN \n", - "16 2021-01-14 18:31:46.502000+00:00 0 FullyCNN \n", - "17 2021-01-14 17:17:33.302000+00:00 0 FullyCNN \n", - "18 2021-01-14 06:01:20+00:00 0 FullyCNN \n", - "19 2020-12-15 07:27:54.418000+00:00 0 FullyCNN \n", - "20 2020-12-15 06:38:22.554000+00:00 0 FullyCNN \n", - "21 2020-12-13 02:24:18.388000+00:00 0 Unet \n", - "22 2020-12-12 23:58:11.893000+00:00 0 FullyCNN \n", - "23 2020-12-12 23:57:00.806000+00:00 0 FullyCNN \n", - "\n", - " params.source.run_id params.submodel \n", - "0 afab43b4a6274e29822181c4fdaaf925 transform3 \n", - "1 None None \n", - "2 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "3 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "4 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "5 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "6 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "7 None transform3 \n", - "8 None transform3 \n", - "9 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "10 7313a11dc6024d1fba09fec2cd08d54a transform3 \n", - "11 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "12 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "13 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "14 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "15 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "16 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "17 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "18 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "19 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "20 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "21 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "22 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "23 743777154cb745cf8a4272dcbd3fa189 transform3 \n", - "Run id?0\n" - ] - } - ], + "outputs": [], "source": [ "import pickle\n", "def pickle_artifact(run_id: str, path: str):\n", @@ -2853,21 +234,10 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "promotional-marina", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import torch\n", "net.load_state_dict(torch.load(model_file))" @@ -2875,46 +245,17 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "1d8160ec", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FullyCNN(\n", - " (0): Conv2d(2, 128, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n", - " (1): ReLU()\n", - " (2): Conv2d(128, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n", - " (3): ReLU()\n", - " (4): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (5): ReLU()\n", - " (6): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (7): ReLU()\n", - " (8): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (9): ReLU()\n", - " (10): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (11): ReLU()\n", - " (12): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (13): ReLU()\n", - " (14): Conv2d(32, 4, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", - " (final_transformation): SoftPlusTransform(Parameter containing:\n", - " tensor(-0.1793, device='cuda:0', requires_grad=True))\n", - ")" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "net" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "42a3d6b4", "metadata": {}, "outputs": [], @@ -2925,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "526661e0", "metadata": {}, "outputs": [], @@ -2935,7 +276,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "e085b11a", "metadata": {}, "outputs": [], @@ -2946,7 +287,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "id": "e44383d6", "metadata": {}, "outputs": [], @@ -2971,18 +312,10 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "id": "77060b45", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 24.3s\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " test = test.compute()" @@ -2990,1573 +323,20 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "id": "1a4af135", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "test.isel(time=1000)['S_x'].plot(vmin=-1, vmax=1, cmap='Spectral')" @@ -4564,991 +344,10 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "8128779d", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "(low_rez.isel(time=1000)['S_x']*1e7).plot(vmin=-1, vmax=1, cmap='Spectral')" @@ -5556,991 +355,10 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "id": "455a4f4e", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from scipy.stats import norm\n", "plt.figure()\n", @@ -6551,981 +369,10 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "2beae728", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "for i, var in enumerate(['S_x', 'S_y']):\n", @@ -7542,7 +389,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "id": "c81c6468", "metadata": {}, "outputs": [], @@ -7552,25 +399,10 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "726af67d", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/subgrid/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.\n", - " keepdims=keepdims)\n", - "/ext3/miniconda3/envs/subgrid/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.\n", - " keepdims=keepdims)\n", - "/ext3/miniconda3/envs/subgrid/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.\n", - " keepdims=keepdims)\n", - "/ext3/miniconda3/envs/subgrid/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.\n", - " keepdims=keepdims)\n" - ] - } - ], + "outputs": [], "source": [ "mse = dict()\n", "variance = dict()\n", @@ -7585,981 +417,10 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "id": "814ef9b9", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from matplotlib.patches import Arrow, Circle\n", "fig = plt.figure()\n", @@ -8589,7 +450,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "id": "a9a037cd", "metadata": {}, "outputs": [], @@ -8599,988 +460,10 @@ }, { "cell_type": "code", - "execution_count": 174, + "execution_count": null, "id": "247017ff", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "80 47\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "%matplotlib notebook\n", "x = 80\n", @@ -9606,7 +489,7 @@ }, { "cell_type": "code", - "execution_count": 175, + "execution_count": null, "id": "a7ef7c04", "metadata": {}, "outputs": [], @@ -9616,999 +499,10 @@ }, { "cell_type": "code", - "execution_count": 106, + "execution_count": null, "id": "799ebfff", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/subgrid/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.\n", - " keepdims=keepdims)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 106, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "#((low_rez['S_y']*1e7 - test['S_y']).median(dim='time') ).plot()\n", @@ -10618,999 +512,10 @@ }, { "cell_type": "code", - "execution_count": 112, + "execution_count": null, "id": "ec6142db", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/subgrid/lib/python3.6/site-packages/numpy/lib/nanfunctions.py:1665: RuntimeWarning: Degrees of freedom <= 0 for slice.\n", - " keepdims=keepdims)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 112, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "(np.log((low_rez['S_y']*1e7).std(dim='time'))).plot(vmin=-5, vmax=5)" @@ -11618,377 +523,10 @@ }, { "cell_type": "code", - "execution_count": 117, + "execution_count": null, "id": "9af9ef66", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.DataArray 'S_y' ()>\n",
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" - ], - "text/plain": [ - "\n", - "array(1.75631954e-08)" - ] - }, - "execution_count": 117, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "low_rez['S_y'].isel(xu_ocean=slice(45, None)).std()" ] @@ -12004,7 +542,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -12018,7 +556,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.12" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/examples/jupyter-notebooks/other-shallow-water-model.ipynb b/examples/jupyter-notebooks/other-shallow-water-model.ipynb index 8de4ba17..215e9d30 100644 --- a/examples/jupyter-notebooks/other-shallow-water-model.ipynb +++ b/examples/jupyter-notebooks/other-shallow-water-model.ipynb @@ -2,22 +2,16 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "electronic-latitude", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "env: MLFLOW_TRACKING_URI=/scratch/ag7531/mlruns\n" - ] - } - ], + "outputs": [], "source": [ "import mlflow\n", "import xarray as xr\n", "import matplotlib.pyplot as plt\n", + "import os,sys\n", + "sys.path.insert(1, os.path.join(os.getcwd() , '../../src/gz21_ocean_momentum'))\n", "from utils import select_experiment, select_run\n", "\n", "%env MLFLOW_TRACKING_URI /scratch/ag7531/mlruns" @@ -25,66 +19,27 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "spread-giant", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'/scratch/ag7531/mlruns'" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "%env MLFLOW_TRACKING_URI" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "indirect-violin", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7 : Unet\n", - "21 : modelsv1\n", - "6 : multiregion\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "17 : meeting22july\n", - "5 : regionsfortraining\n", - "2 : training\n", - "23 : Default\n", - "4 : default\n", - "13 : forcingdatav2\n", - "16 : meeting15july\n", - "22 : parameterized\n", - "20 : test_global\n", - "9 : forcingdata1pct\n", - "12 : test\n", - "15 : datacm21\n", - "8 : arctan\n", - "18 : forcing-data-global\n", - "Select the id of an experiment: 22\n" - ] - } - ], + "outputs": [], "source": [ "exp_id, _ = select_experiment()" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "apart-found", "metadata": {}, "outputs": [], @@ -94,466 +49,20 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "solved-cable", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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"11 7e49159466e68c77065ae0eebd8b07c0790ac59c LOCAL \n", - "12 1d1c05fa21c82ba2726a3a971661417962e1e73c LOCAL \n", - "\n", - " tags.mlflow.source.name tags.mlflow.user \n", - "0 /home/ag7531/code/swe_stochastic_param/spinupP... ag7531 \n", - "1 /home/ag7531/code/swe_stochastic_param/spinupP... ag7531 \n", - "2 spinupParameterized.py ag7531 \n", - "3 spinupParameterized.py ag7531 \n", - "4 spinupParameterized.py ag7531 \n", - "5 /home/ag7531/code/swe_stochastic_param/spinupP... ag7531 \n", - "6 spinupParameterized.py ag7531 \n", - "7 spinupParameterized.py ag7531 \n", - "8 /home/ag7531/code/swe_stochastic_param/spinupP... ag7531 \n", - "9 /home/ag7531/code/swe_stochastic_param/spinupP... ag7531 \n", - "10 /home/ag7531/code/swe_stochastic_param/spinupP... ag7531 \n", - "11 spinupParameterized.py ag7531 \n", - "12 spinupParameterized.py ag7531 " - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "runs" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "later-invalid", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['u_eddy_permitting_0001.nc',\n", - " 'du_eddy_permitting_0001.nc',\n", - " 'dv_eddy_permitting_0001.nc',\n", - " 'eta_eddy_permitting_0001.nc',\n", - " 'v_eddy_permitting_0001.nc']" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import os\n", "os.listdir(runs.iloc[7]['artifact_uri'])" @@ -561,7 +70,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "shaped-jumping", "metadata": {}, "outputs": [], @@ -579,56 +88,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "metric-combination", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loading u_eddy_permitting_0001.nc\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/xarray/backends/netCDF4_.py:378: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.\n", - " attributes = {k: var.getncattr(k) for k in var.ncattrs()}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loading du_eddy_permitting_0001.nc\n", - "Loading dv_eddy_permitting_0001.nc\n", - "Loading eta_eddy_permitting_0001.nc\n", - "Loading v_eddy_permitting_0001.nc\n", - "Loading u_eddy_permitting_0001.nc\n", - "Loading du_eddy_permitting_0001.nc\n", - "Loading dv_eddy_permitting_0001.nc\n", - "Loading eta_eddy_permitting_0001.nc\n", - "Loading v_eddy_permitting_0001.nc\n", - "Loading u_eddy_permitting_0001.nc\n", - "Loading du_eddy_permitting_0001.nc\n", - "Loading dv_eddy_permitting_0001.nc\n", - "Loading eta_eddy_permitting_0001.nc\n", - "Loading v_eddy_permitting_0001.nc\n", - "Loading u_eddy_permitting_0001.nc\n", - "Loading du_eddy_permitting_0001.nc\n", - "Loading dv_eddy_permitting_0001.nc\n", - "Loading eta_eddy_permitting_0001.nc\n", - "Loading v_eddy_permitting_0001.nc\n", - "Loading u_eddy_permitting_0001.nc\n", - "Loading du_eddy_permitting_0001.nc\n", - "Loading dv_eddy_permitting_0001.nc\n", - "Loading eta_eddy_permitting_0001.nc\n", - "Loading v_eddy_permitting_0001.nc\n" - ] - } - ], + "outputs": [], "source": [ "low_rez_datas = [load_data_from_run(i) for i in (9, 2, 6, 7)]\n", "data_h = load_data_from_run(0)" @@ -636,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "normal-dress", "metadata": {}, "outputs": [], @@ -752,7 +215,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "european-supplier", "metadata": {}, "outputs": [], @@ -764,59 +227,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "removed-colombia", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--------------------------------------------\n", - "Initialising various components of the model\n", - "--------------------------------------------\n", - "\t ...init_grid:: numerical discretisation of 96x96 grid points.\n", - "\t ...init_grid:: horizontal resolution of dx = 40 km, dy = 40 km.\n", - "--> Grid initialised.\n", - "\t ...set_coriolis:: central latitude of beta-plane lat0 = 35N.\n", - "--> Coriolis calculated.\n", - "\t ...set_viscosity:: laplacian coefficient 540, biharmonic coefficient 8.6E+11.\n", - "--> Viscosity initialised.\n", - "\t ...set_forcing:: wind forcing amplitude of 0.12 Nm-2.\n", - "--> Wind forcing calculated\n", - "\t ...set_timestep:: calculated timestep is dt = 514.0 seconds.\n", - "\t ...set_timestep:: total number of iterations to run for is N_iter = 60514.\n", - "--> Time-step calculated.\n", - "--> Gradient matrices initialised.\n", - "--> Laplacian matrices initialised.\n", - "--> Interpolation matrices initialised.\n", - "--> Arakawa matrices initialised.\n", - "\n", - "Done! Ready to set initial conditions.\n", - "--------------------------------------------\n", - "Initialising various components of the model\n", - "--------------------------------------------\n", - "\t ...init_grid:: numerical discretisation of 384x384 grid points.\n", - "\t ...init_grid:: horizontal resolution of dx = 10 km, dy = 10 km.\n", - "--> Grid initialised.\n", - "\t ...set_coriolis:: central latitude of beta-plane lat0 = 35N.\n", - "--> Coriolis calculated.\n", - "\t ...set_viscosity:: laplacian coefficient 540, biharmonic coefficient 5.4E+10.\n", - "--> Viscosity initialised.\n", - "\t ...set_forcing:: wind forcing amplitude of 0.12 Nm-2.\n", - "--> Wind forcing calculated\n", - "\t ...set_timestep:: calculated timestep is dt = 128.0 seconds.\n", - "\t ...set_timestep:: total number of iterations to run for is N_iter = 243000.\n", - "--> Time-step calculated.\n", - "--> Gradient matrices initialised.\n", - "--> Laplacian matrices initialised.\n", - "--> Interpolation matrices initialised.\n", - "--> Arakawa matrices initialised.\n", - "\n", - "Done! Ready to set initial conditions.\n" - ] - } - ], + "outputs": [], "source": [ "size = 3840\n", "model_l = ShallowWaterModel(Nx=size // 10 // 4, Ny=size // 10 // 4, Lx=size * 1e3, Ly = size * 1e3)\n", @@ -825,7 +239,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "waiting-entrepreneur", "metadata": {}, "outputs": [], @@ -837,29 +251,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "specific-botswana", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/IPython/core/interactiveshell.py:3331: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ok\n", - "ok\n", - "ok\n", - "ok\n" - ] - } - ], + "outputs": [], "source": [ "# Low rez no param\n", "new_low_rez_datas = []\n", @@ -880,19 +275,10 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "id": "pacific-moses", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/IPython/core/interactiveshell.py:3331: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n", - " exec(code_obj, self.user_global_ns, self.user_ns)\n" - ] - } - ], + "outputs": [], "source": [ "def coarsen(data, factor):\n", " data = xr.apply_ufunc(lambda x: gaussian_filter(x, factor / 2), data, input_core_dims=[['time']], \n", @@ -914,7 +300,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "reserved-korea", "metadata": {}, "outputs": [], @@ -924,7 +310,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": null, "id": "fiscal-objective", "metadata": {}, "outputs": [], @@ -934,1557 +320,20 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": null, "id": "aging-termination", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - 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" icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":7: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " im = plt.imshow(getattr(low_rez_datas[i][var], func)(dim='time'), cmap=cmaps[func], **args[func],\n", - ":7: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " im = plt.imshow(getattr(low_rez_datas[i][var], func)(dim='time'), cmap=cmaps[func], **args[func],\n", - ":12: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.\n", - " im = plt.imshow(getattr(dataset_h[var], func)(dim='time'), cmap=cmaps[func], **args[func],\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 54, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "fig = plt.figure()\n", "# Determine limits\n", @@ -4839,7 +483,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "professional-wagon", "metadata": {}, "outputs": [], @@ -4849,975 +493,10 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "cultural-cooperation", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - 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' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 355, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "colors=['b', 'g', 'r', 'c']\n", @@ -7392,7 +550,7 @@ }, { "cell_type": "code", - "execution_count": 354, + "execution_count": null, "id": "challenging-valentine", "metadata": {}, "outputs": [], @@ -7402,975 +560,10 @@ }, { "cell_type": "code", - "execution_count": 337, + "execution_count": null, "id": "objective-adventure", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - 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"execution_count": 338, + "execution_count": null, "id": "hungarian-chassis", "metadata": {}, "outputs": [], @@ -8401,7 +594,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -8415,7 +608,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.5" + "version": "3.11.2" } }, "nbformat": 4, diff --git a/examples/jupyter-notebooks/test_global.ipynb b/examples/jupyter-notebooks/test_global.ipynb index 1c3b643c..91455134 100644 --- a/examples/jupyter-notebooks/test_global.ipynb +++ b/examples/jupyter-notebooks/test_global.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -11,47 +11,17 @@ "import xarray as xr\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", - "from analysis.utils import select_experiment, select_run, plot_dataset" + "import os,sys\n", + "sys.path.insert(1, os.path.join(os.getcwd() , '../../src/gz21_ocean_momentum'))\n", + "from utils import select_experiment, select_run\n", + "from analysis.utils import plot_dataset" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6 : multiregion\n", - "17 : meeting22july\n", - "15 : datacm21\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "2 : training\n", - "4 : default\n", - "7 : Unet\n", - "18 : forcing-data-global\n", - "12 : test\n", - "9 : forcingdata1pct\n", - "5 : regionsfortraining\n", - "20 : test_global\n", - "8 : arctan\n", - "16 : meeting15july\n", - "13 : forcingdatav2\n", - "Select the id of an experiment: 20\n" - ] - } - ], + "outputs": [], "source": [ "test_exp_name = select_experiment()\n", "test_exp = mlflow.get_experiment_by_name(test_exp_name)\n", @@ -60,84 +30,27 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " run_id experiment_id\n", - "0 e3c67bee07ab4cfd9a1d9721f6b56410 20\n", - "1 0d10f8c7adb14b938e80d1d1d9481042 20\n", - "2 705929e56cd542af9ace6ef464e80a13 20\n", - "3 d7353eb4c04b4c33a249308f332c16af 20\n", - "4 0640a02589a04092952557b9c0c25bf4 20\n", - "5 e196caa242d24949a24903434e638126 20\n", - "6 df377405e36a45bdb61abb8a6895cc4e 20\n", - "Run id?0\n" - ] - } - ], + "outputs": [], "source": [ "run = select_run(experiment_ids=test_exp_id)" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "run_id e3c67bee07ab4cfd9a1d9721f6b56410\n", - "experiment_id 20\n", - "status FINISHED\n", - "artifact_uri /scratch/ag7531/mlruns/20/e3c67bee07ab4cfd9a1d...\n", - "start_time 2020-10-03 17:13:20.416000+00:00\n", - "end_time 2020-10-03 18:45:12.920000+00:00\n", - "metrics.validation loss 0\n", - "params.data_run_id 38491825c56c4c8c8afbf5286ce59c7c\n", - "params.n_epochs 0\n", - "params.model_run_id 2370107146564198b9f7351036632770\n", - "tags.mlflow.source.git.commit ecd9a8da9b41101e798ccd3b5429d3693feb2028\n", - "tags.mlflow.source.type LOCAL\n", - "tags.mlflow.source.name /home/ag7531/code/subgrid/testing/main.py\n", - "tags.mlflow.user ag7531\n", - "Name: 0, dtype: object" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "run" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/scratch/ag7531/mlruns/18/a06e42d44402481eb3a8f9e705770950/artifacts/forcing\n" - ] - } - ], + "outputs": [], "source": [ "client_ = client.MlflowClient()\n", "data_file_name = client_.download_artifacts(run['params.data_run_id'], 'forcing')\n", @@ -147,50 +60,16 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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S_yscale (time, latitude, longitude) float64 dask.array" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "merged" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plot_dataset(merged.isel(time=10), vmin=-1e-7, vmax=1e-7)" ] @@ -294,7 +114,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -308,7 +128,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.11.2" } }, "nbformat": 4, diff --git a/examples/jupyter-notebooks/test_global_control.ipynb b/examples/jupyter-notebooks/test_global_control.ipynb index b36bd6e4..ff60f675 100644 --- a/examples/jupyter-notebooks/test_global_control.ipynb +++ b/examples/jupyter-notebooks/test_global_control.ipynb @@ -4,42 +4,41 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Test on Global scale# " + "# Test on Global scale " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To produce the paper figures, this notebook has to be run twice: once with CO2=1 settings and once with CO2=0." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "env: MLFLOW_TRACKING_URI=/data/scratch/ahw795/mlflow\n", - "env: GOOGLE_APPLICATION_CREDENTIALS=/data/home/ahw795/corded-woodland-377216-d4a175456b63.json\n" - ] - } - ], + "outputs": [], "source": [ - "%matplotlib notebook\n", - "%env MLFLOW_TRACKING_URI /data/scratch/ahw795/mlflow\n", - "%env GOOGLE_APPLICATION_CREDENTIALS /data/home/ahw795/corded-woodland-377216-d4a175456b63.json" + "#%matplotlib notebook #This option does not work in Jupyterlab\n", + "%matplotlib widget \n", + "\n", + "%cd ../../src/gz21_ocean_momentum\n", + "\n", + "import os\n", + "mlruns_path=os.path.join(os.getcwd(), '../../mlruns/')\n", + "%env MLFLOW_TRACKING_URI $mlruns_path\n", + "\n", + "# See https://github.com/m2lines/gz21_ocean_momentum/blob/main/docs/data.md for an explanation \n", + "# The environment variable does not need setting if you place the credentials file at ~/.config/gcloud/application_default_credentials.json .\n", + "%env GOOGLE_APPLICATION_CREDENTIALS /home/marion/.config/gcloud/application_default_credentials.json" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "To load the net from the paper, use the function load_paper_net().\n" - ] - } - ], + "outputs": [], "source": [ "import mlflow\n", "from mlflow.tracking import client\n", @@ -81,7 +80,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -90,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -107,12 +106,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "This downloads some information about the grid, used latero on" + "This downloads some information about the grid, used later on" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -124,182 +123,19 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:Malformed experiment '582020873832152431'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/582020873832152431/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/582020873832152431/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '277856125970161566'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/277856125970161566/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/277856125970161566/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '440961587973869508'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/440961587973869508/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/440961587973869508/meta.yaml' does not exist.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "815957710274620256 : test\n", - "169497814690632640 : train\n", - "858376422888000303 : data-global\n", - "166760893314335591 : data\n", - "Select the id of an experiment: 815957710274620256\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:Malformed experiment '582020873832152431'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/582020873832152431/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/582020873832152431/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '277856125970161566'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/277856125970161566/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/277856125970161566/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '440961587973869508'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/440961587973869508/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/440961587973869508/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '582020873832152431'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/582020873832152431/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/582020873832152431/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '277856125970161566'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/277856125970161566/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/277856125970161566/meta.yaml' does not exist.\n", - "WARNING:root:Malformed experiment '440961587973869508'. Detailed error Yaml file '/data/scratch/ahw795/mlflow/440961587973869508/meta.yaml' does not exist.\n", - "Traceback (most recent call last):\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 299, in search_experiments\n", - " exp = self._get_experiment(exp_id, view_type)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 392, in _get_experiment\n", - " meta = FileStore._read_yaml(experiment_dir, FileStore.META_DATA_FILE_NAME)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1239, in _read_yaml\n", - " return _read_helper(root, file_name, attempts_remaining=retries)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/store/tracking/file_store.py\", line 1232, in _read_helper\n", - " result = read_yaml(root, file_name)\n", - " File \"/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/mlflow/utils/file_utils.py\", line 227, in read_yaml\n", - " raise MissingConfigException(\"Yaml file '%s' does not exist.\" % file_path)\n", - "mlflow.exceptions.MissingConfigException: Yaml file '/data/scratch/ahw795/mlflow/440961587973869508/meta.yaml' does not exist.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " run_id experiment_id status \\\n", - "0 e7c7cddf829549fd8c9a7a20f408cfcc 815957710274620256 FINISHED \n", - "\n", - " start_time params.CO2 params.factor params.submodel \\\n", - "0 2023-08-31 15:46:23.270000+00:00 0 4 transform3 \n", - "\n", - " params.loss_cls_name \n", - "0 HeteroskedasticGaussianLossV2 \n", - "Run id?0\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/data/home/ahw795/GZ21_ocean_momentum_CNN/src/gz21_ocean_momentum/analysis/utils.py:67: FutureWarning: ``mlflow.tracking.client.MlflowClient.download_artifacts`` is deprecated since 2.0. This method will be removed in a future release. Use ``mlflow.artifacts.download_artifacts`` instead.\n", - " data_file_name = client_.download_artifacts(run_id, \"forcing\")\n", - "/data/home/ahw795/GZ21_ocean_momentum_CNN/src/gz21_ocean_momentum/analysis/utils.py:79: FutureWarning: ``mlflow.tracking.client.MlflowClient.download_artifacts`` is deprecated since 2.0. This method will be removed in a future release. Use ``mlflow.artifacts.download_artifacts`` instead.\n", - " pred_file_name = client_.download_artifacts(run_id, \"test_output_0\")\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ + "print(\"Select the experiment of the inference run.\")\n", + "\n", "exp_id, test_exp_name = select_experiment()\n", "cols=['status', 'start_time', 'params.CO2', 'params.factor',\n", " 'params.submodel', 'params.loss_cls_name']\n", - "merge=[('data-global', 'params.data_run_id', 'run_id'),\n", + "# In the following merge parameter, the first strings in the tupels need to be the experiment names for the data run and the training run, respectively.\n", + "# If these are in the same experiment they can either be duplicated, or you can set merge=[].\n", + "# This is used to show the available runs.\n", + "merge=[('data', 'params.data_run_id', 'run_id'),\n", " ('train', 'params.model_run_id', 'run_id')]\n", "run = select_run(experiment_ids=exp_id, cols=cols, merge=merge)\n", "data, pred = download_data_pred(run['params.data_run_id'], run.run_id)" @@ -307,23 +143,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "

Menu

MSE and R²   Correlation  
Variance of forcing  Comparison of distributions  QQ-plot  Bias analysis  
Time series plots" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from IPython.core.display import HTML\n", "html = '

Menu

'\n", @@ -339,1915 +161,20 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset>\n",
-       "Dimensions:    (time: 996, latitude: 589, longitude: 900)\n",
-       "Coordinates:\n",
-       "  * time       (time) object 0181-01-05 12:00:00 ... 0183-09-27 12:00:00\n",
-       "  * longitude  (longitude) float64 -279.7 -279.3 -278.9 ... 79.05 79.45 79.85\n",
-       "  * latitude   (latitude) float64 -78.24 -78.07 -77.9 ... 77.86 78.03 78.19\n",
-       "Data variables:\n",
-       "    S_x        (time, latitude, longitude) float64 dask.array<chunksize=(1, 589, 900), meta=np.ndarray>\n",
-       "    S_y        (time, latitude, longitude) float64 dask.array<chunksize=(1, 589, 900), meta=np.ndarray>\n",
-       "    usurf      (time, latitude, longitude) float64 dask.array<chunksize=(1, 589, 900), meta=np.ndarray>\n",
-       "    vsurf      (time, latitude, longitude) float64 dask.array<chunksize=(1, 589, 900), meta=np.ndarray>
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' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. 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We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - 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" var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "uv_plotter.plot(data['S_x'].isel(time=100), lon=0., projection_cls = ccrs.PlateCarree,\n", + "uv_plotter.plot(data['S_x'].isel(time=70), lon=0., projection_cls = ccrs.PlateCarree,\n", " colorbar_label='m/s', cmap=cmocean.cm.delta, vmin=-1, vmax=1)" ] }, @@ -2260,1007 +187,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def plot_time_series(data, pred, longitude: float, latitude: float, time: slice,\n", " std: bool = True, true: bool = True):\n", @@ -3289,7 +218,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -3298,7 +227,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -3321,7 +250,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -3339,19 +268,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 9.79 ss\n", - "[########################################] | 100% Completed | 12.06 s\n", - "[########################################] | 100% Completed | 5.75 sms\n" - ] - } - ], + "outputs": [], "source": [ "mse = (errors**2).mean(dim='time')\n", "mse_cycle = (errors_cycle**2).mean(dim='time')\n", @@ -3377,1014 +296,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Below is Figure 3a of the paper" + "Below is Figure 4a of the paper" ] }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "plt.rcParams[\"figure.figsize\"] = (4*2, 4 * 2 / 1.618)\n", "x = uv_plotter.plot(mse['total'], lon=0., cmap=cmocean.cm.dense,\n", @@ -4393,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4402,7 +321,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4420,1024 +339,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Below is Figure 3b of the paper" + "Below is Figure 4b of the paper" ] }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import matplotlib\n", "rsquared = 1 - mse / amplitudes\n", @@ -5448,7 +357,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5457,7 +366,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5480,7 +389,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5489,7 +398,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5500,28 +409,9 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Dimensions: ()\n", - "Data variables:\n", - " S_x float64 0.7932\n", - " S_y float64 0.8065\n", - " total float64 0.8001\n", - "\n", - "Dimensions: ()\n", - "Data variables:\n", - " S_x float64 0.7519\n", - " S_y float64 0.758\n", - " total float64 0.755\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " mse_scalar = mse_to_scalar.sel(latitude=latitudes).sum().compute()\n", @@ -5542,7 +432,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5553,7 +443,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5565,32 +455,9 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[################### ] | 48% Completed | 18.33 ss" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/dask/array/numpy_compat.py:43: RuntimeWarning: invalid value encountered in divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 36.71 s\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " corr = corr.compute()\n", @@ -5599,1024 +466,16 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "uv_plotter.plot(corr['S_x'], vmin=0.7, vmax=1., lon=0., cmap=cmocean.cm.balance_r)" ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -6632,33 +491,9 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 7.86 sms\n", - "[ ] | 0% Completed | 103.48 ms" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/data/home/ahw795/.cache/pypoetry/virtualenvs/gz21-ocean-momentum-pWpkzWTg-py3.9/lib/python3.9/site-packages/dask/array/numpy_compat.py:43: RuntimeWarning: invalid value encountered in divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 3.14 sms\n" - ] - } - ], + "outputs": [], "source": [ "norm_S = np.sqrt(data['S_x']**2 + data['S_y']**2)\n", "norm_Spred = np.sqrt(pred['S_x']**2 + pred['S_y']**2)\n", @@ -6671,2014 +506,9 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - 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"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - 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' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 1.87 sms\n", - "[########################################] | 100% Completed | 1.85 sms\n", - "[########################################] | 100% Completed | 2.17 sms\n", - "[########################################] | 100% Completed | 1.83 sms\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 0, '$1e^{-7}m/s^2$')" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "bins = np.arange(-20, 21, 1)\n", "\n", @@ -11238,7 +648,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -11247,1015 +657,9 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 7.22 ss\n", - "[########################################] | 100% Completed | 6.72 sms\n" - ] - } - ], + "outputs": [], "source": [ "plt.figure()\n", "bins=np.arange(-6, 6, 0.025)\n", @@ -12273,7 +677,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -12289,7 +693,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -12299,46 +703,18 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1 , 0.11,\n", - " 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2 , 0.21, 0.22,\n", - " 0.23, 0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.3 , 0.31, 0.32, 0.33,\n", - " 0.34, 0.35, 0.36, 0.37, 0.38, 0.39, 0.4 , 0.41, 0.42, 0.43, 0.44,\n", - " 0.45, 0.46, 0.47, 0.48, 0.49, 0.5 , 0.51, 0.52, 0.53, 0.54, 0.55,\n", - " 0.56, 0.57, 0.58, 0.59, 0.6 , 0.61, 0.62, 0.63, 0.64, 0.65, 0.66,\n", - " 0.67, 0.68, 0.69, 0.7 , 0.71, 0.72, 0.73, 0.74, 0.75, 0.76, 0.77,\n", - " 0.78, 0.79, 0.8 , 0.81, 0.82, 0.83, 0.84, 0.85, 0.86, 0.87, 0.88,\n", - " 0.89, 0.9 , 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, 0.99])" - ] - }, - "execution_count": 55, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "quantiles" ] }, { "cell_type": "code", - "execution_count": 56, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 7.06 sms\n", - "[########################################] | 100% Completed | 6.66 sms\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " quantiles_x = np.nanquantile(residuals['S_x'].compute(), quantiles)\n", @@ -12347,7 +723,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -12357,1017 +733,9 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_device_pixel_ratio', {\n", - " device_pixel_ratio: fig.ratio,\n", - " });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute('tabindex', '0');\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;' +\n", - " 'z-index: 2;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'pointer-events: none;' +\n", - " 'position: relative;' +\n", - " 'z-index: 0;'\n", - " );\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box;' +\n", - " 'left: 0;' +\n", - " 'pointer-events: none;' +\n", - " 'position: absolute;' +\n", - " 'top: 0;' +\n", - " 'z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " /* This rescales the canvas back to display pixels, so that it\n", - " * appears correct on HiDPI screens. */\n", - " canvas.style.width = width + 'px';\n", - " canvas.style.height = height + 'px';\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " /* User Agent sniffing is bad, but WebKit is busted:\n", - " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", - " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", - " * The worst that happens here is that they get an extra browser\n", - " * selection when dragging, if this check fails to catch them.\n", - " */\n", - " var UA = navigator.userAgent;\n", - " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", - " if(isWebKit) {\n", - " return function (event) {\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We\n", - " * want to control all of the cursor setting manually through\n", - " * the 'cursor' event from matplotlib */\n", - " event.preventDefault()\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " } else {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'dblclick',\n", - " on_mouse_event_closure('dblclick')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " canvas_div.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " canvas_div.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " canvas_div.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " fig.canvas_div.style.cursor = msg['cursor'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " var img = evt.data;\n", - " if (img.type !== 'image/png') {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " img.type = 'image/png';\n", - " }\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " img\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "function getModifiers(event) {\n", - " var mods = [];\n", - " if (event.ctrlKey) {\n", - " mods.push('ctrl');\n", - " }\n", - " if (event.altKey) {\n", - " mods.push('alt');\n", - " }\n", - " if (event.shiftKey) {\n", - " mods.push('shift');\n", - " }\n", - " if (event.metaKey) {\n", - " mods.push('meta');\n", - " }\n", - " return mods;\n", - "}\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * https://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " // from https://stackoverflow.com/q/1114465\n", - " var boundingRect = this.canvas.getBoundingClientRect();\n", - " var x = (event.clientX - boundingRect.left) * this.ratio;\n", - " var y = (event.clientY - boundingRect.top) * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " modifiers: getModifiers(event),\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.key === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.key;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.key !== 'Control') {\n", - " value += 'ctrl+';\n", - " }\n", - " else if (event.altKey && event.key !== 'Alt') {\n", - " value += 'alt+';\n", - " }\n", - " else if (event.shiftKey && event.key !== 'Shift') {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k' + event.key;\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.binaryType = comm.kernel.ws.binaryType;\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " function updateReadyState(_event) {\n", - " if (comm.kernel.ws) {\n", - " ws.readyState = comm.kernel.ws.readyState;\n", - " } else {\n", - " ws.readyState = 3; // Closed state.\n", - " }\n", - " }\n", - " comm.kernel.ws.addEventListener('open', updateReadyState);\n", - " comm.kernel.ws.addEventListener('close', updateReadyState);\n", - " comm.kernel.ws.addEventListener('error', updateReadyState);\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " var data = msg['content']['data'];\n", - " if (data['blob'] !== undefined) {\n", - " data = {\n", - " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", - " };\n", - " }\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(data);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Meridional component')" - ] - }, - "execution_count": 58, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "plt.figure()\n", "reference = quantiles_norm\n", @@ -13385,7 +753,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -13401,7 +769,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -13427,17 +795,9 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 45.5s\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " q2 = np.nanquantile(residuals, quantiles)" @@ -13445,942 +805,9 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "norm_quantiles = norm.ppf(quantiles)\n", "plt.figure()\n", @@ -14390,942 +817,9 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " } else {\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 78, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "q = np.nanquantile(v, quantiles)\n" ] @@ -15352,30 +846,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ ] | 0% Completed | 2.4s" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":11: RuntimeWarning: divide by zero encountered in log\n", - " log_lkh = xr.apply_ufunc(lambda x: np.log(norm.pdf(x)), residuals, dask='parallelized', output_dtypes=[np.float64,])\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################### ] | 68% Completed | 2min 57.3s" - ] - } - ], + "outputs": [], "source": [ "from scipy.stats import norm\n", "lon = slice(None, None, 1)\n", @@ -15394,1814 +865,18 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - 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" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - 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' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 1.3s\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "with ProgressBar():\n", " uv_plotter.plot(abs(relative_bias['S_x']), cmap=cmocean.cm.delta, lon=0., vmin=0.01, vmax=1, norm=matplotlib.colors.LogNorm())" @@ -18639,7 +938,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -18655,7 +954,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -18664,964 +963,9 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - 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" - ], - "text/plain": [ - "\n", - "Dimensions: (latitude: 625, longitude: 900, time: 7300)\n", - "Coordinates:\n", - " * time (time) object 0181-01-05 12:00:00 ... 0200-12-30 12:00:00\n", - " * longitude (longitude) float64 -279.7 -279.3 -278.9 ... 79.05 79.45 79.85\n", - " * latitude (latitude) float64 -79.33 -79.17 -79.0 ... 82.84 83.01 83.18\n", - "Data variables:\n", - " S_x (time, latitude, longitude) float32 dask.array\n", - " S_y (time, latitude, longitude) float32 dask.array\n", - " usurf (time, latitude, longitude) float32 dask.array\n", - " vsurf (time, latitude, longitude) float32 dask.array" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "data" ] @@ -21200,15 +1010,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[################################ ] | 80% Completed | 2min 16.3s" - ] - } - ], + "outputs": [], "source": [ "from analysis.base import QuantileCompare\n", "\n", @@ -21220,18 +1022,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/ext3/miniconda3/envs/analysis/lib/python3.8/site-packages/numpy/lib/nanfunctions.py:1389: RuntimeWarning: All-NaN slice encountered\n", - " result = np.apply_along_axis(_nanquantile_1d, axis, a, q,\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " q_0_75 = qq.data_quantiles[0.75]" @@ -21239,20 +1032,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.6744897501960817" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from scipy.stats import norm\n", "norm.ppf(0.75)" @@ -21260,974 +1042,9 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - " if (this.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n", - " }\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.one(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import cartopy.crs as ccrs\n", "import cmocean\n", @@ -22237,979 +1054,9 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cached version!\n", - "Using cached version!\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "uv_plotter.plot(data['S_x'].isel(time=0), cmap=cmap_balance, vmin=-2, vmax=2)" ] @@ -23376,9 +1223,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "from IPython.display import HTML\n", @@ -23421,9 +1266,9 @@ ], "metadata": { "kernelspec": { - "display_name": "gz21env", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "gz21env" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -23435,7 +1280,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/examples/jupyter-notebooks/train_results.ipynb b/examples/jupyter-notebooks/train_results.ipynb index bf450e93..1e2a8dbe 100644 --- a/examples/jupyter-notebooks/train_results.ipynb +++ b/examples/jupyter-notebooks/train_results.ipynb @@ -16,136 +16,17 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "scrolled": true }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7 : Unet\n", - "21 : modelsv1\n", - "6 : multiregion\n", - "3 : multiregions\n", - "19 : data-global\n", - "14 : forcingdatav3\n", - "17 : meeting22july\n", - "5 : regionsfortraining\n", - "2 : training\n", - "23 : Default\n", - "4 : default\n", - "13 : forcingdatav2\n", - "16 : meeting15july\n", - "22 : parameterized\n", - "20 : test_global\n", - "9 : forcingdata1pct\n", - "12 : test\n", - "15 : datacm21\n", - "8 : arctan\n", - "18 : forcing-data-global\n", - "Select the id of an experiment: 21\n", - " run_id experiment_id params.model_cls_name \\\n", - "0 dc74cea68a7f4c7e98f9228649a97135 21 FullyCNN \n", - "1 ec38e81123804b318c65b2c055667cbe 21 None \n", - "2 d5089bb089004bdf8c7de3831fc745ed 21 FullyCNN \n", - "3 2c646c84f25b46e69fa2b323ef9eb132 21 FullyCNN \n", - "4 7b828ab254a24c5b92557e78f601bd4f 21 FullyCNN \n", - "5 454771c464a145dcaf75a786632976ef 21 FullyCNN \n", - "6 4e8e899e198a4ea5b50f27555d19b97e 21 FullyCNN \n", - "7 3d858e5733cb4de99c8fdba1ca8f6b08 21 FullyCNN \n", - "8 a36074fb07a14d778478ed64c1ab5c25 21 FullyCNN \n", - "9 61f5b08d8d794bd58109d1ec6545d1cf 21 FullyCNN \n", - "10 0df152f9ce994f5e8f0176cb7cb6ca51 21 FullyCNN \n", - "11 ed3011fdbb624c39be804b20b057a314 21 FullyCNN \n", - "12 40322e6a00e444daa5a218418f6064f5 21 FullyCNN \n", - "13 0939d22b367f4c9fa298441fa2fe06fa 21 FullyCNN \n", - "14 8375d0b9a5bd45aa8fbe1d837838c857 21 FullyCNN \n", - "15 e3bea2e766f145249c8cafb9bde1ab49 21 FullyCNN \n", - "16 6ec7560d89144e4d8e79906cf83578bf 21 FullyCNN \n", - "17 8476b5a1150b4cebbaa497ef2b2f44d4 21 FullyCNN \n", - "18 d5eed3c5b21948c280fe2e1676875efd 21 FullyCNN \n", - "19 20505560597c440fa4bf25ef661c072b 21 FullyCNN \n", - "20 bc739ec14cfb403f9be6c7ab3b2faa8a 21 FullyCNN \n", - "21 4a5ac38ef8054aabbb8d0b684ba60065 21 Unet \n", - "22 dc0870fb027c4aac802c8df435260b3a 21 FullyCNN \n", - "23 dacde66589874c27a0967e6cbf357fe1 21 FullyCNN \n", - "\n", - " params.loss_cls_name metrics.test loss \n", - "0 HeteroskedasticGaussianLossV2 -1.978643 \n", - "1 None NaN \n", - "2 HeteroskedasticGaussianLossV2 -1.905384 \n", - "3 HeteroskedasticGaussianLossV2 -1.897243 \n", - "4 HeteroskedasticGaussianLossV2 -1.907832 \n", - "5 HeteroskedasticGaussianLossV2 -1.887052 \n", - "6 HeteroskedasticGaussianLossV2 -1.910706 \n", - "7 HeteroskedasticGaussianLossV2 NaN \n", - "8 HeteroskedasticGaussianLossV2 NaN \n", - "9 HeteroskedasticGaussianLossV2 -1.898471 \n", - "10 HeteroskedasticGaussianLossV2 NaN \n", - "11 StudentLoss -1.011060 \n", - "12 StudentLoss -0.967294 \n", - "13 StudentLoss -1.037308 \n", - "14 StudentLoss NaN \n", - "15 StudentLoss NaN \n", - "16 StudentLoss NaN \n", - "17 StudentLoss -0.849705 \n", - "18 StudentLoss -1.065311 \n", - "19 BimodalStudentLoss NaN \n", - "20 BimodalStudentLoss NaN \n", - "21 HeteroskedasticGaussianLossV2 NaN \n", - "22 HeteroskedasticGaussianLossV2 -1.974147 \n", - "23 BimodalGaussianLoss -2.056109 \n", - "Run id?0\n", - "run_id dc74cea68a7f4c7e98f9228649a97135\n", - "experiment_id 21\n", - "status FINISHED\n", - "artifact_uri /scratch/ag7531/mlruns/21/dc74cea68a7f4c7e98f9...\n", - "start_time 2021-01-31 16:57:19.290000+00:00\n", - "end_time 2021-01-31 19:59:40.496000+00:00\n", - "metrics.test loss -1.978643\n", - "metrics.Inf Norm 22.800968\n", - "metrics.R2 0.060448\n", - "metrics.train loss -1.974278\n", - "metrics.mse NaN\n", - "params.print_every 20\n", - "params.weight_decay 0.00\n", - "params.features_transform_cls_name None\n", - "params.train_split 0.8\n", - "params.batchsize 4\n", - "params.targets_transform_cls_name None\n", - "params.model_cls_name FullyCNN\n", - "params.n_epochs 100\n", - "params.time_indices 0\n", - "params.learning_rate 0/5e-4/10/5e-5/20/5e-6\n", - "params.source.run_id afab43b4a6274e29822181c4fdaaf925\n", - "params.source.experiment_id 19\n", - "params.loss_cls_name HeteroskedasticGaussianLossV2\n", - "params.exp_id 19\n", - "params.n_epochs_actual 58\n", - "params.test_split 0.85\n", - "params.model_module_name models.models1\n", - "params.run_id afab43b4a6274e29822181c4fdaaf925\n", - "params.transformation_cls_name SoftPlusTransform\n", - "params.submodel transform3\n", - "tags.mlflow.project.entryPoint train\n", - "tags.mlflow.project.backend local\n", - "tags.mlflow.source.type PROJECT\n", - "tags.mlflow.source.git.commit 57906ec55a7ef49ef827136e9a5e6f3f216a62a7\n", - "tags.mlflow.user ag7531\n", - "tags.mlflow.gitRepoURL git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.name git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.git.repoURL git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.env None\n", - "Name: 0, dtype: object\n" - ] - } - ], + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", "import numpy as np\n", + "import os, sys\n", + "sys.path.insert(1, os.path.join(os.getcwd() , '../../src/gz21_ocean_momentum'))\n", "from analysis.utils import view_predictions, DisplayMode, plot_dataset\n", "from utils import select_run, select_experiment\n", "from analysis.utils import play_movie\n", @@ -155,7 +36,7 @@ "time = 50\n", "\n", "# Prompts the user to select a trained model\n", - "mlflow.set_tracking_uri('/scratch/ag7531/mlruns')\n", + "mlflow.set_tracking_uri(os.path.join(os.getcwd(), '../../mlruns'))\n", "cols = ['params.model_cls_name', 'params.loss_cls_name']\n", "exp_id, _ =select_experiment()\n", "run = select_run(sort_by='metrics.test loss', cols=cols, experiment_ids=[exp_id,])\n", @@ -166,64 +47,16 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "run_id dc74cea68a7f4c7e98f9228649a97135\n", - "experiment_id 21\n", - "status FINISHED\n", - "artifact_uri /scratch/ag7531/mlruns/21/dc74cea68a7f4c7e98f9...\n", - "start_time 2021-01-31 16:57:19.290000+00:00\n", - "end_time 2021-01-31 19:59:40.496000+00:00\n", - "metrics.test loss -1.978643\n", - "metrics.Inf Norm 22.800968\n", - "metrics.R2 0.060448\n", - "metrics.train loss -1.974278\n", - "metrics.mse NaN\n", - "params.print_every 20\n", - "params.weight_decay 0.00\n", - "params.features_transform_cls_name None\n", - "params.train_split 0.8\n", - "params.batchsize 4\n", - "params.targets_transform_cls_name None\n", - "params.model_cls_name FullyCNN\n", - "params.n_epochs 100\n", - "params.time_indices 0\n", - "params.learning_rate 0/5e-4/10/5e-5/20/5e-6\n", - "params.source.run_id afab43b4a6274e29822181c4fdaaf925\n", - "params.source.experiment_id 19\n", - "params.loss_cls_name HeteroskedasticGaussianLossV2\n", - "params.exp_id 19\n", - "params.n_epochs_actual 58\n", - "params.test_split 0.85\n", - "params.model_module_name models.models1\n", - "params.run_id afab43b4a6274e29822181c4fdaaf925\n", - "params.transformation_cls_name SoftPlusTransform\n", - "params.submodel transform3\n", - "tags.mlflow.project.entryPoint train\n", - "tags.mlflow.project.backend local\n", - "tags.mlflow.source.type PROJECT\n", - "tags.mlflow.source.git.commit 57906ec55a7ef49ef827136e9a5e6f3f216a62a7\n", - "tags.mlflow.user ag7531\n", - "tags.mlflow.gitRepoURL git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.name git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.source.git.repoURL git@github.com:arthurBarthe/subgrid.git\n", - "tags.mlflow.project.env None\n", - "Name: 0, dtype: object\n" - ] - } - ], + "outputs": [], "source": [ "print(run)" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -238,1011 +71,18 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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-       "    v_surf     (time, latitude, longitude) float64 dask.array<chunksize=(274, 10, 23), meta=np.ndarray>
" - ], - "text/plain": [ - "\n", - "Dimensions: (latitude: 38, longitude: 45, time: 1096)\n", - "Coordinates:\n", - " * latitude (latitude) float64 37.22 37.54 37.85 38.17 ... 47.52 47.79 48.06\n", - " * longitude (longitude) float64 -43.75 -43.35 -42.95 ... -26.95 -26.55 -26.15\n", - " * time (time) object 0198-01-01 12:00:00 ... 0200-12-31 12:00:00\n", - "Data variables:\n", - " S_x (time, latitude, longitude) float64 dask.array\n", - " S_xpred (time, latitude, longitude) float64 dask.array\n", - " S_xscale (time, latitude, longitude) float64 dask.array\n", - " S_y (time, latitude, longitude) float64 dask.array\n", - " S_ypred (time, latitude, longitude) float64 dask.array\n", - " S_yscale (time, latitude, longitude) float64 dask.array\n", - " u_surf (time, latitude, longitude) float64 dask.array\n", - " v_surf (time, latitude, longitude) float64 dask.array" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "model_output" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/code/subgrid/data/utils.py:30: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.\n", - " subdomains = yaml.load(f)\n" - ] - } - ], + "outputs": [], "source": [ "raw_data = client.download_artifacts(run['params.run_id'].split('/')[0], 'forcing')\n", "raw_data = xr.open_zarr(raw_data)\n", @@ -1251,70 +91,16 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[\n", - " Dimensions: (time: 7305, xu_ocean: 75, yu_ocean: 51)\n", - " Coordinates:\n", - " * time (time) object 0181-01-01 12:00:00 ... 0200-12-31 12:00:00\n", - " * xu_ocean (xu_ocean) float64 -49.75 -49.35 -48.95 ... -20.95 -20.55 -20.15\n", - " * yu_ocean (yu_ocean) float64 35.28 35.61 35.93 36.26 ... 49.38 49.64 49.9\n", - " Data variables:\n", - " S_x (time, yu_ocean, xu_ocean) float32 dask.array\n", - " S_y (time, yu_ocean, xu_ocean) float32 dask.array\n", - " usurf (time, yu_ocean, xu_ocean) float32 dask.array\n", - " vsurf (time, yu_ocean, xu_ocean) float32 dask.array,\n", - " \n", - " Dimensions: (time: 7305, xu_ocean: 45, yu_ocean: 45)\n", - " Coordinates:\n", - " * time (time) object 0181-01-01 12:00:00 ... 0200-12-31 12:00:00\n", - " * xu_ocean (xu_ocean) float64 -179.7 -179.3 -178.9 ... -162.9 -162.5 -162.1\n", - " * yu_ocean (yu_ocean) float64 -39.8 -39.49 -39.18 ... -25.74 -25.38 -25.02\n", - " Data variables:\n", - " S_x (time, yu_ocean, xu_ocean) float32 dask.array\n", - " S_y (time, yu_ocean, xu_ocean) float32 dask.array\n", - " usurf (time, yu_ocean, xu_ocean) float32 dask.array\n", - " vsurf (time, yu_ocean, xu_ocean) float32 dask.array,\n", - " \n", - " Dimensions: (time: 7305, xu_ocean: 45, yu_ocean: 39)\n", - " Coordinates:\n", - " * time (time) object 0181-01-01 12:00:00 ... 0200-12-31 12:00:00\n", - " * xu_ocean (xu_ocean) float64 -109.8 -109.4 -109.0 ... -92.95 -92.55 -92.15\n", - " * yu_ocean (yu_ocean) float64 -19.84 -19.46 -19.09 ... -5.84 -5.442 -5.043\n", - " Data variables:\n", - " S_x (time, yu_ocean, xu_ocean) float32 dask.array\n", - " S_y (time, yu_ocean, xu_ocean) float32 dask.array\n", - " usurf (time, yu_ocean, xu_ocean) float32 dask.array\n", - " vsurf (time, yu_ocean, xu_ocean) float32 dask.array,\n", - " \n", - " Dimensions: (time: 7305, xu_ocean: 45, yu_ocean: 38)\n", - " Coordinates:\n", - " * time (time) object 0181-01-01 12:00:00 ... 0200-12-31 12:00:00\n", - " * xu_ocean (xu_ocean) float64 -47.75 -47.35 -46.95 ... -30.95 -30.55 -30.15\n", - " * yu_ocean (yu_ocean) float64 0.15 0.55 0.95 1.35 ... 13.62 14.01 14.4 14.78\n", - " Data variables:\n", - " S_x (time, yu_ocean, xu_ocean) float32 dask.array\n", - " S_y (time, yu_ocean, xu_ocean) float32 dask.array\n", - " usurf (time, yu_ocean, xu_ocean) float32 dask.array\n", - " vsurf (time, yu_ocean, xu_ocean) float32 dask.array]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "raw_datasets" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1327,22 +113,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from random import randint\n", "plot_dataset(data[['usurf', 'vsurf']].isel(xu_ocean=randint(0, len(data['xu_ocean'])),\n", @@ -1351,22 +124,9 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plot_dataset(data[['usurf', 'vsurf']].mean(dim='time_index'))\n", "_ = plt.suptitle('Average mean flow')" @@ -1374,32 +134,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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-       "Dimensions:     (latitude: 38, longitude: 45, time_index: 1095)\n",
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-       "    S_xpred     (time_index, latitude, longitude) float64 dask.array<chunksize=(274, 10, 23), meta=np.ndarray>\n",
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-       "    u_surf      (time_index, latitude, longitude) float64 dask.array<chunksize=(274, 10, 23), meta=np.ndarray>\n",
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" - ], - "text/plain": [ - "\n", - "array([1, 2, 3])\n", - "Coordinates:\n", - " * x (x) int64 1 2 5" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "xr.DataArray([1,2,3], coords=dict(x=[1,2,5]), dims=test_ds.dims)" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2854,433 +235,18 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "image/png": 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2V9XjVfX5qdo7quorVXX38PjBqfcuq6pdVXV/VZ0zVT+9qu4Z3ntPVdVQf35V3TTU76yqzVNjtlXVA8Nj22H71AAAAAAcFktZuXR9knMXqF/d3acNj48kSVWdmmRrklcPY95bVUcN21+T5OIkpwyPuX1elOSJ7n5lkquTXDXs69gklyd5XZIzklxeVcc8508IAAAAwBFz0HCpuz+RZO8S93d+khu7++nufjDJriRnVNUJSV7U3Xd0dyd5f5I3To25YXh+S5KzhlVN5yTZ0d17u/uJJDuycMgFAAAAwIwcyjWX3lpVnxtOm5tbUbQpycNT2+weapuG5/Pr+43p7n1JvpbkuEX2BQAAAMAKMTZcuibJK5KcluTRJL8y1GuBbXuR+tgx+6mqi6tqZ1Xt3LNnzyLTBgAAAOBw2jBmUHc/Nve8qt6X5PeHl7uTnDS16YlJHhnqJy5Qnx6zu6o2JDk6k9Pwdid5w7wxf3KA+Vyb5Nok2bJly4IBFAAAAGvL5ktvO+g2D1153jLMBNa3UeFSVZ3Q3Y8OL38kydyd5G5N8ltV9e4kL8vkwt2f7u5nquqpqjozyZ1JLkzy76fGbEtyR5ILkny8u7uqPprkl6dOuTs7yWVj5gvM3lL+4QcAAGD1OWi4VFUfymQF0fFVtTuTO7i9oapOy+Q0tYeS/HSSdPe9VXVzki8k2Zfkku5+ZtjVWzK589wLktw+PJLkuiQfqKpdmaxY2jrsa29VvSvJXcN27+zupV5YHAAAAIBlcNBwqbvfvED5ukW2vyLJFQvUdyZ5zQL1byR50wH2tT3J9oPNEQAAAIDZOJS7xQEAAACwzgmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMtmHWEwBYLzZfetuStnvoyvOO8EwAAAAOHyuXAABWoKraXlWPV9Xnp2rvqKqvVNXdw+MHp967rKp2VdX9VXXOVP30qrpneO89VVVD/flVddNQv7OqNk+N2VZVDwyPbcv0kQGAVUq4BACwMl2f5NwF6ld392nD4yNJUlWnJtma5NXDmPdW1VHD9tckuTjJKcNjbp8XJXmiu1+Z5OokVw37OjbJ5Ulel+SMJJdX1TGH/+MBAGuFcAkAYAXq7k8k2bvEzc9PcmN3P93dDybZleSMqjohyYu6+47u7iTvT/LGqTE3DM9vSXLWsKrpnCQ7untvdz+RZEcWDrkAAJIIlwAAVpu3VtXnhtPm5lYUbUry8NQ2u4fapuH5/Pp+Y7p7X5KvJTlukX0BACxIuAQAsHpck+QVSU5L8miSXxnqtcC2vUh97Jj9VNXFVbWzqnbu2bNnkWkDAGuZu8UBAKwS3f3Y3POqel+S3x9e7k5y0tSmJyZ5ZKifuEB9eszuqtqQ5OhMTsPbneQN88b8yQHmc22Sa5Nky5YtCwZQwOws9U61AIfKyiUAgFViuIbSnB9JMncnuVuTbB3uAHdyJhfu/nR3P5rkqao6c7ie0oVJPjw1Zu5OcBck+fhwXaaPJjm7qo4ZTrs7e6gBACzIyiUAgBWoqj6UyQqi46tqdyZ3cHtDVZ2WyWlqDyX56STp7nur6uYkX0iyL8kl3f3MsKu3ZHLnuRckuX14JMl1ST5QVbsyWbG0ddjX3qp6V5K7hu3e2d1LvbA4ALAOCZcAAFag7n7zAuXrFtn+iiRXLFDfmeQ1C9S/keRNB9jX9iTblzxZAGBdc1ocAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjbZj1BAAAAOBI2XzpbUva7qErzzvCM4G1y8olAAAAAEazcglghVnK0TVH1gAAgJVCuAQckqUuMwYAAGBtclocAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMNpBw6Wq2l5Vj1fV56dqx1bVjqp6YPh5zNR7l1XVrqq6v6rOmaqfXlX3DO+9p6pqqD+/qm4a6ndW1eapMduG3/FAVW07bJ8aAAAAgMNiKSuXrk9y7rzapUk+1t2nJPnY8DpVdWqSrUlePYx5b1UdNYy5JsnFSU4ZHnP7vCjJE939yiRXJ7lq2NexSS5P8rokZyS5fDrEAgAAAGD2DhoudfcnkuydVz4/yQ3D8xuSvHGqfmN3P93dDybZleSMqjohyYu6+47u7iTvnzdmbl+3JDlrWNV0TpId3b23u59IsiPPDrkAAAAAmKGx11x6aXc/miTDz5cM9U1JHp7abvdQ2zQ8n1/fb0x370vytSTHLbKvZ6mqi6tqZ1Xt3LNnz8iPBAAAAMBzteEw768WqPUi9bFj9i92X5vk2iTZsmXLgtsAAACsFZsvvW3WUwD4K2NXLj02nOqW4efjQ313kpOmtjsxySND/cQF6vuNqaoNSY7O5DS8A+0LAAAAgBVibLh0a5K5u7dtS/LhqfrW4Q5wJ2dy4e5PD6fOPVVVZw7XU7pw3pi5fV2Q5OPDdZk+muTsqjpmuJD32UMNAAAAgBXioKfFVdWHkrwhyfFVtTuTO7hdmeTmqrooyZeTvClJuvveqro5yReS7EtySXc/M+zqLZncee4FSW4fHklyXZIPVNWuTFYsbR32tbeq3pXkrmG7d3b3/AuLAwAAADBDBw2XuvvNB3jrrANsf0WSKxao70zymgXq38gQTi3w3vYk2w82RwAAAABmY+xpcQAAAAAgXAIAAABgPOESAMAKVFXbq+rxqvr8VO3YqtpRVQ8MP4+Zeu+yqtpVVfdX1TlT9dOr6p7hvfcMN1fJcAOWm4b6nVW1eWrMtuF3PFBVczdeAQBYkHAJAGBluj7JufNqlyb5WHefkuRjw+tU1amZ3BTl1cOY91bVUcOYa5JcnMldfE+Z2udFSZ7o7lcmuTrJVcO+js3kBi6vS3JGksunQywAgPmESwAAK1B3fyKTO+lOOz/JDcPzG5K8cap+Y3c/3d0PJtmV5IyqOiHJi7r7ju7uJO+fN2ZuX7ckOWtY1XROkh3dvbe7n0iyI88OuQAA/opwCQBg9Xhpdz+aJMPPlwz1TUkentpu91DbNDyfX99vTHfvS/K1JMctsi8AgAUJlwAAVr9aoNaL1MeO2f+XVl1cVTuraueePXuWNFEAYO0RLgEArB6PDae6Zfj5+FDfneSkqe1OTPLIUD9xgfp+Y6pqQ5KjMzkN70D7epbuvra7t3T3lo0bNx7CxwIAVjPhEgDA6nFrkrm7t21L8uGp+tbhDnAnZ3Lh7k8Pp849VVVnDtdTunDemLl9XZDk48N1mT6a5OyqOma4kPfZQw0AYEEbZj0BAACerao+lOQNSY6vqt2Z3MHtyiQ3V9VFSb6c5E1J0t33VtXNSb6QZF+SS7r7mWFXb8nkznMvSHL78EiS65J8oKp2ZbJiaeuwr71V9a4kdw3bvbO7519YHADgrwiXAABWoO5+8wHeOusA21+R5IoF6juTvGaB+jcyhFMLvLc9yfYlTxYAWNeESwCr0OZLb1vSdg9ded4RngkAALDeueYSAAAAAKMJlwAAAAAYzWlxAAAArHtLueyASw7AwqxcAgAAAGA04RIAAAAAowmXAAAAABjNNZeAA1rq7e4BAABYv6xcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEZztzgAAIAVwt16gdXIyiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYbcOsJwDAkbP50tsOus1DV563DDMBAADWKiuXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNHcLQ4AAACWwJ14YWFWLgEAAAAwmnAJAAAAgNGESwAAAACMdkjhUlU9VFX3VNXdVbVzqB1bVTuq6oHh5zFT219WVbuq6v6qOmeqfvqwn11V9Z6qqqH+/Kq6aajfWVWbD2W+AAAAABxeh2Pl0vd192ndvWV4fWmSj3X3KUk+NrxOVZ2aZGuSVyc5N8l7q+qoYcw1SS5OcsrwOHeoX5Tkie5+ZZKrk1x1GOYLAAAAwGFyJO4Wd36SNwzPb0jyJ0n+2VC/sbufTvJgVe1KckZVPZTkRd19R5JU1fuTvDHJ7cOYdwz7uiXJr1VVdXcfgXnDurGUu1wAAADAUhxquNRJ/rCqOsl/7O5rk7y0ux9Nku5+tKpeMmy7KcmnpsbuHmp/OTyfX58b8/Cwr31V9bUkxyX5s0OcNwAAwLJygA9Yqw41XHp9dz8yBEg7quqLi2xbC9R6kfpiY/bfcdXFmZxWl5e//OWLzxgAAACAw+aQrrnU3Y8MPx9P8rtJzkjyWFWdkCTDz8eHzXcnOWlq+IlJHhnqJy5Q329MVW1IcnSSvQvM49ru3tLdWzZu3HgoHwkAAACA52B0uFRV31FV3zn3PMnZST6f5NYk24bNtiX58PD81iRbhzvAnZzJhbs/PZxC91RVnTncJe7CeWPm9nVBko+73hIAsN65Yy8AsJIcymlxL03yu0MPsiHJb3X3H1TVXUlurqqLknw5yZuSpLvvraqbk3whyb4kl3T3M8O+3pLk+iQvyORC3rcP9euSfGC4+PfeTO42B8BhtJTrPzx05XnLMBPgOfq+7p6+DuXcHXuvrKpLh9f/bN4de1+W5I+q6lVDHzZ3x95PJflIJnfsvT1Td+ytqq2Z3LH3R5frgwEAq8vocKm7/zTJ312g/udJzjrAmCuSXLFAfWeS1yxQ/0aGcAoAgEW5Yy8AMBOHdM0lAABmYu6OvZ8ZbmySzLtjb5LpO/Y+PDV27s68m7LEO/Ymmbtj736q6uKq2llVO/fs2XNYPhgAsPoc6t3iAABYfivijr3dfW2Sa5Nky5YtVjUBwDpl5RIAwCqzUu7YCwCQCJcAAFYVd+wFAFYap8UBAKwu7tgLAKwowiUAgFXEHXsBgJVGuAQAAACHyeZLb1vSdg9ded4RngksH9dcAgAAAGA04RIAAAAAozktDgAA4BAt9VQogLXIyiUAAAAARrNyCdYYR804ElyYEgAAOBArlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjLZh1hMAAACA9WbzpbcddJuHrjxvGWYCh064BMBho0kCAID1R7gEAABwAEs5cAKw3rnmEgAAAACjCZcAAAAAGM1pcbCKWJYNAADASmPlEgAAAACjCZcAAAAAGM1pcQAsq6We3vnQlecd4ZkAAKxs+iZWCyuXAAAAABjNyiUAAGBdcrMUgMPDyiUAAAAARhMuAQAAADCa0+JgBbAkG55tKX8uXLwSAABmT7gEAAAAq5iDcsyacAkAAFhTrAoHWF6uuQQAAADAaFYuAbBqLfXItGXgAABw5AiX4AizLBsAAJg112XiSBIuAbDmaaYA1g4H7gBWHuESAAAA4JIDjCZcgpEcNQMAOLz0VwCrk3AJAOLUOQCApdI3MZ9wCRbgqBmwEEvFAcbRWwGsbcIlADjMHM0D1hPBEbAQB+XWl1URLlXVuUl+NclRSX6ju6+c8ZRYpTQ/wEqh4WKl03+hbwKWg4Nya8OKD5eq6qgkv57kB5LsTnJXVd3a3V+Y7cxYTpobYL06XH//acp4LvRfq5u+CVhrDuffa3qiI2PFh0tJzkiyq7v/NEmq6sYk5yfR3MyIhgVg9ZnF392at1VN/3WY6JsAVpaV+vfyau+bVkO4tCnJw1Ovdyd53fQGVXVxkouHl1+vqvuXaW6rzfFJ/mzWk1iHfO+z4XufDd/7bKzI772uOqK7/64juncO2n8lerAlWpF/PtcB3/vs+O5nw/c+G4ftez/CfdPhcsD+azWES7VArfd70X1tkmuXZzqrV1Xt7O4ts57HeuN7nw3f+2z43mfD984RcND+K9GDLYU/n7Phe58d3/1s+N5nw/f+Ld826wkswe4kJ029PjHJIzOaCwDAeqD/AgCWbDWES3clOaWqTq6qb0+yNcmtM54TAMBapv8CAJZsxZ8W1937quqtST6aya1wt3f3vTOe1mpl2fps+N5nw/c+G7732fC9c1jpvw4rfz5nw/c+O7772fC9z4bvfVDdzzp9HgAAAACWZDWcFgcAAADACiVcAgAAAGA04dI6VFW/WFVdVcfPei7rQVX9m6r6YlV9rqp+t6pePOs5rWVVdW5V3V9Vu6rq0lnPZz2oqpOq6o+r6r6qureq3jbrOa0nVXVUVf2Xqvr9Wc8FWJwebHnpwZaXHmz56cFmSw+2P+HSOlNVJyX5gSRfnvVc1pEdSV7T3X8nyX9LctmM57NmVdVRSX49yf+R5NQkb66qU2c7q3VhX5Jf6O7vTnJmkkt878vqbUnum/UkgMXpwWZCD7ZM9GAzowebLT3YFOHS+nN1kl9K4kruy6S7/7C79w0vP5XkxFnOZ407I8mu7v7T7v5fSW5Mcv6M57Tmdfej3f3Z4flTmfwju2m2s1ofqurEJOcl+Y1ZzwU4KD3YMtODLSs92AzowWZHD/ZswqV1pKr+UZKvdPd/nfVc1rF/kuT2WU9iDduU5OGp17vjH9hlVVWbk7w2yZ0znsp68e8y+Z/Vb854HsAi9GArgh7syNKDzZgebNn9u+jB9rNh1hPg8KqqP0ryvy3w1j9P8vYkZy/vjNaHxb737v7wsM0/z2Tp6geXc27rTC1Qc4R4mVTVC5P8dpKf6+4nZz2fta6qfijJ4939map6w4ynA+ueHmw29GArhh5shvRgy0sPtjDh0hrT3d+/UL2q/naSk5P816pKJsuCP1tVZ3T3/1jGKa5JB/re51TVtiQ/lOSs7vYP7ZGzO8lJU69PTPLIjOayrlTV8zJpaj7Y3b8z6/msE69P8o+q6geT/LUkL6qq3+zun5jxvGBd0oPNhh5sxdCDzYgebCb0YAsof8euT1X1UJIt3f1ns57LWldV5yZ5d5Lv7e49s57PWlZVGzK5YOdZSb6S5K4kP9bd9850YmtcTf5v6YYke7v752Y8nXVpOGr2i939QzOeCnAQerDlowdbPnqw2dCDzZ4e7FtccwmOvF9L8p1JdlTV3VX1H2Y9obVquGjnW5N8NJMLGt6sqVkWr0/yk0n+4fDf+N3DkRwAmCU92DLRg82MHowVw8olAAAAAEazcgkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgErEtV9aaquq+q/njWcwEAWOuq6vlV9UdVdXdV/eis5wMcXhtmPQGA5VRVlaSSXJTkZ7pbuAQAcARV1YYkr03yvO4+bcbTAY4AK5eAFaOqNlfV56de/2JVveMA2/4/q+oLVfW5qrpxqL2jqn5xapvPD/vcPKxSem+Szyb5l0n+9yT/oar+zRH9UAAAK1hVXVVVPzP1+h1V9QsLbHdCVX1iWHn0+ar6vw31r09tc0FVXT88v76q3j2sEn9fkt9Mctow/hVH+nMBy8vKJWC1ujTJyd39dFW9eAnb/80k/7i7fyZJqur7kvxid+88gnMEAFjpbkzy75K8d3j9f09y7gLb/ViSj3b3FVV1VJK/voR9vyrJ93f3M1X1hkx6rx865BkDK45wCVitPpfkg1X1e0l+bwnbf6m7P3VEZwQAsMp093+pqpdU1cuSbEzyRHd/eYFN70qyvaqel+T3uvvuJez+/9PdzxzG6QIrlNPigJVkX/b/e+mvLbLteUl+PcnpST4znMu/2Pj/3+GaJADAGnNLkguS/GgmK5mepbs/keQfJPlKkg9U1YVzb01tNr9303/BOiFcAlaSx5K8pKqOq6rnJ1lw2XRVfVuSk4aLcf9SkhcneWGSh5L8vWGbv5fk5GWYMwDAandjkq2ZBEy3LLRBVX1Xkse7+31JrsvQcyV5rKq+e+jPfmQ5JgusPE6LA1aM7v7LqnpnkjuTPJjkiwfY9Kgkv1lVR2dy57eru/urVfXbSS6sqrszWbr935Zh2gAAq1p331tV35nkK9396AE2e0OS/1dV/WWSryeZW7l0aZLfT/Jwks9ncsAPWGequw++FQAAAAAswGlxAAAAAIwmXAKWTVXdO9yG9rmM+fWqunve4x8fmRkCAKw9z6UHq6q/vUDvdeeRnSGw2jktDjhsquqhJP9nd//RVO2nhtr/vsR9bM7kekvP6+59R2CaAABrih4MmDUrl4B1parcyAAAYJnpwWBtEy4By6aqHqqq7x+en1FVO6vqyap6rKrePWz2ieHnV6vq61X1PVX1bVX1L6rqS1X1eFW9f7hT3Nx+Lxze+/Oq+pfzfs87quqWqvrNqnoyyU8Nv/uOqvpqVT1aVb9WVd8+tb+uqp+pqgeq6qmqeldVvWIY82RV3Ty9PQDASqYHA4404RIwK7+a5Fe7+0VJXpHk5qH+D4afL+7uF3b3HUl+anh8X5K/kcktbn8tSarq1CTvTfLjSU5IcnSSTfN+1/lJbkny4iQfTPJMkp9PcnyS70lyVpKfmTfm3CSnJzkzyS8luXb4HScleU2SN4//6AAAM6MHAw474RJwuP3ecDTqq1X11UyajoX8ZZJXVtXx3f317v7UIvv88STv7u4/7e6vJ7ksydZhefUFSf5Td3+yu/9Xkn+VZP7F5O7o7t/r7m92919092e6+1Pdva+7H0ryH5N877wxV3X3k919b5LPJ/nD4fd/LcntSV675G8EAODI04MBMyNcAg63N3b3i+ceefbRqDkXJXlVki9W1V1V9UOL7PNlSb409fpLSTYkeenw3sNzb3T3/0zy5/PGPzz9oqpeVVW/X1X/Y1im/cuZHEGb9tjU879Y4PULF5kvAMBy04MBMyNcAmaiux/o7jcneUmSq5LcUlXfkWcf8UqSR5J819TrlyfZl0mz8WiSE+feqKoXJDlu/q+b9/qaJF9McsqwJPztSWr8pwEAWB30YMCRIFwCZqKqfqKqNnb3N5N8dSg/k2RPkm9mcl7/nA8l+fmqOrmqXpjJUa6bhtvk3pLkh6vq7w8XePzXOXiT8p1Jnkzy9ar6W0necrg+FwDASqYHA44E4RIwK+cmubeqvp7JhSW3dvc3hiXVVyT5z8M1A85Msj3JBzK5i8mDSb6R5GeTZDgf/2eT3JjJEbSnkjye5OlFfvcvJvmxYdv3Jbnp8H88AIAVSQ8GHHbVvdDqR4DVaTiq9tVMlls/OOPpAACsC3owWN+sXAJWvar64ar668P1Av5tknuSPDTbWQEArG16MGCOcAlYC87P5IKTjyQ5JZPl3ZZlAgAcWXowIInT4gAAAAA4BFYuAQAAADDahllP4HA7/vjje/PmzbOeBgBwBH3mM5/5s+7eOOt58C16MABY2xbrv9ZcuLR58+bs3Llz1tMAAI6gqvrSrOfA/vRgALC2LdZ/OS0OAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAFagqjqpqv64qu6rqnur6m1D/R1V9ZWqunt4/ODUmMuqaldV3V9V50zVT6+qe4b33lNVNdSfX1U3DfU7q2rz1JhtVfXA8Ni2jB8dAFhl1tzd4gAA1oh9SX6huz9bVd+Z5DNVtWN47+ru/rfTG1fVqUm2Jnl1kpcl+aOqelV3P5PkmiQXJ/lUko8kOTfJ7UkuSvJEd7+yqrYmuSrJj1bVsUkuT7IlSQ+/+9bufuIIf2YAYBU66MolR80AAJZfdz/a3Z8dnj+V5L4kmxYZcn6SG7v76e5+MMmuJGdU1QlJXtTdd3R3J3l/kjdOjblheH5LkrOG/uycJDu6e+8QKO3IJJACAHiWpZwWN3fU7LuTnJnkkuHIWDI5anba8PhI8qyjZucmeW9VHTVsP3fU7JThMdek/NVRsyRXZ3LULFNHzV6X5Iwkl1fVMYfygQEAVpvhwNtrk9w5lN5aVZ+rqu1TvdGmJA9PDds91DYNz+fX9xvT3fuSfC3JcYvsa/68Lq6qnVW1c8+ePeM/IACwqh00XHLUDABgdqrqhUl+O8nPdfeTmRyse0WS05I8muRX5jZdYHgvUh875luF7mu7e0t3b9m4ceNiHwMAWMOe0wW9HTUDAFg+VfW8TIKlD3b37yRJdz/W3c909zeTvC+T1d3JpE86aWr4iUkeGeonLlDfb0xVbUhydJK9i+wLAOBZlnxB7/lHzarqmiTvyuQo1rsyOWr2TzKjo2ZJrk2SLVu2POt9YO3YfOltS9ruoSvPO8IzATiyhlXc1yW5r7vfPVU/obsfHV7+SJLPD89vTfJbVfXuTC7ofUqST3f3M1X1VFWdmckBwguT/PupMduS3JHkgiQf7+6uqo8m+eWpg4dnJ7nsSH1WYOXTgwGLWVK4dKCjZlPvvy/J7w8vD+Wo2e4Fjpq9Yd6YP1nKnAEAVrnXJ/nJJPdU1d1D7e1J3lxVp2VywO2hJD+dJN19b1XdnOQLmVwz85LhTnFJ8pYk1yd5QSZ3ibt9qF+X5ANVtSuT3mvrsK+9VfWuJHcN272zu/cekU8JAKx6Bw2XHDUDAFh+3f3JLLyK+yOLjLkiyRUL1Hcmec0C9W8kedMB9rU9yfalzhcAWL+WsnLJUTMAAAAAFnTQcMlRMwAAAAAO5DndLQ4AAAAApgmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BACwAlXVSVX1x1V1X1XdW1VvG+rHVtWOqnpg+HnM1JjLqmpXVd1fVedM1U+vqnuG995TVTXUn19VNw31O6tq89SYbcPveKCqti3jRwcAVhnhEgDAyrQvyS9093cnOTPJJVV1apJLk3ysu09J8rHhdYb3tiZ5dZJzk7y3qo4a9nVNkouTnDI8zh3qFyV5ortfmeTqJFcN+zo2yeVJXpfkjCSXT4dYAADTDhouOWoGALD8uvvR7v7s8PypJPcl2ZTk/CQ3DJvdkOSNw/Pzk9zY3U9394NJdiU5o6pOSPKi7r6juzvJ++eNmdvXLUnOGvqzc5Ls6O693f1Ekh35ViAFALCfpaxcctQMAGCGhgNvr01yZ5KXdvejySSASvKSYbNNSR6eGrZ7qG0ans+v7zemu/cl+VqS4xbZFwDAsxw0XHLUDABgdqrqhUl+O8nPdfeTi226QK0XqY8dMz23i6tqZ1Xt3LNnzyJTAwDWsud0zaWVetRMYwMArEVV9bxMgqUPdvfvDOXHhoN2GX4+PtR3JzlpaviJSR4Z6icuUN9vTFVtSHJ0kr2L7Gs/3X1td2/p7i0bN24c+zEBgFVuyeHSSj5qprEBANaaYRX3dUnu6+53T711a5K561BuS/LhqfrW4VqWJ2dyCYJPDwcBn6qqM4d9XjhvzNy+Lkjy8WGF+UeTnF1VxwyXJDh7qAEAPMuGpWy02FGz7n70MB41273AUbM3zBvzJ0v6ZAAAq9vrk/xkknuq6u6h9vYkVya5uaouSvLlJG9Kku6+t6puTvKFTK6ZeUl3PzOMe0uS65O8IMntwyOZhFcfqKpdmfReW4d97a2qdyW5a9jund299wh9TgBglTtouLSEo2ZX5tlHzX6rqt6d5GX51lGzZ6rqqao6M5PT6i5M8u/n7euOTB01q6qPJvnlqYt4n53kstGfFgBglejuT2bhVdxJctYBxlyR5IoF6juTvGaB+jcyhFMLvLc9yfalzhcAWL+WsnLJUTMAAAAAFnTQcMlRMwAAAAAO5DndLQ4AAAAApgmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAgBWoqrZX1eNV9fmp2juq6itVdffw+MGp9y6rql1VdX9VnTNVP72q7hnee09V1VB/flXdNNTvrKrNU2O2VdUDw2PbMn1kAGCVOmi4pLEBAJiJ65Ocu0D96u4+bXh8JEmq6tQkW5O8ehjz3qo6atj+miQXJzlleMzt86IkT3T3K5NcneSqYV/HJrk8yeuSnJHk8qo65vB/PABgrVjKyqXro7EBAFhW3f2JJHuXuPn5SW7s7qe7+8Eku5KcUVUnJHlRd9/R3Z3k/UneODXmhuH5LUnOGg7+nZNkR3fv7e4nkuzIwr0gAECSJYRLGhsAgBXlrVX1uWF1+dyBt01JHp7aZvdQ2zQ8n1/fb0x370vytSTHLbKvZ6mqi6tqZ1Xt3LNnz6F9KgBg1dpwCGPfWlUXJtmZ5BeGAGhTkk9NbTPXjPxlltjYVNWoxiaTVVF5+ctffggfCVgrNl9620G3eejK85ZhJgCH1TVJ3pWkh5+/kuSfJKkFtu1F6hk5Zv9i97VJrk2SLVu2LLgNALD2jb2g9zVJXpHktCSPZtLYJDNsbLp7S3dv2bhx4yLTBgBYvbr7se5+pru/meR9mVw6IJkchDtpatMTkzwy1E9coL7fmKrakOToTFarH2hfAAALGhUuaWwAAJbfcKmBOT+SZO6GK7cm2TrcKOXkTK5v+enufjTJU1V15nDZgQuTfHhqzNwNUy5I8vHh8gUfTXJ2VR0znHZ39lADAFjQqHBJYwMAcGRV1YeS3JHkb1bV7qq6KMn/Ndx993NJvi/JzydJd9+b5OYkX0jyB0ku6e5nhl29JclvZHItzP+e5Pahfl2S46pqV5J/muTSYV97Mznl7q7h8c6hBgCwoINec2lobN6Q5Piq2p3JHdzeUFWnZXKa2kNJfjqZNDZVNdfY7MuzG5vrk7wgk6ZmurH5wNDY7M3kbnPp7r1VNdfYJBobAGAd6e43L1C+bpHtr0hyxQL1nUles0D9G0nedIB9bU+yfcmTBQDWtYOGSxobAAAAAA5k7AW9AQAAAEC4BAAAAMB4wiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgtA2zngAAAABrw+ZLbzvoNg9ded4yzARYTlYuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAWIGqantVPV5Vn5+qHVtVO6rqgeHnMVPvXVZVu6rq/qo6Z6p+elXdM7z3nqqqof78qrppqN9ZVZunxmwbfscDVbVtmT4yALBKHTRc0tgAAMzE9UnOnVe7NMnHuvuUJB8bXqeqTk2yNcmrhzHvraqjhjHXJLk4ySnDY26fFyV5ortfmeTqJFcN+zo2yeVJXpfkjCSXT/d6AADzLWXl0vXR2AAALKvu/kSSvfPK5ye5YXh+Q5I3TtVv7O6nu/vBJLuSnFFVJyR5UXff0d2d5P3zxszt65YkZw0H/85JsqO793b3E0l25Nm9IADAXzlouKSxAQBYMV7a3Y8myfDzJUN9U5KHp7bbPdQ2Dc/n1/cb0937knwtyXGL7AsAYEFjr7m0ohqbqrq4qnZW1c49e/aM/EgAAKtWLVDrRepjx+z/S/VgAEAO/wW9Z9LYdPe13b2lu7ds3LhxSRMFAFiFHhtWhGf4+fhQ353kpKntTkzyyFA/cYH6fmOqakOSozNZrX6gfT2LHgwASMaHSyuqsQEAWCduTTJ3k5NtST48Vd863Cjl5Eyub/npYYX5U1V15nDZgQvnjZnb1wVJPj5cvuCjSc6uqmOG612ePdQAABY0NlzS2AAAHEFV9aEkdyT5m1W1u6ouSnJlkh+oqgeS/MDwOt19b5Kbk3whyR8kuaS7nxl29ZYkv5HJtTD/e5Lbh/p1SY6rql1J/mmGG7R0994k70py1/B451ADAFjQhoNtMDQ2b0hyfFXtzuQOblcmuXlocr6c5E3JpLGpqrnGZl+e3dhcn+QFmTQ1043NB4bGZm8md5tLd++tqrnGJtHYAADrSHe/+QBvnXWA7a9IcsUC9Z1JXrNA/RsZergF3tueZPuSJwsArGsHDZc0NgAAAAAcyOG+oDcAAAAA64hwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIy2YdYTAAAAYHY2X3rbrKcArHJWLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjuVscsGK4UwkAAMDqY+USAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABjtkMKlqnqoqu6pqruraudQO7aqdlTVA8PPY6a2v6yqdlXV/VV1zlT99GE/u6rqPVVVQ/35VXXTUL+zqjYfynwBANYCPRgAsJIcjpVL39fdp3X3luH1pUk+1t2nJPnY8DpVdWqSrUleneTcJO+tqqOGMdckuTjJKcPj3KF+UZInuvuVSa5OctVhmC8AwFqgBwMAVoQjcVrc+UluGJ7fkOSNU/Ubu/vp7n4wya4kZ1TVCUle1N13dHcnef+8MXP7uiXJWXNH1AAA2I8eDACYiUMNlzrJH1bVZ6rq4qH20u5+NEmGny8Z6puSPDw1dvdQ2zQ8n1/fb0x370vytSTHHeKcAQBWuxXRg1XVxVW1s6p27tmz57B8MABg9dlwiONf392PVNVLkuyoqi8usu1CR7t6kfpiY/bf8aSpujhJXv7yly8+YwCA1W9F9GDdfW2Sa5Nky5Ytz3ofAFgfDmnlUnc/Mvx8PMnvJjkjyWPDMusMPx8fNt+d5KSp4ScmeWSon7hAfb8xVbUhydFJ9i4wj2u7e0t3b9m4ceOhfCQAgBVvpfRgAADJIYRLVfUdVfWdc8+TnJ3k80luTbJt2Gxbkg8Pz29NsnW4+8jJmVw08tPDsu2nqurM4Vz+C+eNmdvXBUk+PlwTAABgXdKDAQArzaGcFvfSJL87XNtxQ5Lf6u4/qKq7ktxcVRcl+XKSNyVJd99bVTcn+UKSfUku6e5nhn29Jcn1SV6Q5PbhkSTXJflAVe3K5GjZ1kOYLwDAWqAHAwBWlNHhUnf/aZK/u0D9z5OcdYAxVyS5YoH6ziSvWaD+jQyNEQAAejAAYOU51LvFAQAAALCOCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYbcOsJwAwK5svvW1J2z105XlHeCYAAIffUnsdgENl5RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEZzQW9gWbigJAAAydL6QjdUgdXFyiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYbcOsJwAAAMBzs/nS22Y9BYC/YuUSAAAAAKMJlwAAAAAYTbgEAAAAwGiuuQQcEuf7AwAArG/CJYCDWEqA9tCV5y3DTAAAAFYep8UBAAAAMJqVSwAAACuESw5MLPV7sHocVgYrlwAAAAAYzcol4IAcOQMAAOBghEsAAADLwIE7YK0SLgEcBu4oBwAArFfCJViHHDUDADi89Fez4QAfrAyrIlyqqnOT/GqSo5L8RndfOeMpATxn7noCrCb6LwBgqVZ8uFRVRyX59SQ/kGR3kruq6tbu/sJsZwYrk6NmABwq/Rd8i95q9XOAD468FR8uJTkjya7u/tMkqaobk5yfRHPDmqFpYZrl3cAKoP9ixdI3caQcrv+29GmsR6shXNqU5OGp17uTvG5Gc+E58A8/HDn+fE1o3uCI0X8tM3+vw9qxHv4868GYbzWES7VArffboOriJBcPL79eVfcf8VmtTscn+bNZT2Id8r3Phu99Npb1e6+rlus3rXjr8b/375r1BNa4g/ZfiR5sidbjn8+VwPc+O7772dCDzcZ6++/9gP3XagiXdic5aer1iUkemd6gu69Ncu1yTmo1qqqd3b1l1vNYb3zvs+F7nw3f+2z43jkCDtp/JXqwpfDnczZ877Pju58N3/ts+N6/5dtmPYEluCvJKVV1clV9e5KtSW6d8ZwAANYy/RcAsGQrfuVSd++rqrcm+Wgmt8Ld3t33znhaAABrlv4LAHguVny4lCTd/ZEkH5n1PNYAy9Znw/c+G7732fC9z4bvncNO/3XY+PM5G7732fHdz4bvfTZ874Pqfta1GQEAAABgSVbDNZcAAAAAWKGES+tQVf1iVXVVHT/ruawHVfVvquqLVfW5qvrdqnrxrOe0llXVuVV1f1XtqqpLZz2f9aCqTqqqP66q+6rq3qp626zntJ5U1VFV9V+q6vdnPRdgcXqw5aUHW156sOWnB5stPdj+hEvrTFWdlOQHknx51nNZR3YkeU13/50k/y3JZTOez5pVVUcl+fUk/0eSU5O8uapOne2s1oV9SX6hu787yZlJLvG9L6u3Jblv1pMAFqcHmwk92DLRg82MHmy29GBThEvrz9VJfimJi20tk+7+w+7eN7z8VJITZzmfNe6MJLu6+0+7+38luTHJ+TOe05rX3Y9292eH509l8o/sptnOan2oqhOTnJfkN2Y9F+Cg9GDLTA+2rPRgM6AHmx092LMJl9aRqvpHSb7S3f911nNZx/5JkttnPYk1bFOSh6de745/YJdVVW1O8tokd854KuvFv8vkf1a/OeN5AIvQg60IerAjSw82Y3qwZffvogfbz4ZZT4DDq6r+KMn/tsBb/zzJ25OcvbwzWh8W+967+8PDNv88k6WrH1zOua0ztUDNEeJlUlUvTPLbSX6uu5+c9XzWuqr6oSSPd/dnquoNM54OrHt6sNnQg60YerAZ0oMtLz3YwoRLa0x3f/9C9ar620lOTvJfqyqZLAv+bFWd0d3/YxmnuCYd6HufU1XbkvxQkrO62z+0R87uJCdNvT4xySMzmsu6UlXPy6Sp+WB3/86s57NOvD7JP6qqH0zy15K8qKp+s7t/YsbzgnVJDzYberAVQw82I3qwmdCDLaD8Hbs+VdVDSbZ095/Nei5rXVWdm+TdSb63u/fMej5rWVVtyOSCnWcl+UqSu5L8WHffO9OJrXE1+b+lG5Ls7e6fm/F01qXhqNkvdvcPzXgqwEHowZaPHmz56MFmQw82e3qwb3HNJTjyfi3JdybZUVV3V9V/mPWE1qrhop1vTfLRTC5oeLOmZlm8PslPJvmHw3/jdw9HcgBglvRgy0QPNjN6MFYMK5cAAAAAGM3KJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXgFWhqv55Vd1bVZ+rqrur6nWznhMAwFqnBwOWYsOsJwBwMFX1PUl+KMnf6+6nq+r4JN8+42kBAKxpejBgqaxcAlaDE5L8WXc/nSTd/Wfd/cj8jarq6Kq6v6r+5vD6Q1X1/1jmuQIArBVL7cHOqqrfnXr9A1X1O8s4T2DGhEvAavCHSU6qqv9WVe+tqu9daKPu/lqStya5vqq2Jjmmu9+3nBMFAFhDltSDJfl4ku+uqo3D63+c5P+9LDMEVgThErDidffXk5ye5OIke5LcVFU/dYBtdyS5J8mvJ/k/l2uOAABrzVJ7sO7uJB9I8hNV9eIk35Pk9uWbKTBrNfl7AGD1qKoLkmzr7h9e4L1vS/L/TXJykh/s7s8t9/wAANaig/RgL0vyn5L8RpKTu/uXlnt+wOxYuQSseFX1N6vqlKnSaUm+dIDNfz7JfUnenGR7VT3vCE8PAGBNei492HAtpkeS/Isk1x/xyQErirvFAavBC5P8+2GZ9b4kuzJZnr2fqnpVJqfCndHdT1XVJzJpcC5fxrkCAKwVS+rBpnwwycbu/sIyzA1YQZwWBwAAwCGrql9L8l+6+7pZzwVYXk6LA5ZNVd1bVW+Y9TwAANaT5ejBquozSf5Okt88kr8HWJmES8BhU1UPVdX3z6v9VFV9Mkm6+9Xd/ScH2cfmquqqWvS03ar63aq6e97jnEP+EAAAq8xK6MG6+/Tu/gfd/fQhfyBg1XHNJWBV6u4fGTOuqjZ0977DPR8AgPVADwYsxMolYNlMH1WrqjOqamdVPVlVj1XVu4fNPjH8/GpVfb2qvqeqvq2q/kVVfamqHq+q91fV0VP7vXB478+r6l/O+z3vqKpbquo3q+rJJD81/O47quqrVfVoVf1aVX371P66qn6mqh6oqqeq6l1V9YphzJNVdfP09gAAK5keDDjShEvArPxqkl/t7hcleUWSm4f6Pxh+vri7X9jddyT5qeHxfUn+RiZ3Lvm1JKmqU5O8N8mPJzkhydFJNs37XecnuSXJizO5i8kzSX4+yfFJvifJWUl+Zt6Yc5OcnuTMJL+U5Nrhd5yU5DVJ3jz+owMAzIweDDjshEvA4fZ7w9Gor1bVVzNpOhbyl0leWVXHd/fXu/tTi+zzx5O8u7v/tLu/nuSyJFuHawJckOQ/dfcnu/t/JflXSebfBvOO7v697v5md/9Fd3+muz/V3fu6+6Ek/zHJ984bc1V3P9nd9yb5fJI/HH7/15LcnuS1S/5GAACOPD0YMDPCJeBwe2N3v3jukWcfjZpzUZJXJfliVd1VVT+0yD5fluRLU6+/lMk14146vPfw3Bvd/T+T/Pm88Q9Pv6iqV1XV71fV/xiWaf9yJkfQpj029fwvFnj9wkXmCwCw3PRgwMwIl4CZ6O4HuvvNSV6S5Kokt1TVd+TZR7yS5JEk3zX1+uVJ9mXSbDya5MS5N6rqBUmOm//r5r2+JskXk5wyLAl/e5Ia/2kAAFYHPRhwJAiXgJmoqp+oqo3d/c0kXx3KzyTZk+SbmZzXP+dDSX6+qk6uqhdmcpTrpuGOI7ck+eGq+vvDBR7/dQ7epHxnkieTfL2q/laStxyuzwUAsJLpwYAjQbgEzMq5Se6tqq9ncmHJrd39jWFJ9RVJ/vNwzYAzk2xP8oFM7mLyYJJvJPnZJBnOx//ZJDdmcgTtqSSPJ3l6kd/9i0l+bNj2fUluOvwfDwBgRdKDAYdddS+0+hFgdRqOqn01k+XWD854OgAA64IeDNY3K5eAVa+qfriq/vpwvYB/m+SeJA/NdlYAAGubHgyYI1wC1oLzM7ng5CNJTslkebdlmQAAR5YeDEjitDgAAAAADoGVSwAAAACMJlwCAAAAYLQNs57A4Xb88cf35s2bZz0NAOAI+sxnPvNn3b1x1vPgW/RgALC2LdZ/rblwafPmzdm5c+espwEAHEFV9aVZz4H96cEAYG1brP9yWhwAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjbZj1BACei82X3rak7R668rwjPBMAgPVDDwYsxsolAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAMAKVFUnVdUfV9V9VXVvVb1tqL+jqr5SVXcPjx+cGnNZVe2qqvur6pyp+ulVdc/w3nuqqob686vqpqF+Z1VtnhqzraoeGB7blvGjAwCrzEHDJY0NAMBM7EvyC9393UnOTHJJVZ06vHd1d582PD6SJMN7W5O8Osm5Sd5bVUcN21+T5OIkpwyPc4f6RUme6O5XJrk6yVXDvo5NcnmS1yU5I8nlVXXMEf20AMCqtZSVSxobAIBl1t2Pdvdnh+dPJbkvyaZFhpyf5Mbufrq7H0yyK8kZVXVCkhd19x3d3Unen+SNU2NuGJ7fkuSs4eDfOUl2dPfe7n4iyY58q28DANjPQcMljQ0AwGwNq7pfm+TOofTWqvpcVW2fOvC2KcnDU8N2D7VNw/P59f3GdPe+JF9Lctwi+wIAeJbndM0ljQ0AwPKqqhcm+e0kP9fdT2ayEvwVSU5L8miSX5nbdIHhvUh97JjpuV1cVTuraueePXsW+xgAwBq25HBJYwMAsLyq6nmZ9F8f7O7fSZLufqy7n+nubyZ5XyaXDkgmB+FOmhp+YpJHhvqJC9T3G1NVG5IcnWTvIvvaT3df291bunvLxo0bD+WjAgCr2JLCJY0NAMDyGi4RcF2S+7r73VP1E6Y2+5Eknx+e35pk63CjlJMzub7lp7v70SRPVdWZwz4vTPLhqTFzN0y5IMnHh8sXfDTJ2VV1zLA6/eyhBgDwLEu5W5zGBgBg+b0+yU8m+Yfz7s77fw133/1cku9L8vNJ0t33Jrk5yReS/EGSS7r7mWFfb0nyG5lcC/O/J7l9qF+X5Liq2pXknya5dNjX3iTvSnLX8HjnUAMAeJYNS9hmrrG5p6ruHmpvT/Lmqjotk9PUHkry08mksamqucZmX57d2Fyf5AWZNDXTjc0HhsZmbyZ3m0t3762qucYm0dgAAOtEd38yC18i4COLjLkiyRUL1Hcmec0C9W8kedMB9rU9yfalzhcAWL8OGi5pbAAAAAA4kOd0tzgAAAAAmCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAK1BVnVRVf1xV91XVvVX1tqF+bFXtqKoHhp/HTI25rKp2VdX9VXXOVP30qrpneO89VVVD/flVddNQv7OqNk+N2Tb8jgeqatsyfnQAYJU5aLiksQEAmIl9SX6hu787yZlJLqmqU5NcmuRj3X1Kko8NrzO8tzXJq5Ocm+S9VXXUsK9rklyc5JThce5QvyjJE939yiRXJ7lq2NexSS5P8rokZyS5fLrXAwCYtpSVSxobAIBl1t2Pdvdnh+dPJbkvyaYk5ye5YdjshiRvHJ6fn+TG7n66ux9MsivJGVV1QpIXdfcd3d1J3j9vzNy+bkly1nDw75wkO7p7b3c/kWRHvtW3AQDs56DhksYGAGC2hlXdr01yZ5KXdvejyaRPS/KSYbNNSR6eGrZ7qG0ans+v7zemu/cl+VqS4xbZ1/x5XVxVO6tq5549ew7hEwIAq9lzuuaSxgYAYHlV1QuT/HaSn+vuJxfbdIFaL1IfO+Zbhe5ru3tLd2/ZuHHjIlMDANayJYdLGhsAgOVVVc/LpP/6YHf/zlB+bFgRnuHn40N9d5KTpoafmOSRoX7iAvX9xlTVhiRHJ9m7yL4AAJ5lSeGSxgYAYHkNlwi4Lsl93f3uqbduTTJ3k5NtST48Vd863Cjl5Eyub/npYYX5U1V15rDPC+eNmdvXBUk+Ply+4KNJzq6qY4brXZ491AAAnmUpd4vT2AAALL/XJ/nJJP+wqu4eHj+Y5MokP1BVDyT5geF1uvveJDcn+UKSP0hySXc/M+zrLUl+I5NrYf73JLcP9euSHFdVu5L80ww3aOnuvUneleSu4fHOoQYA8CwblrDNXGNzT1XdPdTenkkjc3NVXZTky0nelEwam6qaa2z25dmNzfVJXpBJUzPd2HxgaGz2ZnK3uXT33qqaa2wSjQ0AsE509yez8CUCkuSsA4y5IskVC9R3JnnNAvVvZOjhFnhve5LtS50vALB+HTRc0tgAAAAAcCDP6W5xAAAAADBNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgDAClRV26vq8ar6/FTtHVX1laq6e3j84NR7l1XVrqq6v6rOmaqfXlX3DO+9p6pqqD+/qm4a6ndW1eapMduq6oHhsW2ZPjIAsEodNFzS2AAAzMT1Sc5doH51d582PD6SJFV1apKtSV49jHlvVR01bH9NkouTnDI85vZ5UZInuvuVSa5OctWwr2OTXJ7kdUnOSHJ5VR1z+D8eALBWLGXl0vXR2AAALKvu/kSSvUvc/PwkN3b30939YJJdSc6oqhOSvKi77+juTvL+JG+cGnPD8PyWJGcNB//OSbKju/d29xNJdmThXhAAIMkSwiWNDQDAivLWqvrcsLp87sDbpiQPT22ze6htGp7Pr+83prv3JflakuMW2RcAwIIO5ZpLK6axqaqLq2pnVe3cs2fPIXwkAIAV7Zokr0hyWpJHk/zKUK8Ftu1F6mPH7EcPBgAk48OlFdXYdPe13b2lu7ds3LhxkWkDAKxe3f1Ydz/T3d9M8r5MLh2QTA7CnTS16YlJHhnqJy5Q329MVW1IcnQmq9UPtK+F5qMHAwDGhUsrrbEBAFgPhksNzPmRJHM3XLk1ydbhRiknZ3J9y09396NJnqqqM4fLDlyY5MNTY+ZumHJBko8Ply/4aJKzq+qYYXX62UMNAGBBG8YMqqoThmYleXZj81tV9e4kL8u3GptnquqpqjozyZ2ZNDb/fmrMtiR3ZKqxqaqPJvnlqVPuzk5y2Zj5AuvP5ktvO+g2D1153jLMBGCcqvpQkjckOb6qdmdyo5M3VNVpmazmfijJTydJd99bVTcn+UKSfUku6e5nhl29JZMbtLwgye3DI0muS/KBqtqVyYG9rcO+9lbVu5LcNWz3zu5e6vU3AYB16KDhksYGAGD5dfebFyhft8j2VyS5YoH6ziSvWaD+jSRvOsC+tifZvuTJAgDr2kHDJY0NAAAAAAdyKHeLAwAAAGCdEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMtmHWEwAAAGBt2HzpbQfd5qErz1uGmQDLycolAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRDhouVdX2qnq8qj4/VTu2qnZU1QPDz2Om3rusqnZV1f1Vdc5U/fSqumd47z1VVUP9+VV101C/s6o2T43ZNvyOB6pq22H71AAAK5weDABYLZaycun6JOfOq12a5GPdfUqSjw2vU1WnJtma5NXDmPdW1VHDmGuSXJzklOExt8+LkjzR3a9McnWSq4Z9HZvk8iSvS3JGksunGygAgDXu+ujBAIBV4KDhUnd/IsneeeXzk9wwPL8hyRun6jd299Pd/WCSXUnOqKoTkryou+/o7k7y/nlj5vZ1S5KzhiNq5yTZ0d17u/uJJDvy7AYLAGBN0oMBAKvF2GsuvbS7H02S4edLhvqmJA9Pbbd7qG0ans+v7zemu/cl+VqS4xbZFwDAerWierCquriqdlbVzj179hzCxwIAVrPDfUHvWqDWi9THjtn/l2psAID1bSY9WHdf291bunvLxo0blzRRAGDtGRsuPTYss87w8/GhvjvJSVPbnZjkkaF+4gL1/cZU1YYkR2eyBPxA+3oWjQ0AsE6sqB4MACAZHy7dmmTuziHbknx4qr51uPvIyZlcNPLTw7Ltp6rqzOFc/gvnjZnb1wVJPj5cE+CjSc6uqmOGi0iePdQAANYrPRgAsOJsONgGVfWhJG9IcnxV7c7k7iFXJrm5qi5K8uUkb0qS7r63qm5O8oUk+5Jc0t3PDLt6SyZ3PXlBktuHR5Jcl+QDVbUrk6NlW4d97a2qdyW5a9jund09/6KWAABrkh4MAFgtDhoudfebD/DWWQfY/ookVyxQ35nkNQvUv5GhMVrgve1Jth9sjgAAa40eDABYLQ73Bb0BAAAAWEeESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGC0DbOeAAAAALOz+dLbZj0FYJWzcgkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYzd3igBXDnUoAAABWHyuXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMdkjhUlU9VFX3VNXdVbVzqB1bVTuq6oHh5zFT219WVbuq6v6qOmeqfvqwn11V9Z6qqqH+/Kq6aajfWVWbD2W+AABrgR4MAFhJDsfKpe/r7tO6e8vw+tIkH+vuU5J8bHidqjo1ydYkr05ybpL3VtVRw5hrklyc5JThce5QvyjJE939yiRXJ7nqMMwXAGAt0IMBACvCkTgt7vwkNwzPb0jyxqn6jd39dHc/mGRXkjOq6oQkL+ruO7q7k7x/3pi5fd2S5Ky5I2oAAOxHDwYAzMShhkud5A+r6jNVdfFQe2l3P5okw8+XDPVNSR6eGrt7qG0ans+v7zemu/cl+VqS4w5xzgAAq50eDABYMTYc4vjXd/cjVfWSJDuq6ouLbLvQ0a5epL7YmP13PGmqLk6Sl7/85YvPGABg9dODAQArxiGtXOruR4afjyf53SRnJHlsWGad4efjw+a7k5w0NfzEJI8M9RMXqO83pqo2JDk6yd4F5nFtd2/p7i0bN248lI8EALDi6cEAgJVkdLhUVd9RVd859zzJ2Uk+n+TWJNuGzbYl+fDw/NYkW4e7j5ycyUUjPz0s236qqs4czuW/cN6YuX1dkOTjwzUBAADWJT0YALDSHMppcS9N8rvDtR03JPmt7v6Dqroryc1VdVGSLyd5U5J0971VdXOSLyTZl+SS7n5m2Ndbklyf5AVJbh8eSXJdkg9U1a5MjpZtPYT5AgCsBXowAGBFGR0udfefJvm7C9T/PMlZBxhzRZIrFqjvTPKaBerfyNAYAQCgBwMAVp5DvVscAAAAAOuYcAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRNsx6AgAAABx+my+9bdZTANYJK5cAAAAAGE24BAAAAMBoTosD1q2lLhV/6MrzjvBMAAAAVi8rlwAAAAAYzcolYFm4oCQAAMDaZOUSAAAAAKNZuQQAAMCyWcqKdte8hNXFyiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNHeLAwAAWGWWcsc1gOVi5RIAAAAAowmXAAAAABjNaXHAIbEkGwAAYH0TLgEcxFICtIeuPG8ZZgIAALDyCJcAAABWCKvCgdVIuAQAAMCKstSQzepxWBlc0BsAAACA0axcAg7IsmwAgMNHbwWsVcIlgMPARb8BAJafHgxWhlURLlXVuUl+NclRSX6ju6+c8ZRgVXPUDICD0X/Bc6O/AtazFR8uVdVRSX49yQ8k2Z3krqq6tbu/MNuZwcqksVm5XJgSWC30X/AteqvVTw8GR96KD5eSnJFkV3f/aZJU1Y1Jzk+iuWHN0LQw7XD+96BJAkbSf7Fi6Zs4Ug7Xf1v6L9aj1RAubUry8NTr3UleN71BVV2c5OLh5der6v5lmttqc3ySP5v1JNYh3/ts+N6T1FXL/it977OxHr/375r1BNa4g/ZfiR5sidbjn8+VwPc+O+v+u59B/5X43mdlvX3vB+y/VkO4VAvUer8X3dcmuXZ5prN6VdXO7t4y63msN7732fC9z4bvfTZ87xwBB+2/Ej3YUvjzORu+99nx3c+G7302fO/f8m2znsAS7E5y0tTrE5M8MqO5AACsB/ovAGDJVkO4dFeSU6rq5Kr69iRbk9w64zkBAKxl+i8AYMlW/Glx3b2vqt6a5KOZ3Ap3e3ffO+NprVaWrc+G7302fO+z4XufDd87h5X+67Dy53M2fO+z47ufDd/7bPjeB9X9rNPnAQAAAGBJVsNpcQAAAACsUMIlAAAAAEYTLq1DVfWLVdVVdfys57IeVNW/qaovVtXnqup3q+rFs57TWlZV51bV/VW1q6ounfV81oOqOqmq/riq7quqe6vqbbOe03pSVUdV1X+pqt+f9VyAxenBlpcebHnpwZafHmy29GD7Ey6tM1V1UpIfSPLlWc9lHfn/t3f3wZZW9Z3ovz9po05QBGkd0k0CE4kjkkSlC3G8FY1EIJERp0rvYGJsJ8xQ5eBc9cabCzFzudHC0Zo76vg6IZGALwkwRkeSDIMdHJLKFEEaRRGV0FdROhBpbeRlEkgaf/eP/fRl9+nTpw+P3Wefl8+natfez9rPevbau2j619+19tpbkpzQ3T+V5C+TnD/j8axaVXVIkg8k+fkkxyd5VVUdP9tRrQm7kvxqdz8zyclJzvW5L6k3JPnqrAcBLEwNNhNqsCWiBpsZNdhsqcGmCJfWnncn+bUkdnJfIt39me7eNRz+RZKNsxzPKndSkm3d/fXu/rsklyU5c8ZjWvW6+67u/vzw+P5M/pLdMNtRrQ1VtTHJS5P8zqzHAuyXGmyJqcGWlBpsBtRgs6MG25twaQ2pqpcl+avu/uKsx7KG/UqSq2Y9iFVsQ5I7po63x1+wS6qqjknynCTXz3goa8V7MvnH6vdnPA5gAWqwZUENdnCpwWZMDbbk3hM12B7WzXoAHFhV9SdJ/uE8T70lya8nOXVpR7Q2LPS5d/enh3PeksnS1Y8v5djWmJqnzQzxEqmqQ5P8QZI3dvd9sx7PaldVZyS5u7tvrKoXzXg4sOapwWZDDbZsqMFmSA22tNRg8xMurTLd/XPztVfVTyY5NskXqyqZLAv+fFWd1N1/vYRDXJX29bnvVlWbk5yR5JTu9hftwbM9ydFTxxuT3DmjsawpVfXYTIqaj3f3J2c9njXiBUleVlW/kOTxSZ5UVR/r7lfPeFywJqnBZkMNtmyowWZEDTYTarB5lP/Hrk1VdXuSTd39nVmPZbWrqtOTvCvJC7t7x6zHs5pV1bpMNuw8JclfJbkhyS929y0zHdgqV5N/LV2aZGd3v3HGw1mThlmzN3f3GTMeCrAfarClowZbOmqw2VCDzZ4a7BH2XIKD7/1JnphkS1XdVFX/adYDWq2GTTtfn+TqTDY0vEJRsyRekOSXk7x4+G/8pmEmBwBmSQ22RNRgM6MGY9mwcgkAAACA0axcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJmJmqektV3VJVX6qqm6rqeTMcyzFV9eVZvT4AwFJRgwEH2rpZDwBYm6rq+UnOSPLc7n6oqo5M8kMH4XXWdfeuA31dAICVSA0GHAxWLgGzclSS73T3Q0nS3d/p7jvnnlRVh1XVrVX1jOH496vqXw2PH6iq/1BVn6+qa6pq/dB+bVW9var+NMkbqurEqvrTqrqxqq6uqqOG806sqi9W1XVJzl2i9w0AMEuLrcFOqapPTR2/pKo+OTxWgwF7EC4Bs/KZJEdX1V9W1Qer6oXzndTd9yZ5fZJLquqsJId3928PT/9wks9393OT/GmSC6a6Prm7X5jkvUnel+QV3X1ikouTXDic87tJ/rfufv6BfnMAAMvUomqwJJ9N8szdwVGSf5FJ7ZSowYA5hEvATHT3A0lOTHJOkh1JLq+q1+7j3C1Jbk7ygST/cuqp7ye5fHj8sST/y9Rzu9ufkeSEJFuq6qYkv5FkY1Udlknx86fDeR/9Ad8SAMCyt9garLs7k/ro1VX15CTPT3LV8LQaDNiDPZeAmenuh5Ncm+Taqro5yeYkl8w9r6oek+SZSf42yRFJtu/rklOP/+fu7klumTszNhRJ0+cDAKwJi63BMllh9IdJHkzynxfYQ0kNBmuclUvATFTVM6rquKmmZyf55j5Of1OSryZ5VZKLq+qxQ/tjkrxiePyLSf58nr63Jlk/bF6ZqnpsVT2ru7+X5N6q2j3T9ktj3wsAwErxaGqwYS+mOzNZdXTJ1FNqMGAPVi4Bs3JokvcNs1e7kmzLZHn2HqrqJzL5KtxJ3X1/Vf1ZJgXOBZnMjD2rqm5Mcm+Sfz63f3f/XVW9Isl7h2XY65K8J8ktmewdcHFV/U2Sqw/4OwQAWH4WVYNN+XiS9d39lak2NRiwh5p8lRZg5amqB7r70FmPAwBgtaqq9yf5Qnd/eKpNDQbswdfigCVTVbdU1YtmPQ4AgLVkbA02rEz6qUw27QbYJ+EScMBU1e1V9XNz2l5bVX+eJN39rO6+doH+n6qqr1RVV9VNw+20fZ1vxgwA4ODVYN19Ynf/THc/NH2+GgyYy55LwLLR3f+sqo5J8o0kmxb4RZLRqmrdwbguAMBKpQYDflBWLgFLZnpWrapOqqqtVXVfVX27qt41nPZnw/33quqBqnp+VT2mqn6jqr5ZVXdX1UeGjSF3X/c1w3Pfrap/O+d1/u+q+kRVfayq7kvy2uG1r6uq71XVXVX1/qr6oanrdVX966q6rarur6q3VdWPD33uq6orps8HAFjO1GDAwSZcAmblPyb5j939pCQ/nuSKof1nhvsnd/eh3X1dktcOt59N8o8y+ZWT9ydJVR2f5IOZ/IztUUkOS7JhzmudmeQTSZ6cyS+ePJzkTUmOTPL8JKck+ddz+pye5MQkJyf5tSQXDa9xdJITkrxq/FsHAJgZNRhwwAmXgAPtvwyzUd+rqu9lUnTM5++TPL2qjuzuB7r7Lxa45i8leVd3f727H0hyfpKzqmpdklck+cPu/vPu/rsk/1eSuT+DeV13/5fu/n53/21339jdf9Hdu7r79iS/leSFc/q8s7vv6+5bknw5yWeG1783yVVJnrPoTwQA4OBTgwEzI1wCDrSXd/eTd9+y92zUbmcn+YkkX6uqG6rqjAWu+SNJvjl1/M1M9ox72vDcHbuf6O6/SfLdOf3vmD6oqp+oqj+qqr8elmm/PZMZtGnfnnr8t/Mc28gSAFhO1GDAzAiXgJno7tu6+1VJnprknUk+UVU/nL1nvJLkziQ/NnX8o0l2ZVJs3JVk4+4nquoJSZ4y9+XmHH8oydeSHDcsCf/1JDX+3QAArAxqMOBgEC4BM1FVr66q9d39/STfG5ofTrIjyfcz+V7/br+f5E1VdWxVHZrJLNflwy+OfCLJP62qfzJs8Pib2X+R8sQk9yV5oKr+cZLXHaj3BQCwnKnBgINBuATMyulJbqmqBzLZWPKs7n5wWFJ9YZL/MewZcHKSi5N8NJNfMflGkgeT/JskGb6P/2+SXJbJDNr9Se5O8tACr/3mJL84nPvbSS4/8G8PAGBZUoMBB1x1z7f6EWBlGmbVvpfJcutvzHg4AABrghoM1jYrl4AVr6r+aVX9g2G/gP8nyc1Jbp/tqAAAVjc1GLCbcAlYDc7MZMPJO5Mcl8nybssyAQAOLjUYkMTX4gAAAAD4AVi5BAAAAMBowiUAAAAARls36wEcaEceeWQfc8wxsx4GAHAQ3Xjjjd/p7vWzHgePUIMBwOq2UP216sKlY445Jlu3bp31MACAg6iqvjnrMbAnNRgArG4L1V++FgcAAADAaMIlAAAAAEYTLgEALFNVdXtV3VxVN1XV1qHtiKraUlW3DfeHT51/flVtq6pbq+q0qfYTh+tsq6r3VlUN7Y+rqsuH9uur6pipPpuH17itqjYv4dsGAFYY4RIAwPL2s9397O7eNByfl+Sa7j4uyTXDcarq+CRnJXlWktOTfLCqDhn6fCjJOUmOG26nD+1nJ7mnu5+e5N1J3jlc64gkFyR5XpKTklwwHWIBAEwTLgEArCxnJrl0eHxpkpdPtV/W3Q919zeSbEtyUlUdleRJ3X1dd3eSj8zps/tan0hyyrCq6bQkW7p7Z3ffk2RLHgmkAAD2sKhwyZJsAICZ6CSfqaobq+qcoe1p3X1Xkgz3Tx3aNyS5Y6rv9qFtw/B4bvsefbp7V5J7kzxlgWsBAOzl0axcsiQbAGBpvaC7n5vk55OcW1U/s8C5NU9bL9A+ts8jL1h1TlVtraqtO3bsWGBoAMBq9oN8Lc6SbACAg6i77xzu707yqUwm27491FUZ7u8eTt+e5Oip7huT3Dm0b5ynfY8+VbUuyWFJdi5wrbnju6i7N3X3pvXr149/owDAirbYcMmSbACAJVRVP1xVT9z9OMmpSb6c5Moku7cK2Jzk08PjK5OcNWw3cGwmq8Q/N9Rp91fVycPk3Wvm9Nl9rVck+ewwCXh1klOr6vBh1fipQxsAwF7WLfK8F3T3nVX11CRbquprC5w7kyXZmXzdLj/6oz+6wNCAteKY8/54v+fc/o6XLsFIAEZ7WpJPDVtUrkvye93936rqhiRXVNXZSb6V5JVJ0t23VNUVSb6SZFeSc7v74eFar0tySZInJLlquCXJh5N8tKq2ZbJi6azhWjur6m1JbhjOe2t37zyYbxZYHdRgsDYtKlyaXpJdVXssye7uuw7gkuzt8yzJftGcPtfOM76LklyUJJs2bdorfAIAWGm6++tJfnqe9u8mOWUffS5McuE87VuTnDBP+4MZwql5nrs4ycWPbtQAwFq036/FWZINAAAAwL4sZuWSJdkAAAAAzGu/4ZIl2QAAAADsy2J/LQ4AAAAA9iJcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgDAMlVVh1TVF6rqj4bjI6pqS1XdNtwfPnXu+VW1rapurarTptpPrKqbh+feW1U1tD+uqi4f2q+vqmOm+mweXuO2qtq8hG8ZAFiBhEsAAMvXG5J8der4vCTXdPdxSa4ZjlNVxyc5K8mzkpye5INVdcjQ50NJzkly3HA7fWg/O8k93f30JO9O8s7hWkckuSDJ85KclOSC6RALAGCuRYdLZs4AAJZOVW1M8tIkvzPVfGaSS4fHlyZ5+VT7Zd39UHd/I8m2JCdV1VFJntTd13V3J/nInD67r/WJJKcMtdlpSbZ0987uvifJljwSSAEA7OXRrFwycwYAsHTek+TXknx/qu1p3X1Xkgz3Tx3aNyS5Y+q87UPbhuHx3PY9+nT3riT3JnnKAtfaS1WdU1Vbq2rrjh07HuXbAwBWi0WFS2bOAACWTlWdkeTu7r5xsV3maesF2sf22bOx+6Lu3tTdm9avX7+ogQIAq89iVy69J8t85gwAYBV5QZKXVdXtSS5L8uKq+liSbw8Tdhnu7x7O357k6Kn+G5PcObRvnKd9jz5VtS7JYUl2LnAtAIB57TdcWgkzZ5ZkAwCrSXef390bu/uYTLYb+Gx3vzrJlUl270G5Ocmnh8dXJjlr2Mfy2Ey2H/jcMAF4f1WdPKwKf82cPruv9YrhNTrJ1UlOrarDh+0ITh3aAADmtW4R5+yeOfuFJI9P8qTpmbPuvusAzpxtn2fm7EVz+lw7d4DdfVGSi5Jk06ZN8y7bBgBYBd6R5IqqOjvJt5K8Mkm6+5aquiLJV5LsSnJudz889HldkkuSPCHJVcMtST6c5KNVtS2Tuuus4Vo7q+ptSW4Yzntrd+882G8MAFi59hsudff5Sc5Pkqp6UZI3d/erq+rfZzLb9Y7sPXP2e1X1riQ/kkdmzh6uqvur6uQk12cyc/a+qT6bk1yXqZmzqro6ydunNvE+dfdYAADWgu6+NsPkWnd/N8kp+zjvwiQXztO+NckJ87Q/mCGcmue5i5NcPHbMAMDaspiVS/ti5gwAAABgjXtU4ZKZMwAAAACmLfbX4gAAAABgL8IlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAsQ1X1+Kr6XFV9sapuqarfHNqPqKotVXXbcH/4VJ/zq2pbVd1aVadNtZ9YVTcPz723qmpof1xVXT60X19Vx0z12Ty8xm1VtXkJ3zoAsMIIlwAAlqeHkry4u386ybOTnF5VJyc5L8k13X1ckmuG41TV8UnOSvKsJKcn+WBVHTJc60NJzkly3HA7fWg/O8k93f30JO9O8s7hWkckuSDJ85KclOSC6RALAGDafsMls2YAAEuvJx4YDh873DrJmUkuHdovTfLy4fGZSS7r7oe6+xtJtiU5qaqOSvKk7r6uuzvJR+b02X2tTyQ5ZajPTkuypbt3dvc9SbbkkUAKAGAPi1m5ZNYMAGAGquqQqropyd2ZhD3XJ3lad9+VJMP9U4fTNyS5Y6r79qFtw/B4bvsefbp7V5J7kzxlgWsBAOxlv+GSWTMAgNno7oe7+9lJNmZST52wwOk13yUWaB/b55EXrDqnqrZW1dYdO3YsMDQAYDVb1J5LZs0AAGanu7+X5NpMJtm+PUzaZbi/ezhte5Kjp7ptTHLn0L5xnvY9+lTVuiSHJdm5wLXmjuui7t7U3ZvWr18//g0CACvaosIls2YAAEurqtZX1ZOHx09I8nNJvpbkyiS796HcnOTTw+Mrk5w17GV5bCZbEHxumAS8v6pOHlaGv2ZOn93XekWSzw4rzK9OcmpVHT5sSXDq0AYAsJd1j+bk7v5eVV2bqVmz7r7rAM6abZ9n1uxFc/pcO8+4LkpyUZJs2rRpr/AJAGAFOirJpcPelY9JckV3/1FVXZfkiqo6O8m3krwySbr7lqq6IslXkuxKcm53Pzxc63VJLknyhCRXDbck+XCSj1bVtkxqr7OGa+2sqrcluWE4763dvfOgvlsAYMXab7hUVeuT/P0QLO2eNXtnHpnpekf2njX7vap6V5IfySOzZg9X1f3DZuDXZzJr9r6pPpuTXJepWbOqujrJ26c28T41yfk/6JsGAFjuuvtLSZ4zT/t3k5yyjz4XJrlwnvatSfZaed7dD2YIp+Z57uIkFz+6UQMAa9FiVi6ZNQMAAABgXvsNl8yaAQAAALAvi9rQGwAAAADmI1wCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAAAAYTbgEAAAAwGjCJQAAAABGEy4BAAAAMJpwCQAAAIDRhEsAAAAAjCZcAgAAAGA04RIAAAAAowmXAAAAABhNuAQAAADAaMIlAAAAAEYTLgEAAAAwmnAJAAAAgNGESwAAAACMJlwCAAAAYDThEgAAAACjCZcAAAAAGE24BAAAAMBowiUAAAAARhMuAQAAADCacAkAAACA0YRLAAAAAIwmXAIAAABgNOESAAAAAKMJlwAAlqGqOrqq/ntVfbWqbqmqNwztR1TVlqq6bbg/fKrP+VW1rapurarTptpPrKqbh+feW1U1tD+uqi4f2q+vqmOm+mweXuO2qtq8hG8dAFhh9hsuKWwAAGZiV5Jf7e5nJjk5yblVdXyS85Jc093HJblmOM7w3FlJnpXk9CQfrKpDhmt9KMk5SY4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-       "Dimensions:   ()\n",
-       "Data variables:\n",
-       "    S_x       float64 12.79\n",
-       "    S_xpred   float64 11.43\n",
-       "    S_xscale  float64 2.155\n",
-       "    S_y       float64 9.611\n",
-       "    S_ypred   float64 10.43\n",
-       "    S_yscale  float64 2.181\n",
-       "    u_surf    float64 7.645\n",
-       "    v_surf    float64 7.443
" - ], - "text/plain": [ - "\n", - "Dimensions: ()\n", - "Data variables:\n", - " S_x float64 12.79\n", - " S_xpred float64 11.43\n", - " S_xscale float64 2.155\n", - " S_y float64 9.611\n", - " S_ypred float64 10.43\n", - " S_yscale float64 2.181\n", - " u_surf float64 7.645\n", - " v_surf float64 7.443" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "(abs(model_output)).max().compute()" ] @@ -3294,37 +260,9 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "359\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from random import randint\n", "n_times = len(model_output['time'])\n", @@ -3345,54 +283,18 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - } - ], + "outputs": [], "source": [ "model_output['rez'] = (model_output['S_xpred'] - model_output['S_x']) / model_output['S_xscale']" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 0.8s\n" - ] - }, - { - "data": { - "text/plain": [ - "DatasetGroupBy, grouped over 'S_xpred_bins' \n", - "73 groups with labels (-0.0338,, -0.0195], ..., (-10...." - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from dask.diagnostics import ProgressBar\n", "def func(x):\n", @@ -3406,27 +308,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 16.8s\n", - "[########################################] | 100% Completed | 16.5s\n", - "[########################################] | 100% Completed | 12.2s\n" - ] - } - ], + "outputs": [], "source": [ "with ProgressBar():\n", " m = groups.apply(lambda x: x.mean(skipna=True)).compute()\n", @@ -3436,971 +320,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "%matplotlib notebook\n", "plt.figure()\n", @@ -4415,969 +337,9 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (mpl.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: mpl.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " var resizeObserver = new ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * mpl.ratio);\n", - " canvas.setAttribute('height', height * mpl.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " resizeObserver.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / mpl.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", - " var x1 = msg['x1'] / mpl.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / mpl.ratio,\n", - " fig.canvas.height / mpl.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * mpl.ratio;\n", - " var y = canvas_pos.y * mpl.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / mpl.ratio;\n", - " fig.root.removeEventListener('remove', this._remove_fig_handler);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / mpl.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function () {\n", - " this.close_ws(this, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - " el.addEventListener('remove', this._remove_fig_handler);\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[########################################] | 100% Completed | 0.1s\n", - "[########################################] | 100% Completed | 0.1s\n" - ] - } - ], + "outputs": [], "source": [ "from random import randint\n", "plt.figure()\n", @@ -5394,22 +356,9 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ani = dataset_to_movie(model_output.isel(time_index=slice(0, 200))[['u_surf', 'v_surf', 'S_x', 'S_xpred', 'S_y', 'S_ypred']],\n", " interval = 200)" @@ -5417,7 +366,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5426,131474 +375,9 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from IPython.display import HTML\n", "HTML(video)" @@ -136908,78 +392,29 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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qxvVjkuqSfsvMJOn97v4dkv61pJ+W9GFJJumn3f2hGbURAICpOo2JA049cjAAQOEVIQebVTWuv3TA75vaLf15U0ajsXY2Dy8TnCmd3WjEpaorpbj05XAc7ziPXYpjmhMq7bi1GpfXHo5vDWOudeLpbHfjXarZiZe91Z5M+ejGUqI923E5604rLrfYWI7LUVZrcXuq9XibViqTuSnvsUebYUwvUV47U+67Wo+Xfe+Lx6HqjXg6g368LTY343WYWq5EqclBoqRnpuRp5qRUSqzDzHFx4clrYcxgEC9XpsRoPzGdnZ24Dx8MEuWClSu/ezKsEM+LY75MOgcbj8fqtNoHfp6pduKeKC/drqbac34lPqd/9mqcz2RKcHe6mT4wnk67Hy9bb3gujGl1E2WWt+MSysNh3G/XE/lMZh02W3HQ1lZchvrMmXgdJk6PajbjbTpKnNfa7UwOH0+n1cqUi4+ns7MVb/dMDra+HudX7XZ8vs6UTPfEcmX6l52deP/JrJ9MSfmVtXj99BM54UnKbK924nvQ2fpyPJ3OZL7fTUYxcrBZ3dkDAECxWTGuKgEAAMyVguRgDPYAADATxbiqBAAAMF+KkYMx2AMAwKxknisAAADAZBUgB2OwBwCAGbCC3EIMAAAwT4qSgzHYAwDAjBThFmIAAIB5U4QcjMEeAABmwawQV5UAAADmSkFyMAZ7AACYkSJcVQIAAJg3RcjBFmKwZzQc6dqlrUNj7njareF0qom18WefjUcAP/vZZhhz8dFrYcza2ZUwZuUrbgljPnOpHsZ0urUw5tLlQRgzGvXDmJWVeEXX6/HBt7YaT2d728OYxnI1jKk14nnVauUwppqIqVXjZa9W4/2w0xmFMf3uMIzJaCzH+0+pHC+Xj+PttX2tHcZsXmmFMZk21+uT6SJHo3i5Bv14W/S68TFYTqzntTNLYcz6RiOMWUocO/1uvB+OxuMwplSO9/lKJXeFppyY1kkpwlUlLDiXxsODj+GlRnzeq5TjPnKnnUvKb1uP+5PPPBr3txvrcbufcnvcpo9/Kp7XtdZkzjXtbhyT6f+aO/G5ZiexfpqteFuMPd72w0E8neEwnk5GrxefszJanXi772zFGyyTOzWW4v2n0+qFMWsbcW4wPORYvy6zXJ1W/H2hmsjBxom8sV2K57V9Nf7ulhkYyBxfrWZiWyTytMy7hTPfBTL7vCeO0/4gnk63O1+DK9PIwczsrZJeLumiuz/7Bp9vSPp/Jd2t3bGYH3T3n554Q/bM1xoHAKAgrr8c8GZ/4unaW83sopl9+IDPN8zs/zOzD5nZn5rZaya+cAAAAHNqWjmYpAckveSQz79T0kfc/TmSXijpX5lZfAX6iBjsAQBgJkwqlW7+J/aA5ijRAAAAmC/TycHc/X2Srh4WImnNzEzS6l7sZB61uIGFeIwLAIDTyDL3Yd8kd3+fmd1zWIhOMNEAAACYN9PIwRJ+TNI7JT0maU3S33H3+PnII2KwBwCAWbCZvRzwRBMNAACAuXL0HOy8mT2479/3u/v9N/H3/72kD0r6WklfJum3zOx33X37KI2JMNgDAMBMHLns56lKNAAAAObLkXOwy+5+3zFm/BpJ3++7b73+pJl9WtJflvSHx5jmgRjsAQDgdDlViQYAAAAkSY9I+jpJv2tmT5L0TEmfmtbMFmKwp1QqaXlt+dCYw8qCXpcpLZ6o8KedzU4Ys3kpLr1eSow2ttpnw5jVlUzZ03he1Vp8q1t7My5vmCnbWK/Hbc5si4xz5+IS041GvOzb2/ErL1qteB/rxruPBv24vGFzOy59mSn3PUyUUmztxI2uL03m/a+Z9lSq8f6TKfOeKQ2aKRs7HsX7fOa54UxZ9VFiXpny9e2duDRoqRK3Z9CL97HM9iqXVhMxuSs0mT7oRJiyL1yetBNNNLDYypWy1m5ZP/Dzc2fi47sTdzdaX8kdt2WLzxFXr8bnx2o1Ln08PhMfv5n+pj+M+65M99btTSYx2kn0/9vNajydrTjnOXM2zg3WNuJ5tVrxuaaWyGMzV/ozOVhmu3fbcY6ROT/2EtNpbyeSywnZvNIKY1pbcUylGn9NzZRnz+g04z6hlshje4mcJ5PHZr63JtJPbW/H+0avG7c5k8u1Ev1GZl4nZko5mJm9Q7vFL86b2aOS3iSpKknu/pOS3izpATP7k71WvM7dL0+8IXsWYrAHAIDT6Ii3EB8+zTlLNAAAAObNNHIwd39V8Pljkv67ic/4AAz2AAAwAyaT2eSvKs1bogEAADBPppWDzRsGewAAmAVT7tkMAAAATE5BcjAGewAAmJEZlV4HAAAotCLkYAz2AAAwI9N4XhwAAACHK0IOxmAPAACzYCYV4HlxAACAuVKQHIzBHgAAZqQIV5UAAADmTRFysIUY7CmVTStrjUNjhsNxOJ12exjG1OvlMKZcjkcJb7ntfBhz291nw5ixexjTbMUx9Vq8sy/V4+XaTLTnyqV2GFOpxOt5UgfoaHT4viNJvV687Jn9Z/NqvOz97iBuT6cfxowGozCmXI3Xc0Y5s70s3l6VRHsy0/HEfjjox9tr0Iu3xWgU9y0+jtuTWfZSOY4ZDuLlqlQn0/VbYtkz62eY2Fcvf2EnjKnWc8vVWKqm4k5EAZ4Xx2IrV0o6e2H9WNO4uhn3E2dWc9Pa6cfn9OXluE/O+PyleDrdbiI32K6FMYnuX1vbcV/absfntcw5q7kTT6eTyGdurdbDmH48GfV68bJPSr+fyK/Kca6SOWdlcp52uxvGjEZxmzvNeDrddi9uz3ac6w76cR6bUa3Fx04m58m0J7MOM9urWo9zkNEoPgYzx3KnFS/XOHG8Z/Lq7avNMCaz7CeqADnYQgz2AABw2phZKjEEAADA5BQlB2OwBwCAWSnAVSUAAIC5U4AcjMEeAABmpAjPiwMAAMybIuRgDPYAADALBakEAQAAMFcKkoMx2AMAwKwU4KoSAADA3ClADsZgDwAAM2IFuKoEAAAwb4qQgy3EYM945GpudQ6NOXshrtl5++1LYUwtUTFudfVcGJOoYKdGI94Bh8N4Qtc247KfmZKVmfKhmTLLq+txWdSM1k5c/rGUGLFtJcoSbiXKwmZKeWfKqo+G8bwyZSTrS3E5ymotUfYzsQ4HvXjZM3qJ9ZMph54pETlOrOdMafrMdDLl0LuJ0qmlxIvk6stxGdtyJZ7OpPYNT2zTdqLca6d1eB8vSdVMB63JlZ4/NlMhriphsfn48HPAxcuJfj2Ryzzy+eTxXYnjVlbifrvfj2N2duKY1k6cY3z20TBEjUbcb2XytH4iJlM2fOta3G9X6/E5NLPtm824za1mvJ7L5fj8OMyc0xMx9URZ9ZXVuD2lxLbI5J9rlfh7UKb0ei9Ren2cKFE+HsYx1Xqcx/bacW5QXo+XvVSO99XOdiuMySz78tpKGFNL5GDdTrzPZ/LzeiPuMzPl2UeDeNkH/fh8cGIKkoMt/nAWAAAAAABAgczJ5U0AAIrGZAUo+wkAADBfipGDMdgDAMCs2OLfQgwAADB3CpCDzWQ4y8zebGYPmdkHzezdZnb73u/NzH7UzD659/lzZ9E+AACmziSVSjf/AxwDORgAoPAKkoPNqsVvcfd73f0rJb1L0hv3fv9SSU/f+3mtpJ+YUfsAAJgy272qdLM/wPGQgwEACq4YOdhMHuNy9+19/1yRdP0V36+U9DbfLaXzfjM7Y2a3ufvjJ95IAACmrAjPi2O+kIMBAFCMHGxm7+wxs++T9GpJW5JetPfrOyR9dl/Yo3u/I9EAACwWk2SLn2hg/pCDAQAKrSA52NQGe8zsPZKefIOP3uDuv+Lub5D0BjN7vaTvkvQm7a72J/Ib/E5m9lrt3mas1bN36eyF1UPbs77RCNs8GNxwVl/k6rVhGLOz1QtjNs7U43ldjadz6fHtMCZjeS1ePyurtThmpRrGDIfjMKbV7IcxuxcfDzfojcKYnc12YjqDMGZpNV6HlUo5jKk14nU4TqzDcWL9jEbxdDxxXJTLcWdZrsbLPujHx5eP4/aMR/F2z7S5Wk9si3rcnvZOvI9l9udqLW5PJmacWIeZbZGROXYG/ThmPI731X4n7jckaTSYzLIdn0ml03dLMObfSeZgK+t3aDg8uM+9fLkTtreUuDW+0477CUkaDuK+4twt8fl6czPOwbqduC/pd+N2b19rhTHnbl0LYzLLnjnvZ/r/4SA+z64kcssrV+L1vLPVDWO67bj/L5fj/Ww0is+PmTwkI5OHJFIDVWvx17lS4lzTbcfbYlIaq8thTLkc542ZbTE6pH+6LpPvVevx96BhIr/oNOM+sdaI55XJdTPbtFpfT8wr07fE7cmsn5NTjBxsaoM97v7iZOjPSvpV7SYaj0q6a99nd0p67IDp3y/pfkm69a6vmkyvCwDACTFJVoCrSjh5J5mD3XL7c8jBAACnSlFysFlV43r6vn++QtLH9v7/nZJevVcR4gWStnhWHACwkEy7V5Vu9gc4BnIwAEDhFSQHm9U7e77fzJ4paSzpYUnfsff7X5P0MkmflNSW9JrZNA8AgGmzQjwvjrlDDgYAKLhi5GCzqsb1DQf83iV95wk3BwCA2TiFZTxxupGDAQCgQuRgiz+cBQDAvCqVbv4HAAAAxzOFHMzM3mpmF83sw4fEvNDMPmhmf2pmvzPRZXqCmZVeBwCg0KwYtxADAADMlenlYA9I+jFJb7vxbO2MpB+X9BJ3f8TMbp1GI65biMGe8Wis5vbhZRl3NuMyd48kysrtXN0JYyxxS9jyelxyMFNGeOxxm+uJ8n2Z8o8ZrWYckylDminpmSsNGsdkSkNnpMobJspiZ2RKVWfKUZYyJdMz5eLXl8KYTNnGQW8y23SU2H8s8ZK1TInyTDnTSvXkutpU2fnSfHX9meMis8/3e7mysZ1mXOb4xEzhZX9m9lZJL5d00d2ffUDMCyX9sKSqpMvu/jUTbwgKoWSmWuPgY7i9Ex+XlWp8nhls5kr21pfjnKfTifvJTitxnk3Uxe4ncpWda5PJLTP9f+a8lupvEzlquXwujMmUgs+UVc/kcpnzfi+Ry5USJcGr9fg8Wz/kuLkZmTwkk1dnyn2ncrBhZv3Eyz4exvtGJTGdTAn3TEx9uRHG9NqHfx/NyuyHme+Akyp1nplON1FSPtPmEzWFHMzd32dm9xwS8k2SfsndH9mLvzjxRuzDJUUAAGbFSjf/E3tA0ksOnOVfXFV6hbt/uaRvnMiyAAAAnBZHy8HOm9mD+35ee5NzfYaks2b222b2ATN79eQX7C/M1+VdAACKZAovB5y3q0oAAABz52g52GV3v+8Yc61I+mpJXydpSdIfmNn73f0Tx5jmoTMDAAAnzeyoL1w+b2YP7vv3/e5+/038/TMkVc3styWtSfoRd7/hs+UAAAAL5+g52HE9qt0Bo5aklpm9T9JzJDHYAwAATtdVJQAAAEiSfkXSj5lZRVJN0vMl/V/TmhmDPQAAzMoUHuNKONGrSgAAAHNnCjmYmb1D0gu1exf2o5LepN1iGHL3n3T3j5rZb0h6SNJY0k+5+4Fl2o+LwR4AAGZlNqXXT/SqEgAAwNyZQg7m7q9KxLxF0lsmPvMbWIjBnvForNZW+9CYTBnqTEnGTIngUiXecUbDRHnMRHm6zHJlyi12WnGpwO2rcV31TJsz5Q0zy5WRKRXY7+bKNUcy+0+mVGmmPYNePB2b0HOotUY9jOkkyi1m1k+mZHpm2TNlUTMl5TPHuxIlg8uZEvfluORppmRuJkaJ42KQmE5qHWbKqybm1Z1QOVNJWlpdmdi0jmVKz4vP21UlLDZ316B3cJ+SKave2pnc8X1YGfjrNq/G56xMSfCMTP+fKZm+eelaPJ1EqepMjtrvxHlIJk/b2YzPa5nz7DixLTI5RvRdQZKa13bCmEwJ7uX15TAmsw6XVuIcbJj4TjHox+f9TAn3jMx5P8M9kfMkjp3M945JyRxfnviu1Et8F8jsP5l59buDOCbx/WVS31tPzOze2XOiFmKwBwCAU2k61bjm6qoSAADA3JnNo/QnisEeAABmZTaPcQEAABRbAXIwBnsAAJgJK8RVJQAAgPlSjByMwR4AAGbBVIjnxQEAAOZKQXIwBnsAAJgBl+QFuKoEAAA4CLSAAAAgAElEQVQwT4qSgzHYAwDATFghnhcHAACYL8XIwRjsAQBgVgqQaAAAAMydAuRgCzHYMx67uu3uoTGVaryo/VYvjunEMZVqNYwZDgZhTMbq2fUwplSOd+Retx/HBOtYyq2fjMw6HPs4jhmOwhgfexhTqpTDmJ0rW2GMJZ4NtVJ8S2GmPRmZ42I0GIYxvXYnjMkse7kcL1dtqR7GZIwS+0bmOLXEiaKc2F42oVtJ3eP9ObNcpcS2qDfibdFtx8dpa6sZT2enHcZkZY6xk1KEW4ix2Nyl0ejg47zWiM/n3WacX2Q1lmthzHgY90uZdh+23NdV6/F5NnMe6Xcnk19lcqeMTB7Sbca5wagen4vL1XhePsic++J8ptNsJaYTn0Mz5+LGSiOMKSdy+GEin+l14jx/nNifB7142av1RA6fOAYz6zkznf44PnYy+8Z4FK/nUSamH88rk+tmcpnU+knsG5nlynyfmjdFyMEWYrAHAIBTx4pxCzEAAMBcKUgOxmAPAACzUoCrSgAAAHOnADkYgz0AAMxKAcp+AgAAzJ0C5GAM9gAAMBNWiOfFAQAA5ksxcjAGewAAmAVTIZ4XBwAAmCsFycEWfwkBAAAAAAAKZCHu7HF3DYNSgKXEM3mrZ9bCmHaiHHGmPGaqxF+ilGK3Gpe1zJUWj9dPfTkuEZmJyajW4rKNpUTJweEgsQ4zJeUT29RK8b5RSowgZ8obDnpxmcRqPS4/m9k3MmVaM2XVMzLzyix7qnx94lj2eFOkStNn9p/M8Z5arkQ53Eo17vozfWamH5tUX+eJfSMzHUkqV+P+5aR4Aa4qYdH5oSWb+924fHImB8n0JbtxcT9QrcV9YLkc97edVrxsy2txXpQpVd1ttsOYTLnmScnkM5ltlspRBxPKMRJlqDPtyeQhmbLh7Z1EexIl3DPn9EE/bk+3GX+n6CT2w+X1lTDGEvtPpsx75ryfyavLiZywnOg3hol9Y5Roc2ZePoj3DR8n8urEvpHKdTvx96na0mS+J05KEXKwhRjsAQDg9LFCVIIAAACYL8XIwRjsAQBgRopwVQkAAGDeFCEHY7AHAIBZKcBVJQAAgLlTgByMwR4AAGbBrBCVIAAAAOZKQXIwBnsAAJgBl+QFuKoEAAAwT4qSgzHYAwDArBTgqhIAAMDcKUAOthCDPVaysOR3pmTxKFGuM1Oar7G8FMYsrSyHMbly34nlSpQczJQ9bUyorHqmFGemrHqmVGmtEZcfz0ynvR1v90ltr3KihObSarz/ZGRKg5bGiY4wXj2p/XDUT5Ty9kTp9UTnnSlRnpEpwZotCR6pJEpxVuvxPh/1l1KuRO2gP5ltkSkXnCmHmynPLkmlRD9+UlyLf1UJi85UKh98nI8OKct+M5ZW4txKypV6rzfi8/5oFPc5/W7cB2ZKr2dyg4xMP5npb0uJc9Y4cU73Qbzth4nS0DaKzyOZEtOZ9ZM5z2bOa5l5dTtxGfOMpdX42Oi147LYmbLqg0R57cxSZcrFZ9ZhJrfM5GCZ/Sf1nSsxLyvF+0+/E3+nyCxXJtfNzKvfjbd7Kk9LrOeTVIQcbCEGewAAOH2sEJUgAAAA5ksxcjAGewAAmJUCJBoAAABzpwA52EyW0MzebGYPmdkHzezdZnb73u+/ee/3D5nZ75vZc2bRPgAAps52Xw54sz/AcZCDAQAKryA52KyGs97i7ve6+1dKepekN+79/tOSvsbd75X0Zkn3z6h9AABMle/dQnyzP8AxkYMBAAptWjmYmb3VzC6a2YeDuOeZ2cjM/vbEFuoGZpI1uvv2vn+uaLf6mdz999392t7v3y/pzpNuGwAAJ8bs5n+AYyAHAwBA08rBHpD0ksNna2VJPyDpN4+/EIeb2SVCM/s+M/uspG/WX1xV2u/bJP36IX//WjN70Mwe7HeuHRQGAMDcKsJVJcyfSeZg3faVaTUTAICpmUYO5u7vk3Q1CPvHkn5R0sUJLMahpjbYY2bvMbMP3+DnlZLk7m9w97skvV3Sdz3hb1+k3UTjdQdN393vd/f73P2+2tLZaS0GAABTYru3Ed/kT8IDmqOrSjh5J5mDNZZvmeaiAAAwBUfOwc5fv9ix9/Pam5qr2R2Svl7ST05jqZ4oVY3LzJ4h6SckPcndn21m90p6hbv/y4P+xt1fnGzDz0r6VUlv2pvXvZJ+StJL3T11uahUKqm2VDs0prXVDKfTa3XDmPpKI45ZjmOqtWoYs7KxEsZk9Nq9MGbQH4QxnWYnjLFS/EVkPByHMaVKPA5Zrsa7b6U6mfHMSmpep6+4XSOxP2e0d9phzKg9CmOGg3g/HI/i6YyHccxJslLibozEsZMxHAzDmJ0rW2GMjz2MKVXKYUy5HMcMev0wZpTY7qXkOsws20mZxjt43P19ZnZPEHb9qtLzJt4ATNS852DlSklnbjk4X9m+Fp8fMvlF5WzuHNvvxP3JcKUexpTK8bFZrce5XEYmf6gtxW2u1g/PhSWpXE3024mY0SDukzN97djjnDBzTs/kBuVqvL2sFG+LUT8+z/Y7ce7tiWUf9uK8qJVY9sx3nFEiB8usQx8ntmnmnJ7IH8qKYzLtSe2riTZn8r1J7c+Z9ZPRabbCmEx7MiY1nUk5Yg522d3vO8Zsf1jS69x9ZCfwaH52Cf8fSa+XNJAkd39I0v901Jma2dP3/fMVkj629/u7Jf2SpG9x908cdfoAACywU3VVCcdGDgYAwGK4T9LPmdlnJP1tST9uZn9rWjPL3oqw7O5/+ITRp3hY+2Dfb2bPlDSW9LCk79j7/Rsl3aLdhZak4TFHzgAAmE+mo75w+VRdVcKxkYMBADBJR8/BjsXdn/pfmmD2gKR3ufu/n9b8soM9l83sy7RXsWHvZY6PH3Wm7v4NB/z+2yV9+1GnCwDA6WHy2dRJuH5VSZLOS3qZmQ0PSjbM7D+4+9eZ2Q+4+4HvccHUkIMBADBR08nBzOwdkl6o3buwH9XuY9JVSXL3m7qj2sy+0d1/3sye6u6fPkp7soM93ynpfkl/2cw+J+nTkv7uUWYIAAB2v7n76biqdJuZfY2kV5jZz0lf/JZod//jqTQU15GDAQAwQdPKwdz9VTcR+61ByOsl/bx237H43KO0JzXY4+6fkvRiM1uRVHL3naPMDAAA/IVpvKB5kleV9rxR0vdIulPSv9IXD/a4pK89TntxOHIwAAAmbxo52IRdMbP3Snqamb3ziR+6+yuiCRw62GNm/+yA31+fwQ/l2gkAAJ4oWUr95qY52atKcvdfMLNflPR/uPu/OE7bkEcOBgDA9EwjB5uw/0G7d/T8W+1ebLtp0Z09a3v/faZ2y7NeH1H6m5Led5QZTkO1VtHt95w/NGb76nI4nU6iLOHKRjydai2+YarXjkuDZkpfLq/EZTZ73USJyG5cbrG+HM+rVovb3GrG5Sg7iZhcmcREmfdEedXaUrzsqVKTEyr5nFmuDPe4PakytonSoJn1U06U8s6Uls2UBM8YJkqCDxMlWDMmVXp9UmXnM+3JzKvXiksqZ2TaY+VcGeRMGfeTYafhqpIkyd3dzF4picGek3MqcrBKpaRztywd+HkmB6k34rLi2ZeJV+txDjZI9Nup3KAR9zmZ83Wm9PraufWJTCdT+jiTq5QSfdcocY6oJPr2fjfOCTMlr+vLjYnMa5goUT4aZPaxOFcZ9LYnMp2J5VeJeWXy89Q5PbFNd98zf7jMsk8qP5+Uk8wJcyXlJ9OeSeXMkzH/OZi7983sjyT9rrv/zlGmcehZwd2/V5LM7N2Snnv91mEz++fafX4MAAAc0Sze2XMM7zez57n7H826IUVADgYAwPSchhxsr3LqU47699kXNN8taf8l7r6ke446UwAAis51Km4h3u9Fkv6BmT0sqaXdd/e4u98722YtPHIwAAAm6JTlYB/ce2fPz2s3/5IkufsvRX+YHez5t5L+0Mx+Wbvr5uslve0IDQUAAJJk838L8RO8dNYNKChyMAAAJul05WDnJF3RFxfEcEmTGexx9+8zs1+X9Nf3fvUad//PN9tKAADwF07RVSVpN7HACSMHAwBg8k5LDuburznq36YGe8zsbkmXJf3y/t+5+yNHnTEAAEV3iq4qSdKvanfAxyQ1JD1V0sclffksG7XoyMEAAJi805KDmdlP6wYX3Nz970d/m32M63qCJ0lLIsEDAODYTstVJUly96/Y/28ze66kfzCj5hQJORgAABN2inKwd+37/4Z2H+d+LPOH2ce45jrBq1RKunDh4LKfknT77XHJ9OWlRPnHuNqiLl+OyzW3G/Gqr9fjUoErK3HZz5WVxHQSy15J7C3DREW97eZKGHP5Ulz6cnurG8ZkSouPEmVRMyVfy4kyreVyYj1X4+2VKWV79eJWGNO8thPGDBPlQzOlHTNlG8vVeH/OlJbNlA8tJ9ZzRq8d74fdZjuMSZW6TZQ8rS3FJYwz5Wcz63nQizvE9k4rjMnsP5lSrlmZZTsJfgrKfh7G3f/YzJ4363YsunnPwczs0HxlZS3uk1bXbw1jhsP4XC1J40RcZlqdVqIEd6I9mb6rsRSfs5YT63HQj/vSjF437ts7zfjct7IR53ulRG7QzZSmP7saxtQacY5x+XNXw5jMNu0rXj/DXvx9ISPTntpSfN5fPbs2ieao34mXK1OaPlPivpLIGzPHabkan4szeWxmW4zL8XGaWfaMTHsmVVY9k6POk9OUg7n7L+7/t5m9Q9J7Mn97pIyXBA8AgOM7RVeVZGb/bN8/S5K+WtKlGTWnsMjBAAA4vtOUgz3B07VbqTOUfWfPExO854oEDwCAY/HEXYNzZP9l36F2byv+xQNiMSHkYAAATN5pycHMbEdf/M6ez0t6XeZvs3f2PDHB+1WR4AEAcCzupyPRkCR3/97r/29mJUmr7h4/q4DjIgcDAGDCTksO5u5HfsYyO9jzEXf/+f2/MLNvlPTzB8QDAIAFYmY/K+k7JI0kfUDShpn9kLu/ZbYtW3jkYAAAFJSZ/VVJH3T3lpn9Xe3e4fsj7v5w9LfZtxK9Pvk7AACQYnKVbvpnhp7l7tuS/pakX9Pu8+LfMssGFQQ5GAAAE3WqcrCfkNQ2s+dI+l8lPSzpbZk/PPTOHjN7qaSXSbrDzH5030fryr3cHAAA3IDr1L0csGpmVe0O9vyYuw/MbHJl0vBFyMEAAJiOU5aDDd3dzeyV2r2j59+Y2d/L/GH0GNdjkh6U9Art3rJ93Y6kf3qkpk6BmVStHr6xMmXVz63H86qU47z2TKI85k4rLrNZqcRtPrsWt6daiWMSFRCVeYdVuRTP65aNeDoXzi2FMRevxOu51YoXrNWKyxsOB3GZ1no9fiqy1kiUzk6Uf8yUjc2Uec+Ux+wkyob7ONGeSrzs5VK87Jmy6o2VuMRopj2Z5arW4rKfSyvLYUymxL174nhPtGd5PT6+SuV4W/QSMakStd24xHFGtuxnZtuflFOUaEjS/y3pM5I+JOl9ZvYUSdszbdFiOxU5WLksra4c3BeMRnF/3GjEfUnmnCZJmcP70pX4vL+zFfelGaNRfB5pLMXzWltLlA2/3AljVlbic2imHPqlLzTDmHojzosyMVvX4uW6/c44iT9zJl6HH0+c165+IZ7OaBSX125txeuw34nPj6kcLHF+PHshTtAr1Xg6O5tx3rhzbSeMGSRK02fKhteX45xnUuXHM8aJfaM8OFLB7CMZJtbzaBi32RI5fKV6csuVcYpysB0ze72kvyvpvzWzsqTUSerQNe7uH5L0ITN7u7tzFQkAgAk6RYmG3P1HJf2XO0zM7BFJL9r377/n7j8zi7YtInIwAACm5xTlYH9H0jdJ+jZ3/7yZ3S0p9b7E6DGuf+fu/6Ok/3yjW7Xd/d6jtBYAANhpSjS+hO/earZ/EOK7JTHYMyHkYAAATMvpycHc/fOSfmjfvx/Rvnf2mNkfuPt/faO/je6l+u69/778uI0EAABf7LSU/UxaqIWZA+RgAABMyQLlYAc+L33ow3Xu/vje//4jd394/4+kfzTJFgIAUCTXXw54sz9zjJc1TxA5GAAA07FgOdiB+Ve2ftjfuMHvXnq0tgAAAGmhEg2JO3umhRwMAIAJW7Ac7Iaid/b8Q+1ePXqamT2076M1Sb83zYYBALDoTlPiYGZvvNHv3f1f7P0vecEEkYMBADA9pyUHM7N/Kunn3f3Rg0IO+tvonT0/K+nXJf2fkr5n3+933P3qTbVyiqpV6bYLh9+ktLYUl4zbaMSl5+qVuCDGYD0uS9iZUEm98pe+s/FLLFfjEqMli8s2tgaJkvLdeLk6/USJ1cQ9Z+urcVB/EMesWlyGNGOUKDGdKatercYdz3qiBOvGRlxCc+NsXI7yyqXzYUxzKy6L2u/Gx1empOfKRlzGPFPGtteNj+X2TjeMGQ7i5aotxftYZrmGg0zpy0QZ0kR7Mga9eB1m2lOtx+0pJ/aNxnJc4lmSzObl5G6n7Xnx1r7/b2j3XTIfvf4Ld/+uE2/RYjsdOVhFuu38wee/WqLUbiWREm2sxHmKJDWq8bl4fTXuc9rdOKbVjtvUbMb95B23xfMaDOPlarfjc9/SUuI8u5zobxtxjpGxvJTJCeOYC+fjZT9sP71uc3M1jBmN4u1eqcTrcPTks2HM9tW4PPvVxy/H7anH62c9kRMuL2fKzsfrZziIj4tMifLMdFJ5SDX+jpMpG15NrOdOM86ZS+XJ5DylxBeqTH7e2or3w4zM+jk5pyoHW5f0m2Z2VdLPSfoFd//Cvs+/5aA/jEqvb0nakvQqSTKzW7Wb4K2a2erem6ABAMBNcknjU3JVSZLc/V/t/7eZ/aCkd86oOQuPHAwAgOk4TTmYu3+vpO81s3u1W4b9d8zsUXd/8d7nHz7ob1Pv7DGzv2lmfybp05J+R9JntHu1CQAAHNEpf158WdLTZt2IRUcOBgDA5E0jBzOzt5rZRTO74QCMmX2zmT209/P7Zvacm2jyRUmfl3RF0q2ZP8i+oPlfSnqBpE+4+1MlfZ14XhwAgKPz3bKfN/szK2b2J/sSlD+V9HFJPzKzBhUHORgAAJM0vRzsAUkvOeTzT0v6Gne/V9KbJd0fTdDM/qGZ/bak/yDpvKT/ee/vQ9kXxwzc/YqZlcys5O7vNbMfSP4tAAC4gTm7Uyfy8n3/P5T0BXePX5iA4yIHAwBgwqaRg7n7+8zsnkM+//19/3y/pDsTk32KpH/i7h+82fZkB3s2zWxV0vskvd3MLmo30QMAAEcynTt1zOyt2h2Yuejuz77B598s6XV7/2xK+ofu/qFouu7+8EQbiixyMAAAJurIOdh5M3tw37/vd/fw7pwDfJsSj2W7+/dEMQfJDva8UlJX0j+V9M2SNiT9i0P/AgAAHMg1tTt7HpD0Y5LedsDn128hvmZmL9XuLcTPn0ZDMBHkYAAATNAxcrDL7n7fcedvZi/S7mDPXzvutA6TGuxx9/3lVn9mSm0BAADHNKVbiDEj5GAAACyOvapaPyXppe5+ZZrzOnSwx8x2tDvw9SUfSXJ3X59Kq6agXhmHMau1XhhTtlEY0x8thzGdfjmMqZRvtOq/2PpyJ4y5ULsaxmQMxufDmGa3HsZc3YqXq9ePt1cmpmTxiG2jEceM41lpNEosVy/ef0aj+L3pmfZUq/Fy3XqhFsacOVMNY7Z3VsOYna34+Bp7vA6XGnF7MjLby0rxOhyN4m2qeNFliX010x4fx8u1eWl7ItPJtCcTUy3H27RcjfvM4SD3ZEtm2U7KLF+4vCd1CzFO3mnJwSqlsW5dO7iT6w8b4TQS3YTOrQxS7amV436gVon7nOE4Phf3h3HMle34PHvHuXjZ2oO4D9xpxvOalPW1uD2NerxhB8PJ9MeJU2gqd1pdja+DZ87X5XIcc9sd8SHcOhd/pxgN4jwkcw5dW4v3n5WVeP1sXo1jllbifqHWiNvTvNYMYzqtdhiTce5JZ8KYxlLctwx68fE+HsU768pGvG+srsfrudPqT6Q9o2G8H1brk8nhJ2UWOZiZ3S3plyR9i7t/YtrzO/RodPe1aTcAAICiSnz3uJGJPC9+UrcQ42jIwQAAmJ4j5mCHMrN3SHqhdnO1RyW9SVJVktz9JyW9UdItkn58b+B4OInHwg6SfWfPRJnZm7X7DPpYu/Xiv9XdH9v3+fO0e2v533H3X5hFGwEAmLYjXlU69vPiJ3kLMeYLORgAANO5s8fdXxV8/u2Svn3iMz5AfP/pdLzF3e9196+U9C7tjnBJksysLOkHJP3mjNoGAMDUuexIP8d10rcQY+6QgwEACm1WOdhJm8mdPe6+/4URK/riZ9L/saRflPS8E20UAAAnbEql1+fqFmLMF3IwAADm4r2JUzeTwR5JMrPvk/RqSVuSXrT3uzskfb2kr1WQaJjZayW9VpJuedLdU20rAADTMI2rRPN2CzHmzyRzsCfddtdU2woAwDScxjt1btbUHuMys/eY2Ydv8PNKSXL3N7j7XZLeLum79v7shyW9zt3D13m7+/3ufp+737d25sK0FgMAgOlwaXyEHyBykjnYxtm4UicAAHOlIDnY1O7scfcXJ0N/VtKvavc28/sk/dzebeXnJb3MzIbu/u8Pm0C9MtbTzh9eeu9sLS41XLO4PvIoscqGlTimnYjpDhOlhhOlQZvjlcR04vb0R3FMpvLxxUtxib9EBW7dcXtc5n09XnS1u3FMfxA3qN2ZTOl1Tyz8cBi/P36cuDWxF28KDRIl7seJMuaNpXj/yayf7a3EBkuoVONjZ+NsXNaynigF39yKy362tlphTKrM+4SUy3H/U6nG27Rkk7mmkCktmy29no2bNlcxrirh5J1kDlYujbVRP7j/aidKNY8S56tqeXL933I1Ln1cLcXzM4vPff1hXF57pR6359xyfB7p3x7P6+LVMCSVpz3lrjgHW1mK189jF+OYcSIvarXjmGuV+Hw0TJSPHvTjc0inFX+nuOVCnGOsbcQ5xurZONktl+Nlz5SL7/XinLDXi9dPpj1rZ5bCmEqipLwuxiGZ/Cozr1EiH7ZSvJ73+uFDlRIx6xtx6fVMm8uJZa81amHMPJVeL0oONqtqXE939z/b++crJH1Mktz9qftiHpD0rijJAADgtCrC8+KYL+RgAAAUIweb1Tt7vt/Mnqndsp8PS/qOGbUDAICZydzFCEwYORgAoPCKkIPNqhrXNyRivvUEmgIAwIyYxgW4hRjzhRwMAIBi5GAzq8YFAECRuYpxCzEAAMA8KUoOxmAPAAAzUoRbiAEAAOZNEXIwBnsAAJiRIlSCAAAAmDdFyMEWYrBnebSj5+y899CYyuXPxRPqduKYalxWbnzmQhhz9cnPCmP+fPC0MOZKKy6pl4mpV+JSiv1RXCbx7GpcuvB5XxHvdp1+PK/ReDLDsfVaorxhokxirxe3J1Pe8MqluLxqpuxnrxuXch2P4u3eWIr3+aWVOCZTLr65FR+D/W5cEraUKOmZKRteTpRpHfTi9TzoxzGZ9mTKdWZkymNm2pNZrsz6yZR5LyW2Rb0alwKWpOpoTkp/ujShbgyYGZNU1sH9+2o97rNXqnGZ6qrF5z1J6o/j4ztTMv3JivPGTnk1jHmsshbGrFa7YcyZymYYMzoX96W9Qdzm4TBeh4lThDZ34phWK84bl5fjmWVKgu804/a0O3F7qrVEHtuMt+nWZrzfb5zJndciw0G8XO12fIx1O3HM9tV4RWfykLVyXHo9sy2WVuPvQePEybi1E2/TTI6ayYsy+V4/812gF8f0E98XPLF+qstxv+Hj+Dg9MQXJwRZisAcAgNOmKM+LAwAAzJOi5GAM9gAAMCNFeF4cAABg3hQhB4vviwcAAAAAAMCpwZ09AADMyLgALwcEAACYN0XIwRjsAQBgRopwCzEAAMC8KUIOxmAPAAAz4LJCvBwQAABgnhQlB1uQwR6XjYOSgrW47F7/4x8LY77wgU9kG3Wo2/6bZ4cxz33+14Yxnzn3VWHMtV5cZnNCFZ3VG8VlP/vDOObMUly6cJQ4QFu9uAzgcJwobziMYyqJct9jj0tNZsq8dzpxmcR+N172TDnrcmK5yuW4zWaJdZhoT6sZd1uZMpIZo0S5+HKi/uxaosRoplyn4iqtqtbj9iyvxeVMM+XrR4N4H+t24uUaDuLSoJn9p1yJ+xZJqtYpvQ5Mirs08IP7nXP1uP72nTsfCWPKg06qPdtn7g5jKqO4X9r4+O+FMf27nhlPZ+m2MCbzhWO9ezluTz0u011JlIt/1j2JMt2J0+zDj8bT6fXimPX1REnnRF/aasfz6ncTpeBX4nP6aBCfZ0ejOMdoteIVPUiU1x6PJrMtuon8M1NaPFPKe+tafE7P5KhLK/F3wNZO3L/sXI37svEJlhYfJ/af5nacOG5djpcrs03L5Xh7jRL74YkpSA62IIM9AACcPkW4hRgAAGDeFCEHY7AHAIAZ8QK8HBAAAGDeFCEHY7AHAIAZcBXjFmIAAIB5UpQcjMEeAABmpAi3EAMAAMybIuRgDPYAADAjRUg0AAAA5k0RcjAGewAAmAF3aVyAsp8AAADzpCg52EIM9ozLNbU27jw0Zv3S58LpDNtx2b31O28JYyxROrt3ZTOMWbn8aBizdDYu+7ltK2FM5gVVq9V2GFMrxeUoLw+Ww5jOIN41q+W45OByLS5H2R/GZRv7w7g9zXY8PNzrx22uVOJtcf58XNKz0YiXq9dLlG1sxuuwlyj76Ynh80zZ8NXE8aX1uMzmcBAve6bNtUbc5kyJ0U4rLlk5bEymZGWm3GtGpq+rVBPLlSi93mvH5UMH/UT5+uT8TkoRriphsZm5GqWDj8+nfu53wmmMP/qhMKZUi/MLSdr48sR5disuY779nx4MY9YrcUnwC8/8qjCmPYpLprvic3pDcR57djXu/zYacX9bLcfLXirFbZ6U4TDe7v1EDpbJZ8aJjnvtTJynZaaTKZ2dyVUssS06rfgcmmTvX+AAACAASURBVMkf1s6uhjE715phzLUvxN+Vbr3rfBhTacR5yPbVuD2DXrx+qvW4nxoO4jLm48T+nMllWjvdOGYrXvZMyfRMTjhMlHA/SUXIwU6uFwYAAF/E/eZ/AAAAcDzTyMHM7K1mdtHMPnzA52ZmP2pmnzSzh8zsuZNerv0Y7AEAYEbGfvM/AAAAOJ4p5WAPSHrJIZ+/VNLT935eK+knjrsch1mIx7gAADhtXJIX4HlxAACAeTKtHMzd32dm9xwS8kpJb/Pd5y/fb2ZnzOw2d3984o0Rgz0AAMwGj2UBAACcvKPnYOfNbP9L3e539/tv4u/vkPTZff9+dO93DPYAALBIpvFYlpm9VdLLJV1092ff4HOT9COSXiapLelb3f2PJ98SAACA+XTEHOyyu993jNne6HaiqV364509AAAslgc0R8+LAwAAQNLunTx37fv3nZIem9bMFuLOnnKvpfVPH14is/eJT4TTqa7FpQKXn/WsuEGZ8qC9uBTe4NxtYcz2aD2M6Y/ikoMjj8f9LjXPhTGtXqK0Yy9+PtISj1CeWc2Uzo6n0+3Hbd5uxdNpd+L2jEdxg8rleOEz1Uwz6zAjU6K8359MSfBBL55OpxWXIc3IlAQvleMV3e/GpS+Hg3i5uu24pGenFZfVzZR5zyiXE+unEq+fTPnQQT8uxZkpVTpIlvTsJdbjSdh9XnwK052z58Wx2Gqjju7c/tMDPx/84e+F02g9FpdCr640Uu1ZO39rHJTo39qXtuJ5XbsSxmzYtTCmZ08KYy7V7ghjGhb3bU9e2QljxomccKUWd16rq3FeXUrkPBmZ6WTKs2fO15nTbK0W72PddnzO6nXi3MASCV+mPHtzK95/6o1qGLO8Gh+r21fi/TBT6nyU2F7lRC6XKWOeaU+m/HgmT8uUOu8n9o1MTLcdb/dMTpgpq57J5U7KtHKwhHdK+i4z+zlJz5e0Nc38ayEGewAAOI2K8Lw4AADAvJnGYI+ZvUPSC7Wbqz0q6U2Sqrvz85+U9GvafYz+k9p9lP41k2/FX2CwBwCAGSnC8+IAAADzZhrvTXT3VwWfu6TvnPycb4zBHgAAZmF21bhO9HlxAACAuVKQiqi8oBkAgBlwSePxzf9MwDslvdp2vUBTfl4cAABgnswwBztR3NkDAMCMFOF5cQAAgHlThDt7GOwBAGBGplSNa66eFwcAAJg3DPacEsPtHV1593sPjcmUuStV4rJy9kh8p3tlqR7GLD8lLqFZfnJcnv1MeTOMsUa87Fc6a2FMbziZp/6GcXVDtdqZ++Ti9mysxNNp1BKloRPL3utnyofG+1hGooqker14ubrdTInRTLn4xPpJlCjvZspIduOYTOnUTOn1+nJ8LJcSJU87rfhYbm614ulsxzGZ0qCVWtz115eXwphSohSne7wfmsX7T2pe414YM0/cp/NyQOAklXod1f/8Qwd+vrPVDKcxHsZ99vYjF1PtqawcXAb+uqWvfl4Ys3r7+TBmtL0dxmw047yxuboexlzpxTHn6vH5aKXSDmNaw+UwZjCKS3BfOBu351IiL+p2MyXT486034/3s0zp7Ewml5lXazsuee2J50bK1fic3m9ncqc4TytXVsMYS+TDqXkllqvXjUt59/uJsur9eP1kvksOEuXHK4nlyuyHmXXY755cXpQpq26l+XmDTFFysIUY7AEA4DTyIlxWAgAAmDNFyMEY7AEAYEYKkGcAAADMnSLkYDO5l8rM3mxmD5nZB83s3WZ2+77PXrj3+z81s9+ZRfsAADgJRagEgflCDgYAQDFysFk9OPcWd7/X3b9S0rskvVGSzOyMpB+X9Ap3/3JJ3zij9gEAMFXuR/sBjokcDABQaEXJwWbyGJe773+j3Yp2S91L0jdJ+iV3f2QvLvc2PgAATqEivBwQ84UcDACAYuRgM3tnj5l9n6RXS9qS9KK9Xz9DUtXMflvSmqQfcfe3HfD3r5X0Wkm6Yy2uGgAAwLw5jVeJcPpNMge76/zZqbcXAIBJK0IONrXBHjN7j6Qn3+CjN7j7r7j7GyS9wcxeL+m7JL1prz1fLenrJC1J+gMze7+7f+KJE3H3+yXdL0nPWl/zSx997ND2tC7FpSaHmTLUw3ivePK9t4YxT3n6U8OYrVu+LI4Zb4Qxw3G8mZcqcbm85US55nY/fjKwXgtDNPZ4OpkDtFKKgyrlOGaYKGc6GMYx3kjEJJZrczveVzc34zKSrWYckymZPkqUOh8mSuuOE0PsmZhSohR8rRHviNXEPj/IlPTsxTHDRLnOTBnzUiUuCptZh712XBK2XI1L75YTJdPHntjHUus53p+lXEnTk5Ip5QrcrJPMwZ57z+0+3t46sC21jbhUc+1MXFa8/YGPhzGS9PkH/yyMeepfivOrxu1xLtf+bFxWff3znwxjzj9lLYzZtDjmai+OuaUel4svl+LzdW8Ynx9r1bh/S5yuNRzG575eL5FjjBLtSTSo24nP15nzfr+TO2dNQqYkeEY7US4+c47N5DOVcpyndVpxezI56jixj00qdxiN4vaULN4Px4npjBO5dyZPy8jkn5Oa16QUIQeb2mCPu784Gfqzkn5Vu4nGo5Iuu3tLUsvM3ifpOZK+JNEAAOA0cy/GLcQ4eeRgAAAcrCg52KyqcT193z9fIelje///K5L+uplVzGxZ0vMlffSk2wcAALCIyMEAACiGWb2z5/vN7JmSxpIelvQdkuTuHzWz35D00N5nP+XuH55RGwEAmKoiPC+OuUMOBgAovCLkYLOqxvUNh3z2FklvOcHmAAAwE5n3JwGTRA4GAEAxcrCZVeMCAKDIXMW4qgQAADBPipKDMdgDAMAseDESDQAAgLlSkBxsIQZ7BjsDfe69Fw+NqZ2LSwSv3bMcxmTK7nU24zKA7T9/OIxZ+YpLYUx1/UaVVZ8gU9ZyHAdVSnFZwv4gU2Y5bk+mPHuiKrZavXi5Wp14m25ux8veasVlLUeJsp+ZEqOZkunN7W4Ys311J4zJlAYtJ8ot1pfrYYxZosR9P1GiPFPCfRSv5267F8ZkSnp2Wu0wZjiIl8sSpTgr1UTJ08T6yZRFHSXanCn7mZlX5lbbTNnP+eIaFyHTwEKzclmlM2cP/Lx+z1+KJzKO+4Az1w4u777fI/8xLtHe+mgcU9uIy5j3t1phjF+Nc7nSXXGZ7kY1Phd/4tLB2+G6yrl4Xa9X4+WqleO+fTiKc+9MTpjJncrl+NxXqSbKqrfj81q3HW+LYSI3yMiU6R61M+fZeB1mcrBuO84tMyXBS4kS3Jll73fjPG04iI+vTEnwSjXenzO53HiY2J+X4pw5I/O91UqJMu8nWML95BQjB1uIwR4AAE6jxDgXAAAAJqwIORiDPQAAzMDu8+KLf1UJAABgnhQlB2OwBwCAWfDU0ysAAACYpILkYAz2AAAwI0W4qgQAADBvipCDMdgDAMAMuHIvJwUAAMDkFCUHW4jBntU7N/TXvvslh8bUnvykcDq2tBTPbBi/Zb3/+OfDmM7jieoM7/8PYcw9z40rf127Ja6E0axthDFli4+Ika+EMVvt+G3t5UQFsUTRAG0146Crm/Eb5luJSgfdTvy2/+Z2XDWg08pUFkhUwZhQ9YHMm/z7nbjNzUQllVHibf/VRKm2TMWEjHHizW2pyl+J5cpUnZhUpYNUpa1MFa3EslcSZfMmVWXs1PHcOgTm2aixovYznnfg55eWnxJO40k7fx7GrD7t7lR7LlzaDGO6V+Lz0c4jXwhj2leaYcz5RP/WbNwSxpQSzxs0E9VFr3biXPeWWrwO6+U4Hx4M43kNBpN5jqKxFJ8fB/1EVdl+pgJUXI1rlKj4Wa3H58dUpa3EeSRTaStXuSmOGSXWYaYaV2a5MrlTps2lSuKLR4L3JlTtNLFcGal9I/OdK7EOMya1XBNRkBxsMns2AAC4ae43/wMAAIDjmUYOZmYvMbOPm9knzex7bvD53Wb2XjP7z2b2kJm9bBrLdt1C3NkDAMBpNC7AVSUAAIB5M+kczMzKkv61pL8h6VFJf2Rm73T3j+wL+98l/Tt3/wkze5akX5N0z0Qbsg+DPQAAzIC7F+LlgAAAAPNkSjnYX5H0SXf/lCSZ2c9JeqWk/YM9Lml97/83JD026Ubsx2APAAAzknh0HwAAABM2hRzsDkmf3ffvRyU9/wkx/1zSu83sH0takfTiibdiH97ZAwDAjIzdb/oHAAAAx3PEHOy8mT247+e1+yZ5ozdZPzFxe5WkB9z9Tkkvk/RvLVOp5Ii4swcAgAVjZi+R9COSypJ+yt2//wmf3y3pZySd2Yv5Hnf/tRNvKAAAwOlx2d3vO+CzRyXdte/fd+pLH9P6NkkvkSR3/wMza0g6L+nipBsqLchgT6leV/0Zzzg0pvOUZ4fT8VJcBrCxHZfirNUbYUw5Uea9d+lyGGPv/Y0w5sI9cdnTs097VhizefapYcz6mTNhTH89Lp2dMfR4e7XPxNvi8xvxtriyFbe52Y7LfbcSy97tLocx7XZc8rTXjUuv97vxdDKavXg6lUTJdLO4zVaKB78zpR09UcY2M69MOcpyovx4OdEdT6rMe+YCQjlxdsi82C5Twt1K8XTKio/3bGnQeSq1OY139szjCwKxuPq2pE/VvvzAz1vdejiNjUac7zTujHMZSTqf6NtHO3HJ9E/9xgfCmN5OXIJbyythyNZ4I57XKM4x1pbj/mQwnEwJ5UnZacbn/W4njlkr///t3XmQpHV9x/HPt7und2bn2mN2FxaQFeSQGEDFK1oGoxJiVdRoFMHE0iRamvhHJOVVpowRU0V5VBKCZWWTWCZVClGrNCsSSNR4IRRsCCwsl8u97MKy9zE7R09/80c/i80wM9/fzPbxdPf7VdW1fXzn6W8//Rzf/fXzPN94/jRKSm1QSWjPXmlMCaapickwpi+hBiskfK4UM1Px91VIqEMa1e47RaNawSe1r0+oZyqTCduWBqnGX1fS50qpvVNq1FZqQg12m6QzzOz5kp6Q9C5Jl82KeUzS6yV9zcxeKKlf0tONTuSYrhjsAQCg07g3rRtX7i4QCAAAkBfNqMHcvWJmH5Z0o2pHTX/V3bea2WclbXb3TZL+QtI/mdlHVKvF3utN7NbBYA8AAG2yxN37mJltrnu80d031j3O3QUCAQAA8qQZQyzZKfHXz3ru03X375H06sa/89wY7AEAoE2WeErZQueLS4u7QOCXzOxVql0g8EXu9AcDAADdL0+n9TcLgz0AALSBN6+7Vu4uEAgAAJAXTazBcoXW6wAAtIlXfdG3BM9cINDMyqpdIHDTrJhjFwhUKy4QCAAAkCdNqsFyhSN7AABok2YUDnm8QCAAAECedOLgzWJ1xWCPz1RU3btw284BvyueUClhdiT1I05ojzwxEcZ4SsvihFaB1cn4vUq7nwhjxg7vi2MmxsMYHTwQhswcPBjGWH/cztWed3oYs+ek88KYR4c3hDE7DsYt06cr8fc1UI7bG7riFqN7DsYH7j26PW7tOJnQnn380JEwptwXf1+Vvvi9po7GLUZTNKytesI6mDKdUl/8nVYTWgpXE1pfTk/G83lmOn6vlPb1KQotbK+aK560u1japHN2gUB0rz5Naf2zrgf+bBP9cetxm4q3JRPr4v25JJUHhsOY0ratYUyxHNd7J563JoyZWbM+jOmzuPfxTCHe16wbjuu9o9Px56omHPhftHjjNZOwi0jZ/Fcq8YRmZuJ8yv3xPFw1Ftdy5XI8nb274pwr0/H+evmKgTBmf8KMrkzH+/1CMf7eG/Wf46R8SvF8TpHS7rthbdUbVFum1HLWoPb1KfO5kPBe1YRL/uVqcKWJNViedMVgDwAAncaVs8IHAACgB/RKDcZgDwAAbeHizCkAAIBW640ajMEeAADawaVqD/yqBAAAkCs9UoMx2AMAQJv0wq9KAAAAedMLNRiDPQAAtEGvnC8OAACQJ71SgzHYAwBAO3hvFBoAAAC50iM1WFcM9lixpMKKlQvGVLY/Fk6nuHLhadTeK25PN7XzyTDm4IPbw5j+lXH70IEXvySMmV4dt/3URNw6u3Bg4fb2Utp8Hn98Zxhz9On9cT4JrQKHdsTfxdiZu+LpnBa3Zz9h7YYwpuJxe+3JatyifMeRFWHMU5VyGFNNaFU6ujJuQ1pMaNe5/+kDYUxKW/XGtaMMQ5Kk7ChSYqYqjWkpn9L6MqUNaaPOYy4mrKelZfGymtL2M1XKPGoNV7UHDiFGdytWJrTiqfvmfb0wfjCcxtTaU8OY6XLcwl2SZAm9vBMsG473xWsv+s0w5uCK54UxK6pxfXWkOBrGLBuYCmP2FEbi96rE+/1D0/H8SSgNtHZNXBetWhnHDA3G33tC+aD9Bxuzf6hUhsKY/oH4c42tjVuvPznSH8Y89su49q4mtHBPqcFS6vOZhNbrKZJqsJSW4AkxpWJcq5T64v9aFxL+L5lS86S0VS8m5FNMyGcm4XuvTMbfqScsG63TGzVYVwz2AADQiXrhVyUAAIC86YUarHE/lQIAAAAAAKDtOLIHAIA2cPVGJwgAAIA86ZUarC1H9pjZFWa2xczuMLP/MrP12fOjZvY9M7vTzLaa2fvakR8AAE3ntWsjLfYGHA9qMABAz+uRGqxdp3F9wd3PdffzJV0n6dPZ838m6R53P0/ShZK+ZGbx1bAAAOhAXvVF34DjRA0GAOh5vVCDteU0Lnevb80wqNqRVMr+HTYzkzQkaa+kSovTAwCgBbwnDiFGvlCDAQDQGzVY267ZY2Z/I+k9kg5Iel329NWSNknaIWlY0iWe0AvPS32qrjlpwZjC/n1hTlMJbbonnt4bxhzdE7cZLQ3ELSv7T1gTxlQH41acUwNxm24lxJQG49b0pVXrwpjhs+MW00PFeNH0Utyy0qopLabjdot9R+NW8Gun7w1jjoysD2Me9tPDmJ374h9bn9wVt0AcH49jhkbiZXVgMM5nYDCezp4n4+kcOXA4jKlMt+7/JyntKFPaWqYolOKDMUvFeL3wcjyfk1qVJvzCkdJiNKVVaUqL0emEtp+1wHz8/9Vd8oTtD9BojazBJJOX5l+HKw8+EE6hb+/TYUx5NK5BJEnjR8KQlLVu5OSxMGbmhFPCmKlS3BZ7YCquG5VwjFVfMW7TPdkXT2jfRNzmftfBeDr95XgfsWY03oeOLEuoG/smwphH98e17u64zNeyZfF+bf3Jw2HM2rF4f90fl046cjhexkZWjYQxB3YfCGNaWV+lSNlEpZx6U60k1Dx9jal5UuqZlHov5b2WpSxACVJq3RSNqocboVdqsKadxmVmPzCzu+e4vUWS3P1T7n6KpK9L+nD2Z78t6Q5J6yWdL+lqM5tz62RmHzCzzWa2eff+hJ0kAAA50wvni6P1WluDxf9BBAAgb3qhBmvakT3u/obE0G9I+r6kv5L0PklXeu2Yqm1m9rCksyXdOsf0N0raKEkvOfv0zpvzAICe1wuHEKP1WluDvYCFGADQcXqhBmtXN64z6h6+WdJ92f3HJL0+i1kn6SxJD7U2OwAAWsAXf2HATrw4IPKFGgwA0PN6pAZr1zV7rjSzs1Q7bfpRSR/Mnr9C0tfM7C5JJunj7r67TTkCANA0rrTrHgENRg0GAOhpvVKDtasb19vneX6HpItanA4AAG1RTbn+LdBA1GAAAPRGDda2blyN5IWiKgMLX2W+vDzuLGCl+CKDAyfGHbKGzzotjCmMxh0BZk48NYzZO3ZmGLO/EHeUcMVXhh/pjztSLe+P52HV4iuxHyqvCmOO+vIwpmxTYcxwJe7UVqzGXX5Sct5+9IQwZueBuKtCJeGi+KOj8epdSDiRc3w87rxQSehisKw/zmfVuri7XKkvXn72PhW305iZij9XsRznPDAUL4fFhJwLFn8ZSdNJ6PIwORGvF0mdrRKaKqR0gkj5XCnnVXfcLzTegTkDz+GyBdbP/Q88Gk7hyK4tYczK009Mymb5KXHXy8LyuGvVwLrVSe8X6ZuJO0nNFOLOVoWE7qJWiPfFBYtjKtV4P3JkIo5ZtyLOed1g3GFzsDgexpjF29LJSryfrVTi2mB0NO6itWZlPH9OWBHvi5/cHy8bxWL8XsMr4lqlUZ22pibiZT6FJRSp5b74u0j5D30xoStoipTuoin1TDWh+1UhYf40qm5MWTZSupWlzJ+W6ZEaLEdzHACA3uHqzPO/AQAAOlmv1GBtuUAzAACo/cK32BsAAACOTzNqMDO72MzuN7NtZvaJeWLeaWb3mNlWM/tGwz9YHY7sAQCgHVyqVrv/fHEAAIBcaUINZmZFSV+W9EZJ2yXdZmab3P2eupgzJH1S0qvdfZ+ZrW1oErMw2AMAQJv0wiHEAAAAedOEGuzlkra5+0OSZGbXSnqLpHvqYt4v6cvuvk+S3H1Xo5Oox2APAABt4HJ5D3SCAAAAyJPjqMHGzGxz3eON7r4xu3+SpMfrXtsu6RWz/v5MSTKzm1RrdfIZd79hKYmkYLAHAIB26JFOEAAAALmy9Bpst7tfMM9rc7U2m/0mJUlnSLpQ0smSfmZmL3L3uO31EnTFYI9bQdPlhVurl9adHE4npT27Dy7c4l2SKsNxu85Dg3EL9wPlOGa8GrcPfc4iNofh4qEwZuTQk2HMwK6H4zfbGx+tNpqy8g3H38XMqnVhzL6E9vX3V84JYx54PP4uDh2OR5BXjMYtEMdGEtqZrghDtPtg3LJy+86EVt6TcT5TUwltJIvxNeNHVw8nTCduNZnSRnJ4ZbxNGBiM26KmGD8UtyqdTmgXv2wgzmfQ4xas44cmwhhPONd52fKE1usJ33tlOl5+ctXSs83M7GJJf6/ar0b/7O5XzhHzTkmfUW0vcae7X9bSJNEVrDKtwu6d875+4LHd4TQevm57GLPhTXGbakk69cS4drLVp4Yxy0oJLZ2n45zKU3Fr8cPL45wnCvH+aNLj7e30TPy5lhXj7e3qkXj7P7wsnj9Fi9/rYCX+7Ien+sOYQ+NxPTMwENcPI0ONaas+XI73s09U4316uRzvQweH4+lMT8W1wcBQPJ8nx+N6ZiIhplHK/fFnT6mdJo/G32lKG/MU1Wo8n1NqnmIpXjaqCf/nGhyN10FL+Oz9yxtTM+fYdkmn1D0+WdKOOWJucfdpSQ+b2f2qDf7c1oyEqIwBAGiTZhzZk8cLBAIAAORJE2qw2ySdYWbPl/SEpHdJmv1D2nclXSrpa2Y2ptppXQ81OpFjGOwBAKAtXNXmXLMndxcIBAAAyI/G12DuXjGzD0u6UbUjq7/q7lvN7LOSNrv7puy1i8zsHkkzkj7q7nsamkgdBnsAAGgDb941e3J3gUAAAIC8aFYN5u7XS7p+1nOfrrvvki7Pbk3HYA8AAG2Sct2jOSzUCULK4QUCAQAA8mSJNVhHYbAHAIB2aE4nCCmHFwgEAADIjR7piBpfohsAADSBy7266FuCZy4QaGZl1S4QuGlWzHclvU6SWnGBQAAAgPxoWg2WK11zZI8FM39mIKFd88SR+H0q02GMW9x6bqYQt77sr8b5rBmPW50vO/BUGFOYHA9jNBO3fda++PpSk0/M/oH5uSqH48/eNzIUxpRPi7+v/pET43yqCa2h4+6hGlsVTyetXWccMzETr967ldCivNKYDVtK2/BqwnsV++KcV66Jl41SwnTKCTGFYry+T0zEnz0ln5RfIKoz8TxMea+RhLbzlYSFfnoy/uzlwXh7OLJyICGftGX16JG0Fs7N5kprebro6ebwAoHoXl6pqLrn6XlfL5Ti7U1xIN43ThxMa9VcWrU6ntb6M8OY8lB8zXKrxDkVZ+LtzXQhbpm+b3pFGDNeSWivPRPP63Ip3ravG4rrxorH73W0kvDZJ+I21PsOxzVPQnmulaNxzgmdvFVOaF9fTZg/faV4H5HSen1oKE56airOefnyeH9dSmj37Qm7vr2742VsIqEd+orVcT0zmFCHTE/FNcZkQs1T6kv43lPqz4RW5+Pj8f+DJhJiknIuxzkPJiyHrdKsGixvumawBwCAjuLNO188bxcIBAAAyI0m1mB5wmAPAABt4T1xvjgAAEC+9EYNxmAPAABt0onnfwMAAHS6XqjBGOwBAKAdeqQTBAAAQK70SA3GYA8AAG3g8p44XxwAACBPeqUGM0+5HHrOmdnTkh6te2pM0u42pbNU5Nwa5Nwa5Nwa5Nw8p7r7mma+gZndoNr8WKzd7n5xo/MBlmJWDdYp63c9cm6dTsybnFuDnFujU3KmBmuQrhjsmc3MNrv7Be3OYzHIuTXIuTXIuTXIGUCedOL6Tc6t04l5k3NrkHNrdGLOOD6FdicAAAAAAACAxmGwBwAAAAAAoIt062DPxnYnsATk3Brk3Brk3BrkDCBPOnH9JufW6cS8ybk1yLk1OjFnHIeuvGYPAAAAAABAr+rWI3sAAAAAAAB6EoM9AAAAAAAAXaSjB3vM7B1mttXMqmZ2Qd3zfWb2r2Z2l5nda2afrHvtYjO738y2mdkncpTzu83sjrpb1czOz167NPssW8zsBjMb64Ccy2a20cweMLP7zOztec+5LmaTmd3dynyXkrOZLTez72fzd6uZXZn3nLPXXpotz9vM7Cozs7zknb12rpndnL1+l5n1Z8/ncj0Mcs7lerhQznWvt2U9BJCGGizXOedy208N1t6cs9faWoNRf+U357rXqb+6ibt37E3SCyWdJenHki6oe/4ySddm95dLekTSBklFSQ9KOk1SWdKdks7JQ86zYn5d0kPZ/ZKkXZLGssefl/SZPOecPf5rSZ/L7heO5Z/nnLPn3ibpG5LubmW+S1w2lkt6XXa/LOlnkn4nzzlnj2+V9CpJJuk/W53zQnln69sWSedlj1dn243crofz5Zzdz+V6uFDO2eO2rYfcuHFLuy2wflODtTHn7HEut/0L5Zw9Rw3W/GWjrTXYYuuCPK+D8+Wc3c/lOrhQztlj6q8uu5XUwdz9Xkmau0DbRQAABzlJREFUY1DaJQ2aWUnSgKQpSQclvVzSNnd/KPu7ayW9RdI9Oci53qWSrsnuW3YbNLM9kkYkbWtmjrMtIWdJ+iNJZ2d/X5W0u1n5zWUpOZvZkKTLJX1A0jebmd9cFpuzu49L+p/s/pSZ3S7p5Can+SyLzdnMTpQ04u43Z4//TdJbVSs4WmaBvC+StMXd78zi9mRxfcrvejhnzpm8rofz5tzu9RBAGmqw1qAGaw1qsNag/moN6i8c09GncS3g25KOSNop6TFJX3T3vZJOkvR4Xdz27Lm8uUS/2plMS/qQpLsk7ZB0jqR/aV9q83omZzNbkT13hZndbmbfMrN17UttXs/knLlC0pckjbcnnSSzc5b0zDz/XUk/bHlGsfqcT1JtvTsmb+vgmZLczG7Mlt2PSblfD+fMOefr4Zw5ZzphPQQwP2qw1qMGaw1qsOah/moN6q8ek/sje8zsB5JOmOOlT7n7f8zzZy+XNCNpvaSVkn6WTWeuoe+G955fYs7H/vYVksbd/e7scZ9qG7kXS3pI0j9I+qSkz+U1Z9WWq5Ml3eTul5vZ5ZK+KOkP85qz1c5lfoG7f8TMNjQyz1nv28j5fOz5kmo78quO/WLaSA3OuSXrYPbeS8m7JOk1kl6m2s7uh2b2v5J+qvyuh/PlfKfyux7Ol/MetWA9BJCGGowarBU5U4Mt+L4dV4NRf1F/IT9yP9jj7m9Ywp9dJumGbDR4l5ndJOkC1X5ROqUu7mTVRokbaok5H/MuPftXg/OzaT4oSWb2TUkNv6hhg3Peo9oG5DvZ429J+uPjmP6cGpzzqyS91MweUW29WGtmP3b3C4/jPZ6jwTkfs1HSL939745j2vNqcM7b9ezDnJuyDkpLznu7pJ+4+25JMrPrJb1EtVMQ8roezpfzj5Tf9XC+nA+rBeshgDTUYNRg86EGewY12CzUX9RfyI9uPY3rMUm/ZTWDkl4p6T5Jt0k6w8yeb2Zl1TaCm9qY57OYWUHSOyRdW/f0E5LOMbM12eM3Srq31bnNZ66c3d0lfU/ShdlTr1cLz8mPzJPzV9x9vbtvUG3E+4E8beDmWTZkZp+TNCrpz9uR10Lmmc87JR0ys1da7UTi90ha8JepFrtR0rlW67JRkvSbqi27eV4P58w55+vhfDnnej0EkIQarEWowVqDGqwlqL9ag/qr13gOrhK91Juk31NthHJS0lOSbsyeH1JtFHWraivXR+v+5k2SHlCtI8Sn8pJz9tqFkm6Z428+qNqGbYtqG4/VHZDzqaoderlFtXOYn5f3nOte36D2dIJYVM6q/SLj2bJxR3b7kzznnD1/gaS7s3XwakmWs3n9B9m2425Jn697Ps/r4Xw553k9nDPnutfbsh5y48Yt7Tbf+i1qsDzknOdt/5w5173elm3/YnMWNVgzcqb+amPOda+3ZR3k1pybZV8qAAAAAAAAukC3nsYFAAAAAADQkxjsAQAAAAAA6CIM9gAAAAAAAHQRBnsAAAAAAAC6CIM9AAAAAAAAXYTBHiBnzOxwE6b5ZjP7RHb/rWZ2zhKm8WMzu6DRuQEAAOQBNRiAbsJgD9AD3H2Tu1+ZPXyrpEUXGgAAAFgcajAA7cJgD5BTVvMFM7vbzO4ys0uy5y/MfuH5tpndZ2ZfNzPLXntT9tzPzewqM7sue/69Zna1mf2GpDdL+oKZ3WFmp9f/WmRmY2b2SHZ/wMyuNbMtZvbvkgbqcrvIzG42s9vN7FtmNtTauQMAANAc1GAAukGp3QkAmNfbJJ0v6TxJY5JuM7OfZq+9WNKvSdoh6SZJrzazzZL+UdJr3f1hM7tm9gTd/RdmtknSde7+bUnKapS5fEjSuLufa2bnSro9ix+T9JeS3uDuR8zs45Iul/TZRnxoAACANqMGA9DxGOwB8us1kq5x9xlJT5nZTyS9TNJBSbe6+3ZJMrM7JG2QdFjSQ+7+cPb310j6wHG8/2slXSVJ7r7FzLZkz79StUOQb8qKlLKkm4/jfQA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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plot_dataset(model_output[['u_surf', 'v_surf']].std(dim='time_index'))" ] @@ -136994,40 +429,9 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig = plt.figure(figsize=(20, 30))\n", "long = -172\n", @@ -137061,120 +465,27 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/analysis/lib/python3.7/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n", - " and should_run_async(code)\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "((errors_ds['S_x (normalised error)'])**2).mean(dim=('longitude', 'latitude')).plot()" ] @@ -137188,68 +499,18 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n", - "/home/ag7531/miniconda3/envs/mlflow-2428cb47d93b4486f90b5f8bb1835e697d4a2328/lib/python3.7/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide\n", - " x = np.divide(x1, x2, out)\n" - ] - }, - { - "data": { - "image/png": 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y2eFptbMeNCnimzUNhCYao5vDB5HtdGd7fjpw9beB6//TvF9VOD17X9YmE25GN3c7B8IlbeqxwINnlkxA6Sd0us+Qc9/tAeNdt6nL4NQjITvI4DSRYDW61Ok8dJb4DFVFhK6YR1SgzQqngktdxetJK3x/DQansjHCyIDRHdT7bnt2plXqpp/T1mwRBEG0hVP3A06xhGa46j+A094dnlY7jROmtJc+lvxDRuy20U61jHymqxea98sxQqsJnPMx4Iz3tS8v44lecJeU/eg689KpfnFDUWWRUbu+8XGjB8olyOA0wYgMGq5WMmufA247zF7xlF7xrQcG+ON15r/dCqeCS52hXMXkQXaw+ieFn6OyaoHypaz7UA+Ux/GMqTxwDtzyq+y7jKlWKE8Gl7oZF9SaPYIgiI6x2aJwisXVp5txAbDuefv+Mmk/O03uLJ+uidEhYNZVNPEDtFfhMbCV+ByxKHLk/ZehQ9aOwUWSukEvKJxYv/j0CQus55d0qasD1Q2QFE71KZwAfyidDkAGp4lEGsPJp3AyDOyu+AYw9ff2oJSpwSmySPWCwmncBg1vt8JJP85kcIp4vqnCKdDg9ORfhSsnIJalPentorMKKCqZ8MuL47tVHidIB9t0f7esySuV0g6Tdk9MCqfGGIylRxAEUSe2weXm1cCUg8VCN2V59t7y58Zy99HAFV8XK0FPdNqpcJLtsM1AIscIPeKKM2boBYWTdcKuVGI1phVATuFEBqdaDU5Da+tLqyTjdaRNGAlVOBliOMmKwGo1l4PASLVQT8xkjVeFU02NhDWdEIVTjMFJKpwGwo6/+EvAZV8V/0tDaMEgGlm+eqI8jmNMxm69UY3pMDVKBsacyOhlPLRjt2oBcM8J9eeHIIhItHfYNoko69bNKx1Jedo8p9tyzX2nLcmgaPXT9abbqzxxrT1WV52DzULaSXmxGUikumQsLo7UDfqSPmsvGJz6kv5TaTdbQwynbrjUkcJJC6Ie8Qz0Y//9emCbF9eTpwqQwWkiUSWGUzoI9LnUhRapGi3nVStDcqnzJWTeHOJSF9PoVXKp0/NYtnx12OA0XsueDVMnWlcppXWNVnZMysvmCLByPnDm+7PBCmHBUNbmXA8ctnNYgOLzPiVcHymALEG0j5h229enS9s/Rzvjul6nJ2C2eYn4rMvVsNe57Kv2WF1tjeGUpD26RUzS6avVrZrf/jyMJ2SftaxL3fK59U3mVHWpM9EVhdM4jeE09wbgyD3CjJNlV+3Tj+0RL56u5oIxdjZjbDljbJZl//sZY+sYY48mf78yHUcEIgudz5fTaHDyWLrlsd2I4USqFAsddqkzriIWY3BK5Nt9gQonE7L8sZKzPL3g4jmeMa54pMn2fTGcci51Q8BdRwJLHgGeurmuXE4c5lwnPpfO9B87vLG9eSGIiYjeHyszyLe1W2m/zNHVd7XRZfIy83KxYvEmh6rKhpyFH+8Gp5DBdDuXMpfPdXgdcPo/AFN+aD6OXNbDGNxafA6tK3f+2R8Vkzl13O++xOBUVuGUG8OVjYVakpzBaZy6c978S1FO1i32H6s+Q1sdv/ppYPp59vOAnpnY7rbZ61wAH/McM5Vz/tbk79AO5MnNmDZuRAYNz1Uyybmzr7K8KBaXumYDuOhfgMUPa1mpU6pZNY3eeBlrp90KpxCXuiiFU9LAlMl3QeAUqOYrpDOW3+82UPf9MCmc9EGNTU2ZKpyUbdQhrkaplSHHaX05QWGMfYwx9iRjbD5j7KeG/V9jjK1QJv7+oxv57Hk2rRSGlunnxp2nuwWXcaWyTSKGTAS6+oNlXJbv/J343LA0/lxZ94+nweaGF4Aj98yrSENWjWqrS52W9oq55uPIpS6MrV8kPl2uqy6k2qWOCc9U4VTj5Gmn+sW9HDT8+RnAY5fWkFBE+JkQg9Of/gm47ofuY0nhBHDO7wawupt5iGY8DEh9g3DTsuRy230nA+d+0pCmpWOz5hngqZuAq75pyUsdCqeKFWuPWH/rpy6Fk+X+Bq1SF2HwSTtBdeR7jLjUpZft0XqlbsWXaWCkd2ptxsIb/694bmO4eO9emAXc8uvevae9hOzUVVEVEmMWxlg/gFMAfBzAGwEcwBh7o+HQS5WJv7M6msmxglwl9ZGL/MdyTaWpUmagZWtnZZvqVDg56nif4cfUd5ITkmUUFvJ646lPNu9GEbD3gdOzbSHuNG11qdMMTjvsZj6OgoaHsdVO4rOMqg8or8g3UafCyTQW9HHpgeWuC/S2S90fPwBc/a3q6YSs6N4YEerzkBhO0sjJObBplbhventABqdg/p4x9hhj7K+MsTd1OzNj2uUmuPIwHae8HBteKJ6SuuHpL4XNmksxnNpObUHDQ1epsyx5Lz+Pfo199nd4Q1auSuU7uc7wRm2WpNdd6nq87Jnux9wb4mfxJWoDKpdk1jvWfYYZulzZUmM4GWZgz/0kcM/xwPD6cnkc96j3L3keQXHTIurZVkusNEVGv17nXQDmc84Xcs5HAFwC4DNdztPYJGaVVbVu040PMW2WfL+sQcPldkc747perIL0uDdl96FMAGXZFoz3eiPEmNROhYd+/e1fZjmOFE5ByAH9phXVzm81RNtpWw08KK02xHDyob6vc6ZUSCepF1/+5t5TOJVl2RPahoC67Y7fApf+W361Tt/YZHg9cMyrgZt+ZqjTe2Oc0esGpxkA9uSc7wPgJADX2A5kjH2LMfYwY+zhFStKvvRBjOWGMCl0vg6NUeGkFBXTbHhqWLAE+i1YWJPtdx0JnPE+d368kEudkY671BmOk2Wt1RCW+Ot+ZE7qhH2ANcnKNGWMPvLaD54h1HRlZmbUdAiB6f5dcoD9OXrTS8rD0pnA73YFnphiGNQYnp0ajNP7jDyDsImKybBeyqUugAfPFEuxP2FtsoneYDcAzynfFyfbdPZnjM1kjF3BGHtlZ7I2xoh5l9S6SVc4BSlbAtTFalplFU6xLnXrlXALIW5jOu10I+slQowB7VR46Pd58g6WPLR50H/fKcCz97X3Gp1A3s+qBqe7jwGmHiviai15pGRannHe5tX5SdliAsVNvj5XXf1mWRf1Tx4/AetP+3vzdpfQYd3z4lMVd/jGMjJ+2BNTyKWuDJzz9Zzzjcn/NwAYZIztbDn2TM75vpzzfXfZZZc2Zmo8KJx8jZ3DpQ7IFAgq8li9krO52qkV1NJHPfnxMNaMBIe/Arj24A5cqM1Bw0Nd6oY3iD8XapDQqu/YnCkVJMrdcqnr0Xqldpe6pGMmZ/CevMEQNNwQ323GBQGJy4DxbYhhMJ5Q72uMS116XsA7Io3HJjUs0UuYer36A74OwF6c87cAuBXAecVTOjnp16PErLKq9sH0la3a4lLniuGknatOAFSJpVRK4STjOAbU3UtndrfvN7QOmHqcfxEeE91WOOlpy6DXOu2OkXjTz4FzfGF8xwDyflZ1qbvvZOD56eL/9UtK5iV5n211wtGvEivOWvNSwqWuLjWVvM7A5PFhfDYZjUPqLNkfUw3+vmcgnztjBoNTb4gqetrgxBh7OWPiTjHG3gWR3+4uXzGWBzGxqo/ci6EanAYNx1gUTnL7ynnCsq5vr4Ux5lI3ugl4JGQAXZG2K5z0wyxBw4/YXTRywZcrk2/lHNaHzGg6RoKG92q90i6D08Bk8dkYtne+1Wvn4jd5nlEaw2AcdFhqxaRwinGpSwh5R0JWxyJ6gcUAVMXS7gByIx3O+SrOuRx5/hHAO0wJdWzSr1dxKZxWLwSmHZ99z6k3bUHDI/olVpe6EIOT9j7/9qXZqkdlgoZLqrjU+QwyC+8Czngv8FAXw4nd9Avgtt8A8/4af+5JbxerS7loawynQJcb1aVurE3sdhJ5P8sonFYtEKsFpkQElTYh+7wuQ+jiBx0JhMxBaNSlJlcNTuNh4QCjyjPg+aYGJ9Xga1shXh97M1qlzgRj7GIA9wF4HWNsMWPsIMbYdxhj30kO+QKAWYyxxwCcCOBLnHe51hvTla6UWnoGkSaFgTpw6DcYnNJYAlraahp//lfz9qpUTWtMP1MXbVY4hcj6y8x81Lq6xhhxqevVMtiuoOE5g5M2i5rGg7OtvGSLE5cgFU7jocPSbtIgvRFdgRiD03h1Vx4/PARgb8bYqxhjkwB8CUAuCAdjbFfl66cBzOlg/sYOrhhO538WuPXX2aRbzqVOG5RII3BMIH9bXRkSw8l07m2/SfIWUYfqg5wyBidpIPOpe6SC8oWZ8deoi5FN4jP0dxYWt/DE6elkDCdb+VGf/292Gh/ub+2gikvdae8xby9rJJB5qTOGk9elrq54sdKlblJvhUQoa/w1uS6m9ibH8+0PVDhd9u9ZgqnCqY9c6kxwzg/gnO/KOR/knO/OOf8T5/x0zvnpyf6TOedv4pzvwznfj3N+bzfzC6B3lQghVAkannOpUztCmsHJpnACgOVKP7XWAXZVg9MYfqYuavOrDnSpMz2HkEZjieZSWSWGk/zf58duTyju8FYTuOMIYMuayOsklI011SnapnDaSnw2h4uGoVQSbru2T+GU1E/digHwxLXAPSd059qxpIOakHKvqVkX3S+WgTcNnEJWYiG6Due8AeBgADdBGJIu45zPZowdyhj7dHLYDxljs5OJvx8C+Fp3ctvjuAxOW9aKz6NfBTxyoeZSZ1mlzhS6IEV7X60GJxnDKTZoeHJ8jMJJX6ShMSRcdx78Y3ga8h766u7UZb6L7aZpYjaGyzyrebU1hlOgwUlvmxfeCQytB/700fIxhnqZK78p3s9YZL9Gvucx6Abnqv321Ghbh8GmSy51/YO9o1BvtYDDjJF8/Oju0gDiFE6qwclQLtQYmS0lXh+tUjdO6NWBYRCBbkayIZ17ffFcIG9w0l3qCjGclJekTy1upHBqO3W71G1aJTqPtnSNCqeA9+VMLWh8VZe63OY2u9TNu0kEvv/rT+POK1644vltou5ZJvk85KCsMVycRU+N1yXr2j5lxZducNlXgVt+1Z1rB2FYpS7mXsvnM+c68bnwTsMxlth9RM/BOb+Bc/5azvlrOOeHJ9t+xTmfkvz/M2Xi7wOc87ndzXGP4nKpU+uiO4/MG0p0hWcrQuHkm1hJXeoMXf3RIVH/mt79rZIg0j6VqNpeDm/U0t8iJpOWzXKnoRLqUid/T1f747JuC2y7Q+vC1JjWTpc6rW3kLXPfxxRfcealwHP3Aw+cUS0Pvdjvfvwy4Nrvx5+nqopWPFlPXjYsBU7ZLwsgHZwXj0Lch7GcTmCF0+imCueWUHkCWdiamBhOsi/HQKvUjRvGssEpVvXxzNTiuUBR4TS8MZMXuxROTJmx6ymFU5eWD23/xWpKJknnll8BN/wEePouy3ElDU7Fk0qcop7DywcNj82v7BSObHQfV9d1mw2xioneuW8XrvJapkOQDqaSuqAxVOzURrvUJcg6Sj57cqnL41qlLqZe0p+PvN+3HgLcdYx5H0GMd1xBwwsDfKXu1OupZkQgf1N6puua3sOj9gKOeKX5XLlqmS9otFpH679Rqlej3PJG8582esHgFJsHlxorNzErFbol2y/OgWfucdfpBfUUNx9vWkF29ULx78veVC5/6SU7+Oyeewg47k3lFEghqH2hU95lP+6BM4UqeCTAiDHjfGDFHGCGcY0GR16qutQxYShetaCo4rv5lyL/hWvWrXCa1DsKJ9+CRy5MCqeQxVeMC3N5+mhqeARyqRsv9KBVPpia3Hf0GE5H7Jb51LsUTqxXFU4dbPg6WYnWrXAaTNygZpwvGp01z2qHWYKGR1+uhucxJwlDEn0PIo9PV0TrUBl86ibgtkPF6i6dwLlkduAKNupxurtcY8g82+q8do+71I0l0kFNSFwmi5pV1uvT/gDc8dvkEDI4ERMMl0tdbvCnBXXVDTJyn9OlTk/f5lLnCEDe2CKMQqZzJ22rnQ/gI4e5r2vq+zVHigouF6nCyWNs6YWVSFODU2Db7+r7qQaItP0q2Veccx1w7ieAh/8UnhfesvTftDaUsezcmIUmTMS0z/NvE0a0stzyK2D94vbF/Art19+dTMgMrXccpLvLxoZ5SPJStv/DmPA6OOntKIwZ7z0pO27OdWIcsGVNGxROPeRSp0/uxrjx6gpcckWKAAAgAElEQVQnzpE+X9dzda0EbyOtMxm51I0belEGGgoLdKkznqsUFXXmTY9do78U6ve+GhVOK+YBVxyUVKpjyODU0UFwXQqn5P7smCxmNOtK8blukfm43LZuBw1vs0td2umsOMMTet1J24nPlU9Vu14ormcROpC47sfZ/wWDk2HAk66yYrmnvnvFaJW6YNLZ0BiFk+byaOzMcMc+ghiHSMN6v0GZVDDGqAon3aWuhMLJVlc2HQqnNC+OiSI1n8b8qLETtTw0R0XaoRMT8hzAb2zphdiH0Qonx2/arCy+Le9zWZe6tUm/bNWC/Ha1ji/EcFIGwk4Ug1PVuj2mfb7w88KIVhZ5f2X/qW5aDQS5LUkXqaB325He41cAK+eb98n3UL53Q+uBeTcXj1v9dES7bzhOxqlc+VSNBqfkOr2scIrp6+sGp1YjUOFkcMv2GpyUeH26UaxHQhtQbzCWsexSF6pwMhVOm0udHiiykHabFE7XfBeYdYWQfo4lhVMn3XzqbgR8HQzTY+iYwslSBtTrH7KjmCmr89p9VWdaIzvOMtj2+sUlrxdJHQqnhXco6cmBTPK8GkPF9zdVOAW+1/pxve5St2kVcOmB7ZP3x+AN0G7A5lKXOyYgMCZBjCdWJQPASdsbdqr9ILgVTp1yqUuPMZxrCjxsyo9L4SQH1zEGp0671DUb5ZVEsXlwDVS3rC6mW0WhYry+IXZfus+icDKlrU9SbFgWn0egswYFeX/bNeHbagKD22TfbWVeGiBkWTC5pxX6M4bneeVBwCnvtORFKpySPFz3Q+DPXxQGSDXtE99qicNluJ6rL8Z5m1zqeiSG04hmcIrJlx4QvtUI69/66loT5FI3DhkPCievJNDUYFkMTvrLV5jJU1e6q1HhlFOWjCGD01h2qfMeVjKGk4wXkZ5Tp7ulVh4fvch3QuQFapppDTauJL+nil95DHUYnExxPuS2VgtFCbk83nZPxohLne2Z3nuicPl8+OzO5keSW9HRd69zJ+Y/ZVl0GZx6pKNDEMHc9AvgzqPiz4sJju1UOAUYifT639anS9NyGH5N9VRqcFL6KyblVk41o/VtZPsgf1+rBWxeDSfSEOJ1qavJ4HTi20RIiDLIezrl4LDjO6VwkhQmcpQyN7xO22cJGq7DWH6S4rFLgWNfK2IkxdLJvrB0WYxx74yCAwOTs6+2vlFqUHUZLWTb6ZmssbrRJmnL/o8MfbF5dfEZP2twU1Sv61QSKsfV7VLX1z8+FE76fQn9TT41qQlyqRuH5AZPreKStmOB0FXqctuUoqLGcHIFwwTyHaE6V6lTOxyVlxHtoCW9o6qLmoOGl1mpIqRy3nYXfzo+QlfOGzEtUxqQjo3agpdWMOq1kzoMTiotTeFkukb63dLh8r2vrlXqZlwAHLFHZ95527veCwFvJbFqMvVYp8KJYjgRY5T7Tgbu/F38eal6IeC9VvtFhXo0QB341//VTikRwyk911AXmtyamSeQrZ6OnN2Xv+/2w4CjX+U2Osk0vC51hjp0ySNCMbIuQv27blF+JagYguu2gMV61H6JVE2XVV7ZVs+74HPAkXuK//VnEKpwUl3qwIFnp4l/l8+Oz2YnDQqy7MYEsI+B80x9DgSs7ugoC1XVwbKcyfducOvk+5bidVfNB279jZZA6Cp1ybbRzXmDaRV4S7xXfQO9Y3DSA7zH9B31d0oNAeN630rFcFJd6npEHaZBvcFY1If+1/8BDn9ZXBCxblJluXGbS13BwORROF16IPDIRTUqnGq4951UrcWqLmZdaQ7QHUIvKJxC3o1tXuxPx39xy2Ztu281uWiXuorlMDYWRacbEle+1A7BqgWi42Iqc6ZZcJnu+sXA03eHXzNkv+xcmt61G34iZnfVQd6qBcDQuuKxVbEZ5GKDzdaGYSBSxuCkd5jI4EQQyuSj713SZqD1eipVB0Zc2+pSJ1WILoOTI4aTWsf7BkF6Wy/rP/k593rxuWmFPS+tCgqnh88Rn0/d4j63LmLrNlffTzV6hSicHrlQGNhc+eI8X68/MxUYSty4dQMBNyiNjWkz4LkHs/TT80u0ZZ00KMh+WrsUTtJQIvGV35B+XEjcHVMcJz1ouDQ4jQ4V3/XlTwDTjnNlQny4nu8FnwXOeK8/ryH0osGpEPi7isKpqYzDXe+MqR/t6ffK+oL1kcJp/KAUhIfOSjaNEYOTvrqQFaWiSzsRgS51ekHPBZ3sF64k136v+j1TY+dUdmfq4aDhs64Sn0sfLXGxmoOG+zoVIxtFp88162lEa1jbqXBa4ruPJRVOVQ1B0XEgOhQbx5kv5V5d+HnRcVm/xJ2GKWbQkzfkj/cZKX3lMJ0hNnX6DEaXk94OnPURd5pl8CqcOmw8NHVgY1zq9AkL+d01EO2RYJUEEUQVI3AjRuHkcKkrNXi3GZyUQYgNo8HJtLS6q/7Qj0UxhpNc1czVB0oNXb4YToaJmtRQ06GBanDdJvvdjnypg9o+x4SJ5NrvA2e+350v3jKrt278udngFFJul87MVqTmLVjVVCF00uU9VTi10+CklAffdeoac5z8juI2PYaTVF41tsQbuliAwUnHFPA6FNXgBC4m25c9UT69OtDfoZjYm/p9azUAPTSB8bwS4UlyLnUUw2l8UDZOTS+gB3u1oVY43DBDtuD27H9fDKecJLtOlzpFpjyWgobH+uXLQIS6lT2EuoOG+9L7y0+A638MXPpv2baQBs4VaL4yusJpg9ugEVuWZKDYymUw8PxOqyldz1zNs/RzV+MYZAcq/wYEqfYZK0IVTq4Ovl4uVz7pTrMMtk5n5UDzJTGqz5I8XPSFcBWlTCdVTzhWqaOg4USn8NWhjWHg9t8WXSRURhXXpti6ViqcQt5r1ThTcPOJaEseu1goeh65wLw/JIZTSNDwT5/sMVijWN/qMZzS2HoO9YdMz+dOZurLdtzgFDl8cqlo1UFt5VVWFSPQ4S8v7r7/FGCxFnNJV0PZyKnTeNyEwppn8gHG1XLXbuW2Pgm1brEwZjwxpZ709dAelRROWtvpey7L52in6y51yRhiZHNgnyPUpc7y7PvrMDgpk1jqeLNuWk3gmu8DKxz9P33sdeJbw9MvGJxG/QqnuX/JhAZAuCKeVqkbh4xpg5MW7NV3HGCJAeAIFFmIx2KJAVCrS90YMjjFxnCaJA1OnthDJup2qfPdJxmIUkrnQ84xHVMq35ZzjB1X18xC5LX/8t/JeR1S2ZkMwO0kVPbrimXnChruO964X6+/tDy6FE6poboDgxKbfL9rMZw8Mu3HLolLJ8ilrjc6OsQEwPc+PXIhcPcxwNRj7cdsWZP9r6/A6yNU4aTH2IhVOOkq3Yu+AMy81HxsSAByl8JJfr7hU/AORK2r1CX1sByIOicCAl3qTEpZaXDauCw/SBzZDMy5zp1eKULrtuS4JTPsh+QMTjWtUhcVly9Q4aQaE3LqtoBrnbCPCDAuUctB2ThaoegKJ6mamX5u2PnDG4ANL9j3F2L11BDDKbTtPHW//Hc9aPhgonAa2egf+/nyFEJZg9PTdwPPz1AUTgnGScyaWDYbePRC4Ipv2I8xTRxuWlnc9vTdxUk7Y9Bwj8Lpki8LV0fJpO2SwwODhpNL3TjCWCl7CsLqhUUrdKe59+RseXLvzJ3BoGRVG0TEcMq5XlQ1OEmVQODMjItOurbEBoJUZyeiqTloeJn7HHJvrUGja+DeE/3Xy+8sd51OBQ3vpRhOanlIB1u+GE4BCifbbH1IngAErRzYCWOPLUBpbNyuujC9x7nn5SuD2vlkcCJ6CW+Mi6TtHXIYktTBRUxd22yEGdMBFFwe9AFNus/y7pz5vvB8pb8hMmh46tqWfPYN+BVOBZc6GcMpMSZIV5s6XOpMCie5it60PwDnfTrbfvtvher6mWnuNGOpcxCXm7BJ6tfKC8xEGpxCjpdukUDSDlRwqVOfcbtc3ST6JNTApPx3wN2/PeN9wLGvs+/nHNh6p+y7Lzi5q26pOhmmu9Qx5bdH9zlK9FXKutSd9ykRZ6yTBqcUR/3YMHiXmMrCeZ8CTniLtlFXOCnPPXQ8JV0iyaVuAuJyS7Bx4tuKVuhOsXohMP824OZfZNu8CgLlNx6xO/D4FXZZo0/hlDNuqa562n2stDrYOFY4DY4hhZOJMi51dcZwMt03l6Kq7D0rXYYiG/RejeHkctd1BQ03sdzjs+/tkLnKay8onKTLRKdXEjG1XSU6QLpSlvUZ6vMxovolxg+mMrd2kegDAWHBmNV6Icb9XR2U8BZw7cHAye8My2uhT+B4DxfdH54nIO9mYc2Lcr1X7ge85UtFhVNfv9uwDBTrM6kykr+vP+D+c02dYT3O4VIHAIsfzP6X8YpWP+1OMxb1flTta+nlB7C3UYsf9uSrjMIpcOJWD4sROqFgmuTuhsJJlkVpFFGv62qzVi9wp89bwGs/Crz5i8l1fDGcHG2/zKMtP6bntEmJyaUrnNTtIW7CphhOpjrJ9uxVo2QZCganrezH+uBcxJUNWRRm/m3AxuXF7Sb1fmj/saB8U13qAvtI6f30jJmlkdO4Sl1vTPyRwSmWseZSd+LbREBfFa/qRCvIVx5kN5TEBA133afYwZdqcKojhtOy2cAxewPP3FMtLR+xA910hYnNwHFvAm7+fxEn161wKjFADno3KhofTWk4D3UNjssanDoUNLxXFU7ZRvGx4HbhvqJuk+k9Px24/N/917Z1aGzvkH58nfVNGWzXb5dL3dpF7vqrzGSJOaH8uazP0A5UUEUSRBlM7/TxbxZ9ICBz9XCpjHMGp4i2Wh2UcC5UmivnKQdog7iWo1/kemfO/mh4noB4l7r9vgtM3k7kb+VTWYzCvgFkv8EycVhwqdNWqZODfJfhR19hy3qcw6VOZ9udxedmgxtMFdR7WrU90cuPK82zPuRJrMTgMrQfbSu3vnOHDIGW1bTabnBK7oksi9LoWVbRqMNbwqi17zeK6dqOtzGqueYW+jWGe33Mq7P/00k9zXWr1Qhs701Kxog+ev+A8KhR43XFwFj+Xba91yE896CIKytDX0hS45vyOy78vLl+rVI2Q13qFj9sj6Ep2y1fO9FUDE7kUjdO8LmMjAViFE6xablc6lwNVOiAfWidcC/LrfRU5v6rnaaW8OXetNztZ+/jrA8Dh73UfUy0wUkJGr5+sdlFzEaVcmlS/ZQZnIbMLFRVR9z4c+DZ+8KPdyqcShoBKsdwClWXdNoNK9L9UB5/weeEKwNQVDg9eWNt2ctRCJ5pyHs7YjhxDtx3atFVp9MGpxPeCpz7CccBvrbLUwYLq9SpBifLALGXJ2OI8YXX5SApo8EKp4g6IlQpkR7jmoirsT8ZYnDSF3Zh/WKC6+R9gUcvSrb3Z3WnGhrB6VKX3JPmsKg75MDp+h/bjU5SgVHGpc42MN36ReJz0f31BiBWDQGxi8HoNAwGp8qhHtoQw0n9nTmXOg+bVxvSUhVOHXapk2oQ9bohv99krOYckGqv/sT9y2swdVxLxo6z5sfxXNcvBVbMzZ+ffjbDfuPy2coXhwLf1mddu0h41Fx5kP9aJvSg4VUMgfK9Wr80v/3QFwMX7V88XqphTWmUwWRwMk3GnfUhgzteglQ4+TxBcjGcyKVunFDXLDGEEeG5B/3H1U2ds/sFlzpHTCeXkiS0c3fkHsCpf5dVSE/dUs6w0qcFMJd566/gL7z4oWpSWhNVBqdVDE65MlLB4BTS6PBWvrMYe537T8lL6P0XLF4//b/DLnWx8Xx6yeAU0wmRrHkWuPvowItHztRKRVWIgTT2PdyyBnjuIfO+BbcDN/0MuPGn2jUs9yJ01ZFYYhaDMJ0T7VKXfLK+Ygfb5WJJEHURM1kg3audMYSUfkhMvEXbwNUWy8WpcLIoG8oQFMNJub50Z8m5ojOgTxkq2BZ/sSmcADEYUtv4DdoAME1PUS65+qnpccr11T6dnKgTB4mPeTeKiZAyK/6aUAdxZQN8SxqGGE5lJ0XKtC+hoSmausEpEJOHhJqW+vsbI2L1uDrbR1nG9ZUTm5EGp1HDCpdqO5iqKCuMA+TElfr7p/1BrKo3stl9X457faasTNtgWZ5aYf2ee04wZVj7GvBsTKq2EHSXuiqxzFwTjAtuD+sryrpwt33tx9juR2GVOk3htO55YOnMbP+6xcU0rAonk3oKZsV5j8TSJINTLHW61N3wE+BPHxHLhXaSMgMTG/qLrFvubTN5hRcxYgC4dlH2Ak0/B6VmBHP+9x0cFEUb++RvK1NhVDE4Kc+1isIpBN7KBxps9/NwVtwdNjil5wdet9MudWe8177P6FFnuA+7KAEW7zqqcpaK1wxs7AFkMZwMAxYXF3we+NOHzTOTskOyRetg6ffi/tNEB0MOjDpujDFIuaPKfrJ/1Xxg+VzlXG6P5UcGJ6KdqOXryFe6j9VjCpnILdUeMeAvKD8SUoWv+m5pLg8xLnWxpL/Bkaaal75+bXEXZIM/n8JJv185I8Jw2OpVOYOfK9aTVEKpeVfSn7Stcm3teR/+cn8+Qsi51FVUzKpthy+Gk435twKPXlxyUQoednzumfCIeFGG/TaF09TfA5cdCMy7KTDtANK4RpqySS0bIb/fuHiPYnCSAa59iq1W0/67UoWT0ke5/3Tx/9C6+MnJ1OAU6lJnSkvPK/cbMWIem5q+bnCqoh5M3RNt/WbP2KY5Klaf2/MfgHcfbL+ONd6WxSgEiN98/JvzfexLDyymIetNfSU9m8Lp+elFgz4pnMYodXagpWVTXYq3E3h/Q4zByeFCp+/PvfQlFU6SqgEbmUWy2W5LcKzBQB5fJl+VXOoMz6pdxg7e0jqjbXZRdbkwyFgGIffOF2y8ORoWpFHPg/OwCuWhDnwuWKa6pdUAdn2r/Zx24XSpC1gtTyV1tXW4pbliSK17Xiig/vyvmjtwB/GV6dD64tKvCJWp2qHVB/F6Z5cg2kFMmzSyKf+pM/U4MQGYpm1xnzGplnIDCeW9t7mU5ww1+m+oMsmk52u0eD2d8z6V/a8P9gDle5IfZllt2LZKnfxfDSa8eTVw9XeB4Y1afpU0QgyDap1rCzRsUptUVSQB9SqcNr6Q/a8qUmK4cH/gmu+g1MpxoTGcCq5/gWXUVP7UtFTVmXS/kxPxdYy55PupxxWLVTipz0k/j7GsjHuD3jvc22ReX3g825YzIkaGX0gNV80KsXItMRrrQi0LBYVThXdrJKlfWg1g7g1CJbZ2UbY/fcdsxr8Nog7f+yNavYf8PbDl0ehSp+zT7+uIVh8CmddNLiagIW21vrztMHN+ugwZnGKpLfAqlFVTOjwL7LteFYWTSz1i+9/03Ye+WkYs1jgE7TZ2RFb4ad46rXAyzMC2TeHE7c+jXdfLfdee/6n7Ab97hT+dXLyPJrB4OvDsvdm2w3bOd+adeQr8zR1f2UzD+65Y6sdSS9tWfBeN91STWMeWNePxNoWVQT20eVV239r5Ppl31Hsd1WhXcKlr828kCCCufMlB7fB6834Zc05iMjg9cAbw213yq0Lpx6p5sl3LVY9WXgRFdXOTq80FthtGg1N/tg/Iu9flFGHas1AHkc3hvALp7mOAx/4MzDhfy3ugwkzvF3Ged3dS2xuTgdAUUyiWumI4bbVjPsCy/G3NYeHeFOsCmBonIs4JjeFkjVVWYjJDNfyqxkkZc0u6ZNVhHEyD0WuGppAYTmoZv/ALxf2pwalPMThVUDiZSMc7gZOhar7UOiC2PU7HqDajeE2oZbwQwylCjDD1WLHYgUSWsVZTLOQAAEsfK6ZtVTgldcfk7YvKz9ykga2MavepOapsM9xDUxw6mzK0YHBS8qAb60nhNEap06VOFuBOLNGtYsvvOZ8Ezv5Y3O95VlsVyWVIyhkxekjh5FJe1U3s76wyYKtyrtGlrqZ7c/nX8zO/ukudbbUGyfzbgCWPlL++04WBi6CLoybptIY+yDjrg8A5H88f8+y0wDxFKpy6tcypKbaXCm/ljW6tZOa0L8CdopBW2fIWoMjjkQoniSnNEIWTrG94s/y1Q/HOrpZ1G7UZasmljugSUQanZPBhUx29aM/8d1Nb/dTN4lOv15sWg5MpDcby71LdMZxMfa7QiS59hSgg66dun7ii7fKGbJ9qUHOtUNwYFqtXqdcRB+XPySmcAlzqJA+fnTcYSoXTIxcCD5xWPL/uFetijSKq2muH3YCNy5TfntyTxy8HbvkVcOeRkZkpqXAKOd4UayrsAsVNqppDTXfrncSn9PyoY3yUKpxKBA1X82kqN6rBKXWp88QdCg3gnaIonGJd6lKjSgmDk3xPTeVbBidXefO/KOdGXMepcAqM4TS0DrjtUODcf862SYOTujIoMxizbH0iWT4GJhsUTsq9tCqcDH2mdDxlOL6SwUm5T3rbQQanMUqtBqekcHXctcJyvWenAYvuQ1RD8vDZWtoOlzrXYDVa6mmRdQefr61SZ/q/HcT+ziqdT7WyW7Wg3HXFF8O2Csy+CnjorPy11Ep1xnmOfHGxfOmZ768nL/L6pv995AJolr03kfEWek3hxDkw87L8NtXo1hpNnm+JpW0rz/SbXOqSz3YonPRGPWdwSva1FFl72wxOlg5amTgb8rw51xkGlIrbnM21mgxORDuJ6TvJWXSbwWm7l+W/mwa6Mh6dPiliUziFuFrU/Y7I9Ea3iHgeQITCqT+vYJLbAGCP/YCvTgE+9P+yfRuXZ2m7DAONYW0wZYn9U9albu5f8vulQWfmpebzN63MK7LKtDU+w6ILdXGaHXYT5XjTymK6gHDriUGNq7T1i4G93itUVC6euDbvamQjdlW39NgIhdPkHcSnjGtVi8FJxnDSFE4tTx9uZFN+hbN9vlw8RlXbBSucIlzjAC34deh5Sf+sisJJXkt/F9c/b65HByYVt4WQUzj15ycoQ4258rc1lLRkGesbzNqKXHwoS4y75x4Sz0heu39SUcUUEu/POLkdq3Cy3FOXwWmzpsCloOFjFUMhGd4IPPnXwNM5MPtqMSPGuqRw8nU+qgz0pv4+C3AH5F+KDUvs19i8Erjm+/b4CjpVFU4qLuVV3UQPcKsYGJTfctLb407VFU5zbzCv0FEWprnQ2ZY01lnrUT+FUHgGnlhMNmyDjDLEzlp1i1xdxcXKP1d9U9lkUC7qCrZQgn+r5fm5zm+VNIgYJxwsMVeMRltF4dQu46F1oFYyhtMT1wCX/puh86QENS20YeRSR3SAmPIlA/4OWdzc9PdXX7Gu1bLPFKvHPnqRst00WGL5OsOpuC2BPP+a7wHPPRCXpjOGE4BXvy8fH4k3M/c0V33WHM7fO5vCiTez9F1uara6SE9/h93M529emU+/TF0cYlgUBxY3qRNsOyTu+zLQrylAcxTKvWV9wM57hykc1IminV8H/OP/FI/RYziFBg23GXNM6abGleSehj6b9UuAKT9wx1jTFU5A9uxMeTxmbxGvME3H8Jxzq9RJg1OIwinmuSqxJ2MNfU3F4BQ94Z186u378jnm48sqadT3h7G8S2zo+LilGP4K5yqTYmosJNPE4/zbxAIxD56RPcf+SUUjTmWFk6decG3Tr+/KA0AKpzGL6WX/y38BF38JWDY727Z2EfCYYXZl7vXA5V8Dph2XzST5KoGLviiCndWFt8Kq2OG58f+UpDyrA0juPAp49EJg+rlh14jxHzeer8Y5cKwYUzfRLnWWwayN0S3AOZ8Abj1EyMnLot6T56cDlxxQjLdQhT5taWWbwanVBFbOz77HzvaZcLl9xpSlWhROynUXTxfvueqDXjis5HVGh4CNK8qdq6IbIgsLHhh81nkzbIUinTJGuFZDadBN57cxhpPLVSaVt7eKrhMmXpgF3HdKXN4k1tk2x8yabTvnwJzri9t32D2fnrVea7MBn5jYxAygpJt0qIuGWqYPewlwkSF+i+lY3VBlQtYHfQPFPpIenwgQ79qtv/FmOT1/zTPAkzeoG8PO9RmcTN83LU8u4XgWDd3gJIMR64r4RmZwcrrUaQonvRzIc20Gp02r8umXmfQNVTiZBpYfU9zkZB43vFBM13Z+KLwlJvdiB5xfvRbY5fXF7aO6S12ocsLnUqcogvRnGfpsrv9P0UddeEdxnx7DyRSwXL3v6xajEBcMMJdJUwwnn0udzXBk6werrm0x5YG3qrnU2RROF3/JfHhZw4auBh/cOvseqnCSxsChtcCMC/LnNkeyOuPmXyjnGFYrlt4gK+dl5aV/UjZRYfJMshnHXZPboXWyVeGk97UdZY4MTmMU0wsrVReblAHdHz8IXP2tYiBFKUNc/bQjIJuGjBtQFz7VTK3L8lquVbD8RsamUZe9rSqHdi1RXDftdqlb8oiIqzXtD8D9p8ZdK3ddJZ91GHl0dJdIW0M79Vjg5HcAZ30YOPrV9TwfV5DWmPRzxpeSKjl19ZHHLxf/u973sqqYCz8P/P5vyp2rcpQS5+TWQ7JOsuTkffPfZccqVMGmEuxmaJlpcp0fozLypakahW3G69TFTO30Od7pcz8B3PRzrYMfSFmFk4kZ5wOzrihuX78YeGZqkmwrwMhFEG0gpo5I4/LxYr/MhG4sWnCb+bh1i4ELPmu5rmWAmDM4uQYlCcPrxSRlCLwFnLCPI8Czg75+ewyn9Lu2vxmgRNENTrLuGx3K7jPnQi0lB5tBMZwsBidZH03eznx+QeFUxuCkTlpGqLH+aw6wz79m32WQ7LSfVbHOTI15XLQ3rA/RMR/1wM0SWaZYf9xEnWn3yqcy46KprKar9QU+G6mYUhV4En2VOjVGp2ny6Q9vAh78oz0dFdXg1Ncn1Nw+lzrehPGmDG5jPj6n+oooH40twPxbknMVdXUsoUafnOdJRPq6wUl9hg+eGZaGmscpBwuXzNTQOGqun0zPXr7LfYNZmgOTgHd8DXjbgcB7f2I4xzbONU1uOyZEpSJVxeYdEKNw6lbMVw0yOMVi6jwMJA2k6nIwY2cAACAASURBVIeaGp80dw/pu90cyQeS3bLWHyy5LsrG8ih1rUCFU0iHqKVVSoBorEsNajjw9wcDL351/Qqn0SH7KiilV6kLJbBiGd7gXqlFbVgX3ReZhwD0VelsChh57cUPJSt81WFwcswgqkVp1pXuspXz/1eOi11VRuYpZBEBfWY3FD24vwvTSiwmnrsfuM0z657GcJLPNyLfwQony0yT6dmxEgqnSw8MyxPT3GM4L/4/sjE/m2tPTHxsWOo+zETZGE6m/eqKLq7zQjtcBFEnhWD1ljLeGs3XyyGrism07zzKsFO5znyLIQoQ76L+bmxeCVz7PfF//2C9ihY9b+mmwPeQlTA4pepNR9/m9sPMs+x3/g44Lwnye+9JABTVbEgMpzQPyvfX/7MStyb5/PjR+eM3rcwbFCsrnFyTG9q+bXbOf0/vr20gGlBvq2VUncRqJf2KWIUDY8UgyWleksDyVV3qnrolM7DkDE4lFU7SiKRORgPiHsjryzKluvPZ+gKL7s1/32Znv8IJEIoUn4HGpnAyGctE4lleY9pUVS0fey6QPdd5N4UdX1pJo5Qf3eBkW+lTR6/Tl8/JGxqdBifl+mncpsGsr9Y/CdhqB+AzJ2dB7dX0rCFLTC51mkHVB7nUTWCMBqfEiGRa2Uq3gg4oQeVUhdOp+wEnvCU+P09cG7+KRUgMp+1eHp8XW1oh20OUBqaYObHB99TzZaOq+lPXMUA671PA0a8y70t/Q+DAO62cQjuMgen+4U32PAL5DtRcg0tNVXIzIQYFjHweegMcMjPtxRUjQfn/im8Av9kpHzRSxbYyUWgcMpXNq4vGEBOdCBouZ8TqoJkYnIydVx+B73Uu0GxgXC2TlNrGPCU+n0/hZFI16f9P/b34fOQC4JZfm68pAxivX2Le7+Lyr+WX2Q4m+R0X7g9c8hXxv+r2YD1NUzjJYPJyH0G0C72utHW6myP5etl4nN4nkQan32XbTANsl7uwdClW2bImU7r39RvqoIoGJ2MdFaNw0upqve62GZxck2mLH7LnR04qPZ4sPiGND85VRjXlt1oOBrZSVFfJce/4ev78VU/VG8NJ/+2bVgJ3HyNcq9Tnu+83ioGVZflxrV6lIoNqy0Dga57Ol1E1hpNUOEUbnAyuleo+xoAlM7IVabc4Ji8bI8Dthxa38xbwln8V5UuPDSXzD4RP0soYbXr5VctGqMIJyP/+F+0l/pwxnJL7PjDJP6lki+E0aDE4yefXbJjPC4G3SpTz5FoblgDPBkw8l+rnIX/vWV/xPgQp0bW2YOW8bDGB5oi5X20KGp4qnAaEex6QD/KfCkUCnoNpMsEb2kDD9h4WDE7kUjf+cFmlR3wGp9FMHtcYzisaysxkA8BlXwXuPAI455NF9xYb3gqcAy9/M/CtO8vlKZeUraNjUTi5DCY59YKyMkpZlzrWJwx/s69WljutQd21+EH7vliDSczAGECwIcu2Uk963TYHsvcpnOTv1g1ObVE4WQwDkkcuMKdj67CGDNJ1/vJfyQwvPB3tSNfTbpMGDS8xy8pbdv/13HG6wikkhlPJleJ4S7yLl3wFmH9r/vqMweqea7vOPcebt8tZtJjlu+X9XfqYWB64kPdAhdP8WzMj83BIWdZiOOVk4+RSR7SRgiuVReHYrKBwMqG+z64FEVoNd31ucqm75rvis+zKQkYVRkQMJ5+BqTCgL7MIgiE/etyboPtvcKnrn1RUOA1Myg8an39Ec5WuaHBqDOf7drceAtz+W+Cxi5EfzBp+0+TtZYLap/yqfX/1+8Xn7u8y71eNoq1mSYWTxaVO7gMDnr4beGGm2Hb3Mfa0Hr1QHKvDW8LlcWArdwyn0LIrjUh6HzsXU00qnJSxmi1ouPpeT95e9FFdhupU4TQ5c6njXIS5AERctfQUDuM7MLB1cRsQNhlpIlfnxQYqR/74kNAadcVw0vv9IdfW7811PxTGWCAfwyl3jqEfKA1X/YNisRT5f5o/+X4l99MVX9npUhdaJ1vagau/lf/uVDj1xniBDE6xGP0u7xefpkF8zuDUyEv8+hSXuqo8Ow144HT/cXqejPsTqWyZuCuh1yozq2dUOMUsE6rni2VLwT5xbT7ddhHrEhUye6hSV8USej3fcrs21LLFW8VOu2kJU3lsVZwGJ1NZstzTXKBYpbJvDEUYFg1puxqOWhReHUQahOUsa0z5lMYd7zVUhdOo8s64FE4Vgoa3msIgI10PVdViiMIp6DoyfkVE25B7V0z3zdfRMWwfCejo6avUdXIRBmJiU1A4KUaLXL0wIgaksp2xBfPW0y4oDBV3JUm/o59kUjip9A3Ur1o1Dc6qxHDSJ4OsLnWee2pyMVZpaPHqWqPAnOvMz8rlUtc/oCicGll+v6coNEY2aHVWiQk2NQ/nfxr48xez7zKkxtpF2hjA8BykYsnWbs04DzjjH5UNmmGq0KbqCiefwcnSJrsMTjGGBZPaRxpcWL/wEHHFGws2OMng33oAeaVOkNcZNbjU6WVK/f39k5J3NTl22vFZjCd9srx/UmY8nXEecOb7hUva2coqgDaXukGLwSk1rI7GtamqwUldITcY5d7b1FcqpQ1ODpc6IGwS1zWJ0PAonGwxnCTqqnmpUKTpd510usdWEBE8e2/RiEsKp/GIK6aLI6Cc3C8LhRrDKaTzE4I6g+PC28FR/LSrYqscZcBZX57uPQm48efi/5zPvWKIqaJwKmxv84y8WsGFBAQ2xUd49GLgsJdaKruaDE6hneCyElr1PM7tMmjdTbUWg5NrBtEU98eSjnr/1bLZGKpmRA6J4VSWlfNFkNsb/ge48j+qpRWCVDhZY0I4CI7hpHUWXOoldXYq5hrqtWSHJJW5y+8Gg9O8m4ClM0vMLEa60gKaEdcUx6VEDKcQhVPBpY4MTkSHKKxOZpkEkAanrXYo7rOm3QCOe4N5X6jCyRTDScUYNNxERLtuinlSKYaT53tal5p+p7rSnscArw+Y5v5FKAykC3Lumlr92NKeh3y+vJnlVw/InFN/VIzhBGSKVz1/+hhAJzU4OSYE1Fh6BXdlrWyoCifZz3UNOE37TEq33L6I8rhlbXGbGvdocGt3DKfQsiufp/6+qc9ZKptGTC512n1Xy3nfYF7hdOuvgRu04NHyPg5MysrysifE5+qFwi0t/U02l7oAhVNMX0JVSFeJ4QTYA5qrlJ3w9hmcQhROrnH08DrghceL203PXm5TJxJUpb26wmbsAlzqJOqC2+3nvfObxeupSIGEitPgRAqnsYnrhTXt02d+06j5I4qlNHAFAF9FMxBocApVOJU1JgDAwruAFU+GV45qHBSVm38J3J8sD56Ty1dVOHGLwanNAyS1MbzneCHHfOxS+/Gm2cObfyEku6aG3FWxxDRUveJSp8dDqkvhtGmVcDvSZ5piFE7qzF1uFs0SoDAUV32Qpqvk85lpohytnO9P++R3JCuwnJmtiqdS98IFcnWQtNMb0fC98HjgwFCL4dROhVOrmT1rPcg76ysOqv78L8AZ7y1RbssonBwDXzXNGHTVgS1dUjgR3cClcFInBEaHxLFSkRuy6pKpDWQmhZPHpc71DvTpq33ZiHh3TUr7kY3uRULU/OiTPz6FU+pSZ1LvbJ/97zNE69tkmIm1zxmOVSYM5t8KLJ+dz68cfLaaWT9WH8yrhoiQe+PLr0pLMcJ5DU6aS13sRIu1z5cYnPr63c2uzeBUl8LpLkOMWZn3vj4xblkxL4s7mLbfkbFu5LuvGwHkpOU2L8n6k7ExnPoH84ZM02/JudTpg3/tAdjc22whBHIxnCLa1Ku/nb9mlX5pSHgDW5nxkftN3GBwqqhwsp5jiOHUVPpzktz/imeS7X5uXg08dollcjvZNvVYe74+qRjZTe+3SQzSHAEmbV/c3kOQwSmWWINTQ+sAyYpInUFwWSblih2+awP1GZyaoxAKpwoGp/M/DZzyrnIqBRsmlzqgXCVqVTh1yKUOADYmDaw0qBmPN7nUOXsPjrQiOq3tvg+y7M+7SQSc1K+XdgJKznY54SJm0tRjk1kGVervUMXoqIEy1cZudEs1g52pPG9cAVz17UxarOZzZhJsVVcNxrJ8TrmFC1xICbiU9bejXOmujS6Dk3znW01gyg+Acz5ePMYFbxU7JDmXOktZKmPYAtwzaMMbgWeU1Qdz5TRA4eT7HoqucNqyOpN7k8GJaCeFFa1UVZPyv3QNlWqSkPrZqFg3GIJ9QcNLK5xUdVDEu2kanG1a4V4kJL1kgMJJD3rtcvvfaqfs/5wh2vB7dIO5676psS1vOyy/b5udhaJheKM4zqZwaigGp+Vz7NeyETIW0A0LpjI1aRstvUAlqk/hJO+Rz6XO1L9xhdSInTgyoRppBrYScU+Pfa3YJvP9xDXAkkfD2xD57uvlRhqZtn2pqAduPURsm7RdcnzA5FP/pLwh0/Rb5D1RVzfLDtK+NovbAMs9VybH1RiVsehqu7CT4g7PGWZKXoe3hCFSJWSlupBJBB3Ts5f1mLpYkGqsTkPhtOztyNXfFn8rn8xvzwUNDyXQ4LT++fIhTjoEGZxicQVb9smEWw3F/UKZScoFL9QK482/zJ/vojaD03DS4FQwOIVeK+Y4W5DHWMt26j/eZpc6U1p6cEvArSQzScZduCr5mMam7Qqn5N5P+YH4VA2rgGGWS9teBc7zPuH67EoBy01VZ0X1lVD0+/f03cCxr48LfthqAUNJQ3vTz4CZl4iYFkC+HKkS3yo85wh2X5ahdZlxt68fpTtLLnJBQX0xnJTO+IzzgbWRii7eUiYNDPW3Td1TxnXPd95V3wLO/UQ2M8xCB6iWmXSTzD9oJRZN4XTjz4rXIoh24FqlTu0XSCOM7JDr57Wa2WppprQk6ns5tC4ZgHoWOvHFcOItYNH9wOKH7cfFvEejJVZJTfMTYHDaakfgK1cA/3ZVkjVlARedrRWDU07hZLgnsv+qTgpItqwxT75uWFocjL709eJzysHAA6dl19INg6rCaZ1BReXDVTfaXOpMvzttvz0KpxVPCvdsPRafbUJszhTx2edTJJkMTj6XOkdyIaTGsL7iuEX9/c/eE94nt7WZ8jlvt4v4nPYHsU0an5sWg5Naf6QxnFyr1CX3eLuXicG/iq4ct8VwshqvI13q9Gc3uG1yzcjJedsEmvW66urTyvaGx7XYJCD4/kPAgdck20ImCMoYnAyLMsn/HzxDfO66D7DDK7L9av1kuyebEldG3V7AW4g34hleNls5aXpWR+wyZHCKRUatN2E0OKmrLygGJ1W6bFPuAHmXIq/BKSCoG+BXBDWG0fYYTrbjnKvU1aRwcjXUdc7IG10slbxKdxWXYc81e2g83rUv4j4F39OyA8rk3kuVV2F209IJqMulTn0PfcFMQxROKo2hYj5v+F/ROV79tD9t+dtvPxQ48pXC6CRXoNz6RUk+22BwUldRqYuLD8gMTu3yI9fduUKMNWVjYfEWCjGc1O8298xog1OAS92yJCZBOlPvu78e460aYzAGfaZP7WSRwoloJ4UYTiPm/+UEg4zhpBuTZpzvTxtQjAJN4Mg9gGu/7y7jzz0UoHBqAmd/FDjrQ/bjYibCVENKLCZXKtPgZu+PZOqlVktMpJiuq8646xMDhWOTZ/OVK5LjlWOO2gs4SlFoyXu6eoGIj6Oyw27ic/bV+Wvp7Y/qVuVbxt5EsMLJ0lfd54DkHyXIN2B/1qe8K3HP1o/TFU7asK6MwsnV/2cszqXORNrf7/evRBzdduoudckYapudlW2bi8Zn/TqqmqlfieGkl13dpe7lfyuMg43h7N5u0BYf2PACcONPi3l33XOZp5D7ob+zk7bxu/caiQxynTM4Kc/ht7sAF32xeHx6rGFybpfXZgZrV75lvVMmFrLJk0I3XO2ixfFLXeq4vW63rlxf0wScLXxCj/e3yOAUg28QbjQ4abPf6uDE5FKnV2YxK2mE+NgC/sGWrCirxHDKLhZ4WKRLnb4yVVSWFKlxmXyEYuywKttk0PAghZP67B2+7bEun9ZjKwanVjFWjnrete+2lUPqyJfaUOguDS5VjM7mVebtjaHiuyoNay73C4ksz9JVbnhDZnCSs4G5IIusuK0MerysOpDGN9eMaVV0lzrTrFVKsq1srCrVWCk7V7cdmnyHvSy53r3VTwvXuKNfkynaoAxsVzwJLJttPd35O03HLZ8rBmkmg1PZMmBVdpHCiWgjevtg6xdIhdNkOcjU+gwm5akpyKws22kdbYjTofLkX9z9Nn3CQyVYsahRGORE0DfgVzhJ1HhWR+wO3H9q8RjVjS33bAwGnlYDeO3HgR1fmX3PkdyD+bcJ5ZKNQswpS7ujGsjKGtp9+3SF057vzv7/3OnAIevCFU5Z4oHHJfRZDE5pe2xROOluTZKhteZzYkj74B6Fk+m7D90bIH0flHdoZFNxAQFbWAcgUTgNim16XaEbnLbfVfy+IUV5N6DFD7v7aGDWlcW8G8sqQ07hFDKm0seCg9uIPMUaZdR6R3ddNZEzOGn5XHBb2HVMk6my7tiyNu9ZsOJJ4PCXA7OuKqlwMjx7fTypr0KqLjxjc7uWK/pJY+cXzs6uU4dLnXVl1N4IDm6DDE4x+GZBTBWjek5LjeGkzCDkjFIGqbfEV1nU5b6Wqj9qUDiFGoNCDAk5lzp11iiyEpXpmF5aZyci0v/WtQwnkCkTXAon+fzVxsm1ClddBqc6XOrS2c2AeDKF61t+Yx0DWN7KylvfILyzODZljj6jK98Xk8FJqqFCOramGTfpTiDrE5NLXeXZkzYYB/Y5AGmA/nYtzZpTPnLz/VP3A+ZApiHkDE5aueDaNb2umgknvlW4xm1ema1GlAbibYqZ7dPebThRmxn3DlCTbSufBE58m7ljXwgSXsKlroorIUHEIMvd331XfOYGDqrCKRkkykHmyKZ8MGpT3fTohcVtst1Q0/aVcadL3aDDQOuJyWajskud1h+xzaansUwcv0+NfeKbJGw1NeV/cvyINsC/8PP265nyqz7bX64APpPEzFTb73tPBE57T1zw8CCDkxar5+8PLh5bCETvedayD7DmGdEvLLRD2vm2tnfStuLT1P/0TRCFtuW2/pocy/QZFE45IzKD9348fgXw5F+Va+oKJ6mA0UJy+BROusGpf0Ckobu+6gYn42JQge+v7V1L43KNhvWBCwqnbfOCh2CUa7kMRhJ1zBhTD9n6DLp6/6g987HoljwqPudeXy6Gk4yx3LSIGYDiM1FjOJnqvuZIZmAc3SLuyW775n+Hi1ful/9uDBruKSc9ChmcYvD5RxoVTrYYTn1idSnAHncAyBd+nxEg1A3KdFzuOqP1xXDSY/PYSO9d8sJsXl2cAbDFuoqtROXxppfWVSGc+DYh7Q7FpIDJudQl5cnVeLvc8nwKKltaJsPlppX5GZnQmFGuxs+1YkLhPH0VD0vQ8CqrbGQXz9LvG9BmVyJiOBVmQpJZJVMMJ4m6iIDPgJmq20az9NKVWByNci/wzm8CO+2Z/Mam2VUjlLcdCOx7kH2/buwouwJdCLxVXKVu+12TfVqMhDKGF/1ZuspHoXMRGzTcYHAquzw4rVJHdAN9CWv5/o1sAk5VOu6pwikxOJ37SeD4v80MDMEDaNmGRhicXG1pQWGrvKObV2b57pTCyRQ03DabzjTDkAlp1ADydaNp8rbVyCusVFWDii8wbmGiVKkXByaJVcSA4oTRslnAU7e401ZxPXe1j2ZSIxvzF6hckmrpDUuAK76BYv9ENzhZFE5fuRx4/8+AnfYwZMkTUsMXi/LxK8TKuWsXmfef8Y/JdfoMLnW6qt1zP648CLj4S9l3vTxK18n3/W9+eyGGk97X1Fzq5Cp1L8wU23ZOgpzrITrkuMIVKsWGLWi4mqeQtPR0pMGpjFEmBvVZhqwsJ8kJCNS+bX9xv/W8En0XacxuOcbguvFOVV2Zrjm6JVM4jWwGoLigrl4Ir/HxAz/Pf//bL4jPnfa05ynLnDvtLkMGpxgaHnVCjMFp5XxgRbIyRq6wOyo93wtVqKgtBdtoxFD960f8A8TQDlq0wSnh4gOSxlTmrwU8fplyfITyS0ceb3xplXu2ZY1YrlWy5ulEThzISe8wJK/8zjSGk6NhN6o0Siqc0k6QodE55jXA8W/Ovo+GdlodlWc6CIh0/VP3u2adypKL4dSnGZwM+bLNGuh5keWpMWTvhKtG69sPy+oAWz4BUe/oA512xHAyMWl74BVvjz+vfzCJaZTEsKgS92HH3YF/Ps6+X3c3da7wFjBwm3+riM9i6lSbYjip+SjjUqeiq9X039AYAe48Kj9YWrVQuP+EKpxseeK8ZBni9naKXOp6HsbYxxhjTzLG5jPGCoFFGGOTGWOXJvsfYIzt1flcWkgNTomxv9US7/+SR/LHyXpzUHNtkfHGog1OFrW1yl7vFS58rnfK5dK9eZWibIxROFVxqTMFDbfNpst2p4zCydCXbjWSgf1A9h0oDpJ9g2abC4xE9msbhphT277EnbZKyOSebP9cqC51IfXliGcgr6fR1w/jQPTFrwHe/1PzPl//3zf5/kiiDlw2y7x//eLsOt4YTpFtSKHNTPK6w+7AJ5V+xFbaipX6dQoKp2SVOnlc+l5oQcNlP1Atp49fHpZ3o9cFz67BWwiqC3LvMBP32OYC5iL23k9SXGhl/ylofGbpg/vqmDReJPPXCzL+qcq9JyV5dIS1KSgmFWWnqZ/fGFYUTpvz8UunHuvOI1B87yZvB7z6AyIYfXqMx825R+m6wYkxdjZjbDljzFgzMcGJSWdnJmOsxOinJnzuMF6XumaWhhpwuK4YTi53PFc+GyPAeiWoXStZecVlCAntoM28NOw4adWWL4w+EH/0IuCB07PvOct2pNU+VSjYKveEP34QOOWdcWnnrjNcXKWg1cjLLQFP0HCHscZUCTuDDM/Kn6+jGtNiDGs20vsbYnAKjOFUl8EpTZf5O4SPXWI2Hup5kQ2Ra0WOjcuz/+93xKGQ+QREedU737k865L8kpjK2sDkcr7xMm6EjGHR118hhpOnEVVnxEJd6lzc8mvx3uoB3mWaegwntaxaDU6BHTfdeKiXo0fOB+78HTD1OKT35aL9gdP/AaiqcGoZOlBBq9S18ueVmdklugJjrB/AKQA+DuCNAA5gjL1RO+wgAGs4538D4A8AjupsLh3I8iVVK1ceBBz6YhTqjNSNXo9zKQePWt1kq6vSSYDh4rb9vpdtO2Qd8NI3JBMaLoNTn/bOae+bXEUzSuFUwaWO9YXHcOrzqA8AYXD66BHi/1w4Ad11FwaFk6bqlfgManp+9UGYNAiYgpz7JpVVeMsw6aD1zVqtAIOTEoMx5DmPavfOF47C5lLnm1CuFFIj+R2+/pophlOZNsh1vjSODUzKG0Ane2I4qWMxdZU6mwIrVTgp5Tc276Z7vvyJLJ3QSSH12Q5sJb7bFDlOIvOfi9k2KurJkJXTcn0l5f6mdYyWD9mP3pysBtdqiFABJiZtD+zzZWD/s/z5AIr1Z8GArfTRjGP+LVmZHt0SH05CP7ZvQJQt9VrWd5MMTj7OBfAxx/6PA9g7+fsWAM8orY2UMTjp8ZlMMViaDqNSFZc62/H6cdd8V8QRUfEFDa9j4K+i3zv9pZcy4vT6FYKGywbGpHBS86GvfmLjwT8Cj15s3nfLr7RrN7PKSP7GkKDhehq2fa7G6NxP5s93oRvKbLjaI2ZpLAB/o2n7jXWUuznXZco7dfbIlq9ls4BV890zYOLk7NNWdq74eva/67lvXp25ZDaHs/uh1x+rFgAr5trz7kNV8JkY3KacG2PfYBIQt5V1zMsqnHyzNnW71MkZZNOqn6osPXUpaWSfNrVcsMJJxmqwqLRk+qYVEr2zWwEudWXuWSGGk+d9InqJdwGYzzlfyDkfAXAJgM9ox3wGwHnJ/1cA+BBjPTKVmiqckrZcGmgKxyXvrD74ufjLwr2noIKxdOhdLnVv/Ur+2NTg7orh5HCpy1/YnoZOlVXqTBMDXpc6xzveP9kQowjmdjyN4aS5Rza1SVsfLpc6IFMsGA1OBkOYDd4qXku2HTmFk+/ZqS51Ac9Zd0fU76VJ4WR6XV2xH3VF8pcvAz5yqD9vaR4sCnU9f0EKp8g2pDChntyv/sn5a8kV0Gz9BVUB19efrVJny18aw8kQmzcUk5rwyRuyRWNCjZLqOzwwWXznJVzqYg1muoJ0eEPYCpC2vpIeNFwi47jJMVRzFHh+hjntvj7gc6cBL3uzeb/OfM2t1hbDqdUy12OjQ9kYr7ElXt2v179p0H9PrFmAFE4+OOd3A3BF6vsMgPO54H4AOzHGdu1M7jS8QcMNhUBtLJujmXLEptApxHDSjFGPXgw8dav4Xpjp0CvCQIXTnCmGgzwKp7rxGRYKgREr+O5aZzsN+fCxagFww0+Aa75j3l9Y0aKZWKz7s86JU+FkUjHJAW6kwSnmmFCDkwvn7/IZnGxL1dbgg37XUZmkWx9kh8RUsuUljQXAgT87loCV2FaBATIjkrxOOtsr65Ok43HS27NgjmXcl055J/D8dPv+wa3LGfn6BvIKJ9eqN1XRg3M6DU4hLgubDOnK01vKwg/J75HP3alwinSpk8frhnfZYR7d4u5cGI28usG0JoPT1N/n4zXY4lgRvchuAJTo2VicbDMewzlvAFgHoOB7xBj7FmPsYcbYwytWrGhTdiGM8XIFOd2lLkUr67Ku1t+nFXOSQP2xBieDS11hUMH8igQ9aLitfoqp20Nc6u462rydRQQNVwMZ21BXSPMZi1KFU3J9uYCCulrg7KvdaZjyazMmmgxOMavVcV4sJ8NJHEzV4BKlcAqoL3VXwMJ9DYzhlObd0o6o5eC1HwVe/8/+vKVZkAonU5xRJX99/e5V6lhA0HCdgsIpeab9g3mDiAwVYJvcVGOhsb4shpN+vP7+9xtiOIViq3ekbQ7zbQAAIABJREFUkie0PVXTGdgqUWc1SqjVYw1O2+a/N4bC3in1MqrBxRYuYtkT4lPWda7YVjLt2BiiNg8NNa6UaWK5MZTPN+tDlPLIpHDSPTGsdSkZnKoS0iHqDHUEDU9jGnHLMc38Shm6wema7wgXCiBr3NRzc98tFZ5uxDBVcnUFDQ8lRBacO76CwUkNGF3IR+QA6YLPhl1L0hwRDWz/oKJwigwa7gouWcbgNLS+eEyowclZv2nBMF150BNKJel6ma456GHB4OS4fz6jqJwd1Y+74HPm9FxuG1LuDYgyk872OmKHlB3cb14jgsYvuq+4r7TBSXOpq7RKnaWQSZ/2gsLJpQCMMDiZJhhUNY80oKUG4NF8eS0TPFufddYN1oOaO27+ZDWjhv0+hZMpJkHA/dqyJr/qHwUNH0uYXi79oYccA875mZzzfTnn++6yyy61ZM7I6f+QuJAiK2u6wUl/d2W9ufc/mdMsxOOzGZySn21SOOn1G+sLMDiFLFoBRA38ZAxOGxuWAXccbsmPKWi4Z5U6lypITjwA/j6e7lJnIqT+LvRbdZc6h8EpRuHUahaNW7IvJY35+iSECab0k9IA1I7npw/gQ9zWXC51tomLgmtiifbbt7BNWxROhhhO/ZPE71SvJYOlG8MUIG+47RtQYjNpC7ek5zmChku+aprcV7Aud4/sWiH3Q31WA5MTl7pWfLzbqgqnVjP/Tsn0RjaLUBXcMJZR826rO+R3KbpoNfJlzaROjxnPvnI/4MO/yfKqkhqIm8AlX862fyzpAzWG8u9UbN9Xn5jtG8zaEontuZDCqTJBnZ2OzK751BVel7pmZnCyudStnCeWfXzgzOQ4h7udbigIXdFLz6dxBovFSwGrsGp+clnbC+NQOPmeyyVfEW5vgFAkXfcj8b/RpS6ygvWtCKM/g8ZItuKFPLesEsjUgfM1RgvvLHa0zv908TiTEcqIo4Jzlh3PfbYZDWpfZUOTKLvun8+ga4sFsOD2/Pc0YLmlcyFdCyRqXAk9JpyKet2np4og8CErhWzzIuD8z5gDfJY1OMlZ1VYNBidZxP5zNvDFc7Pt7/qW+MwZOFSFU4DRxYTsaJpm5njLHsNJl9uXcS1TZ7uB4gBIdqQaQyi8e77ORsgqdb5BoQ1bO3XvicCc68ulSXSCxQBeqXzfHcAS2zGMsQEAO8KtSm8v65/P/tdd6iQFt6PknZ28PfChXxfT1N91n8Jp3eJsmwxQzvqAny4Sf4B4H0c2ACufMqcFZG7H2QUs1400OA1sbd/vWsjFtEqdNUCtNDg5JmLVgLkhMUh9Bifr6kyOYwqKAelSZ+i7NbTJ31P2A5641nwd3ixeq6BwCjA4qTEYpeq9f7LhMEs/0RfzqK8fWGJwN2Ieg5PJtceFaUDsizPK+ov3sGoMp0KfcSS7n+oKh3qssILCSek7DUzOjpflPV28Rw8a7nCp8/WBvF4lSn9VXbWscB11ZcatkC7gUveErY6ef97UVmZO7vFf/hu4+tuZul6996rBxRcnLlU4abG1TCtZxsQQ7RvI0tAn32152jFpRlWFk7iw/R2TRq1cPgNiOFn7aWRwqkpIh6gzs2telzrDS6HOULcainrJonDalBjLHkhCVbliOBUCUmsDrzXPmPOpV+imhkS+IKUD/daM/sLGxLaae71wewOERVoqOUyGttjZFN2ir1Nwu0oav/4BYLRkDCfXvik/cOfn/M8AN/5ffpu+og8Q3jC5BrkuFyrfLJYthk07YocFK5x0qbbtHnk6SHKZZ1sHTp+tyc2mu9QjynXv+J1Yktj0bHVYnwhMaWJw6/hZMSAzVsvnxfoq1CVJGdtxd2A3JXi7lOIXVqmrGMNJYjU4SZc6LYZTweBUwqVOnzXV2xyp5DC6zfhWqbNcS/1ehyJJf08u/Yr5OKIXeAjA3oyxVzHGJgH4EgB9Gn4KgH9P/v8CgNs575HlB60KJ21SRY27prvwAPEGJzVA7b0nJmn3iUGKHKjIgcOVB9nzL11d0vTrUDiNmn+jxNWGGlepsxmckt9nUgrJAb6qcPK61DX9BqeQ9j80aLipP68a+Ec2CpfLa75vz69uLBnSDE6tJrzPTuZvZLOYbAZEgGsdUwgIoNhX0+twW7vrdanT72OMwUn9/RrqMzSthldV4dRqij6L7Gc1hrP7ua0yNpQBrkc2AZf9O3Dep/LprF2U/S9XqQOAB8/I50tXOKYKpzYYnHgLaXn60K/CJvGksUyNP9kOvvdAcYKs1TLHYNMXhfIpnGx1h6x79AVPXrSXkoZUnkX0P/sHshhf+gJKtjxJxb2+8IBLuGF6pwsGJ0MMpzJxVXuAsWBwmgLgq8lqdfsBWMc5X9qVnJRxqZOGDkBUQKaltlsGNxnpG6pWzvrAb1gzOKkd/YfOAv74gbB8GmeNtBUXuo7WKKoVW4wRQr3/vqDhLh4+G7jg8/5KTG90miNJ46VUNK40XBWLaZ8eXN3Estn+Y8oOPP92/+x/V2N436nAEYod2WZYarfCSW3ATdfL5SnUZbUFvOVL9nRkA2Z1qWvm74fNB94WUBoAtks6ViHlgbeASduZ9w1uU82lLjU4WeJIhKDLkyX9BoOTd5W6kOsl1zCtWKQuLSwVXDLR5ojD4BTgKqEeJ69RcPFI9uvx+4oJ+bcVjLytYhkvY1dwBREmeookJtPBAG4CMAfAZZzz2YyxQxljUvr6JwAvYYzNB/BfAH7andwa4BaDk/5+pG6wNoOTvhS2x+BkQjdshNR3fQNav9KmcIp4p56Z6nYNc00mmQwAXpc6rV88eUdg17cox2gLIVjz1UgMXiX7Q2m+9PzqMZyS9E39efW3NJV63oRJ4SQnAlL1i2LEf7dlMjBtbxTDnUnhZDU4WdyNJLb7KScEbb9PnzD0lmdDUGOjwkkpf3qQes61c0rEcOJN4eJ91J7CfbQ5nN3PbXfOjtt6J5H+ltXAE9e405RxkHLXsRmcNOWUim2C9uDpwH/NtcdLU6+pXm/fb7iPT/Pen0xktsmlrn8S8NLXA3u+B3jbvwEfPiQ5v6mt6Jk8W2mYTV3f1EDy/cX/9fpv25eKz4biUqeWG7U/K5VHUQqnQWCrxOC0RTc4WfKkKp90A5rtuZvq1oKyUMZwSu7RovuBm39hTo9c6twwxi4GcB+A1zHGFjPGDmKMfYcxJqMw3wBgIYD5AP4I4HuWpNqPb8lUX6fA9sKrnR3Xkqd65V1QOCnXf2ZqeD5tMZxs+9qKTd6rFVVV7hpTiapBQ0NjOJkGUNf/pwjWHNKJUmmOiNkWtWGJCVQdus9FiNEm2IKuPa/tXga8+4fJLkf1suqpfAyyQgDjpnl77QonLcZGjMLJanDyrDYjO6U2BZg+8LcanBwzgXK2ZVOAezGH3eA0sFVJl7o+zeCkxoSLbRSZ+X85a5lz51JmlF3xz0zI9zBdZcZw34c3ZC4W6u8DRMfWpkCT//s6lPK5y3e04BokYxdsNgxwPQonfVOnFE5ET8M5v4Fz/lrO+Ws454cn237FOZ+S/D/EOf8i5/xvOOfv4pwv7G6OFawudTaFEzMP5puj+Y5+KYNT7AAdIt+5AVkNLnWAO3C4q203xe60DdRSlzrtXv9sETApCR6sx3DawRF+VbrUORdDCDE46c/BskpdoT/PMiPUHUdkca5s+THFcJp+bpJPxRjBuWhf/+m3lgwbDHImo6gtvo9rZWvAXw5rc6kzTLCY+prqxDnTFif6/d7Ak3/Np6mme//p7jwA4vfLNnrxQ+I5y76C6pHQ1y+MTiF9JNWlTs0bUJxMSmM9mQxOhmex/5+Anf8G2GHXsHucXo8hqC+lrlIX3ZcLrHdkngYmAZ85JXP3a2kGp1ZT9G/l2FU1zEqMMZyS/TvuIT4nby8MQXKcq3oF/OP/5tuDPfYTn1EKp8HEaM6A9/wov88UV2qnPfN5VevrLathfU5BCifpUpekefcx2b736XM/vW1w6rp8hXN+gGc/B2DRtHYYV7T9wmojBlqWF16tlPUAa644IL4YTiYm7xjmUpcqnLpgkzQZePRGUY1NE6N6UeXfoQon3oTVNuszyBViOCUBDNXOg9PI4Rog1xBvxZq2pyzvtIeQHJtmdVN3zIiyw5vAGz4lKu77TgaevFGseFFQYbQ7aLjjnhZW+XIonFydetkAmwIbynTVa9nqHVcMJxl0fGhdtqqlDd7KBgg6A1uVk++mMZxUlzrFiB3zHH0KJxVTMN9QOE/kz8oMuP7bp/wgU40VDE4BLnX9k9xK2dQVQSqchs37OS/OvFUOGu4pt6HUbRQmCBu2Ver02Iot1aXOUO9K5bE0nnTK4MT6NDVSDS51Pnz9pYJLnc3gJF3qTGoqJSSD6oJiS0sqU739qTJ1i8WlTtbDP35c5POkd2TPQl0EwapwahXL3cI7RIwsWY+mQcNdsS6VIMQSk8HJNlmh35Prfqid5xloq7/vPT8C3nagOQ9elzpDe2dyW1Tbfj1mmG780Vcfu/H/gA1LgA/8wu42ylv5NlxVOAHAB34JvOJt4v+tXyxUUD4Gtiq228Mb8xOW+iS9zaVOLqaibpP4YpTlrhfYv04VTq14D4FgQ7chbhggyrR632ZflQ/7YVKjq+VVj5eUGqiawLybsuOaoyKvr/sE8MFfiLi9ko9Kw3GMwqlfuEYfovexlDwtVlZ3/uxpeYNTqNHXZHAqrBIqjfAy4Loimth57yyd5oioZvb7PnD/KebrdZmuK5zGFFKaZ6J/kihojeH8KnMqVoWTGhR4KP9/btZaNzg5YjiZ+MEM4G8/n0+n2TB3GMoYDWqBi0CbOkaFU8CyvDpq5WdswA0VrOu+7rqP+3oFhdOoKCu5a5dVOJXshAYbnBydJNNgH8jPusSUnVYT+NcLgTd9Xnx/4DTgTx8uGoDKxBNyoTcOMS6MrhhOJsPVW5NGUBo9t7XEmtNd6myx40JiHbA+4Om7LPlMT7R33voHynXyCy51SgynkMCvOWwGJ0M6JvfkUFIVkuysjhaNfaqLopSpS5oj9gkCud3boZQDFYtLndy/5ulsqWRjOiaFU8Aqda64YKEY43aQmx1RAwVXOYtL3Yi2WEK6UEO/OT7Ocw+INN79Q+CTx5YzOBWUQYEudSEK2zpDZvn6S3q/yBoDSLqCmfqP0r1INTg17EaTtO51GJxYf7m2yGYIlGltszOw426iXJjaWttzbDXNqqM1z2TPizeTiQxXWTAonKq41BWSN1z7oFuK1wfEIFsdxObS8S1KoZZdqXAy3E+132Ry4VTRJ98A4J4TgEcucJzTVBb+GM0rnADgff8D7P1h8f82LwY2vpA/f6/3FtPUvRIAoVy580ikv1Xen9SgaXrPDPF81PsaE8PJqWZR9m29k7jHpYKGRyqc0svL+JaawumZafnj0litqkudqnBKfseyWeK9Ug1UO+yaT4c3s3Pl2PiNn836tjHiCZcSXV7jDkWxqNZzpn5UlEudIYYTlKDhatsm3500vwz42O+ycvT/2fvOcEmu6tp1um+crMnSjKTRjNIo55wTioMkBCIoooBAgEwQAoQBk0w0xmAM+NkYYwz4EWyRDEYIECIYPdkEIwwIJCGBApJQmJFm5vat96NqV+3atU+qrr6370yv77tf9+2ucLrq1AnrrL32+f8EXH6j/bdMMQaEUwxWHmj/rp0pnP7txYXxn0Rns95h8s+4Amdyolz5ZMeyMVLhlLPrbLvPPh9Y/4C2cbFPU7j039PVBReSxJIhTSqcHi8e1rqr8u0hYOGa6vkrZXIMMjVPLo4K4cRStIYc33VP6/5ul1KPH9s1Oc4JCqlwUuKvQ0C/U3YKU6FwKoWvOY4fHFI3qX83Ojd9pQ54YqNOYksDRFv9+Oafi/MqHgow/kG6cxI1XFYHhIIGkiXCSXgcBB/LQjipXizcz0lTK7qIDwqpY94krmfFiGvr9HDK3j/pSe5F29lC6rRBBy+P++D6sfj/TYTDRV/3AQYIBO9vk6R4TmRbIDOx8cySmsLptz9I+7tT3gwcfLm9jXKGo9VQOFXCdKZA4eTrDySJYpuo5SF1jgXLVrus4LFdV04I2mBMTbWtxVuLjsXNnjWCw+nhpJBAj9zJlKrZ5NPVNksCDLCE1AUqnCrHV67p9odUz5/+w95avK9s0LLUqQonj2l4aVttEQRplrP7LYlO7vgG8Me70vedTWlmZlu23tF51baCFDEclOlN4kf/XFUclTyclLpUOQ4nnEIUTiyEzxoOyT5fdXRB1ja9YFsUrPwvVzi5Qoa1bNSlOUR2rW77R+B9+xZ1Z1KErVFIHZ33vh+nrwscIhEXXHMfrR6UQocVa4JuTMPJdJx+L1c4Ud2hNpv2vebHwOXfSKNGVh5k/SlTjQHh1A14xWgNpRXijm/Ytw/xcKqYYbsUToKYufk9wBvnpw/jb3+olDeLz+edti3lay8UTjseXgxeFu2SylklkkQfwGgr7y3XSkKGd1jIPyDd/4obgb2f6TgP3JMwH+FUyVKXZZDh19W1eqllgMn3q+vhFKJwUvwJOGyrbaWQOlZ3fUQj1Uk5IA1WFdWFUCO5CK1g0/BEV3RQVpSJp9Lfce+tRSYMeVxnNroM//kRcV5FUWMc5ZTbamgP28NWXKCBFZ/o5asxsdnqLIPgOiF1rglLPnAkhdMm97NiRFva2SyIwoB7qJUhSYp6KFeInRMu3wr0VIXUKccY+DoN0AT4IluSFM+7JJH+8Mvy/5w0t7Vj/Bg2vxxXW+kjnM54T2F2m59H9rENeTi54Ov/QxVOrix1POlMTqhMOoi8iWJ7F3zt057n2Msi/+dG8nTuyQ7w9TeKzVn5v/+hYsKneTgBaYjWY/ek72ny6RpHU592+xeKz1TFsaUO+K6JN6TOQTKVtmsopK6kcDLue54wT0aJe/5T//xXTL312O/TMNlH79G3HZ1TJZz4vSJvy7H5eh/eYSF/oabh8jqW5pEhHk4ihM+HOUuLeV/sgu0v/j1sO6vCadKeZRlIr9Ef7wY+cynbl9fHdnV7oLw4Nn/7YsxM25PC6dCryvu/LCBhEuCe+1hN+LlpeBchddq2hiuc1le/p/LStZu/wi2QmSYMCKduIMM7kslyFgQJ6fFBkGF0hMmOUMKIh1qG1BE2PZ7GOWvlNW374GWY+7j0KKSOGgRXXLymKtAaShoUWk2VE7eioD0MjG8DLF1bPn/l3C7CSVNj8X1FpzOxMT1viXByTEZd5p9NeDhZTUodg0OgaCjVQbZSd469FjjkSvvxFmVKM9nByGtDKxdNgWc1A9yD8YraykE4afdmhAinjcB9P0nfr1fCouTEP4asKP4pXnwknev41K4BeiiKDXlIHVtFblzhpJSnFFKnqRUDCCduGu5UOLXKEyWpcNLIJ02uzyFXdCsKJ9eE17ddiMJJflZjoiuzp2rnGiAIxphnZq+OlZOtCHzMc/d3i/HSsCCcHvzf8v8dRi7Ywof5MXrh4bR0D2DJbu5ttOfNpuSoC6/CSUy2fBMsVzYu7uHEQ15sZXL1DbOXuMv+il8A53yk+rktuUJF4ZRNysn4O98++/72G1IPoRvfnP6vZakD0m0IOeEUEP70OEu+rdVR2zi0jsKp9L1F4eTcTkEyCdz3U+Arr0be1/g8nLjfkgZNcUYYnu33p6QQ+GNfpX8/OtdNOJ3+buDM96bZ19SMewrh5AqpI7WK/Iwg69MOh4sD8IQ0LtNwnlxlNP1/wx+qi5Qcp77d/l0sWuyZd2UUn5woezEB5fZGXqtcEdUpFnXbI1WFE0ES/EPjCIJTaak8B5OsbZOJiNKd9GNp7Yd2btNCft9LKl+6Biykro/hZROMMTdmr+/ofXFmGErM9LA/DMlmFstXiDaLh7NETIgGTwurAOzZ9LSQOg6aEANFvW2KcDr4ivLxbHJQ8sGS0DpVn8LJ5n0j9/epjRoNqduUKTM8GaUIvVA4+SblgN54c7QFo07Q4q8Jtvux6mjgvL9P31dCDERd/fU37WWqg4qHk4twClRb2ZQiROhOPFUQlae/u7qdJB2CVV2KpP13twWsUrkUTiP6ex/o+Z5koRKGrSTXhVfh5AmpC1E4uULqeNl5SN3wrOqCgjQUB4BdT7WfH0ApTAhQkkh0oRTyKZwmtZC6hpQVTSintk68Jnv97LSWol/A+9t/OCMLKzbVFWnZL08ypaVtUD7UNOGkJdSoEXb37Xc1p3Di6kkbghVODsJJVThN2ImXXOEszj13u/I2rvZv7jJ9EcIaUre5/L9pA7//EfCUTIOefU99NtWtyUm/J99dtwCP/c6jcFK+0/o229jERzh5vWsCFU4h6pt/OCP13yQfW06iETpi/OkaD0jTcI7PXQ584hnuMhGZtGxP/fuRudXP+P0YXwAc9HxYwzkneZ9PdX64+E47tqsNkNdi5xPL/5MCWu4HAA/8vHo+ICVZQrzPYiwTKrAonOR8rhIloFxTl+KL5rxcRTQ0WlU47XJK9p1oD4YDCSdnSJ1ynfhcvVvTcHVbpnDiIgRJOIWq3qYJIWzCtsaYYwGsM8bsb4w5gP/1uoB9h6t/COx6WvpePhjJpHtSpoWKAeUKxFPMTnYAW0idaxBiW5U3rbTz4cfh5R3RFE6WRkibKNswZxlwRrZ9KaxGezgSfYKtKU+o7JzI46FMmvSwtL+IewX0zs216q/6TVm2BTLCqSGF02QnDeHUVDLOMoWYlHoGU7ZBQolwEs3LHuv0fXY7LZUsA9UOppuBtjaYkEgSQTjFhNTZBr8ZMUC/KS8PC6mjQasWYx5qGl7ZT7mv//tlfdBn20+CTwCiCKeMYGrCw8lmGq5NLnwhdSEKp9zwVfHi4mXnWUeHxxWFk0I42dQVhH+5KA2NJpT8DxQFUglNZKnrkRJpoHCqi4eMMTcBWG2MuUH+TXfhphxaW9geqfYbsh2ndsG14KYRTisPAZZ4FNAEH5mkLbKFKJzSL+znjYEktDVIgsI2WaLPf/k15TuW5ThXFCmE09GvzL7bXGzPwdt4mzeiFz6FU/b/kw8D9/9E2V14LNG40Wc7QPjlVz2EkzIO1vq2x+7V9w/xbg39PpYYK5VjknlxZdfo4V9XtyuNm5KUVJmzTD+mS+EUAiIPh2fp34/OqX5Wuh6sXbEtYEkCKFdIa8q/SA8nTfGfn0+opT54KN+weDs0iqD2o8mM5Ln6sZOSroRKZmWhehyZW1ZaWRWRzOc0VzhNFuc9/xPAq39b3c+WGbpS/kgPp4RFI/F7lO9jUziFhtRlHk42T8/WFqJwAvB6AK8GsBLAe8RfBOuwhWDJrsCqI9P3oYTTsZnEVk0fi7JSqaJwYtvxh/UbbwEeEj4FBJuSiho7fhz+APKQOm76aDtWKLQG3Bi7wkkNqdMIJyWkjr/f7CGccoVTQKciy0jQMuqVNy7/29mUeTjx4zsGUS6F08RG4OPnpH91YRtA2/wJCPnE26VwEnVk55OA14m0t6VjQZk41FRGrDkxLBuajLd2moZLRYhH4bRk90K5BTCF08aCcBqdV92fOs+8TKGEkyVDWsx+Eu2hgriLeeYrWepMMaCJ9XAqtRMWhdPq49JXfk943fnmO1LTSRcqCqCOW+H0yG+KrCtewik7jq9Obl4PfPudxf+l1cEJ9/PgS0TgUzjd/V3gHsX7rwkMPJzq4gykKqcHUR1/vcex35YJrS1sj1Tbpop3Igups7WNJcIpa6OW7VHexkk4ecikIIWThSjuhrA9gqUhd/m0PedT+ue+kDoVTOGUeyYpXkZEwOf9hDgmb+NjPOa2OwBYtHN2TIdpOD+fLWJAElS5R48nooGg1c/yCfR9QuHNUhfh4eQMqQvot/PnM6vHZN7NIRX2sxcDr/xF8dmxrwbO+XC2rcU0PBRPZoRTaTGdYUQjnNjv5CSMVo5N64vP85A6h4cTjELocsLJk+kymQR4SJ31GWTHHB4PW0jqRnleOT0zDf+fzxefax5O/PdfdbMwtLf8vpLCaYwpnLLrNTQCjCljax+pRnMeV9umfccVTv/vH6q/06pw0rLUaSF1pkzo5ucl0m0LUTglSfIZAKcDeFeSJCckSXI8+zuh90XsQ/CwsPwzB+G0fO/0lRROsvJx+beMd3UpYWyTY9vnuYcTexh4ec98L984faFG6OQ3V48VCk0iaZO2J5P6oJI6qef+X3as7CGbsBBOXoWTFlIXoIp415rqNoRDXwicwAyy5SRvYlN1AOKajG1yKJzot0q/ihi4FE4hIXUSfBXX1nBKlGK25YpOzYmqMXZFYen4YtVUDhJ4eWJMw8mbgO8/wkPqXISTUDhJ0tE2GLX5B/mgdWSE1jDwgm8B5/6f8OMBVXKbT7b4NTnhT0MOVj4ugauFVmSZOEpyfXY9vvm2NHuQC1qImSSceNmfehS44cXp++FZ1etYMhTP2rTQFTaClKN3pRTyEE5AmeyiczaBJk2PtyIkSbIJwA8B3Jwkybfk33SXb8qhKpyGq+ORysSGhU+tPBjY6Vjg+V8rL7JpHk6mDS+RS/AqnBT/lhBFL89MVQc8OUsyaV8o2e00/XProqOLnLB4OPkMvG2EFOAmnK4R3o5X3pSatPNz5KdkIXUh41ipcGoNAX99GPCH/w0nnJxETreEky+kLia7rCjLol2KZ8E3WedjKbpP2oJpaayh1OvlewP7Pjutt4//Xt/GBnk/KaTOpnCSKnSgfA18i9FJp1Ce5Yv0WZ346msKDylevpiQOq194Ioqa6QB93AaCxtHdxVSJ8BtCTjUMbRlfAfY2xjeFgw5PJw0rDwYOO61+nf03MVmqVu2V/H53d9z+4JxaCF+tpA6beFhC1Q4IUmSBMDTe1yWGQTFFNlkoWpq55F1mhOWSUfJJFaYhpdC6hxKGw5nSJ1Y4eNl4YaWOVuvkDLa/y5oqheXh5M2+Z2cSDsNIu942WwKJx/h1KoZUicbE46RWcAx1/LfoZsHAAAgAElEQVSdy993FMLJRVy4QuryMIEuGhkr4eRZvaPyL95FfM6MDG3SUImSwkl6ONWYYLdHgaNe5laH8ePLTGMcrrphC3WjY7ba5Q5weAyASctFoZijcxWSTYROyfOEEE5RRF1ibzPaI6mh+z7PRFRnRhONPAyATbZKPkghA37LgKTkL6X4ucXWnXx7CqnrVGXxtgENDRxKIdFKSF3MRAKoLkA472ugLxzh/oCMLdpxtOyiPgw8nGojSZIOgB2nuxx9Aa2d0ginyn4sS93wOHDxDcAOhwJ7n1dsw8dCud+cJ4kFR0hInUsRDFgWSbhRcARe9RvguruqfVhsWFqtiajSZnNj3fw7qR6SCic2BqEEH1p5VKUAjTUdJFdI/9Nqp5m07rgp+38IePD24r0PPoWTuggXoTbRwtZKx+/CNPzqHwDXC9LEBi2kv7MJWCCarvVM5a71L1QHnnw4Vcfc/sWw8wPV30pj9REL4bR0j+pnNg+h5fvox7jxTdm22T3jdVH2sb6QOlmPNYVTrqhSttcwNBY2ForOHuwA3Qc5V9JMw11ZEjWSHigvyrZHs2yBnbC26vKvA4ddpX9H6rSYkLq169JMgPxz6TVrm6NpC5A20/AEwPc+IL7Inp/cHmYLIJwyfN8Yc3DPSjKToKV9J8JJi9ul8BIaTLgmHTykjseFAu7QLg6vaTiLMeUrSLxcOVuvkDLpyfVz6Ccu3gYpnJTydybSsvCHsaUQTnxyXkfhpP0uHqftg8uTIUlSpYNc8bJNxjqb3RPMfHLdJeGUr/KIMvFGd3wbff/Fu6QD2znLs0M4QupsnzUVUnfiG4CrbgH+9AFg1VEIq6MiS13Fs4evcImyWAmtpJD38g7QtIGFq4EHfpYakA6Npaszld8sQqek4s82yOB1LWZSYXvmgHJ68JjOrCUGVps3sElcIOG0+5m0kV4GjXCa9KyeukDXL8+EolwX20RgNAs75G0Ovwf5YoPHw6lSJmFoHxzSY1FKcPzrC+POT5i1sAh5CMUgpK5b/Hfm23ShMeZc+pvuQk05NELmifv9kyWevIDDtviWj1MaJpx823zxZfqx6yicZi1MTY+lQis4CUWGmMXF+ZknYX7OhBFOiocTfdfZXP5fOzeRZa12qrwpb6iUm481lWNqIX4qDPDhY1MvJsCuyLaN6zf8Ie4auo6l4VuefE6+Z8O2oEP7tgPJL5s3qDzmZy/jOynlEeXlHkA+8N86tqDwcNJC54DUIqVyfhG5QtjxcODyb1S3JxVTSyEr5BhRzVLnUDip7Q9XONmIER5SF0g4Napwyn6TJJwqKnIhqgidM5QUTqPF2CiUNLNdN7oGTv9acY584Z99HhJdAVgUTtn1uPQrwNkfKj5LJqvP+k7HpK8HXhJ2vmlGTCt4PIDvGWPuMMb82BjzE2NMwznKZwpsCidLBpBWO21IqBK6Jh2VFJLsYZSTHytR4UrlTbG1RDixQVaJbRUeTnKgIAdAx78OVmgSVVdsrkaYdTal17DUwWsKJzY5d6mDAObh5FEGJBGhLC5ijiagQ2LFy6aUmfAodJpSOFFYF1e4JZPlgQZlGSTkk2mTDmwJLRaCoHYentU8X5Y6F0bmAMv3Ct8eqKqJ5PNbUqJxEmjC7+EkFU6tNrDd/sD9P01D6oikkL+5ElInOi9bZ9kR4VehSGBvM/i5nvWP4cckNSVhPRt0+0hJArVHtgFxiSzP3ssMODGgesDDAuQ9toXEjS1IX3kSAV6W3MMpknCS5XP+Jl87EHk9fvwvej1qjwD7nB93rIFpeLdYCOAhACcAOCv7O9O5x5YI12KaC7QQ6FoQClI4JWn931UJP2uCcPrtf1aPe+d3gA8dVf08FBXSJpL8DZ3EPe+zwIszD7jcQJcRTtIgmJctD0tyeNiQb0trCHjJrUWbu+ZEYO7yannyfW0hdRNhv820UrUNgfeJfP+X3+44RuQYLUS5EgrTAi5y5Bco9cfdjCUtC16ua+xSONm2cREj9N2yvcqTeVu/rfXHNoUToNez/Fjk/yMW2uSxK88Ae+8NqePjVZeHE8PQeNgzH6twWnNC8X6HI8rf2RROd95c/j8km1vF120kbQdywmms8D0NJc1shK7Pu1groy0cOAQaF0C/YccjgP2ew8qlPCsLdgDe+GgaJphuGF+GKUSMS5glwHsrRD5x4isdFlMv2r41XJBJo3Orsb0El4eTPLZtMu4KqeOdP1rljq3VShuniScRrXA69lrgprfYzyvfk+pLIrGE93Q2ZgonHlKjKZzYe5/KI+8glDjtJ4TsN3SQ5hrQErHUHil37DY23HfO/Hd3STjRcWRIVojySJWrKwrA0iYtsQLWLn9XF8T22yDPC1RDDCodoEXh5CIDKX29JEhNO/VxmtiUKpyIcNJ8q3g5ZP2wDUZ5tsJYDyfbRI53zNvtF35M6X2y/sGiDvFnWDN2zI+hTBhsg8E8Y2UXCqc8lC6rI/I+0GcaxrPJz0ZGOHEimZ6xWIUTh880nP9eanc6E8Bvv58q/mIJuM9dAcxeWv28NRQ/MRmE1HWFJEkune4y9AVcCVGc+23St+P9wbCmcFK23/5Q4LmfAm54KXDbx+xl0NQ8WsgIh9a2b3io+lkMpILblYlV3T9wEjc6l03yucKJQtgmURmr0Hf/lIn1KqbJYmw2ycYldO/O+ku9PbKF1PGseaHtcXu0qHsty3glNmzOeb6GCSfqnwDgGX8nN7C8j8Tvf1S852OW2DGdL4x1ZHa5n9X2NS2hgLYQDNp1dnmKxmZulh6svpC6isJJiwJhWepsiuuFq4qMi0Oj+oLP7KXA+gfKZfPhyGuAW96Xvj/86nTh6e7vAaeIuV/LQjhJTE4AX3gp+0B7jmUbOZLWr9w0fBR5ZudghZNnO2dInW0uVGPuEpqlDsa9aMfrRB8jhnAauH4SNAUHTWa1ztyQwinrsOYsBx76lX5s6eHEK5AkYqweTg7TcJrsUYYNWbmHM8JJmobLhiBm8qJNErXBF+AIqduclrdEgmim4SKrkwvaoJKu6fsPYMfphIcouYg5rnIohRtZyAvfOaXCqZaxaKITTpOTwBBrdCsDb5pAZuemUKLROYUhtq0BlsRPSQVUI1PGsz4O7LHOvx0Z+3NIMtHl4cQzfdgyTgIFiWXaZXKl1U47mM4moXBSQuo0ojI/juUaccKpKQ+nbT2Z3WyQhPLInGLwwT+fvcR+DFvocv7eo3aMfR7uvBnY6xnlkLqK+bDluuYKp0eLz/h7LaROI0Bd8JmGl35v9v4bbwZu+Uvg8htRqwvX6pF10G1ZhQMGCqcuYYz5KJSLmyTJ86ehONMHq8IpJKTOKGMOi8IpJ8eVya9xJMzw/V/5TBy/G0LaBjm+6VVInebFEqpw0o4h/0865UXY3DDX0h/m986hcDIBSRyefDjtpx67J/2f98ehE9xo0qVBwomXcXRe2bcMKMo2eymw/wX1z/NJpnrl18j127V+ofIsi2bPNUbkKuqSAtpyPbVjleYrMsTQcW7tO0mQ+0LqKh5OnpA62+9a9/7UW4jmkNp13uEw4HamfLPV5WNfDXzr7en7ZRRBYNKs00Bq8C5B5SbF99GvAG5WkqpWkvRYwuc42iPpfIOH1AHp3LlOW1X+IjtHhIeTzFIYBS3iw+bh5Bq/scyFfYyYK/QlAF/MXm8E8GsAX+lFoWYMNMLJ5uHUahdkkkuWudlhGl4xXKujcKKQOnpIRAWlbA4y44JroOaDNkm0Ndy2AdHExmwSyyeZ2TF4o15SONVQJdF14SsoxJ4HHcvxwPPU6KWQOpvCyUM4fZUyLQjjzRgkSXG9+f7JZLnRrcT2C+XbpoxkGl9YkD9rLSSQ7VhAvKwXCF8N1OocGZESJGFsS4v7tevt50mSlJyS9bVCOM3TyzUpiI6KwsmyWrf+AeAty4DPPD9e4aQpB4bGqmnBQyEnVyf+KRsMsmviIpzUztNjIC5TLsfgM9ncna79pBJ+YnsmyQeNZxwlzw9ANw0//d1h5aI22GcaXlIoZr+dTEs3PFyPkNbqkQyvJbh8RwYeTt2Cxl40/poHwJLHfQtGbYWTJXzK5uFUCv1nbc6TjzgWUnxeOZrCSRwrNqlAENg5H7kT+PmXqt8/7W323WuRKjYPJx/hlJ3rym8W/iUEm8LJdt1tof0uAkzD+gcLsgkoLxCGqrNjJ6ONKpzYOEQleLLrtO79dnPtWJQUTl2G1Mk+iIc32vZttdlcpmWvwy5lHFAtu+u+BN0zjXByKJy8IXXKmPbwF6eeq/s8qwjJ0u67S03Iseb46mc+JQ0d22clIIUX2nMi7397BCCfVKDw5woNkXVBRvZosCnw6qiL1BBC7bMtQ+EU3AomSbJ3kiT7ZK+7ADgEwHd6V7Q+hlYpiXB67HfK9pnCaXMA4bSJTVh8IXVWwskxKKPjkZRSUzilX6QvoR5OLpQaVAqpGyrOUTquZfLb2ZxOvHym4XV8bEqEk8U0vK7CiR+uFFYTElIXek5aTaxDODGCrxJSJ8gSIDVyPunPgNXHlc9NmLUozST4xkfLGQXLBS7/W0fhdNKfsX0CB2fagECqWFwx5Xy7H3/acSJmGi7l2UMa4eQLqQs0DX/igbQu/fSzcabhj96TXofFwkDT5nsQAj7IXbsulcHz1UfCyOzqvvkxlJCIUluihdQxb7G6otxc4aSE1NF13fnk8udaSB2HFlIXOgmha+T1kuMhdUSaUSrvNmpdD9kerj2rGMS+XsjlXQPubtK6D4AkST7L/j4B4FkAIg3rtgDY+krbQJuSWXQ26RMqq2k4GQCLff7wvw7CyTNGMi1U+j55rFCF0zJb36qVi53jw8cA995a/n7tmWl4jA3BkzibwomFsNkyxsmybrd/2s7wFPC5aTgRTtl31tTwlpC60jY1JqiaP9H8HfqXcOJqY7UdZuRgLxCt7hL384n7qttc+S3LuRhRTERErFrMFrbvO1bIeVSVIz+fDKlT1DS+kDpb5EhlO/nbLM9C6XcFEhp0bFoAtBnPy6xrIWUfEmO9POkR6j3PGkJUdIRuQuqCCacWnM/nrEXpq89WZJpRRwMGAEiS5DYAW2fWOqoQbUE43XEjsPHR6vatFkqm4XxV/5kfq25PkJNGqVyyKZlcIXWUteFTJJ2VCqeMcPJ5OGnu+jbYFE5RIXUO0/BSSB0PqelC4STLNOma6FmOle5cvKVyyjS5Gx4C3jgf+KGIrQ8mDYTCiTfABC39K+1D1+yPd6XlILkq72jouo/OA476k+Kcsv5wA3HboMmlcArqMExahlVHZ+cJJKlUhZNQsVRC6lh5aDtf9sM7vwM8/nu3wumpx8JNw+Uky9YZbmKChxjy8cuvTF/3e275825IAp6ljiZRWpjK0j2A414LLN2zegzbSk/+nh0nH4QwFWHd8nPTcLqO53+i+GxsPrDiwPI+9MyRhHxItI8d9uzn5fd0v5SGOV/BUwiwUrl5SKwknIbs1+PCfwX2PEf/rlKPlMUDgmuSNPBwahq7ANhhugsx5bCF1NkmS1dmqewnN+vPm83DSVNjEqwKco8K3DfZBIBZi/VjS8Ss5PtWvb3KrFCFk6Y+TVAan/BtnvNpZSxgCadqDTOFk1DrWNUrnpA6+T4UXEVr2sCLfgBc9W3PdY71cLKZGteZ1LbF/ZDfd2PJEADZT3DsebZSnoD6ZvOT5ItapNaKJe9iFE7HvaZ4H7JYqrUBTg8ndv7xbbJ7xLPUaecMJJwqZJovNBX+tiTfJ/uNNJ4OJf3U+i3qZVuM9fh8p1uFE12DqJA6C+FENgsLVzuO5VHx889ci43zVwAvuQ04+c32bfoAwa2XMebl7O+VxphPAnjQu+MWCRFuBvhXN9rMw4kb5Y5a0nUC2WTBkercZv5oy3pmWsWEiCTCtpA66eFkWsDTP1hst8+zgRP+1F52eV5CixFOVoWTQrR0NmUeTooapq5peF4+YUxZKVM3Cid2PD7p1BoamvgTghVaBrjt48Ans1jqYUUWfdDz9X0nN6PSoD/xQPqbS4bydI2S8qv8HWPMnHL+Skt5LTJ6wD04kfvvcHh2nu39+wCWDlV4OMlnil8D6ljef5D7PH+8K/XvMe2qwomO9+TDdtNwSvFKqCicPGEXQ2P1JvjtUWDdB4pQr258d/jAKg/LVRROxgDHXQfM21Y5RuVNGZrCaZKHrtVV9DDzcLqOdN/Im2tI3ANSq1FWGknIP3RH+hqqcDr++mKgQgonWS8qZVeUevTqGgwPjdm/l/Vo9bH24wxC6noGY8zjxpjH6A/AFwBcN93lmnJo6uez/sr+LPE6qYbUWTyc8n2U45JXnq8d1hROvpA6l/q9LnwkRbff59sp5tPcw4mTTwCw26nusQAHb38rhJNnou+65nUIHL4o1WoDS3dPyYBGFU42k+saIZd88UcjlVxkVBOw/fYla/X+MGQMaANf1KJ+sxvCqULKODzXQhY+VQ8nF+EkyC8ZUqf9tpCwNDqerRwcdXxV6di5lUAo4RRAaOUZiRXCqc7zzJErWyMIJ5vCqTUEPPMfgEu+HH4s62fGTwgvWhO++D5NiLk7c9nfKFJPgaf3olB9D3ooQlerc9NwylLHCSclS9P4NumrTIMtV9Y4CbL6OOCs9+nb8XJTdi1agbcplyphgwbY/3nFdu0h4BhBkJz0Rst52TnyCVBbn0fajNc7m7J9DPIdNaNgV8Yxl/KLn1+Ce+rsea5+DO1YgLh/lix1BDmYiAmpu+HFwG8ymfH4wuo2tomqSk4m6faaQXuewctiUsdDpGzhAd5VTQ9o/+NenbL6i9aE7WdVOLHrLOsI7yipPj2uhM2q57MonIBUjTQWGlIXmKUu/36kJuE0DBxwIXDAxen/+zwz/hgEvqpKnWAudw+dwHhCIvjneVvAFT01CDN+/znRTHWHJjzyWaV28+7vpa9yIeGuLPq8tEjhCvVoFb8pJ5w8IXUl4pRUWrTCOBTm7SfBszG+/OfAQZfZz899GobGUi8JwsA0vCskSTI3SZJ57G/XJEk+O93lmnJoq8Xb7CjaFKVdAPQ6bgupc+2z7q/S1xNe5yxqkMKp4lcTaOjtm5g9j1WNUL8VjjmM+AqeLLLfRsT04l3dBI+PgMvLyBYX85A6H5luGaPYklCEgiucuyWvbKj8JmWROxSmxUgcR0hdr9po23WpGEZ7/F0laJ6kHcO0in6zm5A63z3lfV4TIXXyWZPqolJInUXh5FNyurZTy2uxNHCh4uEUeg9CCCdGPgPNhtTZkkVo2xCSjv45klQ5ri2mEnwq/tJ2M9+WIJgOS5IkN00xxrQAzEmSxJGqaQtGPpEKVDi1MsIpz+TFSKYRReG08mDgl1+rrmg7s4uweF4XsUJlGBoFPn5OMUEiVBROnkniIS8oHqijXpaaalLazPy87AGiRqI9DLVxkQQAobOpaNBb7XQbmvRx0iRRJl0EnsXLVj5rSF12LJ+poqse0H0ZGtG3kx2WLP+CHdJ7/PCv3WWYrcjybQSE5omRm16z5oFIA57BC6g2jlJddfaHymF2gL4SEIM2qwehZBOgs//cw8m0q9ec3xO5wjA8q1C0aJBZ6ky7PECxhtRNluthNOE0XE9RQgTh0Ahw3V1F+Tgu+Czw+H3Avzk8P4Cyb4QMyw0Z6CzaBUGDD4KUWdcNqSuR14zg4ZMc06qaYEpFk6YyBIr2dNlenj6DhQ+HKpx43f39j4A//LL4zBh7NkxV5q/ANXACRNso7t0gpK4rGGOOBPDfSZKsN8ZcAOAAAO9LkuSuaS7a1OLIa1Iy5PNXFp/JUPvWUEHcjMwp0n9rA/nDXwz87F/T9yXCyeIPdNiLgO0PSd/zVPMaVIWTJ6SuqedkJVPhehVMyuTq5benZtnf+wCw5oTAk7Lru/+FwC5PA+YuA35zM9vEQf4AdnULJ5ykAbY1AY1Fhe1SsISA9/klQkCUffXxwK9vosLEnUNb0Ni8oZ63U0nBr5QjDyWN6G/XngVsfIL9vsDzc8gxCj23PtLgvL9PX19wM3DT24Af/TM7Bo05mIdTVyF1nmeHK50bCamTqiNRltoeTprCSfFTG19YNmWvRKJYrDQqxxYKp65C6gTkWI+PU7tRxwFFOZ0hdXKRwKJwCiFwVXKpRkjdDEFMSN0/G2PmGWNmA/gZgP81xlzbu6L1M4TCBvCsVmeEE5mG88mJGlLHTBaRFH4hLsULl2q6TMMpi9IjvwHu+EZ1G6uHk+X3nf7OlGhyQiGcrB5OSRG2wjHBVraMYKHlJFF7DxRG6ZXieR4DrjgZdpgcq8dS0tu3R6A22JK8kPf75DfpE1l5TpVwmtAbfRvhVAmpI4UTXVPLAEo21Ps9B9j1aaK8cpDpWk0YqhrhhQ4gRoWXlfb7eZa69kj5ms9ZVh74yU57mceztyWUI61Wuew54aSE1OV11ygeTr1SOLHfOr5Avy87nwTsepr/WHxVNSeK2WDQheOvT71XYrwliACa5AOcLgknHlLHMyOZdpW8lM+lTd03ezFw1S3AJV8MW6QAioGzZmLOwetnZyPwgYPKflSuUOsmVud5v2aMn8gfIAZ/A2CDMWZfAK8CcBeAf5zeIk0TNCNfTSVgWum2Oxym7wcA2zMbUu7hlIfSCjVyzORV1nnTQmnCds2Pq32hc1ExAi4iREJd/GqlZNEpbw4nZWSo9NxlyueOCbX2P7X9pZC6rF1ctEtWVhuhYVkUk+W04bjXAHsoHkOb2Dit9HvYsXY8EjiDpYGPXfyQ9Yz6kzqEE1/80frE096VEq+7nhp+zPP/CXiuK3EKg1XhpBBOgL++7XZ6+rpg+zQss3QutkBOfXLsgmYMIckXnkKz1PlIJY4nHxHfsZB/GN22QrveS9Yq2yl1/7rflOu8aevbhaomJ2ND6iIIJ5rLlsIyIwjk5ykCYZo7xYTH5u2MI7qlW5jWliBwigqp2yNJkscAnA3gy0gNKy/sSan6HdEhda1ySB1/+DiBIcPrJifSSqt5Fekncm9nDDBvhfsQcqW+0lBEmh8C5WsjQ1QkksxTR07gyMOJ72ta6WCTT8hlpjWO9Q/q98kbUscJJ8Usfcej9GPR8W77eGoIXvJwUsohJcKVyaWN5Rb3ZN525f+XrAX2OR943f3ACuE/RJNQfj9IScGJjXzARwon2+phQP2IUThtfygwIpQ2thSrEi/7qdhP8T/ghvDt4WLAv+9zgMtvLBMLlfSsnk5Ueji1hsplIEJM/v6EmVW3h6sm5SEKp5gsdfl+gf4QQfeYh9Q5PJw0zN02JeNiSDNS1/zm29k5HSbZLpRC6piyUfqZbRQZ6WU4jlZH165LX5fvJTw/tAFduzBGXZB5lMWE1MnPko47w1e3K4OAQsZzwmmgcOoSE0mSJEhtDN6XJMn7kNobbH2oLFgMiUniUPmV+lXfZIQ/wwnrEzhC+570IOV/ObE7a6ESCojwkLokSSf9NpguCac6CAl99hFMlXvETMOBckjdJV8CnvcZR39kC6kLVLAc92rgzPdWP9/M+mMbsTdvhfB/jCTcZV9MdbNWSB3ri7VyzF4EPO2t8f4vPiJnxLKgRpBlyaMpHM/pMdeKMbhl8dK004gAIPXUjIH03XShlNkygOyQIWqA/nyYduqTS4lx6DsZUrf9IcClXymPkbU6ffKbgHM+LAujl6PiKVUjpC5XOGVznmCFU8DxSVX2gw+lr5RcBYhTLO5yUvWzOUvT16cs2Ya1c1iz1HnGn9sf5v6ew9jmfjMLMT3NsDFmGCnh9G9Jkihuw1sLRLgZUK5skiyh1eqOMrnnx1iwY3k/mmCEEE58MONaJTv1z9NXG/FEZacHn0yg6QF85S+Ba35kP76tbASeppsTNYRkMi2/7PzIw4n2peNS1q/8+I6QuolN/lhm7fvf/RfwlUzMp6VxfxZbaNYk8je8GPjSy/2m4Qt3EvvKGPcW8MDPlPKLYy1ck5rVEa7+frra2GpXf9+ns2yFvOPsbCpngwHKCo/0DZ28Wh4fKh2u7CQ8JFZo6ugxQeBqRE1OKpgiVBMA9n12OtEvhdR1ypnAfAMu6eFkhPdPbhou6kxnE/DV12bHGK4+977ztkfqdU5NEk6lkDoRlqsO4pRjPnJn+irbRQ2VNrcBhRPPUlfKpGjKK4+AfUW6tI24vvn1UH57qw0ccgVw7R3AbqdVy6NBJZy4wslCOJVWwBVc8qUiS58LrsylvcqAtPXgcWPMawBcAOBLxpg2gAZzp88gVBYsJLFP44Ts8tjaWYkS4cQUThwxps2ukDob+R6jcFp7VtlrSZ6r+Md9nBpduP+cls9d6g7tewKNBzubC3J87jJgl5Pt5cmHKErokO38ElpYuU3hVJoDjIl+LrL9k308TYRrK5y69LaxHdcFCjmtq3C66jtFAhO5DcE2lmy1U5VZHcQonELHovzYLtKV3s9eApz74WqYepIwRU328Y5HiHqhPNBDI1W1nnUcxwknSZCFejiJuWgvFE75Pm1gzYnF+25A7SkPK5SoiApsIXWO82yzCrjgM+HlIrJxhiOGcPowgDsBzAbwbWPMjgAcNOAWDG2wwN/LRogUTgRtcARUH8rJDoCEhY55PJyoDLbQCSAlTMbm2ycf+aQha1hIYrg+S0g4Z0n6sNhAqwqlolkUTmf+Raoi4SACQDLinc2oZLvSsjTwh1J2aDbVB78H2kP9teuL8EMtpG32oqKhko14yZDao3CSShZ5vzXvGKC4N4RWOzWrO/lNwIGXlL+TE9YND6WvvM5Obq6G1IUqnEIg762vU5ff18nUYtuPPJxo0k3XnDouvo+ctPs60dZQ9VkfUggn1++vk3WiiZA6J0IUTqw9yp9bjx8c3xdIB10AsGwP//nkc9ke6d7DiYewlQindpVckQNhlXCy1BetnFQnZi8urt/nrwR+/S172bX2jT5zKpw8IXVL9wDWnmn/niD97a2QVokAACAASURBVErefQOFU5c4H8BGAJclSXIfgBUA3jW9RZomaApZLdMT1f1cOe5pD/gza1U4xUz4XVnqSE1gWS0PhTWz1DQonGz9glNR5FAfASykjvm2BIdIMSWItTy+kCnlfpc8nCzheUPj/nGlC3JMMG+lXh7526SNAG2TK5y6JP5fchvwil+EbTvm8Tir+GUKwmn53umiC4cvJJMvbs1aFFZOiZj6Mdfja1g5tnE/AxUlmvgumYS62BtCklXGdxYitqIW7Ubh1GvCKVNnh5h9h2Cf89NXriyTqMzxOvrnLtX4LqfoZLYLoerXPkZwT5MkyV8lSbIiSZLTM2n33QCOp++NMRf3ooB9CaM8mK4HhftxACJUiQ1ytts/fSVfge+9v/AMAfyrX1Qu33bcT0oin7hljRo12hsshtsSBz4f2HZfvVxAOYvU0CiwZLfytjnhJBVOG6sdEimcSvs7PJzogT3osrJKy6dw4rCZhsvwGMqcUMo2lk1mh0b1+iJNfTWFUwiovhx5TZG5kNCxkG4lhdNEZhqueTgJhVOdwapMKe9btZLf1yacLJ0e1TfTYh5ARDixcyeTZX8038B3aKw6eNEUTjaDaaCehL5uhrZgr47AkDrpdScVTzbQoPisv0xTysoQUQ0VJcIQ8LvbgCce1LcHgLnKcWVInTbxNC3giJcCB15afFYhnJSMV7bJwpxl1W1ldkMA+OPd6W8qHdPhMQYwwmmyvoeTS7lU2k4SThHt6gBOJElyX5Ikf5Ekyc3Z/3cnSZJLa40x37PvvYVB1lX5XNECDLXVpHTd5EjwAFQXF7RjxygaNA8nOXasKKJrhEJrCB2bhnzvwlXf8R/HVZY6IXWhKgZt0u4rj4bLvl7+3xWaTJAKp2iiR5SZvHpkHXZeC1bX8t/ZJeG0aE3hzeWDNgbm0EzDfahM4i331rTiJ/TyGIB7rPKyn4WNTUrHVggnXm/GF6ah6ae8pfqdyRROWuY3fkybIEBeO0lgaCF1FQ8nQZjbIEUSTS5m8mPlXlEOyxMXXvEL4FqWhGnlgcAbHy3sDEJgU50763PkQr1pBVjq9D9q9zRJCt47XtNAeWYIlNWpkopHGWjwiWtrKM32dMmXypPv1ccCL/3v1D8GAO77SZppiCruTx0SPG7S6quYraFyumsOemCJkFqye/oayuS3WlVTYX5tKGPZ/MyXRHbEVsJpE6rp1U21IeOdm2wIiGyZv7LcKJcmRp4O2WYaLgeSV30nNbUsGfnyjkJpcGR5ZUcdm5JUg21Au4l50nSy0EM1pE4onOro8eVk3KtwkpP5BgknMoYmnwOqI5rCyTVp1zrU4fGqSox3iDQROvdv/WV2kVISCTeWjEDw6lBgSJ3MItRiz20IxuYDqwJl8fKYT2QJAj71XPs+WngsbxcnO0yRKTychsdSjw/+GYdWHyR5SG3F2Hzgtb8X2yrPnsROx4qQT4v/HJD2Sc4sdS6VXeAkuzLYG3g4TSEUhnMLhaZwcoEmnr46qHnuyAQfUabhUuHEJpvaoiVQYxW7jqrIsW0suIolJETHRzgFhdQFKpy2OwDY73lV7xqXp5QGOd6YYOPrIUubNzTWncJJlmt+ZoEhE9+E9Nk85HQqiX8KqbONOSshdS39c46Kwsni4STV5DEIrR/zV8QvfpoWcMLryp/xezg0Alz/O2Df82mH8r7JZBEJwTOcUzmHxqpJejhe9IM0gySgjAcCFE75pr4wXeHhFGzXEPI8KibhdB4t67sLc5elESrdQM73Ca4xVWybWyeSpA/RlJYWqDXznKHQBgvc0FoSPpSljtAaSrM9rTqqut3CncrbhkqITQv5LZBZ6i79d+DEN5TPb+t4aNJAqzirjgQuuiE16wuFK05/72cC530UODxLqz46t4i/BQrCSYYSPfWoReEkQ+ocHk65gZ2jfHUVTvJYC3ZIw1C4/JrMC9sWhRM1XI/cCaz/g0XhFEAkuBo68gKQeOpRVo4spK7U8cjBQBchdXKVuFK/fQqnyLj5fD+baXiHKZyIcBLhYEA10xefUFQGnkg7f65eGZtf9hWgUI/5K4DjxSAkL3ME4XTxF7JyTtRUOAUO5EON4aX/kW1VvwnIMlEd+ePdjn00laFIQJCH1ClGorNYNsgghZPNw0kph/T+0rB8b/+1LJmG11A4tUfc0nCOisJpEFI3hdh6TLLk8+CbdJPSwreYpJG3XfU9SkidnNTVVThpagTte9c2pXLVRAix5TQN9/g1JlLhtDl8YaQ9BJz9QWDxzuHl0SDbcj6+r5DsSbFPKUtn5OMprwN5rsq5RYi/IYy/DtTFtXcAp71T/y5XOAUSThRC74Jt7L5gB+CF32t+jKHVtSNeApz6jvS9zfLg1XdbSBYDrDlBfBQauWD8hNOlXy6uu4aluxffVxbANMKpHdeW8P2AgkDXxkMaYkPqpJKqrqqtLrbbH1j3Pv07VzsV/TxuGfRKkyP/rWjAozRqlAmlPaKkMZeEk6Ui5pNcHsaTBHawbPVMhtRtfwhw9Mv95weKSQP/DauPjVvZc6b9NMBe55bVDiQfBewKJwC467vZPnR8UyUvSqbhlpA61yqJb6KuEQtUFkBZHWD4FnVSFtNw6pjfty/wkePrh9S5JojnfbT62Q5HlL2eOhNV03C6ZrnCKf8ifbnky+lfCOSg3TsIFd/HGjXm59UIpyTzcMom3XlIXXbOUkhdRwz4OOGklGl4XKzGiPrKO0etPgzPKuoQn8zbOqudjkm9u+oSTsGGi4EhdTIsJW8328DFX0zVnI1BlIlSnNtUPYB+HaXCSTUNV+pGZWKqtJdycMoHeMPjaZhefjyLzx9Hqx1OBrlMwyXhtPasIqNe6EAR0BVjhEFI3QBNIVbhRLYAPvWQDJ/WztVr0/CHf1P+3zYJj1EY+65PU4RTyDY+0/CKp1U2BqL2nCeP6Qb5WDtSUUFlINgWgobHxW+JJZxEuaQ36uLdgGf/M3DEi+3HIDJM9Q1qCLMXA9vspH/nI5yk4vD8TwBP+/Nq8hwOW4KZxbumXo959ENDJunacU55C3DYVel7W3swNj8Nj6scz7O4VPlOkKO/vgl4PFND88VvPrbygY65dG2aXIisXAhy7FHHNFzawISqzUKImFJ2eEFsucYgvcCV36wSiARnO1UjpG4LwEDh1A14JSBzbS07kqZwch2vJTqqYAacCCepsIoYoNEk2JUW0oeKJ4+n/C0x0LPJpp+4P9ueDdacpuFS4URkgiyfIn1eLLylCLYVDdXXy9LgDDkIp8fvS98/erdCOEU29hrmLAFWHlz+bN37C8IUSOtPZ2P5OLkkm+q2UDitOjI8/KkSUudROEnU9XDS6hQnOE3LbRouQ+pKCidlYu6brNti8Akjs4ty8JVU12ppaygdyNUxB23Sw2lolMnbFYXTTkeXB5ajkVLoSpksbZwtdFjbB1AUTtkzyO+VNkmpGOErdc2lcDIGOOnP9P2tCxTtsjIRAJas1bd1mYaPzRe/yRTtQQzhVJqYGZSe40FIXVcwxrzMGLPStcmUFWa6UXnWPYthRNr41EOah5NplZ+/rk3DqezZ7ZJtCQ9tB5qZQPkWaHqucHJs4/uf7gO1QzEhdU4o47UjrymnlydU2kB2X4ct7WN7pLuQOvk4L10LnPJWlrUtAXY/Q1GpsPeXfgU4/vpsHNHDCavt2KqHEyvgia8vbz9vW+DwF8Wdi8YiuRJOmEcPzwaW7e0+poZzPpLu5/MEco1FVXJJGzsEEhNP/jFN8nPze9LP+eK3OncMOOae5zDSlNokkSCljml4JUtd4CJxEOGkjMVozhvr4dRLhBKJQcdStt89IJFLnyG4FTLGvF77Y5vc0oPy9Sc0OTOFV2gTHGPCCKeWhZ0PCmFhslkZOuEzYeaYm2VbI3KnDmJXF0odc1KEOPmOb1oeDyfRyeeEk6N81HElnSrzDzjKpQxgbAM9W5a6pAM8em/xf2WAbMKIBF+nw8MraXtenl98JftcUXXkIToWQ84QeEPqJMRvbtI0vOThZJhnDw1cREhdKVyVlWvtWdVjU+f3ktuAa35cfH789VViQKsPw7OKz4fHi7JomSAJraH+UDgNjRUD9co1Vc5zxl8EnttWJIuXg8vPTrvmvP1OOkWYK68H9/2kup/8TVGEkzL5dCklXVj3V8BhV7Pj0IB80k44zVkqrgVb5IghnCq/r4uQkgEk5gH4qjHmZmPM1cYY6dx74XQUalpge9ZtCM1WVQqpY4QTD0OPMg13ZKmzeThJ2Dwj82NGTtD0g/iPYd1VqNe92wR68BDoPtB1j8pS54CmMDv5TcBr76lu6xpv2BRO7WF9ITO2fPn/7VTNRH1/HvLpqPtLdgeOfVWxf69gqz5jiocT1cU9zgYOe2H8ueTvXbQmfd0t842VmXBfcw9w1c3uY57xF9WsZPueD7zwO/62xVUXtX21Z8TVBpQSLjGF5shsMV6g15j7nLVP+eLSaPUYMgNoqGk4HafDEiURaOx76FXFZ9sfBixcE1ZsTeEUS2xNBZpQYhJkHVn3fj1apc8RQ3uvZ38dAKcBWEVfJkni0HZuaVAGC7SKpk1wKiF1HpVMrOKDysJD6pyNmEsBk41jn3jAvo0Pu5+evi7doyibC9Ks0xZSR8gVE6Y6GPjFV4owGknY5CF1sjxJ9f3khD7Zsl27vB1WVG8S0og0L1+nXOaKaXio0s3T0O10NPDsTxb/S8JpfZaRcK9zq8ekAeChVwF7nedfkdJQIZw8g1A5V61tGh7g4VRROIlJiFQ4XX4jcNTLgVPenGYtKZUzqz+L1gDbMK+FY18FXP398rZa58RXJkdmF/V+2V7A1T/Uf2MrC2Wr5eEU4SXgw9Bo8fuJ6HD5K8xaCOx3QfZPBDnx9A9mHhIRpDpB+x1c4VQKqfM8UyGTYJvy07fqafst2j22+TdI/zHCCX+ql4F+T8yzVlGaDDycmkKSJH+WJMmeAK4GsB2Abxljvs6+/+m0FW6q4VPFSNDEd8VB7u000/BWu1iEA3ofUicRo3Da+WT9c98krNcKJ23hqvhA/GsLqSOrh43+8U0IYrx+XKS7TVHRGq4upMZAdk1yMdoW8lk6RqRXVV14FU5sTCvVzrGQfeHC1cB1dwEHX559L0LLWi29n+c4+DLgmFfWKw8de/tD7d+VPgtUPRVfFm/5+MyWETaE5JDlWvf+NJSRIh8q6uoaCifaVxLGvIzckPzAi4GXigy8NmjHoiRQ3Srlm4Ssq4e+sFhA6NbDac7y+vOgaUTwUkGSJO/h/xtj3g3ghsZLNJPAGwrKIgGkUtY7bgK+nZnptYbDQySA+JA02oa2u/v7UM3L8/MHKJxs5tIhWLg6TS35+RcCD/zMX34ZUjeZyaZPeB3w358EHr5DbM/8n3J/mKxx+823gR98CDjqZdVJTkcoLfg55fvJjr6aGeOHoGVMaA3DGlNfIZyy90Nj6aQ92MMppNMRCgr+PxEErvSj4wuA8/4urDwSXSuc6no4aSu90sNJmIa3hcJpQiicVh6U/gHlNgCIk/eqCqfx4nzD48V1arWBJbvqxyGFUx1LvdCBfOggXWa8bNpfAQD2f176Wkl5HkjSS5QUTmQaXsMDQ3sGa5uGW86tEU6jc3XSyebhRANt2yQ+Rk1g86iylXWAOngAwH0AHgLQRSc9gyHrqtcMvJVmjaXMuNbthHcmnWv5PsXnUepal2l4oMLJSzhlxzn/E8Ca44G3KWnavSF13SicAkgNVziyN6ROEk5PNaMcyK9/wLFs1+/gK1L/Sw2tIXHs2P7YQsTR9QshnFzZAZuEl3Biyhy+WFwH2hhunGdKFNcpFN1cn5f+tz5f0upWNOFU2rB4K5MX5WOJiGeD2rhZC8sLx3KuqhJngQonQlt4mQJZmZPqtj5UQv6QZqK867tu9f9UQ/6m096evv7gb+LrW+wiS5+im1LPArC6qYLMKPDGfscjU3kozxax4xHACdcX/w+NBSqcLIP80KxQ1CBtfNQdSuLqsIdGgQs+Czz3X/zn9JaJFFsRslSuODnmWuD41xbfnZFxntw0nBqyEjmSdUoVD6eN5e/zc7LBQIlwUla2rB2ZEmap+vqMVrcjTE7ohBM3f7Rhye6sM48knEy7vA+RHJoUvomJo8803DuBqCmp14gq6eEkFS1SFs+fq8UW0ocQE46kkQ/Ds4p7PjxuD7nlyEPqeujhFBRSN1rUdSJx8t/YwPEruzj2+cVXxbYOoofIsdYwqxttfVuJ097FzqERThYFkKpwCugvtGdxZE7q0ybPsVkSchIi/E16zYTA9VwOPJy6gjHmhcaYbwK4EcBiAFckSbKPe68tFLyd2ufZ6YTJh+V7lyemGmweTgddpm/jg3w+e6Fwosdz+V72bX1l7opw4uW3HKcUAtMCrrqlSDAif7/sg+g+EOHU2di7kDobtH5xfCFwxrvtnp7tofJYMTqkThJOglDQCCdSq2rH6OUE1ZYZjPyt+MJv1wonT3hoyBhJRRfPwMKd9GdP/Y3KeepkM7MtXgURm3RMy7aVZEFaSF0A+HGGlDC40qJ3xP3SFsLHFxSRNXXQi5BTba6Y388uPZx6lXWyxwhuuY0xP0FRQ9sAlgB4Uy8K1ffgcutLs46TGtWDr6hu32qFhUjkhFMNNlOqVHzburDzSWHH8SJwFUkSTvfeBqw4IPuO7bvL07LP2GCBGp/2SDGxpQGonOQQWSB/v0o4TcQpnLQVy+WKWaHM2AWDUhgfXw3iq3tPPuK+v4deBXwli9cPWd3hDZasOxSSWOp4yAumgYmjlIJWrmnAinUdhHg4EbQBKTcNP+M9wN7Pcp9vjrRZcSB/9ocLYnR4HNiYmfcPz2Z1x9HZTIWHU0hn12oXppYVAtO3fx11FrtPV/8Q+PyVxf+fu7K8Lak/XQqn4fEipE7WDY4rvwXck4U3ctXZARcBt/xleVtZ/1wqh5AsdTbCScsa5COcKr8vUIGh7ZP/yxXAHnXJAD7sCOBPkiRpMrXjzASvV097a3ODbxk+DaTPfquVpqV/7N7mQupCx0ZWwklkqXMtMNgUOnueC/zP57ojI0JC6qTnyvK92P+eiRSNq7mio8ksdVqZX3yrX53sG0NXxphdLtTRmEcmb+HXYqUMGeVjvB56OC238N60wNdkSJ2N4CNoZEYIekHIqR5O2Xle9jPgvSGWI/x5YM+4TfESUs987aUrS10MYVJSOAnSmb/K9z6Usjs3VK9fdUcRAdMUtDYi/+2xhNPWp3A6E8BZ2d8pALZLkuQDPSlVv0MzTG61gevvy/xEFMSYhlcQOMELziDQRJaPAITKxvnvvueHwOb1wJ2Z0Z923fJOhYXU8Y6IBikypG5iU3VbAKWGPGHkT4yHkzZBW7A9cNDzy5s9+Uh5Oz4YTDrlRk+u7nFySmJ0LgsDiIzjbrXKAzq+uptvQyF1DSicKhm9ZIhj4v6/bmOr7ZegrHCSZZIhdURarjoGGJtnP9fBlwNLd48pXPV8XHkmQ+psaA1lRMk0K5yAQmZOHip1icIgsDLJcEM5SXQNeknhNDyemYZ3UPExOOZVxfvt9gMOyRYZ+HO3aA0q16mSUcgVUsfrYoTCqdUCVh+Xvp+3snjOKyGHlRNayhYxMLKRVsdcm16nAWojSZJXN002GWMWGmP+wxjzy+x1G8t2HWPMf2d/02+jUHei4gNv/5ZkbTctXsWm9waqClie2KUVODH2qWTzZy5r7w95QdXfxUaSEfHTGOFkaSuGlMmm9X+PhxPQ0PjVMTZdvAswXySE3OsZwLl/W9gk+IzYXSr6WBzCFkzyNPDKGK3Shtf03olFexi4+j+Bk95Y/nxIIZzy6xbTr3ACJFDhFEuw9WICr4bUZb+b2y+EZjMr1SFLfx1EbHpI6sqcq67Ciany+H3T2r6YZ5qPu5saU45vI5ThDcB1/6MVdY7FvBmE4FInSXIX+7s3SZKG6cAZBFv89PC4/QEoxbF7FE6hn5e26WPCyRtSx66NTPPdUq4bDaBMq8iwINPXAxEhdYqHU2ILqYtQOGnnKnZIX+RgkIdskdqJVttc6iLuF1XHw2mczTUmhXE2kA7Atz8UOLPLbGJa+bwKp14STpPpnwyb0vzUeGp538TjjPe4v5eQ9xpAyetreFZYyKRphSmctPDC0Osa2s7seU5q6m3zCaqLudsB+z4nvEw2wknr9PP7OyYM5dm2q47Uz1N57jzZFV2kTkXWrsB2j41JJ0g8Zffm9fq2NtQinOTkMUB9McB04tUAbkySZBekoXqvtmz3ZJIk+2V/66aueBb0inDiOO2dwMVfBJbslv5P7XOMwmnv84CLv1D8XyKcApUeVmIjO87TPwjscHihIDz9ncD1vxfHyMo8LkIPJ5WF01hEK5w8hJMtS91wjxROoRPW8/4e2OdZbD9PGVyLmrE49R3Fe6o3+RxEqtBrkgPdYsluReIkAtXdksKphgKJb+sj+up4GQG9IeTUhaTIkDqOpGmFUwDhVFH+1yAKW20xnlEW2kKuwW5npK8LV1fP0W9YugfwtLcpXyjWKyHYQkLqZiZNNt0ISUkqwSc5tk7OSjgFejgFh9RN1UMaqnBiDdzoPPt3VO5cFWSK0LvH2SAr8SmcAggnq2m459rJ3/r4793bSbKFm1IT+ZQbZjp8uUbnIMqAT5IrY8zfQqaxB9JrcdnXgO0P8R875tyAO8QxZP9QaPcu6eg+PfRe+nrQ/YnxZwpBbg5uMYMcHg8b7PpC6p7xd+XjlvZtWOFkTGrqraXb7QavuB0450PiXBF1gq+CXvxFYNEuxXcUTjo0xkLqRNtqm3T6fl9MSF1pVTeScKJj8vbPp3CyDmhiBjYWhVM3k60BeomnA/hY9v5jAM6exrKEw0dyNEFCDY+l2VwJpDz2TXhL5TDAigP1soUSuj5Fx6ojgef/u7tcmtIEKMj1mOQWEi6FDUHzXFH3V/6XPpZAM/1IqPretp9XadNgSJ1Uo/PjhSqcgDTM+6J/q18OL8T58pC6Lj2cyGwZ8F93l2o4ZL8mQfdqzYnNnJvXIbkPqaznKUkDrMezfF4J51ee61BbBSAbPylEaMiiGsexrwJec2/ZMmCqxBOxeNH3gB20zIV037olnGYmdTMzSz3dyBv7GHmhopiQcIVrnf0hy3d0/BaCK3GMuXQ3CF0NkioSjraUd4JNYFup2kGC7o/MypQrnByDAa+HU0RIHQDsmvlOjWRxxye/KdvOonDiZd74RLYvGWY6CKeROXpcvw1OhRNlautV/YhsPJsKqeMrI3ScyU7h4VQKkSU1nfD1oHsQla0oAEQ4lTw7DPDY79K3PKTO9ft9hBOtQvpIDhfqrq70tJMUZeJ1prOx/B2/jjsdDVzMooTySdiYPaTOSjhFqhV4JiyJkBDsyQ5wxU3AES9RytLO6kBWbq/Cif2+095Zb0LWTymJBwjBsiRJfg8A2ast692YMeZWY8z3jTHTT0r5/M2ozl74r82dM1c4RWZIrTw/gQqnY65NU5X7PGtCQO1VZzNwBlMob2Z+dXURonAqKSYs1yP/V4bUZf1Y0yF1MVnqSvtZFgolmgypKylMyMOJFr0DQhoJ695fhFv3AnJMqSmccjuMiOMefDmwKiN/vaGMNM/qA8IpX7QMJMnU72weTuICHvT8NDP4uBoVLQ9aPV7pa4eHU51QSPmMaWOLkDlLaygdY3BRwpSJJxpCXUJ0awup6xWMMacaY/7XGPMrY0xF0m2MucQY8yDzELh8OspZQlBKUoHcf8VFOFkeZtPyd3CmXS3Pjp7QD1+63G4R2qnzzoE6J8q4oU28aNBnjD4go0HK5g3Asr2Bl/5X+v+EjXASHk5JkhILQ9pAzHaPLFLJ/S8AXv9wER9MA5Egwunx9JXK0dlkH7jMXc7KEks4tctEB63m9kq2aQu9ydGDkLqLbgD2v7D8WWs4nUiQhxMPkyOSr0Q4JUzh1PCz07EonB67J33d7XRmGu64v/QbNHJy3QfcREJo5123XnjVgfUOm+7r2HnxbmJbIeuft12amRNgCqfxLNxSCamzDSDlIHev88T3FmWl7164FE4rDtDbedMqk46bMsLpvI+m9aCyffb7jr0u9ZeoE1I3b2U5u2k+rh0onKYLxpivG2N+qvw9PeIwOyRJchCA5wL4S2PMGsu5rsyIqVsffPDBRsqvwklgsM9mLWrunJ0aIXW8LPJ/n9fMykPSVOVWRUfEM0V9VWcTsPczi88pkUBjhJNjbMRtEGz7a//TAuRI04RT4GKodb9A0/BL/z19lWr7umgJwimYrJgClPrIEV1ZVyekDmDPn4+8sZAcXvQipC5AZAB4roXFw6kbwiHKNFx4OJnKG/9xbM9YbBZFHgZLc6J+DamzwTZP9O7naSdnCKa11MaYNoC/BnAagD0APMcYs4ey6aeZh8D/mdJCaugV4WR9MGFXLPB9ZXku/mJKdtjK0mvCSZNO+kAdy3b7Z/tqHk4s05s2AKRrtWl9avpJA8+OJaSuNHhLCoWI6tNjWxVwMNdcISGz1Mlr8+VXFu9zwokGjJthxeylRdmCstSJlcmla4usazKkLnZV14fY1acmFE6rj6028u3hlFxLMhULD38g4ofXP24a3vQ1yRVObGDNy7tsj6JMUpZ70hvT1UteLiJOOA64sNinG4UTx+nvBhaK+eeLfqBv28tO0kVaUqY/gma+Tr+dK5wmJ9NnQarfbPdeXr9z/xZ4HZt4y7bK1Y+EeP7R/qoSMyOc6LqQGfrsxakXmw1SdRXVx7WAHY9gHwxC6qYbSZKclCTJXsrfvwG43xizLQBkrw9YjvG77PXXAL4JYH/Ldh9JkuSgJEkOWrKkYQNWDh/hlG/X4GSEiI8Y03AA1pVpLZsWb1eMGC90A2p3qJ8j5AqnWdV9QhFCOAFskdCz2CTvmRZS9+hv48qoobbXD6lWPCQCfU/1U+XQ4wAAIABJREFUZdIxdtNgI+mlwqlU/mn2dZE2DVTvJieAq76TjlPy8kaWla5fqGl43VDJJsGjWrY/zL+dhpJpuCOkrg5CTMOHxsS1qeHpGJIBNzYq4/AXZfv1GfGydl3VPL+EOlYFqF7DGUo4TXcA5CEAfpUNZGCM+RRSX4GfTWupfFAzRHgQEg4za7H+eWdzNf5eohInC/vDmHeafaJwAlI56IePAR6+M/1fC0HUCCetA6LB4aYN6TWl30tkgZzAbbtv+jq2IG3UuXFw5di2yZMnBEWahYb4W218LFPeEOG00b5tqxWZpU4MFNvDwFnvA37yL+WQuqtuSSepjaLLzr2pxrY1lCmcMhULD7mj+rfNjsVnSQeY2JwRnQ03nTYPp4tuKO7Hop2B390GPJ6F2Q2NARNPArucAizbs/gMqIaTEvJBgPJdnQnaIVek9fTGNxWf2bLz+erlMa8CHv5N2mk3ifVCbaFmSck+KymcOinpJMl82yRQ1stWC2ixCaqsM/nzqtyMEtFuOR/tbzOATyaLMvFnWi2/IIfqEE426fxA4dSvuAHAxQDenr1WDF6yzHUbkiTZaIxZDOBIAJZUvFMEaWorEdMPAsDw7HBT/a4VTo6QuuEx1scHegWFoNUGDn8xsMfZ5WvXiMIpcDJKbU7Fw8kzkcoz9TIF9h9+GVVEHTUWQwG2UBgYUkf9scsOIQa5wkkJx+am9NMCrlgx5Wdl+d7p308/l31fV+EUEOkB1LivvVA4sbpy4eeq4xC5nf5l8bYxwsmncJKEU0TYZuk4HrWZDMEMPR7ft98UTud/3P39QOE0rVgBgC9X3JN9JvEMY8yPjTGfMcZsPzVFc8DlvSFB0r+QBpCHRXFseNidoQxAJa27C7Rd9GpdJGInLabFJkbKShIRaHlHZvTJU65weiJVjNCxyHRbDuK2WZUSXnusywinGsbQ3obEonByEk6Pp/f1pD9Lw3P2PBcVtcCZ7wUu/0b5s9jVAvlZnqWulaZOttXLuohuLBvycJJoD2dkbmYMrSlFdj8TuOBzWd3MTMObNgwH7CF1q48Fds5MJw+4KH3NyaXsOSgNELLPNIUTwOqp4/6Hggjy5fuEbe/rZLfZEbj0y8D4Avd2MVhxUNW4X/OwkwqnodHCNFz6GNgmnd7MRXI/Rz9SMtoV31OfsiDrCrX6SPWVwJ9prZ7bViGj0iDL3z9QOPU53g7gZGPMLwGcnP0PY8xBxhhSkq8FcKsx5kcAbgLw9iRJpndB0KtwihifAcCf/Bh4yW1h2zYWUqf0/7ztp0dnuKG+5mlvBbY/uNzmNaJwCgyLCQ2pk+O5U/883ZeTYk2QN3W9VPL7F2ga3vSibsXDSSicppPcl+Sj9qx0HVLnef66Va41CSpDezi1rNhmlXu7qGM3QZB5ojWArP3p0sPJRjJLRZz3ePwe1SSM+wax9882PptZmG6Fk3bV5FPwBQCfzFbYrkKaTeWEyoGMuRLAlQCwww47NF1OvYi+Ruq6O1n4BhENyna0Gm17eCaeClQ4BTaavQqVqoAahRjCiU2MAJ35zkkbS6dGE63NG9KGPlc4ZZN62yoJ3Qc+6eQ47rVV42ntGC5ID6e5y9OJ46zFqbqIgwinucuA8/5OP96iXYCVFApWU+GUf5aVia5frxrz2M69ElLXUGNb8nCarXt2GZMSPq3hwjS8acNwQA+pk9jp6DREVj6//H7TZz6CWmuIYu73sz5ehL3ufBJw9t8A//pC9z7TMTjYdl/g3ltFOZSQOq5wag2n2yQspC6EcPJ61YlJSq6UVfZzreTudiqwz/nAzien/2sLB9I0vMOIfLXdF2qkugqnkTnAYVenKcR/fVP5mAP0FZIkeQjAicrntwK4PHv/XQB7T3HR3CgRTo6+ILS9mb04XMXbrXLCFVI3Oq8gx+nzkYaN+JsOqeNwhtSJhTaCbBvkeO+QK9K/B24vPtug2ETEwmZpELyfL6SOFE4NjxVyhZPSd0x3qvQS+QjLwka7um0IQkPq8nWSmkRikwitY6Ehda02QMO6bspL+9YKqVPKZYOPXOwmpG66FU7HvKpIwBOFmotwlWs4M8dU061wugcAVyytBPA7vkGSJA8lSUI6478FIPLM5ttNjX8AEB5SN74NMJplJ5PEE8ef/AR40fftx0mS4pwrLWnpZSalVzpkx/SQ9otpeL59C5UMadr1ylfLfAqn9akUuxJSZ+u0jF3hNGsxcNx1jobWEyKXkwRCSt9qAxd+PlWySGx83N8Qq+E4IY231oko4Te9wFQqnC75kp7h8aIb0nvBPZxcz0OrXdSNXjw3pBLiBte+e5tnazTVz3xQCceI+73HukJhYwyw33P9+8QoQ7sFnWvuttXvtHCWXAX5VNq+mJbIUscQGlInUclS5/JwckxUWsPAbqcxnxCLwimxKJy08udVSBJOkQonY4BT3wZstx876MwcHA3Qp/ARTq5Q1bpYfVy9/Xz+JbzNPedD1e2shFPN38bLMyvLaNWUotTV/tkyI0tvUtvYjH9+9MviyybRbZY6X2hXy9E2B8FGBkgPJ0vI5rRAqN20cWhdhdOe56avc3xzu8hFbrlfk6AyeEmywJC6ErnYDeHk6Zcl4aTuG3C9pIH7US9Px+JayHMdGxD52VTihOuBQ6+cuvNNN5ncEKZb4fRDALsYY3YCcC+AZyPNhJLDGLMtpe4FsA7A7ZhuqIZ9Hmhp1gnzV3rO1ykIp+32A57/78DPvwj8y0XFNlLhNMeW4RjFdnxyukcPsh3HriKRwsi3b4utlqmEUydt1DatLyucJiweTqXzJ4XCqTTp442zQZUE8RFOUukmFARamTY+Xq+zCmqEHYRTR6jMmka3x4157lYdpX++dA9UstTlsn3LtZmczBROPSCcDn9xqhTyKRk5tCww3RBOvVYgkQk+kfBTAS0cVBv0Up3a/GS6Kt1qp/c76VTrm6398IbUxWSpczz38ji20IVksqjKHU9IXV6mLkhBuc++zwb+65+Ag6+IP9YAA9jgU5fUGZ/58JxPAU89Wv182d7A/T8JP47s9/lEYv5KYGQusOnx4vNRG+HUAIm77v3Abmek3jqNwKVwsoTUVQgnz4IdABz9iviiSdRWOEkvTgvy8X7DCqdKSJ0SZjRd0EKeAGC/57GPa5qGH/ca4MiXho8d+iKkLlAN5zq3LWS1ifLaFE6cgO7GNLwlnrGT3pC+3vaP2aFa1W1dUBVOWwYR48V0EWsNY1oJpyRJJowxLwbwVQBtAH+fJMn/GGPeBODWJEluAPBSY8w6ABMAHgZwybQVmJAPaGr4W9TJOjLZARbulL5ftmd6rEU7l7eRYR9BZWETj2d9LL5cXtRQOBFc14s+Syb1idl3P5A1pknNkDpF4TS+kG2nxcqHKpyovI6VTsKmJ/yS+rrEgVpOCquhkLo+IZxOeWvaaT9yJ/DbHzTT+JI6rrM5JRb4RFy7fqadmYZv7I33WauVZqJ7/H5+Uvc+uUE4M5P3kmEuD6deE05ZtrixBj2arMiez1kLq19p6XqprucKpzYzDR/S95fwKpxsWeqU++zqJ2R5rB5Ok0U7lasWLWHIFdPwGgM5eV3mLgdecqu+7QAD1IW3f6NsrQ22Z8Pjurn2ZV8D3qaoKG2QXo9yEtUSE/IRZpbdNMa3AfZ7TnPHc7V/45maSo4pJn2h3xmayNbH0bXCyTMGyEPqms7w61A4GYNpJZ1K5Ej2/k8f0sf1sWO4VituoapuqGSTMIFzvth5G9BleT3n2/3MNLP3hoeysYVyX4NO4wmfLI2/Ik3DQ5Iu9SNqJ1LZMoi1ab9bSZJ8OUmSXZMkWZMkyVuzz16fkU1IkuQ1SZLsmSTJvkmSHJ8kyc+nt8SoSTg5Quq85+sAuz4NuOIm4ICLs3OLWyeNbV2Y6pC6GIVTZV/Nwynr7Dub9Y7/qT8CN701fa8qnBwhMSXCaTQNvQKEYswR0xyrcHKZ301srP7+ip9RTeLA5eEUeoy6iO0k5m0LnPuRYsDfCOGUqeMmJwqFE03cNS+nVqu3puEE7iXie57P+yiw3wWpWovgfaYdCpZeK5xIITA2r7fn4VB/pxJSR59tfjIjnEzh4SQnSbZno7bCKZJwkt+pHk5ZW0bn4BOUkH6iDuHUbxljBtgyETI5AaZmMuLy3NMgxwkVwmmovF3THk69hKvNIOLfp3CyoYlsfSXUDL3KCac+MQ03chI+nabhisKpPVS+xlq973lZQrbvRUidxTQ7CsLDKf+4ifLaTMMNsG9GRA+N6gqnKA+ngAW6uiF1Mw3y+Q3eb4b+XoFpJ5xmJJoOqfOBVoFWHGAnNkw7vJGlY/SacMrPF1oupWPSBhpU7s1P+q/nyOzi93YiQ+qGxorJ8erj2YaOTt1HOLXFgDJX1Shlmtwc0FnV9XCyEU6RJGEd1B5sNLyq0coUTrmHU0YkaZmBTBt48uFUJdf0amupTBHXfcmuwNl/XVbsBYfUOUIq6+K6u9JECTY8lSmcRvuFcOJm6xlps+mJ9P622kWWOtnO266TbzAt2zJXP+KaYElfKquH02TRd/jCZOXKG20XsxI3YzPGDDCjEEw49WF9lG0EV6caw37bTCScHP1HTjhJD6dAhVPTIWouZXnIfqFZ6kIJrYu/WP7f1ux6FU7TiQAljCRUe1aUflA4BYbUOY/RQw8nV99eSpyk3asYDydZVkWBGjRnUQi3maZwovYgxjoD6INnuxnMsLvVJ3B5b9jQlcJJYUMrCqcWghoBgIV39SA0iCN2NUNrXLWGiAZhmzf4J/+UgcW0WEidTeFkqgqn7fYHrvxm2TeA7seRfwJc9h+0c3EeDVJVkftoZZNFW4NbJ/67rsIJmJqGPKbtLJETDZpO5wqnzVWFkxY6seEPwE8/C/zq6z1YbRU49rr6+3qfaVdIXZed2viCInRCw45HpK/b7tvdeaKgEbJKljoeptseRRFS16k+g9Znx5HoAKjem9XHpeTR0S9XtnXUsdXHiW21bECtzMsua6smWZY6FRZz4xj04wR/gC0PoYR/X05GRPu76YnydxWFU0MZ5KYEjjaDLAkoeQEhNKQuX6BT+uY6qO3hFBhSF5v5b6ej485PqJR/OkPqFIWTRK566XE5+yGkjvrcrkhji4dTr+8zJ5y0UMkQ+GxkujINnyKlXNPIFU6B7V6xY/nfGZr5d7pNw2cmDr4cuO8nwBEvCd+HHjpfdgvC8z4D3P4F4LaPhRFOUQqnPg2p0xpXjXChQdimDeWO/1kfB/7lQrFt1tibdkEkuRROSICJLF0wERCU/l3i0BcA87YrF93n4cS9VPg5rEbEPsKpQYUTfZ5M9nbyGFpPT3w9cMAlxf9NZjkzJlM4TWQeTuz3+ga1vVQ4AcDiXbM3NQYV3Siceo0DLwF2P8Od0KApUH/sCh0sKZzYdSOFUx5SJ03DPSF1tvoh2/5ZC4FXWCLEXc+wnOy0WsChV5UTP1D5JeFk9Z+SHk4t8XkABgqnAaYCoX1TP9ZH+VztdEz5O+nhZOuL+nHC4eqXyYtq81Plz0MnXiNz0vt+6tvqlU2CJtS1PZw8Y4Be+DwC1To9lSREDHyLMr0iCvpJ+UKq4rH59Y/B+99Sds4mPJwcbchjWbL42UtRrlc1PJxstiCah6YLmkF+P9znGOTzwEjCaab9TgsGhFMdjC+IN9mOVRXtcnKq7rjtY3rlVD2cIkPXepFtq3yi7KWOh5OjY6fBy6Ynyo3ZHuuq2+ap41sBIXWZwokGRVpoFUfJ/NgT20znzO+lCKmz+sLIsoZ4OAXUA19YUD+E1B35MtHJNJjuemRuSgBsfrIgFUido9UjDte1ufBfgSce6K5s3fy+0PZlOjowY6aGbCqdU/lM83Di1609kn43OamTr7b745PQN6WM09rE095RLQuFBAIBqtwGQuq2kEHRAH2O0DClfqyPLu9GzcPJNwbpJ7j6LVINb95Q/jy0fRkaAd7wcL1yaXjs3vRVKq685cjuR0x0QGsY2Pf8uPMgAfY8B/ifz4tjSbUtrz+Rp2gc7F56jaJ7HVJX05urSdC9cqm+o47HyvhgF1bGOd/kePb+8Kv0dcluXSicPHMJXndDwg5VhdO0V/o4bOUeTgPCaargC7fQQCvi2iqQbCCHZ4VXym4y5sWgG9PwloUdBwrV0qb1/t88ybxL8lSyDhO7ZLIYFPmULjz0Ki+Hj3ASoS1aSN3p7wa+/Ep3WSvn5efqQuEUYwpYF77OvTWkmzWH7h+CVitTOD1WeDjN2xZ4+c+BOcv85bNhzfH274LRxbXvJ0PdaYXLHF3x1+BtYSlLXSd8tZrIZFu7GhtmYUNIH2LaAJKUNAMCQuoIXagIu/GqGGCAbvGCbwOP3FWonPuxjdMUGO2RdDFM83CyJajoxwmIq0w0lpoQCqfYlf6mEeulQm14DOH0+j/EnYPwjL8Hzv3b8mfOxY9+qhOeRZmtwTQ8z1TYDWls8XBqxIjcQTid8W7gxjcB26wq+8w1oXDSPJzqhtT1VZ0PwFaucNoyfsVMwLwV6etBl4bvU1HFMHCV0jHXptnrYkPqeu3hJM/n3U5pUFTCieTZbLXMNplbsKP92Nr5k8liUKR5+ZS2j+jsicSgay5XMPnv5OftmYeTb0AwjQqnq74DnPau6udNhNQtWQusOCh9Lz2cgJR08q2g93xi3U1q+tCyzbCOujY0c3QtpI4rnIaRZyXkdcMHGmBuu5/+fWxGJOt5IlYDaULlI5wqpuF16l4fhjANsPVg233L6tR+rI/ahPvQF6SvrSEW7mtRB6w9q7fl6xVyhZMgnOYun/qycMSGJtLvCLXG6AatVnXxwhVS108kpE/h1LOy1jxuLxVOsaQmR0ld1FAZQ679rk8DXngLKtnPc8I84Dwu0QCgCwxc2CJMw+vWiT56trvAYElyqrDyQOB1D8bFdrcCFE4js4ATXkcfhh2XHtZeK5xyRVENCTyXTI4vLBvrUigbEU/P+TSwdPfq8RbsCCxaYz92tQCZwinzcLIRTud8BLj3VrGrZ9Xg1LenA+I1J2SbZddGUzjxFZE6hFO3Hk6hx6gLXyexdG36V3d/F67+fvG+NZR5OCmZyFzotWl4Pgiu0cnUNdTd/cz4c/Ubnvt/i+edkGdeZM+lnNQBZe+rITINn9Sz1NkwayFwyZeBbfepU/pwBCmciHDKFJ7SO666g75/DAam4QP0E6aqPi5Zm3rThUALBTnpTcDxr0vbHd+EfN7K+uWcTthC6lYfC1z6FeCjp019mYB4pcFIDYVTHdDYVkK2y6XtTB+RTrYFzR57ONVFL8pz2IuAn38R2P7QLg5i8XBqwsItmGzVoihCVdYI83CqbRreL/U9ELlVwdapcBoQTlOJWCPBnA11mIbzRiO0UvqY56bgSvutwUYKXfeb8nbL9gTO+Atgbbaaudup+vFKIW+hCqckUzgZ+6Bi3/OVmHyhEJAYnQMcckXxPxkK0kS3rsLJpeBw7mYbEEzBykHdYzdpGg4whZOSicyFflw5JwSH1In7f9xrmi/LVGPXU6qfkS8K9+ogUk6m5SWFI3k45VnqIu73qiPrld2H8z8BfPp56fsQUlGm36WJVazPX8zItp+fiwG2PkzVIJ0vYnih9K+tFtCSSuceTqSuuqU7I+M6GLaE1AFF9tKpxPGvA256S/zEj3xPe0k4nf0hYIfD9e9kvz3Vnoih8Cqcev1sxjIyPXjeVh0JvPHR7o5RMg3n/Ws3jFNASF1pc36vIsQKo3PT1yAPp4CxQ2mbma5wiiWcZP3sw6QRARgQTv2MXOEUkKXO9pmGPKRuipQa0ZMczz7GAAdf5j8emYTTPsU/9vOTwinGE4sfP3TVgOKiyduAN6Ylwsnn4dQjhVMvV4eX7Nbd/k11MuQVlXTiwp2myqumlyF18hr2OmPltMGkzwMnnLSQOiCdREw8VWSpm+yk7cFUehP9yU+A9Yrnx1qmQIsx2Myz1AnC6ekf1KXy3ZC6A4XTAP2EfiRAfQs6rjEfRzdZ6pbvVX/furApdqYL26xKX2PNe/Ns0z0cO+/3nHr79ZPaw7qgOUWm4bGYCcTFkt2A+3+avo+ttxyx9UQbJ4TU/9lL0tcgD6eA678leThF3z/xO222DX2OGfCUbcUICakLyQxhPX6PCaf8PKEKJxubXxMdPskMiHU3LQBJRjjFGv1Frhp0iHAiTyf2e5fuWbyv5eEU2XiXPo80eq+DNScAL4pZFSY0rHAy7VQ9GOPTA/S3OTIv2zY72bfb0gmnEnEinnctSx1QrFqTaTiStG5M5WB0wQ7AigPc24QM9iT5Iz2c9n8esN9z+Q7Za+RE9gU3F++b8qgaYIAm0I+TSJ9pchO+L/2IVUcDR70MOPO9012SFHXNe/PoAEsbfO2vgevurF2sIOx+JvCsf1S+6KfJ9zSbhsdei35sKwCUfsdZfwUckvm9dUM4E2qF1NH8IIRwWpS+yrYsH5t1k6VuCpIb9QK51UEXIXXnfyI+WqpP0K9P2QBAmGl46bPAh4/Y1V4bH3pTcQuEKpxCccwrleM54txpm80b/BnqKvtGNnwLV6evlDKVN7hzWZa0GMJJGpKH7lf+IvwY3cDl0WRD0yF1rXbaGYZ4OJ31PrZfHxNOnIzY61y7pLtCtmxhhBPBGGDiyfJn+aTBRjgNF9ens7n/lBIxHk6EUNNw2/429NqvaoAB6qIfJyOhCqctjXBqtYGT3jj9JuGEXGkQSzh5FE6zFxVjul7h2Z8A9nh69XNjgKe6DOFqCtYxNr322dSzH9sKoFyu0TnMPqSJkLoaZcgVTgGEx6zF6euTj+jf8/FXUFSGZl7ep/fNhrrtu/bbZyD6eOY0gFvhRCEQ/LPAiREdr9chELlsMNTMvEHCSU60Q1ZW6JpuWl9D4ZQhdNXgiGuAlYcUsfqV7CNZWnafmoE3Pi+4GbjzZvu2pf2mMaSuNrrIoKWBCKckwMNp/4uAL1yTvu85UduFaXjpd7D9j3p5eTt5Dbc0hRNXw53yFuC//gl48OfpZ16F02gxGOps6v5ZuOjfCj+DJhCkcBK/LfF5OHURUnflt4A7bgzffoABmsDKg/XP560EHrtnassSCl8oiG9CwhejBqgPatNjlSJj89JX2yR6WmH6iKj0KZx6ff7I+zodBNh+zwN+/S33NpWFoJr1Vj1mF6bhIWMQ8onbLBb8oCicXGOsnU8CfvV1vUz9Rlz60Ihp+IBwGqAXoIdaVTgplW54VthxyYS81yv3XXk4NVy2GMLpd/8FjC+IPUH2GtiIt4eAnY4u/peER2sI6AQYFvN6sHR3PVufut80Zqmri8YVTkOFz5fv95ZWY3rdbHZBrBlTkJV0nUKMK7c4wolggCNeAux/AfCOVelHtvuX+3OMFO1PZ1P393v1cd3tLxFtsMngVTiJuhcysN1uv/RvgAGmCq970F7HL/868MD/TG15YmE1VVZU7dffDyABHr0HeOD2nhdtq0DdkLqVh6SvGx9vtjxNYXyb6SPDghIY9ZgoqLsYOR3ExdkfjN8nb/MaUDiFklb8mtI+IQonGlPanjGZtMWG8z8BbHhIlKmfF8YdqGsavoVgQDj1M7RMdPI73vAMB4aBeVe7G8J0h9RxhGTHoO8e/S0wd9u448eahkvIBrfVBjqo5+EUAt/Ecyoa8ou/WE/50aSHE/l8BUl622FqqG7RbXw+kZUxYbdbbEidQjTb7h8NkMg0HMgIpxk2qAH8hHLd/QcYoB/g8rCYt23614+g1X7bWE1TOJHaevEuhUpzBodVqHj6X4cvmDaBXCkSOfHb/Yw0vH6Ps5svU7cwBnjhd4E7b5l+Pz1fFuQZrNKYVjSqcKqxPSVfCVE42QgnzcPJNd4YHgPmr9DLNNPGKXVNw0M8iGcABoRTP8Mpv1MIjmDCiYigKQqpC5X59vKhyieegcfttWl4ZXclpA6YBsJpqkwdUVZ4BaEXCqfMvD3kWTCtqSGcihPW243ISlddl793ugeovYI2MMkJJHF9Ruakr+2RYvvOFJuGN4VowqmBLHUDDDCAG0/cn77a0tnnyhvbmKnLha1+xf4XTO35ZBbP4P0McOAljRenGRhg3nbAPs+c7oLAH1LX68XuGRBSVweNKJzoEDWOQREBQYRTNoeytWWlLHU1Td5n2mJgbdPwgCzrMwAz5CnbSkETW+fDzRqN0IcvmaKQut1PT18XOrJlcaiTwoYQwohzKXJsY3zIFenr4l3j9iNUQup8hFOXK0U+4/R+bMgbD6lrFZ1hCImU35M+vDYcJkDNNzSaegttqUhEaFhInaHU3UOjLKRuY3+bxNsQag5e+XxAOA0wQM/wxAPp6xyLF5PPw6kfV7dPfzewwxHTXYo4tGpO/PoZ/VQ3fOPLnvUvDY+H+w2mpkKmfJD6u3ZovBxAOJFqviKYUBRO0ZipCqe6puEDhdMAvcbILODE1wO7nVH9jia9sxbGH5c62V5X3J1PAl77u2Ii50PJib/hhiSko9v4RPH+qT/GHX/v89K/upAkBp3fRm4MjVWzb8WgHxRO0Wh4MhydltWTErkxdBtS51DzbZORv/s+u3lvob6EQsza1I60Irc1h9R1Y1g/wAADVLHiwML7Z9526esSS5ZW71ipD5/LQ64oFtxmCuqG1PU1+qlu+Ainfior+nS8q4DGdt0oHKkNWrB9/L65winGw8lGnjdwzWeah1PtdmfLUDgNCKd+x9Gv0D8fmZ3Gkq8+Pv6YPKTu+V+N9yuKQSjZBAgWdxoIp03ri/ebn2r2/D7YCA9bmtuhkZRwqpuVZLpMHZtAkyF1+fsII+ap8nDq2gBT2X/uMuANjEwdmQts6lMD1CagPfe260phtDykDph5gxog3jRchgTX9RoYYIAByrjiG8X7Y14FrDkB2N6SYe+UtwCzFgFrz9K/77eJ+kyFyx91gO5hradTNb7cQkPqTANPsy0dAAAgAElEQVQhdXuek3qnrjkxbr8jr4kMqfOYhneDZIpEE02jbrKCkhhjhv1mhgHhNJNRN5acm3nvcFhjxekapYeq6UkedXSOh5UTThMbGz6/B9YJouVzkquS6XU0BiF1wVkyKvv1uYeTL6SOPwMv/a8+TfHcELSQOttkYyjzwJOEU788C2RaH7RtpMJpxYHpKy1gDAinAQZoHkMjwI6O8LNZC4FT3uw4wMydbPQV6k78+hIGQNJfE9HYkO5pR7+WSyDvl7s0Dd/l5Lh9KNPxTz6TvjZBOHVzyafKFqZp1Cac+PM0Q+qqggHhtDUiNnvcVGHaFU4spG5iihVONmLJNsFcexZw698B4wtqnq8PstRFowem4YSQ35sI9UfP0KXCKSQjI2HOkvRvi4OoK/xajmXPjAybpaQLkxPlBAz9Mqh5+c/CyUFbfbbViZUHAq+5p8ga2YhXxAADDNAopNfaAPWw3QHAjkcBp75tukvSPSiZSV9NRC1liQnJ6sX5rZv32VzIhiYUTt1g7vL0dfne/m3JokDOYZpQFU5OUab1prHiQGD5Pp5FBQ1GfTvTMCCctjRsf5jf14ke1n6ZSBGaUBXsfLJuyBmSjrVEOE21wsnyKE5aJnwnvQE49lX2bDc+eAmnPmzIuw01kyjVt4CmMF9V6fNmM8Q0fKuBUp/pmdnwUHnTVUcDt30MePKPRcY6oH/I17nLiwGfD3U8nIhsAoo6PiCcBhigjzCDZxv9hOEx4NIvTXcpmoExKf/QT+ohW1k2bUhfY6w2amELDanLFU7TdP5VRwGX/Qew4iD/tkQq+jJu1sFUZVpvGiOzgatujt9vptRPD/p85jRANC77qn+bLVnhdMFn3Md2HXfb/YB7/1/6fq9z6p2/LmwEm03h1BoG5s6vfz7fhLTfyEgAzSucIkPq6LkJkRN3g25XgHKFUx8NQKcaMvyS15nZGeG0XhBOez0jzUq3dh1w+xeKz/vyWfCgVYNwKu1PhNNASTHAAP2HrbhtH6AMl2fjlIL3FZaybM5sK4Zn9bw0UZgpY6X8Xk9jv7z9IWHbkcKpQjhtxQqnuijVzxlSVxUMCKetEbnhWp9NpHqa+jFAufP/2bvvuDmqen/gn+/TQwIhQKSH0AWVZkQFCxepFrAh5XpFRbneq9erYgHxp1wQRBBROqGj0otECAkJvQWSUAIhhIRASIWE9PqUPb8/Zs7u2dkzszOzszszu5/36/W8dnd2dvY8s1POfOd7zjnqD8Co7zqjOHRvlvD3V+Gb4eTX/rnG9ZPLUepcdek0PMShUI8KWPe7c1qNnYZn+TdslGLGnrEuh+/hPO52aPm8bW3A/t90n0ccwTBr4o5Sp7WlnLpPRJXycmFMjZPF83y1DKd6BZx2OgiYegPwgQ9F+1wW16FNnvpW1H04bbKl/X0R4NTHgPffjL7svPbhFFddr40bJ4c1aapZcWfN2EG2eKFch4NImIvwjm5gmw8n/91h+JXLL8Op1hNktdGqsnggT7rTcHM7i7JMs+lRFjHgZLCcnIdsA/xqbnBQuWzbyOC+UE1SAaem6FSXqEkU98uYo9NSEwoxIE6j+ZWlr85N6vb5BrDTwcDQ7aN9Li91pWLfijm4EdTWDhxzGTDy4PLpZtm329/5i0q1WIYTmOFEeZX1JnX1KFfWL8L9TtC+GU61BpyqjFKXyfVUx07Do2Sx1Dv7bctdncftD4j3+WKwML8nprqStuqd7ZvB+KwF5sOwBskk/EUJ+3Aiyp4etxn9xtXploOyI5N1Nb8MJ7dJXVcdm9RFDTYB2QrWBcnbefmA/wh4M4E+nLJ4Y7weykZwz8m2apHFIxXVW1bbv9Y14OT5jqwrDt3ud2KptUldtYBTBg/kSWc4lQUVIvy/9c5wGvEJ4IeTgY99L97n2Wk4ApuChTlhN2OGU5TtgaPUEWXPoGHO4/oVwfNR67A1G0+bX1kO/Q3QPRTYao/GlqdZNEVTd/bhFFmT9OHUIr8WlTniHGC3w5y/LKlnh9W24dGzSN/B/NYY59Hvgq9eB1rJcJM6rR5N6iJlODWgSd3wPeJvq+w0vMS2DsJsP3Gz37LCtv9G2W/ydieVqBX0uJmZvcxwIi3ECMyN1unTZG6PI4Ez3mlgP5hNJk9N6vwccS6w+U61BR2LN58zfJ2SJPbhRLm1xS7AN+9OuxSVindq6hFMyeBdIK9v3QdsuZvzXK+DenUaru1zgme5LdqkLsqJK/N9ODHgFFghC7NeygJOOazU1JrhxIATUfb01DAyLTWnrNxM3Xwn57FzE+Br16ZblmZVzMrPccBpl88CP5lW2zLYh1MuMeBE2ZF2p+Fp2+WQ0vPiaBR1DDiduRho77IvN4vrSZ9jEws4tdufV5P1gFNbDrb1hqkxSwzI5120uJldmt6GGHAiyg59XNpmn3TLQdmRdqBJ23Yf4EdTgC12zWe/h3nApu6OVu7DKccYcKLsqOedmiwHUmz0icWb4fTVa4FnL03mOzoH2b7YecjigbzQ5zwmVZmJm8XSlfGAUzFA0hwnqVTEDUZmhS1IFivDKcd3Uoma0Y9fAjbZIu1SUFYUj+sZON9vtXvaJWhubU3QpC4JzdqHk18GK5vUESWslUep89p6b2DT7YDDflc+fZ/jnL96yfJ6Wj7XedSp27Uy/8eOnvCfa8/JYbO9M+0S5JfkPeDEJnVETWmLndMuAWVJFjsNz6tNt0u7BMGkGToNT0BWR1qvxS/mBNTZm6NJXRP9WpR/dcyuyXIgxaZrMHDajPJmdo2Q6VHq3LsaSQWczO3Mmu2VU3o9tXenW45U1Vghi9u/V1bU2mk4U/ebnogcJyLTRaQgIqMC5jtKRGaKyGwROb2RZSSiajLYaXgefedB4NTH0i5FMGY4OZqxD6fBWwI9m9nfY4YTUcLqGhTiSTmULI9S972HgcXTksswMoMKnZsks8ws0EGCjq7g+VpB7JH+mrHT8Ajroo0BpxbwKoCvArjabwYRaQdwOYDDAcwHMFlExiilXmtMEYkoUFY6Dc+7nQ5KuwTV6RtBgzZPtxxpa7U+nMrkdz9vovAg5R6b1KUvyxlO2+4D7P/N5JYnTZrhVHBPxq2c4VTrHcCyPpxyeF9GLOVnkzoyKKVmKKVmVpntQACzlVJzlFK9AG4DcGz9S0dEobBO2zra2oAvXOTcfG1lO3/Wedzx4+mWo2GM+myOA8s5rElT06pn54d56zQ8La0UmDMzgKL04ZR1Ot2YGU5o3VHqjP23rRMo9EcMOFUZJZNaxfYA5hmv5wOw1vJF5FQApwLAiBEj6l8yIjIuQPN7IUoRfOx7aZcgfbsfDpyxAOgeknZJGqPsBmp+93MGnCg76hnkaKVASk10k7oWWE9mkClMk7qfz87H3YUC+3CqWVmGUA73BfM417/eeVy3NPznmeHUFERkIoBtLG+dqZS6L8wiLNOs6YNKqdEARgPAqFGjWryTEaIGKR7ructRC2mVYFMTYcCJsqMRF/N5CBikKctN6pJmBpw6QgRnhgyvX1mSVOzDqYmythqtrA8n9/lHvgEM+UA65Ymq1iAZA05NQSl1WI2LmA9gR+P1DgAW1rhMIkqMW6flsZoof0YcBLzzTJWZ2KQuESJyFIC/AmgHcK1S6nzP+90AbgbwUQDvAzheKfV2o8tJDVDPzg+Z4RROK62ndqPJWY4P4hXYpA51GaXua9fUtsxGqnX/1Z9v9dFwaDKA3UVkZwALAJwA4KR0i0RERcVjNQNORLnzrX8CfeuC52mSJnWpXlUaI6AcDWBvACeKyN6e2U4BsFwptRuAiwH8sbGlpIZpSJO6/O6sDZHlUeqS1qwZQIqdhmOPo5zHQcPifb6s0/Ac7gu2DMUj/xD+88xwanoi8hURmQ/gkwAeEJHx7vTtRGQsACil+gH8CMB4ADMA3KGUmp5WmYnIQ5jhRJRbHd3R6qk5voZNO8OpOAIKAIiIHgHFHHL3WABnuc/vAnCZiIhSvPXadNhpePqK6ymHF9lRhWlGl0d6lLpWznA6/BzgoB8Dg7eM9/lm6jRc+/BXw3++2Gk4L2KalVLqXgD3WqYvBPB54/VYAGMbWDQiCqsYcOIlEVFzao4Mp7QDTmFGQCnOo5TqF5GVALYEEKEHVMoFdhqevjhDqOdVs2c4tXWmW440tXcAm21bPm2Po8IPoyt5z3Cy7L/tEQKQbKZBRJR9rVBXI2plZjA5v/Gm1ANOYUZACTVKCofkbQJ1PXEywykUfaGdx5G5omrWDCDdhxO39XIn3R5+3rJOw3MYcLKVOUrASf//O3wsmfIQEVEdsEkdUXNrjgyntK9IwoyAUpxHRDoADAWwzLsgpdRopdQopdSo4cNzMpoUlWOn4ekrZjjl8CI7qmbNcNL9F3HY2PhsnYbnie04F6UJaXsncOrjwAm3JFcmIiJKFgd4IGodOe7DKe2r7+IIKCLSBWcElDGeecYAONl9/nUAj7D/piZV1yZ1eifN787aEDozohUCc83aqfYXLgJ+NgPo3jTtkuRXWafhaScCx2Dbf6P+H9vtB/Rslkx5iIgoed+4Cdj3RGDLXdMuCRHVQ5OEPFK9qvQbAUVEzhaRY9zZrgOwpYjMBvAzAKenU1qqu3pGbpnhFI6+KM1jM6KomrXZYHsnsNl2aZci3/I+Sp22udG8PMd3xoiIyGLrDwFfuSrf5ykiCim/9bjUb93aRkBRSv3WeL4BwHGNLheloJ5ZSPVsrtdMiuuphSov+56UdgkoayTno9QV+p3HVu44noiIiCjXzE7D83sNm3rAiaioGOxowHeQnV4/rXK37LfLuE1QJbP5WR77whrocx7bGXAiIiIiyiXFTsOJklW88Gen4anR0fMcR9EjaWtvnf+VwjMDrj1D0ytHXIOGOY+7H5FuOYiIiIgopubIcOLVN2VHIzoNZ8CpCr2eWiTDichGch5w2mxb4KfTgcPOSrskRERERBTHlrsZL/IbcGKTOsqOugac2IdTOG4knU1xqJWZHcp39KRXjloM3cF5/P6jwOpF6ZaFiIiIiKIZNhLoGAT0r8/1NSwDTpQddQ0KMcMpFFVwHtu70i0HUVbk+AQPANj+gLRLQERERERxdG3iBJxynOHEq2/KjoZkOHGTD1QMODHDiVrc9qPSLgERERERtbT8Bpo0ZjhRdjDglL7CgPPIDCdqdd8dV9ofiIiIiIjSkuOMewacKDvqOkodm9SFwiZ1RI72Tmb6EREREVEG5DfgxKtvyo56Rm51oKmNo68FUuw0nIiIiIiIKHXFpAkGnIhqV9fsI72zMuAUSGc4tTHgRERERERElD4GnIhqV89R6pjhFI5y+6xpY2tbIiIiIiKi1DHDiSgBde00vAHf0QyKGU4MzBEREREREaWPASei2tW103CdPcVASiAdcMpxFJ2IiIiIiKhp5PjajAEnyo66ZjjpJnXc5APpYeCZCUZERERERJSi/AaaNHbUQhlSz1742Wl4KMUMJ64nIiIiIqJUfPo0YMvd0i4FpS3HmU0aA06UHY1oUse+iYIp5Twyw4mIiIiIKB2f+23aJaAsyXHgiVeVlB11bVLHDKdQihlOPDQQERERERGljwEnotrpoFB7Vx2WzQynUDbd2nns2iTdchAREREREVGuM5zYpI6yQ+9I3ZvWY+HuAwNOgb70V2D3I4Dt9k+7JERERERERJTjDCcGnCg7Bvqcx+4hyS+bo9SF0zMU2O+ktEtBRERE1Bp+ODnX2QtE1AA5PkYw4ETZsXG181iPDCcdcGKGExERERFlxfA90i4BEWWWeB7zh+kelB064NRVjwwndydlH05ERERERESUdTnObNIYcKLsaHMT7obukPyyi6PUcZMnIiIiIiKinMhx4IlN6ig79j0R6FsPfPTb9fsONqkjIiIiIiKi3GDAiah27R3Ax0+tz7KVch7ZpI6IiIiIiIjyIscZTmxfRK2FTeqIiIiIiIgoL3TyRA7x6ptagyo4j8xwIiIiIiIioszLb2aTxoATtQYdFWYfTkRERERERER1x4ATtRY2qSMiohYnIseJyHQRKYjIqID53haRV0TkJRGZ0sgyEhERkZbfJnXsNJxaQ3un81joT7ccRERE6XsVwFcBXB1i3n9TSi2tc3mIiIjIK8edhWsMOFFr6Oh2Hvs3plsOIiKilCmlZgCANEFFloiIiLKL7YuoNbS7AacBBpyIiIhCUgAeEpGpInJq2oUhIiJqSTkepY4ZTtQamOFEREQtREQmAtjG8taZSqn7Qi7mYKXUQhH5AIAJIvK6UuoJy3edCuBUABgxYkTsMhMREZEp/5nIDDhRa+jocR77N6RbDiIiogZQSh2WwDIWuo/vici9AA4EUBFwUkqNBjAaAEaNGpXf27BERESUKDapo9bADCciIqLQRGSwiGyqnwM4Ak5n40REREShMOBErYEBJyIiIgCAiHxFROYD+CSAB0RkvDt9OxEZ6862NYCnRORlAM8DeEApNS6dEhMREbWy/CYPs0kdtYYOdhpOREQEAEqpewHca5m+EMDn3edzAOzb4KIRERGR1gSjyaaW4SQiW4jIBBGZ5T4O85lvQERecv/GNLqc1CR2/iwwZBvgUz9NuyREREREREREwT7/J2DzEc51bE6lmeF0OoCHlVLni8jp7utfWeZbr5Tar7FFo6azyRbAz2emXQoiIiIiIiKi6vY8yvnLsTT7cDoWwE3u85sAfDnFshARERERERERUULSDDhtrZRaBADu4wd85usRkSkiMklEGJQiIiIiIiIiIsq4ujapE5GJAGwNDs+MsJgRSqmFIrILgEdE5BWl1JuW7zoVwKkAMGLEiFjlJSIiIiIiIiKi2tU14KSUOszvPRF5V0S2VUotEpFtAbzns4yF7uMcEXkMwP4AKgJOSqnRAEYDwKhRo/I7biARERERERERUc6l2aRuDICT3ecnA7jPO4OIDBORbvf5VgAOBvBaw0pIRERERERERESRpRlwOh/A4SIyC8Dh7muIyCgRudadZy8AU0TkZQCPAjhfKcWAExERERERERFRhtW1SV0QpdT7AD5nmT4FwPfc588A+EiDi0ZERERERERERDVIM8OJiIiIiIiIiIiaEANORERERERERESUKFGq+QZ0E5ElAObWafFbAVhap2XnGdeLHdeLHdeLHdeLHdeLHdcLsJNSanjahaAS1sFSwfVix/Vix/Vix/Vix/Vi1+rrJXT9qykDTvUkIlOUUqPSLkfWcL3Ycb3Ycb3Ycb3Ycb3Ycb1Qq+E2b8f1Ysf1Ysf1Ysf1Ysf1Ysf1Eh6b1BERERERERERUaIYcCIiIiIiIiIiokQx4BTd6LQLkFFcL3ZcL3ZcL3ZcL3ZcL3ZcL9RquM3bcb3Ycb3Ycb3Ycb3Ycb3Ycb2ExD6ciIiIiIiIiIgoUcxwIiIiIiIiIiKiRDHgREREREREREREiWLAKQIROUpEZorIbBE5Pe3yNJKI7Cgij4rIDBGZLiL/607fQkQmiMgs93GYO11E5BJ3XU0TkQPS/Q/qR0TaReRFEbnffb2ziDznrpPbRaTLnd7tvp7tvj8yzXLXm4hsLiJ3icjr7nbzyVbfXkTkp+7+86qI3CoiPa26vYjI9SLynoi8akyLvH2IyMnu/LNE5OQ0/pek+KyTC919aJqI3CsimxvvneGuk5kicqQxvWXPVdS8WnW7Zv0rGOtglVj/smMdzMH6lx3rYPXDgFNIItIO4HIARwPYG8CJIrJ3uqVqqH4Apyml9gLwCQA/dP//0wE8rJTaHcDD7mvAWU+7u3+nAriy8UVumP8FMMN4/UcAF7vrZDmAU9zppwBYrpTaDcDF7nzN7K8AximlPghgXzjrqGW3FxHZHsCPAYxSSn0YQDuAE9C628uNAI7yTIu0fYjIFgB+B+DjAA4E8DtdScqpG1G5TiYA+LBSah8AbwA4AwDc4+8JAD7kfuYK98Kr1c9V1IRafLtm/SsY62CVWP/yYB2szI1g/cvmRrAOVhcMOIV3IIDZSqk5SqleALcBODblMjWMUmqRUuoF9/lqOCev7eGsg5vc2W4C8GX3+bEAblaOSQA2F5FtG1zsuhORHQB8AcC17msBcCiAu9xZvOtEr6u7AHzOnb/piMhmAD4D4DoAUEr1KqVWoMW3FwAdAAaJSAeATQAsQotuL0qpJwAs80yOun0cCWCCUmqZUmo5nIqBt7KQG7Z1opR6SCnV776cBGAH9/mxAG5TSm1USr0FYDac81RLn6uoabXsds36lz/WwSqx/hWIdTCw/uWHdbD6YcApvO0BzDNez3entRw3rXR/AM8B2FoptQhwKkUAPuDO1irr6y8Afgmg4L7eEsAK4+Bk/t/FdeK+v9KdvxntAmAJgBvcVPdrRWQwWnh7UUotAPAnAO/AqeSsBDAV3F5MUbePpt9uPL4L4EH3OdcJtRJu12D9y4J1sEqsf1mwDlYV61/VsQ4WEwNO4dmi2qrhpUiZiAwBcDeAnyilVgXNapnWVOtLRL4I4D2l1FRzsmVWFeK9ZtMB4AAAVyql9gewFqX0XJumXzduqvGxAHYGsB2AwXBSbr1acXupxm9dtMw6EpEz4TSt+YeeZJmtpdYJtZSW365Z/yrHOpgv1r8sWAeLjXUNsA5WKwacwpsPYEfj9Q4AFqZUllSISCecys4/lFL3uJPf1am37uN77vRWWF8HAzhGRN6GkzJ5KJy7bZu76bpA+f9dXCfu+0NRmdLaLOYDmK+Ues59fRecClArby+HAXhLKbVEKdUH4B4AB4Hbiynq9tEK2w3czji/CODflVK64tLS64RaTktv16x/WbEOZsf6lx3rYMFY//LBOljtGHAKbzKA3cUZzaALTkdhY1IuU8O47ZavAzBDKfVn460xAPTIBCcDuM+Y/i13dINPAFipUzWbhVLqDKXUDkqpkXC2h0eUUv8O4FEAX3dn864Tva6+7s7flFFvpdRiAPNEZE930ucAvIYW3l7gpHF/QkQ2cfcnvU5afnsxRN0+xgM4QkSGuXcvj3CnNQ0ROQrArwAco5RaZ7w1BsAJ4oykszOcDj2fR4ufq6hptex2zfqXHetgdqx/+WIdLBjrXxasgyVEKcW/kH8APg+nh/o3AZyZdnka/L9/Ck5K4DQAL7l/n4fTnvlhALPcxy3c+QVOL/1vAngFzqgQqf8fdVw/hwC4332+C5yDzmwAdwLodqf3uK9nu+/vkna567xO9gMwxd1m/glgWKtvLwD+D8DrAF4F8DcA3a26vQC4FU4/Cn1w7gidEmf7gNOmfrb79520/686rJPZcPoD0Mfdq4z5z3TXyUwARxvTW/Zcxb/m/WvV7Zr1r1DriHWw8vXB+pd9vbAOplj/irheWAdL4E/cFUNERERERERERJQINqkjIiIiIiIiIqJEMeBERERERERERESJYsCJiIiIiIiIiIgSxYATEREREREREREligEnIiIiIiIiIiJKFANORERERERERESUKAaciKhuRGRzEflv9/l2InJXHb/rByLyrYifeUxERtWrTERERESNxvoXEWWFKKXSLgMRNSkRGQngfqXUh1MuipWIPAbg50qpKWmXhYiIiCgJrH8RUVYww4mI6ul8ALuKyEsicqeIvAoAIvJtEfmniPxLRN4SkR+JyM9E5EURmSQiW7jz7Soi40Rkqog8KSIf9PsiETlLRH7uPn9MRP4oIs+LyBsi8ml3+iARuU1EponI7QAGGZ8/QkSeFZEX3LIOEZGhIjJTRPZ057lVRL5fv9VFREREVDPWv4goExhwIqJ6Oh3Am0qp/QD8wvPehwGcBOBAAOcCWKeU2h/AswB0avZoAP+jlPoogJ8DuCLCd3copQ4E8BMAv3On/Zf7Pfu43/lRABCRrQD8BsBhSqkDAEwB8DOl1EoAPwJwo4icAGCYUuqaCGUgIiIiajTWv4goEzrSLgARtaxHlVKrAawWkZUA/uVOfwXAPiIyBMBBAO4UEf2Z7gjLv8d9nApgpPv8MwAuAQCl1DQRmeZO/wSAvQE87X5XF5yKF5RSE0TkOACXA9g3yj9IRERElDGsfxFRwzDgRERp2Wg8LxivC3COTW0AVrh352pZ/gDKj3W2jusEwASl1IkVb4i0AdgLwHoAWwCYH7M8RERERGlj/YuIGoZN6oionlYD2DTOB5VSqwC85d7dgjhqvcP1BIB/d5f3YQD7uNMnAThYRHZz39tERPZw3/spgBkATgRwvYh01lgGIiIionpi/YuIMoEBJyKqG6XU+3DSpF8FcGGMRfw7gFNE5GUA0wEcW2ORrgQwxE3l/iWA591yLgHwbQC3uu9NAvBBt9LzPQCnKaWehFNh+k2NZSAiIiKqG9a/iCgrRClbdiMREREREREREVE8zHAiIiIiIiIiIqJEsdNwIsoVETkTwHGeyXcqpc5NozxEREREzY71LyKKg03qiIiIiIiIiIgoUWxSR0REREREREREiWLAiYiIiIiIiIiIEsWAExERERERERERJYoBJyIiIiIiIiIiShQDTkRERERERERElCgGnIiIiIiIiIiIKFEMOBERERERERERUaIYcCIiIiIiIiIiokQx4ERERERERERERIliwImIiIiIiIiIiBLFgBMRERERERERESWKASciIiIiIiIiIkoUA05ERERERERERJQoBpyIiIiIiIiIiChRDDgREREREREREVGiOtIuQD1stdVWauTIkWkXg4iIiOpo6tSpS5VSw9MuB5WwDkZERNTcotS/mjLgNHLkSEyZMiXtYhAREVEdicjctMtA5VgHIyIiam5R6l9sUkdERERERERERIlKPeAkIkeJyEwRmS0ipwfM93URUSIyqpHlIyIiIiIiIiKiaFINOIlIO4DLARwNYG8AJ4rI3pb5NgXwYwDPNbaEREREREREREQUVdoZTgcCmK2UmqOU6gVwG4BjLfOdA+ACABsaWTgiIiIiIiIiInyQ1ssAACAASURBVIou7YDT9gDmGa/nu9OKRGR/ADsqpe5vZMGIiIiIiIiIiCietANOYpmmim+KtAG4GMBpVRckcqqITBGRKUuWLEmwiEREREREREREFEXaAaf5AHY0Xu8AYKHxelMAHwbwmIi8DeATAMbYOg5XSo1WSo1SSo0aPnx4HYtMRERERERERERB0g44TQawu4jsLCJdAE4AMEa/qZRaqZTaSik1Uik1EsAkAMcopaakU1wiIiIiIiIiIqom1YCTUqofwI8AjAcwA8AdSqnpInK2iByTZtmIiJrWqoXA2F8CA/1pl4SIiIgouqWzgAm/BZSqPi8RpaYj7QIopcYCGOuZ9lufeQ9pRJmIiJramP8BZk8E9jwK2PXQtEtDREREFM0/vg4sfxv42PeAzUekXRoi8pF2kzoiImq0gb60S0BEREQUX2HAeWSGE1GmMeBEREREREREOWIb7JyIsoYBJyIiIgq2cTVw4e7AW0+mXRIiIqLqFr8C9PemXQqilseAExEREQV7dzqw9j3g4bPTLgkREZHB0qRuxTzgqk8BD/6y8cUhojIMOBEREREREVF+BLWoW7/ceZw/pSFFISJ/DDgRERFRFewrg4iI8oYdihOljQEnIiIiIiIiyh/bKHUi/u8RUUMx4EREREREREQ5EpR5q99jwIkobQw4ERERERERUXMwM5weOA24+jPploeohTHgRETUcvQdP/bLQ0RERDlTGABWzHVf2LKYjPrN5GuBRS8Dj53fiJIRkQcDTkRERERERJQPbz0e/L5YmtQ99oe6FYeI/DHgRERERCGxPwwiIkpZYaD03NoxODsNJ8oKBpyIiJJQKAA3fxmYNTHtkhAlT9j8koiIMkIVjOdBQSUGnIjSxoATEVES+tcDcx4F7viPtEtCRERE1LzKAk6FyveFGU5EWcGAExFRElipaR3T7gRWvJN2KYiIiFpTWZ2LGU5EWcaAExFREmx32Kj5KAXc8z3guiPSLgkREVFrqpbhpANSzXAz8IW/AeuWpV0KotgYcCIiSoIaqD4P5Z+u2K5elG45iIiIWpYRSLLe8GuCQBMAvDcDGPMj4N7/TLskRLEx4ERElIQCM5xaQjPcLaWWIiJHichMEZktIqdb3v+ZiLwmItNE5GER2cl4b0BEXnL/xjS25JQ57zwH9G9MuxRE1TsNL76f83N233rncc176ZaDqAYMOBERJaHQn3YJouPIY9G1etNJBtxyRUTaAVwO4GgAewM4UUT29sz2IoBRSql9ANwF4ALjvfVKqf3cv2MaUmjKpiVvANcfAYyriFkSNd47z5WeN3WTOrf8rK9RjjHgRESUhGKTOlYKmlveK69xcbvOqQMBzFZKzVFK9QK4DcCx5gxKqUeVUuvcl5MA7NDgMlIebFjhPC6alm45iABg0uWl54FN6lr1nE2UHQw4EREloZCjPpxyf8cvRa2e4UR5sz2Aecbr+e40P6cAeNB43SMiU0Rkkoh82e9DInKqO9+UJUuW1FZiyibRlww8f1DWBDSpy3t9p1h896bP5OuAO7+dUmGI4kk94FRL3wJERJmRx07D814RSwPXGeWLLTXNuhGLyDcBjAJwoTF5hFJqFICTAPxFRHa1fVYpNVopNUopNWr48OG1lpmySDfpUQXgrSeAV+5KtzxxLXyJfS42m6AmdbnnaVL3wM+A6femVxyiGFINOCXQtwARUTboDKdctbNvlgpZI3GdUa7MB7Cj8XoHAAu9M4nIYQDOBHCMUqrYK7RSaqH7OAfAYwD2r2dhKcuMgNNNXwLuPiXd4sQxbzIw+rPA0xenXRJKUjN3Gt40gTNqZWlnOLFvAaKw1i8H3ns97VKQnzw2tWJFJro8/s61GugDxp+RdikonskAdheRnUWkC8AJAMpGmxOR/QFcDSfY9J4xfZiIdLvPtwJwMIDXGlZyyhbdpC7P540Vc53Hxa+mWw4q2bgauOiDwNtPxV+GdZtssk7D2Y8i5VjaAada+xYgah03fhG44uNpl4L82PpwKhSAvg2NL0tYua+IpaAV19mcx4D5k9MuBcWglOoH8CMA4wHMAHCHUmq6iJwtInrUuQsBDAFwp4i8JCI6ILUXgCki8jKARwGcr5RiwKlVFZvU5fgYqM/Tbe3ploNK3nsdWL0ImPDb+Mvw3gi68zvANYfWVq6syVX2PFG5jpS/P07fAp/1ef9UAKcCwIgRI5IqH1F2vOvekevfCHR0p1sWqmTrw+mh3zgjqfxmCdDR1fgyVZXjC4e0tGKGU9dg4wW3mbxRSo0FMNYz7bfG88N8PvcMgI/Ut3SUG8Vh5nN8DNTnaWHAKTP0+WXjmhoWooCzhgIH/Q9wxO+B6fcYb+XwnHXt4cB+JwKjvmuUnwEnyq+0M5xq6lvAxA4rqfm5J5t1y9ItBtkV+t0nRqVg6o3O44D1sJW+PF84pCaHlVc/G1Y6d5UH+oLn6960MeUhouzSwZo8nzf0ebot7fvtVKR/i961zuP9PwP+um+0ZVx/pPP4zKWWN3N4zp7/PHD/T90Xnk7DiXIo7YBT7L4FiFpOz2bO4/rl6ZaD7GxN6ooyWlHI452/tOV5na1bBvSuK72e+H/A038FXrkzvTIRUT7okd3yHHDSZW9L+/KHinQgs3e18zjlOmD52wkuP8fnbCD/5SdCygGnGvsWIGotPUOdx3fZ2WUmWSvhGa8o5PnCIS15rvxdsDNw3eGl1/1u5l1gsBTcToiolB2U5+NBgU3qMkf/JjrDKXE5PmcDYKfh1AxSzymN27cApWSgzzk5dPakXZLW0+U2a7nn+8BHjmN6bdbYLtozH5zIevkyKK8XW/29zmOcgHXmt2Miqquls4AbjnKem8dApfJVFylmODHglBk6w6nYLYHrtfuAvY+tnL9V5Wk/I/JgTilFM/oQ4Nyt0y5FazI7Cu/PaJ9ArczWaTgy3slqVsuVaTkNvtTURCGn/zMRJWPGv4wXxvGgWnZk1jDDKXv86iF3fCuh5ef8/JX38hOBASeKis250tNhZJX1rfOfj9IRmOGU0QoDKzLR5TVIt9HtH6NjUPTPmtsJtxmi1rNibum5eQwsVBlwIGuKnYYz4JQZhTqfUwd667v8umOTOso/BpyI8sJsxti3Pr1ykJ01w0m/l9GL9LwGT9KU1d+yGv1bi3naD/m/5PV/JqJkmM2dzPNG3i7m9Xl60hXVR+ekxgiqO/mJEqTauCr68rNi+Vzgxi84z9mkjnKMASeiPFgwFXjzkdJrBpyyx9v/AIDMN6nLauZVpuV0nelKva3SWrUiq3yeE1HLMQPQA7bzXoa9dl/p+YYcByLy7vUHgMcvdJ7HaZYZJUhlrZtlmLl/LZ5mvMGAE+UXA05EeXDNoeWv2aQue/QdtzzdhWLmSnSZDR5WUSx3jO2T2wlR6+ldCzx7uRMQMDNK8tykbsHU0vO8ZWc1k9tOAh79vfM8VoZTjM9su5/zuHFN9M82knm+zVuwjMgHA05EecQMp+wxK01KAW89WaqYZzVIkdVyZVlegy/FznJjnPa5nRC1nicuBMb/Gnj1bqDfqHPkuUmdqd437vp7gaf+UhohlOzqneGkbX+A8/j+7OifbaSygK7xf+bpZiaRBwNORHnEDKfsMSsGM8YAN32xdHcqr0EKqpTX4EuxSZ05Lex2ye2XMuStJ4ElM9MuRfPrXes8rl0K9G0oTS8LODUww+mRc4GFL8X/vPdGXZgbd288BKxaGO/7Jl8DTPyd018U+YuV4RQj82eLXZ3H9cujf7aRkt6/CgPAWUOBif9X+7KIYmLAiSiPmOGUPWalqWII+oxesOc1eJKqjP6W1QQ2qaty55QBU8qSm74IXH5g2qVofp2bOI9968pvcpX14dSggFOhADxxATD6kOifXTTNaUblDTSEqUfdchww+t+ifydQGhlUB+7ILs4odUFZUX7nq022dB77N0b/vkYqy3BKoEmdzkJ89vLal0UUEwNORHnSs7nz2JvxNuitqOBpUmfKamCnWiDh/p86d8aoJKu/ZTUF2yh1IcW5A01E+dbW4Tz2rgH6jQynte+Vng806OK92FdUxOD3pCuBqz8N3HK801G1qVqmuD4/rlkc7Tu9n2dTqGBxzi9B52G/93rcuoy5LWeSsY2rJJrU6c/xxhGlhwEniue+H5bu3lDjdA1xHjesTLccVKmskuMNOGX0RF8teDLl+saUI0+y+ltWo2ro1F4Py0xErcPM0PHLBmpU9k6YTKq+9cC6ZaXXq98Fxp3uPJ/7FPDu9PL5qwUe4vQtVEYHnHipFSjOeg76jF/9uHtT5zHr/Y75ZjjFDTjp0ZJzWnehpsCjIMXz4t+B565OuxTNbdkc4O7vAVd/tjSta7DzuH5FOmUif2bFIC8ZTrzjFV1eK23FO6VlnTjFWE5O/38iimbjKuexd51/cKZRNx7DNC267nDggp1Lr9vay9/vXQMMM96vluFUa3OmWkYGbSWxMpwCPmNuAyYdcMp6hlPYTsPDnot5zqYMYMCJ4nvkHGDFO2mXonnddQrwyp3AIqOTTBGnX4UNDDhlTsG8oPee4DN0wl86G3j7Sed5ZgNhWZah3zKKWkapI6LWowMyvauBlQvs86QZcBp/pjMKnLb4FedRKae/Gm+my8bVpaAD4ATSwn5nnE7q2aQunFgZTjGCgcWAU476cCrL7BPgvRnGfGEDTnp5Oa271NOsCcA5w4ENq9IuSdNjzTOOZW8Bcx5LuxTZ8NYTwMxxaZeiSVlODoV+px8nZjhlj8pJH063f7P0nHe+osvSbxlFUJM6XhARkZe+2F38CtDn03TumUsbWxbTs5c5o8B5PXUxMP7XwNhflE/fuBro3sxYZpWmVWZQ4/IDnf4MF70cvszFOhyPr4GCspWu/ox9epwglf7tsxhwemcS8PevAQP9wZ2GX/EJ4wVHma3Zo+c5x4Glb6RdkqbHgFMcl+wH3Hxs2qXIhvt+CNx6PPsUqgdbJkKhHxg0LPvDuraisgpQlvtwMjukzGnwJE1Z+C0f+yPw0q3RPmNtUkdEZTasdAILL/497ZKkTwd5/LKbgPIM7HoKymg5aygw6arS64fd4d/XvV8+nzfDqVq/ULagRpSRvopB/vAfaUlBo9T5Bfji1F2y3KTurlOA2ROB1YvK6xjmdl/RpC7kOtDzZaHukjkMCjcKA06UjIEEhu6kEqVgPQAWBoDNtgNWzmt4kaiKsgynijcbWZIIslquDMtCkO6x84B//iDaZ4pN6lixIvK1cr7zyCHESyPDNWokuiAFT3Do+qPKXz93ZeVnvJkz65cD3UOAA//TeR0lwykOfYH/yO+B99+sbVnNLM45NU6GU0e385jFDCd9g1kNAMvfLk0vu7nsOXe/+2q4ZRcDTazv+WK1qO4YcKKE8ECWqOn3AAumVE4f6AM22xZYPA1YPrfx5SJ/5l06bwUqC0GKIuPMmqly5YWZIZaj456y3MmzTSNqZXnap+vpjfHhu47ob8CoX+ZNzZu/DLzzbPn7nYMrP+P9LVfOczLEDz/bed2/Hlg6y/87rQGnKMdK4/vfYNcTvuJ0Gh4nGCgCdPRkI4DqpW8EPXs5cM2/laY/e1nlPNroQ0IunKPU+eI6aRgGnPKiUR0zUvpu/jJw13ft7/VvALba03k+66HGlYmqU3lpUmfIarmyTKXcJHH1u/E+p2ydhrNTWyK7Ft8nbvlG9Xm23N15bET91AwwzHm08v0uS8DJlgGy2+FAe6fz/NHzgMtG+XcIntgodQAWh8xGaUVxspXiBKkAoL072xlOsyYEzRRv2cxw8seRJBuGAac8mDUB+MMOwNxn0i6Jv2a/cF0+1+knwC8QlCRbZUrbuBrY3+30uVo6OOCMwhLnZE7RmZXTik7Ds7p/NKBck6509p1qIwLlRVCHno3g14lqNUGdhkdbUI2fJ2pRG1Y1V/+Lm2zhPG5sQB+e3iZ1Xl2bhFvOZtsBbe3OBb4+Jq7y6aMqqSZ1ALB+WW3LamaxMpxi1ms7urPZh5MOOPX6dM5fi8zWPzMkjzfdNqzKVVNdBpzyQA9hPu+5dMsReNBq8gPaHd9yHl+9G+hbn1451ADQ6Vas+kJcwJ+3LXBvxL5eKJ5iHzlA5f6Q0f2jERURPYqRtwPX3PLp0LNR1iy2T+/bAKwLuKgpsNNwourqeEz840jnr1kM0gGnBmQ4Vesn9O2nwy1Hdxzd3lWa5nceTPJmXT0CCc2i2nq2/T6xM5w6y8/bS2dnI/tMB5zWvhcwT9wMJ3ad4E83N8zhOrrxC8ClB6RditAYcMqDYmdyKe8QQRdXzR5BN4M7qxY6Qadxv06+ohWmz4T2TkDaKwNf/b3AA6cBazwnrFfuSKx4FMAcBayiD6cM7R9i68Onrl/oPNz1neqjAuWB+dtm6f+58QvABTv7v6/MgKiexr4diMoklgloW3bOs40/9JXy1z1DnceNa+r/3dWC+9UyoLRIASfLd0bZLszl9jZgHeWRUtWvbeY9XzlaXdDIdkGkvTzAddlHgasOjresWrx6D7DindLrtvYQH7Jse7Zt95FzgTfMLjd4fq8qjy1BFk9LuwSRMOCUBzrgFPcAm5TAgFMOo8NRmP2eFPqBKdcDky4Hnvxzst9z87EhyiJA5yAno8H0xoPA5GuBcae75azxNxl/JnD+TrUto5UUAppaZXX/aES59L4zf3L4UVWyrGzIYkslZcMqp8LX6GCUbZABU/FC2nbaZ4W02YnIUSIyU0Rmi8jplve7ReR29/3nRGSk8d4Z7vSZInJkI8tdod7BUVsmzYO/Al65q77fmweHnw0c9OPSa92MLWywpxZJfUfXEOdR9+MEwPf4V3MGqxlwarEMp8WvAnMerz6fKlS/2L/+iMqm5HF/m7b25DOT1y0D3ns9/PxKOTfgrj28NM16Xg7Btu6euAC45Tjj+zJa/8wCvYvecTLwpz1TLUqzY8CpFo26Kyxu5Dvtg0bQBVTaZas7487CDZ8v9Z/U6CY1exztPHYOqmxSp8uiT0C1VtCevQzYsKK2ZbQS8+51xb6SpQv6shSXxn5dW6fvbJm17K3y16pKk7rH/+hU+F6+rb7liiqoSV3TH79bm4i0A7gcwNEA9gZwoojs7ZntFADLlVK7AbgYwB/dz+4N4AQAHwJwFIAr3OWlo97bqu28+dxVwN2n1Pd786C926l7aLp5f0NGqUso4NThZjaVZTj5bFMTfxf/e+Y+C7x+f+l1I7LAsuSqg4Gbj6k+nyrEy/yLmy3Y1pF8NsvVnwWu+Hj4+fX3m83jwwScbNl1Ya5BmMHsT+/7qxf6d1dAiUg94FTLXbfUNSzglIcmdTlMR4zCPBmsW1olW6BOfvg8cMI/nOedgyo7PtTboz4ppdG/TCvTlYgNK4Dnryl/L+1918+404GV8+v8JUYlqT1nAaeZ44BL9gNeG2NMrBJw0vtf1vqs8h4fyt7L6PZJSTkQwGyl1BylVC+A2wB402mPBXCT+/wuAJ8TEXGn36aU2qiUegvAbHd56ah7wEnv0+zrrEJ7p3PBrumR4cIMYFKLenS2bt788Num3nwk3rKVAm44qrzJ1OqFwPyp0ZYz5YZwWULT73UG5gjqwy8t1bqd8GY4Tb3Jf15T1KDR7kc4j20dydeNV75TfR6TbX8J1VQzZsApUzc8qVWlGnCq5a5bJjQqyFIMOFm+r7+3cam6rZzh5A0s1bOfB5tBw4Dhe5baeXdYMpw03XlmlvqXaQVlGU6eYXezfIcpTIW2FuY+Yl6s5MHiV5zH1+4DXnSDvdVGqevezHncuKq+ZYuq2IeT5bTf7Mdv2h7APOP1fHeadR6lVD+AlQC2DPnZxql3Xxv6vMl4UyVvwElnONU74HT+jk4TpFp8/AdOk0DNvPkRqfwhNgy/bfSZS8J3dVAoAPf/pJQlNPVGYLVPBsaj5zmPqxaGW3YjLZ8b/L43w+mR34dbbtTrr31PdB7rkeEUlbm9FUcZi9sheIj/hef3ABmrmysVPRsyy9cXhrQznGq565a+Rh202gIynK4/Ejhvu8aUI6iJVrMf0LxbnE4hTyrD6d4fABft5f++d1vrHFTZabg+6Kx9D1j7fvi7OL3rGpDlkqJ5k507hfUWeDzI8AkhTIVlyRvxl2/uI43MCEyC3u9fvQu477+du7XVmtQVA04NGLkpCmuTuhAjtOSkMkOBbHUm7w/rN0+Yz0JEThWRKSIyZcmSJTGKGJLteDXjX8Ckq2pfdv9G4LaTal9OVhUGwgU8/M5l7V3lgZqOHucxDze3dj8COPh/S6/NJnVJNwn0C2C99k/gMTc4NPthYMU8+3wA8P6s0vPrjwb+9b/A7d+0z7tygfPY0R29rPXWvzH4fW+GU9hMtqjXX7ruUY8+nLRq58qVC5zjlLm/6FHGwuxDbzxYOS1oPejABc/h/rK2biZfC/xh+/LsyGpycv2ddu2/lrtuZRpW2TE16kcOalK38IXwy1m/wkm7ffWeeOUIOiCm3aF5vXn/vycucB6TuoB++VYn5dr3+z0nSFvAybTi7fCVwFu+AVz8IWD1uz7fbZzQ5j4DvDE+3HKz4rrDnDuF9ZbXTvXDVNwu/1gNX9DgPqMS5bnWXrkgRIaT2ylttYDT4leApy+prXhRBGVlBgacMjziIoU1H8COxusdAHhPOMV5RKQDwFAAy0J+Fkqp0UqpUUqpUcOHD0+w6N4vsmyrt38TGPer2pf9/mz/zOFmcPYWzvm+Gm9zfa2ts7wpmg4+1TvDKQneUcDKMpyqBEWiCro5O/2fzuPfvwpc9Sn/+V69u/T8nWecx7VL7fP2ua0c0s7csbGtC/McogrlQamwfY9mMeBUrUx3n+Icp5bOLJ/e3wssmRHzOwP+lys+6Txmuf5J5Wa6QcUondBncb+3SDvgVMtdt/IJjarslH1po5vU1XjQ0M1Dnh8d7/N5vaBOgu9vHTPZbupNTkZT2Iu3UAEnY1nL3gp/Un37Sefxoj3sd/qWGnfabjg6XIW1FeUlS8QbcKh3X1/m92VpPYThDSivnIey/cx6h9r9f1++FXj3Nf9lX/UpYML/q618704PP29gk7qA36XZj+2tYTKA3UVkZxHpgtMJ+BjPPGMAnOw+/zqAR5RSyp1+gtuf5s4AdgfwfIPKXamelWszmNKsWb+zJ1SfZ/nb9ultbaVOt4FSRk0jA077HB/vc95+7s2AU7UsnLLlhKjz+QWG9Hfp423QoCxrLTfOq93gzGJfqrb6hTlNFfwDnEGi/q/FgFMd+nDSBnqdZo9+51NdZ1/jubmr6+BxBB0Pi31L5azeFdWqRcCa92J+uMHrZsNK4PWxldNXv+skhLz5sPO6N0KGfE7qaGkHnGq565a+RkUV9YGy1u9b6+6Qg2ME5Ab6gCUBEdecbPCxDfmAfXrc1p3/+rGT0RT2N93p4PLXHZZOw81lrVoYb5Q6293dKz4OjPs18Nj50ZfXKtYtA6bd4f9+lvePupetiQJOa5eW/w8P/tJpDrvGuDgwK8JXfrL6d9SSHfovS+ae3zrWv/OS150RlGzv2XiPUb1rmz+jtcm42eE/AjAewAwAdyilpovI2SKih5K6DsCWIjIbwM8AnO5+djqAOwC8BmAcgB8qleKVbT2PV+aF6Prl0Zo1NJNF00rPvf3u6SbDgDNqHdDYgNOBp8b7nDfDyfw/vNngsyYAF38k3vcApWZSNv0bwq0vWxDMez565S5g9sTS60fODVe+RrJl2pvT4gacYmc4ddTvGLJ0JnDRnk5fXTY97jbn7dy9lsFUQo1S1+Tn6z9/EPjT7sC8GPdBGl0nvfv7wG0nVt6sXDan/HWULhmyGGi2SDvgVMtdt/Q1rEldezLfpy+K/IInQR76f/7tx4HcbPCx9W8EhmxteaPG7sRs6+3YK8pf/9ezwPF/L5/Waek03EwLX/MuMBDjLo4+8XsPdpMuBx77Q/TlZUk9Dxv3fN8ZvdD08f8yv7x+312regfOzUpy3io+3oBy//ry/2HZm04m08P/V5oWdX1GCQx7t+ENKy3L8/l+M0h0w1Hly9uwyj+rwfubLXsTeJzB57xRSo1VSu2hlNpVKXWuO+23Sqkx7vMNSqnjlFK7KaUOVErNMT57rvu5PZVSlo5EGijOMWTxq+Gagnsv3ta9n78geVjzJvtfoJkDHngDTj2bl57rbKdGBpx0R+W1GrZT6bm3Sd3YX0QfeSysgY3B3SFotiCMN+B09ynA379Wej3zgdrKVg9VM5xUuPXhdcd/RJu/EU3qdDOoOY/Z39dBTm/2Wi31olABpyY9hnk98acYH0pw3WxcUz1b8v3ZzqO5f7/wN+CmL5XPtyHCoDM5qVenGnCq5a5bJmShD6diWULsNPqk2jkoehnmPl16vufngaMvKH//ms9V73hx4xpgwm+Bvhh3M9LWt778jphWax9OtovDfYwma91Dga33LvULo9ma1Jnr/9nL4vW7o4NYYbKZXr0bmDWx+nxZUc+OTW3NLwYbXc1l+XzfyCZ1mV4RFt79u28Dyv4HfYd/7RKn830gevA9ynbpPQfYmmTYvn/e88FNqR/9PfDXfcN9JxC/H0CiWpnnzIUvlmfj+Lnq4HBNwb37Tnt3bvrHiOy6w4DrDre/Zx6TdH1xP/eGY08DM5wG+ipvnIWtv37Tc4zyHseGjSw9X+85jtbjBqpurint4Zrw2erJ5vlo7C+TKZf2zGVOEDJptvNbRZO6hPvQ0sxmlI1oUqdv1OrO9L16hjqP3tEGe2voNy7MdegNn4+//Kx48xHgrSpND3cY5Ty+9WT4JtFJBuP+sH1wv2x+xvyo8sZjlFGOc3KOSjvDqaa7bqlrVMBJpwIHbVRhDqC1NM0zT3QfOwU44OTy9/vXA6sWBC/jqYuBp//qDO+aN/0bge5NK6fXOmCirWJjptf+Yrb9c7aAk2+lL0IZ9TLDpDjf9V3gH1+rPl9WSXhnQgAAIABJREFUJN0xqMlWYTIrHZm6A+HZHuLcXYz7fZlaD2FUyXDSx8U3xgEPnOY8j9rcbKA3fIXTe+z2XijZ5gGAf3y91KQ6qmrHKKJGMve/0YcAV386uWVX7Duq/gH5LDIvfnRGkQ40lTWpc7Of6nUz55ytgGv+rXxa1+Dgzxx9AfDDycBunwOG7Vya7r2wNDPWn/oz8Med3UEhVHlTyv29mf1V6lN+F7A7HeQ8trU755FqbHWwvnWlbfT5q6svI4qHznSCkKsCBq+JI1QfTnWqg9hGyK1nwEn3u2OOgGjS1xAv3FQ+vXdt/O/0/i+27W+NEeBaPrf6Mu/+fva60PjbV4Cbvmh/T9e1pc1prnjTF4FbTmhc2UxLq43orH+fKseRWjOcxp/p9AmVIakHnHKt0X04BV2shbnDpA9EcQ62ZmClrdOe2VPtIkRf8MfpWyhNSjknBFvAqeYmdQXgpmP83+/wOXFZA04+ARXbbzV/qj07SS8zStQ/6SGFk7L8beA9Y+SPelWKVy4Alr9VOb1sf3XX51lDgXFn1KcccdV7VCbJccDJG1Du21C+b5jvv3yL8xj17viTFwHnbVvZr4ON99ht2+f1PKsWlobL7rIdu0Ky/WbeZjZEjVLPDEJvnW6gr/m7C7AZsAScdD1iqz2MGcXJcqpnk7rFngw2v+wRbe9jgeFuGYPOPYOGlb9ev8wZhfetx8unf9DT1AVwMuvmT7V//5MX2acf/zdg6I5ONqw5EIsf202sFXOBsT8HXr6t+ufj+vNeyS7PVt/39uFUr1YPZr9deluQOjap27jGefTdRn2uF/pqCTh5jk/V6u5maxU/r9yRny40CkYfYIX+0sjt774ScgGe9dWo5ofVkhUi9eFkKfOzl0UrTwMw4FSLtEepM/vvCBVwcj8fK1Bm7BztPgGnsAfxvLUnfvRcYNV8+0mk1gynwkBlBSeMjkHOxaaZTeEX+LH9Vtceas9OihN8iJL62Uh/3Re44hOl10mlbc95rLzC975P5XE7o+NQc9+ddEXlvI2iVOWJuO538Juo03BvhpO5TenjQ9Tj64tu/2yrF1Wf13bOef6a8ruWep4/7wVcvLfzvNOvAmz5PWaOA954yJjFMo/fHVyieou6f61f7vl8AXj0vMpRjTaudjJdTAN95cfHDaucmwbT741WhrwxAwJdnoBTWxuwyyGl99u76ttc3atasFuPnAcgMLvW7ItKWzansjPfPY8qf60KTmbdtYdWfn7FO/7bRs9QYFu32XKxeWdA/dEvy3zqTcC9/+n/uSQkeZ629SWaxCh1YVib1LXXL1mgVwecfM6PftdpOsPpo9+O/p0VGU5Vbupl9aZf79p4gUczWDfQG/5YtGEVcNnHSn0qaUlsG0FZ7t5964W/2efzu64qFCxBxnzcFGHAqRYN78PJs1GNP7P0PFSWSVIZTh2VI34AwIIX7FHZwgBw1ubAlBuif28WTLneefT7vaNm+JgHi7jbkO7HwExF9s1wCqjUeA9+xaY9ESocto6Lsyipu7A3H1te4bNVqD77K2Bno6mHUukGW1a7w/AueKHyvXpfLOQ6w8lziuxd53TUqpnH5K4hldNCfYe7fsJUtmzH7rE/L+9wctHLzgW1qS1CE7hbjwduOc74TjapowyJegxZ937567lPAY//Ebj/p+XT/7CD0zTWVOgr3/6Xvek8PukJTD1/TXmQtpo0zgVRvtPMStl8hPNoHgu/+Bfgw18HRn7KORbUqw8eG1vd02TeGAzqP9Cb4QQ4NxbNpseDLQPs+NWf350O/OUjwLuv+pdNB1b0NhwUPPMLwjTi4rLWOsH8KaXntgynRgWc2vz6cKrTOqzWh5Nf6w5d77b1E1tNswScztsOuGS/6J8zrzm9NwiCzH/e3vwtyv711F+cvtT6PTf/A5fhOQ6N+ZF9Nr+A05UHAWdv4VlkRn9TDwacapF2kzodTQeiZTjFOmF5Ak62IMZd3wFuPbFyet86AKq8vHlSbB9s+Z8fOQf4/fBo28J9xgHG+7kTbgm3DJ3mbjar8w18BQScvHd/dYZT0AHMW0nKaoZTkfv/161jU8tyK0Y0VOW/dSM7+Zs5DrhoD2f45F5bQLjed6dz3Gm4d99Z+15pn2nvLn+va7AzEuiE38b7DlsH4F5+d85WGnflbz7WuaDWBvpLfa3EYTsWMOBEaYkccPI0VdXZBGEuqgd6PTeI3OOXty4w9uflQdpq0ujkNcp3DvQ5mUvffQjY1r0INANOW+wMfP06J5uoc1D9+uCxqZbh1O6T4dTj6c9EB5y22Qf4nxeAzbZ3sh7M/vT0//w/LwBfcoe697ugtd3MGe5pnuYNzFXUpdY4N/AevyA4cBUkzrblPa/UEgBauxS49nOl17b97M1HSs91kzp9U8QWCAyj29JfTcP6cHK3M92nol8GsN/I0boO1tFtfz+ItzuHvAacgHBZ3l7mtlroD//b+t2Ei7JtTPyd05fa7z8APGDcwEji+P7WE/aRg5fMqJzGTsNbQKN3XO8dKvN1pD6c4nQa7mlS5+edSf7fmzer3wUuHVU6CLZ3ASN9OiiNEsx42QgqmcG//f4d+OAXnOcjPgl8JKACqzOczCZwfmUIGknP2z9C8Q5cwG9W6C9/P0rndmnQ22u97sLa1rv3gkQVyn/rf/53fcpis8C92zh/qr3C460Qrlro9GWR1PoqizdluLJj4/0dzbtp3ruYbe3A/T+J/x1hAk5+NwuC1us5WwKLw/ZnEHLZUTKmiJIUVH8Z92vg/zx3f9d7Ak76eG3WY7z9IX78B+68nguYYsCpxqpzGk0golxIFfqdZvsjPl7a//3+546exo48XG3dt1mCDIefDWz/0fL5Nt0aOOZSZzS7LXcFNt3WCfaY24I+Nm+5K/DRk4EPfKj8fL9yQel/9448BgBHnFP+ulrA6U97AOePcLpxiGvBVOCd5yJmtHm2jVrO/d4bkH5ZuZruNHyvLzlNyuKeW2zXJY0KOOlMqmo31f1u7hUGnOZ/cfpGvOu75a+rHVvyUAfbuCb8daoZLPXeIAjit67jBm/MwbCCfgO9X6pC9X00bF9tefhNwYBTbZL4kXvXOcPLh/meiu8zA05hshRqaVJnbCpRD4o5aV9a4dW7nf559Hof6AMOOd0+b5SD1F5G8xfzc+Z6/e444GvX+i9D96tg3o0b2AgM2Qb4wN7l89oqaLovAfNOU1l5qhwIzW0o6xlOugKTdIaTPlnY9j3vOlee0Y6m1bHTz4qyuJUhVSiv8HRvBgwdUXk8+PNewA1HJxgUC+jDacPKUkebWeQNOJnNRzcaz0d+2rnwiFVR99wdDZLGiFkcpY6yJKjeNenyyu3V3CeVKmUCr5wHnPMBYNJVlVlQw/d0Hgt9wGv3mV/uPNQacKq2H69dWluQ2CZKPWygt7SPVws4dW7SgJFODVH6zdTz7na4/f0DvgUMGe487xnqBpwsGU5az2bl54CL9wbudEdsXrukcvneeuEn3EDmJls5j72ry4N1tXQerV13OHD9EdE6Fq/YZyIEEAsFZx/RF/7ebKlq27oqOPtoR0/4YNBDv6mcZssOalSTOl3H0nVhv/9hyUz79BVznbJWay7qp6w5V44znADnt/nD9uVBST9LZ5WPwDfQF745qG/AKWYdy2zVELgMI/HD75rk+H84x9WwHYdn/Td1MeBUiyQOWuN+5USo5z3vjKg17Y7Kefw6+y7LcApxoVNLhpN50Rg17dM21HAeeA/+hb7KZjRalMqc2S+A+bkoFalikzqjctTfa++s0FZR1Adbb/8WYQ+25oEy8xlOeujmhANO485wKovWu1aWDCdzP9j6I8mWJYj+/WdPABa+ZEwXtwNNn9989oRkvx+oDDidPwK46IPJfE89eMu78EX7fN2bOhWfOOtMbz9hOuxPuqLsraiY/+9Ltzid4LJJHWVJ1BtY5vGtMFCqKy162Xk+7leV58EON4N4oNd5v/jdel+odbCQKufZqz8DXPWp2r7Da95z9umX7A+s9fz/A32VASe/i+FGN6mLRP9OIeqcOuBkBlsqAk6bV3ZD8MY4pwmcLUNVrzvdD9aHv+bUIc0mVzd+ofJzup7ZObh6uf2seTf8vLVkOE29AbjjW8CLbufH3v2zWgBAKSdg2ekGnKrt34UB4JlLS6+3O8DpT8zWjG24UbcwO71P+sbNZts6j4tedh5t//OSNypbFGiv3Okca8LezBfPvmius6Bzuu111ujgte47FwCeu9o+72Wjyvcfb5O6oP/V3LfLrsliBm90EBkIV0/TgVabIVs7x9+wwbOcJHUw4FSLJH5kPSLGxlXOiFr3fN/2Re5DQIZTmI6rVS0ZTkYFa4tdws2nNXIEkyR5KxsDff7BtigXgn4nhyi/iy3gNLDRqah4D7K6sgMAf/sKcPt/lH6TdZ7Kky5btZPSfT8sPW/GDKcNq4BHfu/f5h4AnrsSmHyt/aRRsR+o8t99i5Hhy1Ir3cRgwVTg8fNL06U9+KQWJ73bJqjjVsDer1RWhK18dG8av6Kit58wd5WTrihXVE6N1//8L+BvX2WTOsoWb0b4lrsFz28e3wp99uO19xymR3X0HhurZfv4WfwKMPYXRjmq1BdWLXAen7k02vDYQf72Ffv3L5sDzBhTPm+hv7SPV81w6omf4TTQn9z/Z/PV0cAHvwhstUf1ec0MJ31B7z2PD9rcaXLu9ei5wLTbK6d3dAE/nQ784KnSNDUArDaWsWAKMOF35Vl2qgAc/BNg8JbBZd4m4MbV4OHBnzVVBJxC/p5PXVzKktddT3j3mWp9ROpOwzsGOeu92r7hDQ5/+/5Sf2JexxsjgNWzSd1mO5S/ttU1V82vvpywdS7vOfmcrUrXgN73XrjJ/lmlnOOLN9gcx8KXklkOYD8+P/jL0vPVi4H337R/dqDXc4Mh4Hc26+O7HQZ84c/VPxPE7CczqC6ojHn8rkm6N3Wu5cIkkgDB12sZCjAy4FSLRNLY9MYQcMds4tn27zM3JL+yrHkPuOdU52Tm2zTPMNBv30D1wTrOcNhpNANJgveO3md+nkzAqeyAaAacIiyjy73zpSt6SgHT/2k/YZnZCG8+4lQu9Z2W2RM9ZQsZcDKH/s1KhtOd3waeG105XVcao+yvj5wDPHGhc+cpSKHPXtm2Nqkzft+GNkHwOcxLm3NR4bd/eoMKb4yPWe4cj1IXdp/UI9TFoQNNoW4aJLz+ggJOgHMxaB2lLsZ5gKhWSgFPXlQ+zTusNQD8dV9gsdvpsvcCxFbJ917k6AynihGgYjapu/lY4Hnj3BT2uPLQb+zNh2rlHeXI2/Gwmck50s202ulg+7I6NwmXnWlzz/ec0QFtbE2M/+PeymlBtt0HOOEf4TIyuwY7/0ffhtLxvCLDaWhln2B+Nt0O2PVzwNAdyjsst51vn/4L8MBpxjx9TufZ1W7WBh2HO31GSrPxbo9hMpwKBWDiWcDr9zuvi10MeD77nqWTY1Mx4NTtZlxX2Te8fWXp4KCtbj5omNMpPFAecEo6I8R73gxzzdO1aeU0b+aS/xdWTuo3rgVMbz9V/lqv3/mTnWOL3yhpUYz+LHD5gbUvB6ge7LxoT+DSA+zveUepC/odzPfajP6zYmeRG/Vcv768nrkUWPmO81wN+O9nQ7d39u2wyRpBZc5QnZsBp1q8MT7cfLMmVu+nya851bplpb5CAjsis2xU7zwH/OPrzp2XuU+jeJDy24h71zkdzD52vuVNt3xx+i7Ia8DJPPgPHQHscoh/wCnKCaxstDLz7muUDCe3QqxH3HntnwCUO4KBN4U2oGzeykGcg21WMpym3ws8+Av/96MceHVgpdodBmnzqWy7+8t3x5e+uyzg1MhOVn0qMdLm3JUJm+F0yzeA8b+O8f0BfThlXdA28yljVJLuGgJOWr0znD70FWCfE8qnVaTbe/7fnqH236yWUe+I4vI2Z/Kz/G3gKcsd64E+e8DJO62Y4eSZrs+lketB3ibWEc6zYfp2q9XapaXny+cCS14vXRjtcgjw60XASJ+AUy2dhusbV7ZjzHVHVE6rlgHyC5/MhzA6epxz+fznS10TeH/nrpBN3L50CXDajGjdJEy/p/x1z9DqWdlBAYqg7GyvigynEL+nX4sL70V0tZt2Oiulc5Bz4V8t4ODtK0vfGPbr7kLTv0VbR7R1E0ZFM0LL79br6Z/L1v1FImXx/C7eaxZdNv0bJ3XDeN3S6vOEUUvduNDvub4KGXBq7yxtR6+43dosneV0KRDHX/e116vNmweqYL+++NkMJ8Opo6tyX1o6y/59gRlVDDg1h0fOqT4PAPzja5UjCWjVLsDee630vG9D+UZcLcPp+iNKbYo7BxlN6nwuMHVniGZv+1rxxBmj7wJvEGPlfOCsoc5IWFlmZjjpO2R+J7VII8AY62P2w6XnB5wcfhnFJnXuyXmVz3CiH/xizOyrCIEBsxPNLAqbtWUKW1GUtuAMp2KF1dOkrqHDSPtUStva3Qwnn+OB7aJq2VuV06op68MpOye/UIIuDPVw4YD9bmXgcm13KMPcVa7hzmx7V+V2XdEvoDfgtJlPkzoGnCgFK+eFn1dvo2VN6gbsFzTPXFb+2uzDyaTPj1EDThX7XYT6QiP65zDXka2Jmx6kxCaJTsNtF2dLLR0sV1vvg7cKfj+Ivom3fnmpG4KDflw+jzngS5hl1aJnaPXASFA9pVpTtrJ54wScfPqUtZ3Hgv4PPfCN7jS8Gu8+qYNu1bJu9brq6HHqX0ne/PKeR23bszewY72W8JTpy1dGL0NFwMmT6abXXzFb07MNmdckaYjSYb3XQF/4m/hlGU4dpe1o4lnO42WjgL8ENFmd8a/gslTL+vTrw6nNuNYc6AWm3gRcd2SpTNZlhRgVLwMYcKpVlAsA6wWFpUmduYGY0fxZ44Hrj7R8FiE62iuUDkS+aXohNswod2yK3+35vjmPO483HO0/akMWiCXglHSTOp1u/IOngJ0/HX4Z+k7brPHAtDuB8WfY5wuTomxSPietIN47N1kwYEmrTezAa+wDvgEnT4A2k03qqvThtNJydyfWKCpV+nDKsqB9xzwWRs1wsq3zemc4tXdamnpWaVLXvZn93BI69Z8oQWs9d9GDLjKLTSQ8FyC2kcDmepqd6Awnb3BKn1ci14NqCTg14JhZ6APu/6lzIzBqgKtzUPwmddrARqcec9bQyhEDTbWODhjEDBKpAnDWSmDUd8rn2WLXcMvyXuTHESrDKWB9ROk7NVaTOp/BgGxlto3gp/UZAacw/Wx6v1f3UemXMeTdV7sG+zetjct73rSte29LAFszz2E7O4/dbhNM7/967OXVy+D9jPdmdLGe4TmuFAacY83fv+r/HY1g1oOCtmHbcdHbh1NQoLNshPDO6IEua0sgQ7UuEgo+ASedPd7e6fw///oxMG+S/fMaM5xaRJSNdGVAp3FlzU4Kzl0mpZw+mEwLphrzBWQ4eYcmVQX4prx6l2c7iVVkbPiwHQS8lSvzztW9/xm8vDSZF9dtVQJO3t8piFmh0yObDI84Upeu0Ey/1+kHoWz5xm8g7dEqkBPP8k/b9DP9nuQ6DEyK7aQV9sCrFPDCzc7z9990KsHzp5Te79ms9Fza7BcwO3zMfd8MOBn7QUMDTj7BgUHDog8RHCfQ4D225UnYO0dR+3CyVXaXvO6MVhq3PNW0dcI6emJQuboG+2Q4MeBEKfBun0EX9nobLevTo6+UURFEZzh5M1GrBYq89S7Ne9EbpUlPEsfMmeOC3x/oK40KFfXc1DmotqwEwLk4e+JC57m3jx6Trn9uuy9wyBnlI0PVytyW/LarsE3qOgMywsIatHltQZFIWfcJNKnbuKbys19x+y177A/A20/bl6MDTp094QJdfufATbet/lnAaa4ElMqbhDBN6rx9zdmC1nseDZw+D9j7GHe5nnU8bGRAGXz66J35QPlr7w1YXY6ztwAe+Jn/8utl6azyPmHN7cevD0nAvn17R6kL3aSuo/Yb5xXH+Crbsl+n4ea1ZtD+/5qxzoKC9BmqczPgVKso7U1tB1NbgGbFO05His9cWt47v/cz5obkbdZUke5qZDj5tbUtjkZiORDqaVHuMI39JfDUX5whY/1kpcNpG/N/LUadfQJO1x3mX9n0Mg+gG1Y6lZuow4z7Bb68omY4Ac4odlHvqo49rfo8jWTua8WDdsj/yezwT6cXv3xraVq30QGoN8PpQ19x7oxu6d4J1ftN7xrgErcJVkdP7RV0bdE04NJRwX2b+O2zJ93uBpwi3AmNE2hQIe/EZFHQPm3+L1GbUNjW+bzngOsOB2Y+GPA5d18esnW07wPcJnWead7fw3uOamu3/2bMcKI0eI+bQefNYpM6zwVImGyc7k2Bns0rA8B6v/U7purR5SpEvBgp+053n3/6EuDl250bIO88Fy0wdOvxwe+bmQQrIjRbBEoZTrVkYg1sLHXGHXSO0ev9P58ADjkd+NJfgKE7xv9ek3kMP+Bb9nnCnv+idNjtp2fzEDcYAjLtogSr4mQ4ecv23JXArAnlmR26ieMLNwH3/Xdpujm6XrFJ3aBSmbfdN6CsPkGEo/8IHPr/Sq93P9I+n745lMTouIWC08G+9xxp2zfffhrY/Qhge59mUYBTX+zZrLSde9dxUD9Vj54LPPir6nWs4m9ttK7R9RwddG6kKz7pDPij9XkCTn7HOe/23d7lZjjF6MOpLU7AyXvzznP8q7YP+TWpK3bf0lW+L3mXb3bTc/Mxzv+9dmnlzYwM1bkZcKqVrS+WqTc6FQKvwEqGsfEum+M8+nU0XnHAAHCH5wRZ0VRioLTBrn7XpwxBI+bpgFOEVPLnrwYm/q5yyF1Tkmmt9VRsVxvQxvzCXcItyxtwijPCVWB7dWO7aOtw7xJEGNpcDSB0cEYLU0GpJ+//Z16YRG0mWHa3oEqHyd5Owyva3Lv7y1tPlCZ1Da48ifb3Aq977kSF8eRFwPuzSoGx/l7g5duc44FeJ20+h/mh2zvbx/zJzmfCqHXQAL+LkncmJXvHMSlhB2oIGwDWxlpuJGiv3ec8blgFzJtc/p4+dhxzKfDLiP1pdXRVb1LnvaD3G6bath3MfDD9/h+ouenzTHHU3ID9TgdFzeDuQH+4C4uObmDXfwMWvFA+XTfp8zsO2vodAirrTVFuOOiM9wn/D7j3VGfa9UcA1x4efhnVmPUwnTF95HnhPtvR45Rx4lnhO3X36t9Y+mxQndAb6N7rS8BPX433nV76GL7TwcB+J9W4rIT6cDqqSrOdoPp4pCZ1SXQaDmeQIvO6xcwI04GEjWuAxa+U9l19DaWbEAFAZ0AmmVnX2+2w0vPuTYFPGiOunXS7p7xu3UM3f0+iK4hJlwOjD3H+n10PLU33jlL24t+dAX16hoa7htrtc87jNp7AW1CAfeqNwHNXVY5K51XMhDIynKIEwCuWZ9Tp4vQx6b35Zl5Tb1ztvy16jxNDtnFamsQapa4zegDS+zNW9OPllm/tUmCpZSRVv1Hq2oyAk9nUu9q6Xb8cuHDXyu5VGHDKMd0Jt2bLcPrX/zoVAq+oQxz6bSh6Bw26o2TtDNadv2+t/eLObFL36HlORH7pLGd6sYIVow+nID2bJ7u8JJnr0DzQH+IzUlfYypZ5oNuwMt4IVyL2yvY+x6PsN9r+o05G26IXK+f1C1opFaPJV8LbRVQVJy3Lfhn2Dqw57HG1JqJjf+40u9O8mS56vzGbCXQMqjwRTvwdcNtJwNxnw5VRGzTMLbO77Y09zWmm+tp9wNnDnODZ62P9Pz97gvMYtmlrnM6izTsufse064/0H1ghTYUB/4vLHY1hgKNeYPx/9q473I6ifL9zyr25N70XSCEhoSWhJZRAkBZ6QEroPfQuCBZQUUFAlCYWEBT8gQhKtdCbVDGC0iFKLykEQvot58zvj9k5++3szOzsnnrv3fd57nP27tkyZ3fKN9+83/vJTCg6yEntbYcI5iQdY2S9zrcCrYOAmecAU+a43bOpDyKzZanjmYnhpHPE3nZw/fUfUnRvSANdjl0uDCfa17Yt9zK6RoBlRLiWZIPLCfBfzvK+N4x3H2vGWXFC8N+oBRqXRAsLX7FfIw50tulEjQ2rgwwfe+Yq4KHv2I+luPtkcn+ivWLTPhm+ofv140KOU66hWTa4MJwGTxThUyb06g9sdbL4jIIu1Kos0XAXDSdDvXybMHTpQsyKBYIN9Levi/+lk0PWvUzOf/e2BRw6Zk3aLfgdZaCZEh1JJ1glFrgWkqROdOFYdWbde6pXvhyw/p5iu99a5utuuA/wzQ+AtTcP7ndZ2LrnJPv3OoZTOYx7aiPHcXKaQJMWdLZZGE7KvQaOBb54V0gTSFgdTnR+lwMGORIGTFDJJ1Ka5OpNgGs3Dx/Pi3q2rVwgVudnUWxHqZP2ukLwSB1OXRj/Ubzm125un8gGGqMjmydK5LjU0Gz3VSpnsRCseDrnSCmkDsCTlwE37SFU8V+8OVlInQsWvuLOrqg11LSZEpPLnFRxleEUM8OVhDr4zDwH2O964OBb/X3DNxKfn/w7fL7JWOfFsMChhFGAus4OJzr4LHrDEL7qynCielQ6h5PStmgmSRXyudC2n9eIYy7wJg9xV5paPIetbM/zHwl+v/R94H8a1smhllTFNqdSkpC6wKBv6bM+1dTReoMX9eFjX3tNrKhJxGU42SCNVbm6RY1XmdlTOql3+i6w/w1u1823httpiAauYTjpxiHqZE2RolYIOZxsouFeu6Vjww076o8NnZsTDl0JVbvHNA4+fpEQv1YRl+FE2ce8WH3hcB1T3zVMmB4XZ8L5n9+T++tC4BWsu7O5TFucICbp5UBO/mwZ+Ww482V/20U0/PR5QT1IFS4yC9IW0Y3ZcXTCKsVwUqG2z+u3D48d8t6ZrG//2J4ftb/UduUS6i3t7UqE1NF3xDLAfjf3ANEhAAAgAElEQVQAA8YKp8k9p4QjXTJZYJuzgHPfAfqvbb+2ztEYlYnPBbwAzPstcMv+XrlZdMY16/VIPYia43asBn4xI7iwqkZa0OzlhXZ3hpNcfKW/xSbZoobUbX4MsK7HGk3S36qLdXccIT5N9axYsC/sqyL4UZps8lqqjZ46nLowdANeoV1MGK+dHtZSoiLfusaoS01ZSltpYjgZHFJ0xUHHcAqIjGu8paX7KZ34R/P8fdVwLDSqcDh9RrRTLDcleIDhtNRtBUsHdfBZy/OiD5kIjN5SrKDJifBfzwb+/fvg8cZ3yc0ddaM6nOhq3hOX6A1o1zDB1Usj7hUnU5jG4SS1Cmh7lKs6cZ2PTJlU9VW0fXRGZ99RwCTL6rUtE08S7Z6h6/nbNqd3A6VvLYEbGE69+geNzXKzElGRWZWOT/9/0guxSBKG29TqEFKnajhl9GPF/AfjJxdIkaJcyAkp1bkA9CLNOoZTFGT/lskCLY4OJ5XpQfX+dMcD0QwSamPwQvUnDbqJjytrk9rENskBG+j4WGjTh4/YJrN7XA4c+Ltk95bo6y0gjJia7PyBY/3tOJp+W0YwUlTMudkXSy85azQao3EYTiENIheHk0P4lI6Fr75HaQewrBvDibZn1R4xyQdQyHcTR3/XBGoDZLLA1DnAuJnAykXAv28F/m9f5QQmbOXeg90X7zcm4Z2VcDgVCz5TEwCWfQLcd3ry6wUcThF1bvGbwKLXgAe+4e9T+9YFhLlZaDe3+weVSBNdO7ItMKghdYyJeZP6nQ66+dEyS1IwIGzffviCHyKtg/quo0LqpGOumpk8y0TjlqxRoRtIOtuAxy4GPns7HD9LRSdlZ3rTXhrqMZmwlyq7ieFkEEGmDTOk4cQVh5PGgCntU6675ks/9IaW8zsNlpms0jCF1JXb6ReLCDzHdbZLdh11UKbvdO5DYgWNToTvOTl4/LCN9Nfl3MJwMjkcGojhtGaZG8Op0ClWQ9SBgF5L/W71UmCFSQNNA9n50/LIPkQN9QDiP0a5KiuNvzEzgt/rjE7TpECXjEBFsaM8xxDtH3+nrkg3oMOpWNCzupr7Bp2s5YrE0pAIlY6v05pwzZYUOEcXUqc6nJSJJ8uY64NRIDlFiipBGtUlnQvvU+eALYmGx5h4S1YTywCtg/396vVtIW/9daEyMRlOlGVTLFbf4aQLL2pxlDugNrFJFzIKdHzsbNe/s0qE69gwaTfg6L8C04+zH3fUX4BNDrcfE2cBYrdLge8YEvnoMGAMsO91YluGGMq6Hli4rrKGk4tej8rSAPxySWeUzN6dyfhzGNvzCywEx1kA8+wLaTeXo1tUur+i5wmIeaBE6B7UxnE09vYluqCVYjhR0BC0cq8XxXAq6eqR/kx1kLSv9H8nDbVVIbUuJVoGAsMcQ26f/VnQyVZy2Ob9+5qw6A3g0tFBx5gLvngvXAYb1L40kuHkzQWiFhXriNThFBeqhhNgd/TQibs87r2ngGevkSeEryc7e1NFKRg0nGjnphMNp/fSxV/LAURlRSx6w9/WZW4LXKOjsTPPxQFt4L1J+t24GeUAEVc77zfCsHr/aQTexYCEWVbUwWfsNuFjTAP3wb8HDr4FOMDLSjF8sv+dFCldb4/weaYBvt5edWpctS0zaDgpdf6Zq4DbDw/TiQPHKW3sAUWQLwqmkDp1n+wnXDMdSkj2S0n3zSHbDB3Idvquv11iTlrK8NrdwFVTYzqdyLFPXyl+4yt/CvelKxcD950R47o1gCmkToWunU2bKz6dhDSJ8enicDKl3d75++Zb6ELqIrMTMUt9qLOTOUXPQ2c7AOaPQ3LyqNNBXLVE1O95N/r7eg8LHzeAMFOOfRDY7TJxXcpYCYVZkbov+9wdzhd9q64PV5tKFMOJOrt4mQ4nlzFFXWDa9zr3yTxlQiWdEAcm6e3+Qsmk3YP7qwnGgHHbRrO115kJTDJkQJOIw1pnLGxTHkzZ6Ep5Mjlg4s7ASc/47BeqVySZXnGYffTYfG/HLHUJQuoA3zbrPVR8yoULOs5aGU40pM6hjqrvU167EoluAiF1XlkoczsWG94BOgdeXMTpS1yclnFC6mSfQu1U2tcBwqaVDn6bwyl07Zxfp6Lw0AXB/0tZyImjS0K1kT543u0e6rk37BT8zvVZSUS9tw7CcIoil9QJqcMpDgqd+oxrhXaUJlVqJaIhdraQOjopk/TmKNFwdTIsGVQLXgmG8slrRYbUFZTra8rt4lgIMRdiorMt7A2uB+jzX5sIBCdxON1xBPCXrwEXadKZJw3Hoe/l+MeCmhOla2sG7p2/L4QLWwYCk/cHznkbOPYBcoAXUqdLvd6oIXXUwdS23MBwUtrLsk/Ep8pYom2jZAh7v0/GY/fTxN/r9snnRfWJpIFO31+7wlRyhXqeOjir4VlAsP5uRCjfJUd2RBm+/AD45EX7MYDItnlh/2CGPgD456+BO+fqz3nx5ujr1hLFQpimP/ua8HFqGz7rVZ/p4GIw0XalOkt179DEcNroq+Z7OIXUrQl//2KZoSopUlQKnWu8rGheX56xMJz+9Vu/jwcEi1DnvJ12jPc5Fxg8AdjKC82gocVqe6OLbXJSkc0Dw9YXWT9v2R/481liYvOXs4GlH4R/hw3UYWFzOLk4k565MvqYNkVnJE4yl0BIXUKGEw3xKbT5Y9H47YFZPxDbg9dNdu1qYOj6wf+lfoxEEq1DCp0jRfbdko0xYjJ81k4LMHwKsN91QsuqZVA8Bx1dJM63OGo4uYTUaRwk0t7KZMRzk200kwX2vkaERo2babmvhR3jgmwFHU4ZRcMJAL76i+Ax/zRoLCYqu/I8kzAK4yxqPnlZ9DFxQupKDCdSd0ZtEjymjTicOtvctcgyWb0m2hOX+YlYTJA2uey//nWT/91jPwweq7uWKVvqI9/zt1cpEUF0nn3uO+Fz1frxyxnhYyik30BlpTeQw6lMMZrkYIwNAnA7gHEA3gNwIOf8C+WYTQD8EkA/AAUAF3POFdXuGoJmr6LobPMNILXB0Y7c1hhppSiFyZgYTgYNJ8lw+tW24XNU0XDdqrv8Xh2olr7vb7t0kp+86NNkXcG577S4c65gnVywuDIefRtWfyE6G11IDH1G/UjmkqS0cQBaRpuJrRAFuTKUbfb1m1TonFnq/UK6Px0itEY1ogDL+6+zw+n2I/ztNY4MJ/lbZDt66wHg5duBN/8aPldO+uWzU9vIvtcbsoVpnkuJ4URD97yyxV0RkxOoosHhpE4kgGD9VTUf3nnCzdlryyQk8d4z4lPValKd4Y0MXggb/+tojGF1QjpgdDCkJ+T4ZcCoTX3HHXXYhpyG8h2T+mua2Nl0V/K9ERlSp+pacK7XpAHq72RO0fNQaBdtSdZbW0gdACwhOmOZnMjQq2LLk0SfqGqABETDlevTflNOvFlWOGreewr47C3774gz2S12mFmSbcuiQ990CUNUqM4D13A6IGhPlKtvCYj+shR2lRcOwBFTg1lB641B6/jbxzwQZMNVAuM0NnzrEKENRMcHqTM2Ygqw1xX+/mw+XkjdHw7xt/MtlWM46RY8S6zsorAx5UScZYWQ9u6XCSa1CfT3J5lMl8twKnSKTHtbnxpku8iFqbWmBY//6zn668QZPgeMEQuaqmOjqbfQgY2DOIualHloAu2bosIUSzY3OUft29pX+ILqhQ53m5hl9HOzJ34kFnwPMdgxgF8n5HjyyIX+d28/COxM/l+lOJyGTBILtzrn3Fv3h/dJ0LqrIwuocy2dlMeIqcACL1mBHNtYJvhMP3tbPMekkTQVRD0ZTt8E8CjnfCKAR73/VawCcCTnfCMAuwG4ijEWYySsMGTaQRWFDvgMJ9XhREShtY1Ro5uSmOFkaey8GDxe1+mYQuootnQU+L4xgnKsgk7gZYiTSUeokrhsHHDzXvrvaEfXTDznUbTxu08WzI47j3crQxyBSR1sHYluwI9ahZROijgOp3pOPuc/IoQIJTrXuBkTdPD79GXgtoOA1+7St9P/3Aa8+H9mh1O+RS9YqXsuOoaTxE17xgvbkwxKU9vVOZzo6jytH4VOd3aiy/s21RWXldcl/2sMEXGp4XQIWeegRs2WJwH73xickA6eGDxOZYxyDoAH045bGU7S4eRgeOV7AbOv1n/X1FuTpc6B4WRE6nBKUWN0rlEcTt5YbMosRp3nJmdIvgWYcVpYIoC2FdWhTO2nKz0tRJZx11aLYpDQCUPbCnM7dJls6nRmohCL4UQWtVwZTjaWRWeb32fK603YIZluXbVAf+fYrYF+oyp37RFT9CGiMuMwHQeGrQ8ccz+w2yXBYzP55OFcuV6GpCsKXJgyNluZF0Q9kw6nACvMMrbQtqHTqNz8GOAQkvl63+uBjQ8BRmws/i9Xw+mjFwR78tppwAcko1op4YCljQUknGJMv896BTj2fvGMtv2aH0rZnCDDtVOIvweXfiBOSJ18ALQMobko99t6oS1eSJ2p/9GxxCnkHExXX9U5vfobbQxUV3KCzp52YUlSR1U70XCiz/Tm2cBVk9EIqKfDaR8AMn7iZgChWADO+duc8/ne9icAFgFwDNKsAky0vAJlOCmVsW2Zn1FCt+KgE+otMZxMouEmDSdLY1cbhZbhZAipo9j2LPN3FCbF/v2JnsKmRHhRTqpohjA141+18NE/9fuX/NffDjicSCdyhGYlRqb7feUOt/uX63CyDc46hlOUw0y+i67CcLp1/+D/xUI4hAEIDwqlePJiUKfMhLfuJw4npY2YBjrd89Kl66Z4/hf6/TrINkJD6mimO52eWoDhRLbjZLVxed+B3041TyIM1XefAn62WTirIgDcdaJw5tYKkuG03m5AX4/lSH/X7pcBUw4IMjGP9hhy8tnqMoaq16HGRbEzyLK7+wSxCCENr6kHm8ub6wWM2Vr/XVNvTUhdhIZT3BDPFA0HxtggxtjDjLH53meoY2eMbcIYe44x9hpj7GXG2EHku5sYY+8yxv7t/W2inl8zDJ8sxJ1VhpNpDA0wEMpg36jODtmmV37m98GZrPtYHrUgQttd23JzO3SxkWgfz4vATAPjgiIWwymBaLitX6GZqcpik1cZX58vHAEUe14hHBzlwMQe3vtnwN7XCmYsxdgZ4YXFbC4ew4nKJzS1+pNXG1zYRbY2V+wU9aw0HpIx0OaMCYhUa37j7KuA9Yj219BJwL6/Ijo93rN6+LvBkFtXmOZlsUPkEtjMjAm2zTAvpDOJEzbOmO6iRUafR1Sd02mN6uaizUk0nLJ+fZu0m7mMOsh5kq6/iXKiqXI1FEmzdgJu9ak/IRu0GxhODYR6OpyGc84/BQDvU6Pm6IMxtgWAJgD/M3x/AmNsHmNs3uLFBiZSuTAxnOgAoTa4jjWE4aRUXMpGoBVWMpxMXtlCO/C38wR1O1AOG8OpEC0kJlcsqpkNhFKF6WAkfytdkYxKT19NvHZPUE+GxgYHVj4dVhiiOrtyHU42RwF9xrIeRq6KeOXVOZx2u1R/Sr1FwymKnXphv1LIaCdwzWY+3bVYcGTTcd+w66P4vY2Gsc6okELi9L0lZPPIFW4aUkfrqm4FPGsIqYuj+eDCcKJOlIBDJWIwXPS6+Px4Xvi7l/8Q3ldN8GL8ui1DVE2ORfn7MwaHHAD84dDg/8s/9Q2vEVPM9842WZgcreH7qH3TC8pkyTapSEPqugoqwSY/l3O+iffnEKNVJWxxvNB5kfVS9semUNKXPWbiiU8F+6AzXop3X7VNyfsHEqpkvbBVB5gYTsWiGLsCDKdlFoaTg8NJLTtNFGFCHIYTffauk1nbGFBo923jpJpQtUCfYSLUiWL6XGDjg/THu8LEvGnqDWx2hOPYm4+3gLRikb+d7+0vetsQ9a6Pud9e1mJncPyh46H1POqsSMDiok6AKzbwt8tlVMfV7Spn/JSh76ZQYht0bc9k47g4LuIwnErSEd5nZxvw5l/Cx5U0nNrDGqAmMOJw6qO4E1wdTrr+JlTHNDZU3xH669J5QdwFDxe7kya8kCF1mWzDLhRWdZbIGHuEMfaq5i+WqjRjbCSA/wNwDOf6kZdzfj3nfBrnfNrQoVUiQa27s36/TTS80E7ogcp3v9zaP4/+LLm6YHJwLX4TeOG68P6Vi4H3n9OfI8M4Sv9rHmOpklYxlCXQAMm2nJTR2O24scmVhIyLlWjWiNEBbqs8UXROm+6KDZItZhsU6KAmX6trBhVVgG/irsDEWfpji53AlZPDGd/qgWKHMJhU0XM56KxaAnz+P+CLd739xeh3JM+Xg8ZRyu80rWTojAq5q9AuBtTP5oePccG/f+/reMlBsdgZ1NTQ9SF04KNst1iO5pgMJ3rPqMFfOs4bIqSuGM6I5WooGkPqyIru6S8CZ78ZbVywrP+ObYYLY3qxf8ATDY8IqVsy3/59iq6Irscmj4TXN8j+K8ox0XtI0N7oPxqYcxOw36/dbkcnHb0GCIcR58FxI5NxXzxabNB4+vvlwG92Ddof7SvMY7zJRqTQ9S2H3yUy8knMOD34vU7T0gT6m13HENuEqGN1OKSuO+HUfwInWibR47cP/i8FyuM4NOJoOBUVuY2m3npxfYm/Xy5Yxm0Wm6nf2oJ5Zb1vIZh8hDmG1MURqY6Dcu2N2GGVZTicph0LrLNdWHfOBdq5n2Gcd7GLv/zQ3450OCkMp+eu1R9Hs9Q9c1V0GQBhF0nbqHVI8LsoO0b2dy4hdaEM8EXxPlTnMxDsv2RIbCVBr1kKqWM9k+HEOd+Zcz5Z83cvgIWeI0k6lBbprsEY6wfgrwAu4JzHyEdYBZhoxjSkLpThrcNnlHS2Bzu1z962h9SZ8OEL+v23HgD8djf9dy6i4bWopHRiTidOT14GfPJSsHOpp8NJndQZqasRg9Tjl0QLqCdlOElDxGWVZ9RmKJXV1eEUcrJxswG4aokYeP76dbdrVxPFTjFQqeLo7SuAG3fxGTQSvGg3nvwDxXWzzeHBxcRw0jonJMOpHfjr2UILwCUrjIp7TiZFI6Lj9B19olnJp9/TVcWkaZRNCDg7Y6Rpffg78kD38lQLvOBP2A67E9juPD+0LgqyD1GfVUlkOCOyYvUbGe1wKnb614miaev0PwCxch3lcArd1zYmpAynLoJKsMkv9kLtrmSMWXKW1whqSB0gQplMEzDK/GMZsb3RvsDUA93uV1TY6P99BHj6iuDEnGXMWlIq3vwL8BFhcK5eKthKVBOG4vN39fsXvqbfT6FzUK+7EzBmK///pIteQHCcdR1DbP1Kx6quEVKXFEMnASM3Nn+/++XB/w+5DTj8Tne7DRDv3PldeMett6cI2WtqtTucXvCyrpmSKAFujsJiIRh+mHEMqaO/K6lOlQ68CNx3RvKQ/Qk7RR9DbZpyGE59hopFz96D458bZxEpai762j3Ar3fw/49yAJbsVK/9m+xuE0nDhkzGrzchKRFXhpPO4aSUQafJmckCG+2nKRPpeweNt5eBZYPZ0F0wZKK/bRINbyDUMw7mPgBHedtHAbhXPYAx1gTgbgC/45z/sYZliwcaUvfoD4LfFdpEZWZZjypsaJA60XATXvq/+GVU40x1K0y1oOEF9GNIY3z5duD67YPHqhmTaglazhOeCA8O+90AnPxcdMN+8lJzlorSvRLG+UpHVdSge87bQldG1jFnhpNyHOdmA7BkLDSAkwAQ7Ux1Er73NPDhP4hDwwMv6MW1VXAurqsblIzvUMdwIiF1rnThKBQLwkj84v2g4abLMmJ6h1HGAg2xdHI4keGFhgm8bcncQdEI7BopGg4AQ9YFdjzf3VCURrfqcC6F1Dka2EAwc1PS/iKbQ2SWOhWN8A5SRKLKbPJvAVgfwHQAgwB8w3Bu9WUNJLjCcAJEKJPJqKcOpxFT4k/2Npjtb7d5YWwv3KA4nLLxMs5SJ9JlY4FLx4RTZ0uoOoWASE5AdSZNoP3FsA2D303YCRiyXjxGk4qADqCjA0DamrtcFP6ufSUJqatyluJGhJqZuXWQObrChDgMJ/kuRk8XIXtNfeyOBtl2bO+aakqd+R+RyUvF1DnA0PXIdel4aGifnJcfUmcED8po2I7TQcdwCZ1KHU4VmH4nGZ/f+pv7sTbH45ovgT8eFdwX5SCSoXRRc818i3g+sWQesvCZr4qNG8Vek9ISusU8tY6piXnkokUUAzFKt++7S4C5D5EdEWPUvtcHf6f0Q6ii4Q2EejqcLgUwizE2H8As738wxqYxxjwXOg4EsB2AoxtCsNIEGlKn+y7bJP4K7Zq46gQMpyRwEQ2vCcMpRkxrRQcTDWydEO08VJFGQAyWwzd06/Dff0a//9QXgBlnhOONXSG98lGGRd/hYtWKx2Q49VZoqSrDiYq+lzK+1djhdPvh+v2da8LGf8lQUkWcuWPGEslw0jhsTKwT9dix2wDr7SG2C+3mQeqtBxzKQ4tWEBnmFr4S3a5MkwvaN/XWRNNQg9BFH6Jcg6oRQuqkaLgLvvEe8I33/f/le7h5dvA4nUiqqgmm4rO3gU//E7wuxeZHByfbZ/5HaGiEoDzTqD4/dTh1CVSTTc45/5QLtAH4LQDtMmxNZA1KN5MMJzmxZbIQ+uOzTX5fa2OXmDB43fC+XHNwQpaJ6XDSjSOrvnA/P9cLeP1e4E3DBJJz4Okrg2F3ap9wxF3AaS+Ux3CizoFYYVzQO5TaVvjjcXcMqasF5HzDBdLOluNRvtUeSiXHdZt9Tt/rwHH+4p9c7Jq0G7DHT4PtxWUBhnNEioYnhetYZ+pjdJqnNkw/Pp5WmrYs5Z0eCZuO7mpNX+Ws4RRhd2Tzog65ZJuWyOTIuKD0K1HvVjL9df1gsQAsetNnY6m/cYfzxaessyM39jMV0/t2tgHNlrkXY/EWQlgmuHgsoyRShlMYnPMlnPOdOOcTvc/Pvf3zOOfHedu3cM7zRKyyvoKVJtCQOoplnwivY046nDrCnbTMkEYrSBTDKVEZ24MsjjgMp5MMDhMKF/FsIDhZiqJLV9vhZGuUziwCxx5/na8Ae/7U//+0eWJ1Z5cfJqfWujKcJGZfLWLrXRxO2aawIOHa032jYKfvAvv8nGSDkL8h4Qh464HAjyfEP8+kGfXZ2+bwBp2Is6tzQzqQAWDuI/5+U11WJyDH/A1oGeRfy2RY3eYgPNp/jCjL4IniN8i+JKruqsyvnb7nlYfUI92KZBzhb6ACzgrLO6mVM4oynKLQMjAYdm16D7osdbOv9re/9VE4y8odRwB/OMS7rqauzb46KIQ8cFwwg4kJUe/IatCTd/D5O9H3SlEvlMUmJ84qBqH/9GpVS+uCkmh4U/B/U33O5v32qMvcGoXemkWhfKsfxgB4DKcYjhuds4WKgA9cB9jlYv25+9/oL3LIfkHFwleBRy4EXr9H/D9uplkWohyGE0VchpNu/Gtf4TvJQote3RinvxhfzN6E1V+IpEIfaRJvqCgxbr361NRb6MG8fIfeqSDfmSmbHgBsc2bwf2lbSF3Q3kNE/aX1zkXDiReDtkdrgpAyQM+EdLUpdH3MsA3j2/HD1ge+SRaotjsv3vmmslQSK7VrEwK6umGrEwDRcNKUm/aHkpEax3GSyeqZr+KGEed6NpVOOqVzNfCLLYHbDwMWvh50OO19re+sku1ivT18baUPiKZyZxvQf23gyPucfk4kGAv+TumcYz1UNLzHoNABbYW+YgPCcMoHs2+ooA3wI4NGUzl49Pu+4QEYGE6GzovSXk1wZc3QTjmS4VTlRkONo+ULle8cV05olgAb2pYHjSsae5sUkrbsauRNnQOc/Zp5An3YnT6bq3Vw8F21DAK2O1dsX/iln1p5zk3BMiR1BMx/EFj1WbJzTTBlDFJXKLgimmmCGlI3err/nWklVje5kROFQkd5LKBsHthgb/E+4zhnVeewfOfLP/X36eoIba8uK4vltl9bXaoV84YX3RlOKgKhJpo0wPQZ09XR5r7CQW2CqwOMHrfVqfpjdM8xkxeaIYB9xZKeew1hgb77VPjYFPVEuWzyWxljrwB4BcAQAJo4qBpD9g1UXBYw2yE0ZXaSMK2mVsFGBvz+YNWSsIZTHGdWVEak1Z+bw3SmHBB0PD9+SfgYVR/lkNvMZSmH4UThajfpnO4S7SuBZd5Y5KqX1x0weEK0zosrFr8pPp+52n4cEB6PWgeJRfS7jgfuOlHDMvHsQpPu5C4XifpJIY+V45ysuwGGk0OWOl4UmaxZRshabHG86VfZoXPu0PHMZnvobK1TDMma4mDH8+OfU207aEVMh1NshhN5zheQe8kFAtf+ZPbVYj5UYjipWUUt73P7bwtHEGDWvwSAd54Qib5oVr3NjvC3S8y/ArCPRgz9/adFu9KxZZOAMSWkLmU4dT+MmBret/QD8wsudAjad65ZVDZTA1I7Dp3htNUp8cpqg64BmjovF7aPaeVMYuNDhUgnRZT4bdQkesGrZgF1F1Av8E8Jo4PzsBaXCQPHBplLJmRybjpBcZBvBcZu6zt9ysXEnYEJO4ptlR48fCP9RDffIlZiSwNNA4RBSYQYTp4Rs/T94G5V38wIS0idieGkdTh5E55CO4wreVF49+8i014m661oKOGyZ74MjNlaf666iiPf6x1k8NT9nkBIndc2Cx3Ag+cDqzQCouUyFK1GX40GVF5M7hSkZZThcIB5df/sN8UqNwCstZn5uq5hJvR97fYj797KM9U941GbCs2QUZva32HHGuCZa8KLKDfv5Va+FDVBuWxyzvmOnPMpXoje4ZxzlwwL1YXs72RiC2lsb3wwsNeV+nOSMJw22s+fFM/6gVhsOft1YMuTgRULgOULyPWzQe2aJKA2yZov7Ywp2g88eSnwnz8Ev6fSDL2H+slrdDAyTRxx+otigce0oKpC53SX+PTfwIPfEttxw5RSBOESksSVd7HWNP+7+Q8CFw0DlpD8AczicDrj38DWp4X3yxBJ+T512SWdNJyKwBv3iTNbH2gAACAASURBVM+pc+Jl7qPQjqFkLLTZF2XZHprxNilLy3Q9HUy2YBTalvnZz1QkcTjJZ1diOiki6lPmiO0Sw8mxP9n8aG/Du55qW9kcc9t/w69vrpE6Osj6y4vmvnbJf5PX2fAN9QynD58Hrmk85SEgdTjFx3GPAl9Tslw9frGgr+pQaPPiUfNB4VcVd84N/q8b9Gf9MLxv+JToMusQJ6TOhSoaFb6x03fDjpEoR9YHz9mFw3+1DXDjrOiymWASg7N59XWgRtHbD+qP4UXf4TR8crzrm8AYcMxfgfV2r8z1AL8DUw1n26Q7k2usVPYSIWPdUDZX+innCITUUZgGkYzmuVGHkzUbi2WQlLpA7SvFPVQhzYFjzSsp6iqOluWiaZuBjHZeP/b6vSK17UPfCR9fdkhsAzCcigX9O3RBJwmNpga7aXW/30ixyg2IDFKn/lN/XddwXxfDRlf3+430y2czIJ+5Sgjw/+u3buVJkaJSKDmcvL5MTn4zWZGiWgdpx8RxCs35LXD+p8Hz+44AxmwptqkjmWX01zYJPktbcClJK672azbnmNoPPPDN4P/U2RDF6qIMpyRJCQZPEM8ldkidpo+imlPlZPLqyZDv0yX7rarh1G9U+JifbebbGLLeqs6sk58DBq2jf2cy1EpqFmkX7ajDyTB2VSpUSFfHqe1qq8eurBtXnPh3n1EcFy520KAJKCujrElTWLeAHpmlzhJSR0GjgqJAmVGl68ZMjiJhzEbuAFnvo+6l2n3HPqQ/TsLUH5sYTg2M1OEUF7kmO+1ORaRouAG6TlvHCPpKRNzvYYaOrNKi4V/9hf37OKwQiTfuA+41hIJQqFmgXKH+XrkK88V78a5DB0fTubzo/96kNOBaoPSevPp36B3evxEOp0ZkOKlaaMs+0R/nHFJX9BiLOtHwGOKm8thip90pYDJ6qJCjDPmihpis16bJiqrNJcO3hm7g79MNcgGGk9J2OjTZTMpmOFkG7lrFqMcRDVdBneXUcLKt7lMM1ehoAe6pwp0cTjotBW/SLDOrmrBmmfhsW+ZWnhQpKgVZb+UEwYXJIfujcllIgD9xXkQWHzvXEBFzDxcs9sfQUHk8W/AqsgBF+1UqdK6DOuaoYzR1eEeNT/kyHU7yPFf71tQHJu1rUyjw7Blbu1jzpXAaqBpOprqy8FWRWXG5Z0c9pISADd8wfI6EynDS1esAw8lgb77zpPkecaBzwAZY4jaHU4W1ZfuvHT8LoSu2Pg049R/Jzh24jvg02QA655JkJpogn7HpmrK+NvcT9TEqU/mgCcH+XJrxofrjOC+JMzaMmxn8v5Q4KYYu5v43+osXJqytzdHhiYZTmYsYGf3qhNThlARxQywCouFxRNAcBv4okUpT2JoLw2mPnwDbfi26DICI+5bhWNpyaDp4l8b9rsMAc+VG0cfoEGI4eQ2Watkcflf0deh7klTKEK2YA9ucIeLbNzFkVmsEyMlsyeHpfdoMX+pwaiSGU6E9KHj/oWHg5UV3P1nnGgPDKY7DyTGkzuRUoQy8Yqd4/vMfCu4DzO1LdTgxBqy/F7D4DVJGHcNJo+EkjdPX7g5n1qumwympc3zZJ8CrBif8ikVB0V55n0pQoGkWRNvqvooTNP2fa3nkOGW7j9bhJPuAjD1ERlZdGxMvRYpqQNZbqdPnxOTw2p3qFEoCneTB8gXhlPY5i9NIywYgA9Epz4fH00Pv8Ff0Q2OOMpbQUJgohhMNAUnqcMrm3UPqaKbOPX7i7+87Itm9UwQh63qnJQHRpWNEohY5Tst6arJlOttFMpYkkAwnKb2hsxNpOzG1mQe/nez+KiJD6iz1uJzMeBvuk/xcHdadFQyB1CGbN89ZTTqnh/0JmHm22Db9XtMzskohKLbCM1cF/5f9eK/+XuSEoV9vHSzCeI9/TLm3gT3uOi9xZVRO3AU4+i/BfSWHU4RtKtvAXleFtc50MD3n5n7B8qYMp26KuKswkh7Y2Rajs2L6FLubKs6KKD0CltF3Ni4Mp/E7ADtfaL/+fjeIzgnws2/poJv8qhNfHXRxwpWC2pDloEhXhWzivRJ0cHzLSzu85YnKvQrCOTjj9GjtqnqiZJhKeqjD5DibI6ybRnI4dbhNzp0nzFywpnTZ71wYTnJwD4TUWQY444CusJnU3xjlcNIxNNUJlO59B7LUSSOV/O7nFZZj2aLhVWA43bI/8Kdjg2K/a74UK7c/mQj8RglPLYfhNPVAYIsTxDbN3iJ/l0vd1GkBuBpPTX3E6tjBv/f3qffUPWNOdBBcGAu1Cm9MkaIEKRru9cUuxrbsM1SnUBLQ/lJqsBTa3fShdr9cfEY55AdPCNtu2Sa/Xw/1+0pbpSEvJnavBP09SR3sSRlOWxzva6P2IdkAx26brBwp/LoeNQYX2sh4FMFw4gUxTiaBXHAp2fyaMSzAcDLUwVbLHCMOtCF1ig6mCS4LaeO3D7fdGWdUVv4CEH3Z3teYv5e/w2RnmjI5j53h92VxHU62OW6UrSCjEpp6ewwng8O0WBD9Y0g7WNouakidWt8cHEu7XWr+ziarEWWfNfUWWoDTjokuA6B/zuNmijpG4cLyrTNSh1MSxB2Qs83ir9AOPPszt3MY099nn58DZxLdgCiGk0n0Vp2wFTrDOlJUu6RXf6BVk6J26hxgoqej5NpA971OxK2aOjuKStNXA9c2hNTRVSGXd00Hxze8lJdq1pdGYv7YkFUYTi6T447VQkAVaCh/k3DouIYVOWap61ipXxVych54xpZ8xlFZ6kx1n+4vdoZ/Y8nhZAqp05TfJcsky/qiikWF4QQE9UzUciaBNUtdwoq27GPxSQ2ZX+/oiywuei14fLFYnjDpTt8T25ThVDSswmmvoUudvjS8T4dMFjjuYWC93cg+xdDWGda0zbvQtHXOv6gJbooUlYC0f2KF1MUQDTeB9pczzgB2/I63mBTBnppzk98e7z4xLPStYrQSTkH7DHXypmalow6n9giddym+DpQZUhdXw0lmdvLO6zPcP+bgW5OVI0XYiWRDKZ16xn7O+88AD3wjWXnk+5UhdWpdBYLzDdOYa8raGBc6B4yzhpNDHT/yXuDkZ+OXKwlsNu5mR9rPNWWnzOSI9IPBgSQdS6oguY1VF1gs1Tif5MJBvsUjaRgWEkyOq6LSr/gnBP+12V4TdhKfwzYA1tpcf4y2jbBgGSqFsTPC+zY9IlyHU4ZTN0XckLpszhcNf+dx15uYO/6B4/ztKOOpWDA4nJQGuOS/miKQjuzcd4Bz3rLfq89Q83e0cWx8sIhbrYThVw5cGE4uFEudqHBe+W1dhQWgsmKMHTjBqiXknzp5nHSroVGi3BK84Ph+PIaTzsnrElK30X7i01k03DBw0f286KdAVr83htRpWDMhNqWO8p7xnd0FhYYPCEfISlIXqikannRQl30OnYDp+r5SEQz9p/P9vHdAHTemLHU6xBGod4FaT7UMJ+kQYxEhMhYD64oNgE/+naiIKVI4QzooRm4cfayc4ESFl7mAOmiaegPbfV18RskEbLRvsA3efaL5WEC09cETg/9LqO1u8LrCrvvAC8Wj2mpRCy+9yO+Jo0dIIW1cF6gaTnKsoIuatqx6Kdzg4nBa9VnwWNP7X/pB8nJs74XCrT1dfK7WZLV10XCSDt2kTlEJ7UJLhUPqajW/MT2rc98x62pN8pze6jyldM2s30+ZFp1MDnwTKwlQWGSa5yidJrlm0TfQa1E9YpO9TkXDj7nffLxtXrfH5cDsa+zRLbo5gKuGU1z0XzusA6izAVOGUzdF3BCLTN4XDR8+WWSWo0aE8TxLpzp5f/EZNShLUWEVssN9+0Hgpr2CukUStCPL5iofCubaIbuwGZLEVRsZTjE9xbrnq/62TQ+Ld816QbJf5PN0mRzTVZK2ZcCHhuxa1cQ624X3dba7ZRjjRTcHBudCFyNuSN0ZLwHHPgjserF3rDfheeEG4JMXzee5OJyKnWHjra83CTO1L11InToJM2Wuk32ALqQOCK5uverpn819BDjyPn1ZbKhGSJ00WNs1IucStC/hZTCcAL8PTxpSp05gx2wNbFCGDkQopE7Tt1Kj7UuHSYbpXXw2P1bRUqSIjb4jgeMfFxOEKMi2VInMZ7kmkTV47enA1IPC9wDMixBJHTpAcBxWJ8WfvQX8bh/gN7sCj34/2P6ibC1a7qSOnkQMJ68/kn0uDZGpWPrwHgyXuia1vuTzNjlkXSQwTNj+GyKMaMxWQsd0l4vDx2QcHE6StTfrB8nLAhjmFBVkOAHR0SeVgqmd0NBh1T7e8iTvGNIvDFkveM3SwmhE6JxaX2wOJ2q76hxZs68WoWLDNhT9J52L0fnnZkcZbkDkACgzSH3ftvnM4AnA5kfZxwka+isxzlv0nrSr+bykUMubOpx6EOIaLJmc53BqE6sJfUc4pE5k/mC811W+TpLEvteLiVz/te3XiQqpe/xi4L2ngA9f0JS7zAGf0qN1cO2QVyyMPsaUutOGEMPJa7BRmRFU6J5TNu9rNQzbCNjqlPjlqwck+0UOJi4ZtdTm8JtdKl6sSOh0OZwZTkU3I+K9p0SGFp22ms05PGi8MLRKopzesVGTeScNJ80xUifAyHDShNSpzmSds4uuesnVqdDzJZXhU4/hstZmwND19WWxwSo+mZTh5NUTHaVfQhq1hQ5PaL6MCaocK/7+Y9/p5MIalFDf1SaHuTlRTXDScPL2uSRsMF1DfOFcrBQpYqG3x6ZmTPQvLuH5a20mPldp2BVJsM0ZwHGPBNlBdByggrZbnSocVOoxTiDtKJApVLPIJtvs01cC8x/098dxcrmEV+sQx+Gk2hXTjxOfg8Ynu3cKPUx1jY6tku0rj62mo48xEXo6YLTmOwfRcGlTlJvNUJs0qcJZ6urNcKLhvTO/HpRikbYhLSPtIxgj0g8WhlMmH65jtgV7+ow7Nddda3MRjphrDmo4bbRf8J3vcpH9+qE5egINJ8BvJ6o+cR9NcoORU4VTdd2d3K4dBZufQUsiKUPMvkZIHU5JkMThtOAV/6/3EIcVeqLhNHwjXydJIpsDRk+PnrSYsix9NE98LnlHfOrSmpfbqZ8WwXRxTUFJtQhMsHnVTQjpWHkNthIMJwAYtan4zPeqzKpqLSDZL2rWOVs9Ux0DlQhZiAvdanKhw60OFwvxGDPLF/jbmx4hPuO8X8bcQvCMGk4Wh1NTH2Dbc8S2zjEmj1GhlkeX6j6TJSEQXhlUZ4OuzKbEBZGwaTglpC2XGE4Wh5P87mkvg4pzGHQEJIMyTpY6daJYbihBnJA6V1RasyBFiigc96hIKR0HM88BtjsX2OTQ6pQJ8PvHfmuLCYjEbj8SDiogPsNpyhx/m/ajcWwel/FJZouj4YJxECekjmapA4AZp4nJWpqlrjLY4XzxaeqbqRNBjndR41E5IXUusDGcWgaKhVupwViuU0wrGk4ZTmWKhgNm+6tWoP1MJhOUYpHvn4bUqeN+lIZTsUMcIxfA5HzHtvhP7ewoXTmq4bTe7sQhmjMvus08B+g/OpwxPRRSF9MeVVmffSPIFADw9TIZ3rYFV1r/ZbRTF0DqcKoFMlnf+Ch2is5TNoDtDWk+aTpd20AQZUjwgv6YeZ6x1u45c3QhJkk69VOe97ejVspoB0hxxD3B/23hLxKVYDiVQupiUhNNz6looJw2MqQzoqiG1Fnqgjo4uzhTKg2dAbH/DW4Dy4s3x2O1Uc2f2dcA5zsw8FS41AkX0XA6GRm9FXDyM/5grArOSugcTrI8zV6bXfNl+BiW9euBHAxNDic6WDKWzOGqDrhUZDJpSJ1kONn6FOngdmFWxoH6zJL0r2Ub2irDKWKl1wY1sYCKu47X16MUKcrFwLFuKaUBlFaz8y3AjhfoGZ6Vghz7bOztuOPjducBA8Z65xocTlFi5S6Q9lqvhA6nTD4Bw0kZn6v5bnoSvnKeyDJteh/UXpZjYdTY8kaCsPg40GapYyJ87qxXxUJ96fsyF3DH7wBssHdwnyvDydWpWk7obByYHDe2ZyTt3ZzN4US0RnUodHrOH8/2lpkmbbY0temibINM1pd6yeTIfNhi04+YAnzt1XA2Q9WWjGtHqU54FxZoUse9C2hbOeA3+nvtcEH17p8QqcOpFsjk/PTYgPCWygYwYQf9OflWvyGX07maQupU6CZgSVgJwzZwP7a5L/DND8P71cwAHauBxW8Bq0l2JrUDScJwUgeVm2cD7zzh69BMckxhanLGyI66XFZCLVFiOCmDqs1BMmoT5dgyBlqTV3/pByKb2MrP9N+rdXXirsCw9d0HFhp+EIVeVGciYxZetMHlGRmFET1j/Yh7gqGacx8MOnEHjguKDe57nQht04UfypC6FovDKZMlwogGhtPPtwDe/FvYSDH1JXGYc3SlLSmrxkXDSYbbVTq0oJSqOkaWOhXlCJgDwb6osz0ew8kUPmlzUL10S6zipUhRcdRSC6jvCJGx7rA7zMfEHR8zGeIEIrYgdRpEOnocbMjBE8Snq92jIhtHw8nQB5ajE5QiCFuII7WXXR1O1YY2Sx0HtjlT2KV0rlRu9EUmIxiSG8wGtvCE+68gYf+2euy6IM2YsL9kuGi1MMwgDG5Dp4PDSdoKJg2nYoc4Rr4L2a/ZstRRu+3jf9nLSB3z2bx/n0TvXrElnR3b3nkqw8klXFIXwZNEy1QH1SegswupHl6DIHU4VQt0gk4F2ABReUuZpAwVN9/iN6xyBoLRW7k10Eo5nOJCZ3ypDpqOlWIi+1tiCMkBYfSW3jEJHE4fPB/e99hFwLzfiO1DI1IWS6irdDIV+pBJ4tMocNeAkDRg6TDYaF9g2ly7SON+1wf/L8vhZJi8PnutGKBe+aP+e/UdmAzaSuCrvyj/GkkZTu89A9x5vNjOt0Y7o6mA4cYHA6f+Q3+cHNxllqC8ZkDOZP3nLJ+vjuF0z8n+ZEjSrE2w9k2qw4k8j6QhdbI+SIPrb+eGj5Gsz0rXnRLDKUZIXaVB+9ZHvqd/jqaQI9PzsDr/ukgocYrui1q2M8ZExjqbFlGSBURd26M2TyWYQWttDpz7P2DqnOhjdcjk3NgfHWv8vlx9N6nDqXLI5MzhUDSzsKrhlATfLUMXTZc1V1ffqSZsJZxjuSbgoFuEZIkKq8PJsx3mPhx9j0m7RuvslotMFhgwxu1YqUU0aVdg8gHAbpf438VlOBU7vZA6RWzeynAitsKHBltUgtbHDLlPknev/ra47CM10U7OQX9Y18+Pt2S+s19M+ddBRLwB+1Jni5oxNlf5P8sY+17li9RNQFfnM7ngJLy5r98ATDpGlOHkkqVNh+2/LWJNXSZOupC0pJ36nlcA6+3pdqzO4aY6LCSrZdHr/j65yiDZJi5hdyoe1IQzJlH6p0bT4InAzLPFdr9RQpcgqQFXD0iq6Jbeqk+uGdjrCqD3YPM5zX2VjIZlhBCaBno5yD99pb/vvaf97dCkghv2VwBSsLYcJHU4vXIHsHKR2K7kiqRsc0MmiiQFqhMRICtMGaLhZMj2IjPfbH60/b5WhpNFH4oXgfefA27cVS8+GXW/Qrv4DS9ofqdkOFXa4SSfmSmcpBagdeajeeFnPOMMYH1D3622pZLTMdVwqhQYY3cyxvZkrBarPT0E9WZumDBiivuxpepA+ltqs808x56YwdXJRcOW4iKTjxau7WwHLh4OPPgt7xzV4ZSG1FUMjAnN2GWaDNSL3/K3pe1sspWk2L0N5bSxk54K67Hpuj+6r5Ldo65t2BZROtcI6YHRWwCnvyiyZNYbrs/jtHkia3K+BTjgxqAzLK6GU0EVDZeMZ8uzo/eQjs5RmwKH3Rk+ls4Ds44hdcb7cr/Mr/zJPWGVPE893lV/uGpQ6qyLszipH6GCiPPmdmKM/Y0xNpIxNhnA8wAS5k/tpsg2i1Wiva4Exm3j79c6nAr+dzrkWwibIKFBL893GQy0DKeEg8j0ucAhv3c7VtfZq8/ki/fDx0jHUMtA8ZmE4aSDXKGLky2FdoCFxk9NaUWuWTjJttMwP2ygdaUchpNpoJfvm+rqPPxdcv9MUKRxzNbe/iowLCoxgXFxNugcTlSrQ5bj2IeAOTeVV55SqBwHph0j0o2roJpyppA6QMyJZHuU78Q02NmeZSikrhDcvvdU4MPn44mZyvrQ2WbuM9qrFVKnsMIShdSVWZ9p35prDr6/bb8GbP8ty72V8sr6aTPOu0qyhMbBLwEcCmA+Y+xSxliC9I4pcMZLwOF3ie16MAmj8I33gBMcs0AC8CdzpE/caD9/u2Wgn8BCh71/Fqd0yZDNRYc6y4WjBa+IzxDDKXU4VQwyMdB9p4nP5QuAW+cIaQqqQ1kKqTPMRfqNql4ZAWDQOmE9Nt3YG3A4VbBN68bhKIaTdDgMnuBnvzTfIHHRnEF/w0nPACc9rT+u92Dz3KZYENnfpKRJKUudRTScyiyU9ncCbz8o/nT3kJD1bscLgIk7h4+ldSDfO7jgGRfSXn32GuDOucCCl+OdrzKaXB1WFOMN8jlJoFYpnd5oaMG2/guDzhxKzvmhjLGDALwCYBWAQzjnz1StZF0NfUcBc34r0p8DQsz3Es97nCHpxAHhHR+yHrBysTmTwegtgbcfENtJK4q8p5OGk0Z4rhKrCNOPj69xo05S/nWTv/3u34G/necfU3I4JRANb+4XzsYl6aPT5oaPN4GWNwlDqjsgk/VXQnSiqJyLUKtNDwfGbWu+jsm5+sV74X2UussyQjD7k38LTakB4/xyVRqVMHacsudpnDl0tUleY8yW5ZenNIJJZpjFEZzJmkPq5DVke5QDs1EXKGFI3d0n+oZQHAen/F2FtiBDjkI6oipl1O51FfCXs4iTLmZI3a4/0rMxk0DVRaDY7rxgevljHwR+Q0Iy9/818MRlwEJvsiifvzW8MXU4xQHn/BEAjzDG+gM4BMDDjLEPAfwawC2c88bPfdwIGDTer5/1YBJGQdotrqALAhJ7/EQwVT54VtiRptAXwMxarCRcQurUcSXEcGq8MJAuC1lnOgg7fP5DwE17+X044CfJMLWTejgBdWMjnY9U1K7TMZwsDqeONTHnNLVglni/4cSngBGTk12Cc2DG6eIPICF1JoZTRzCkTrbtYgH4/YFi+0JFC5TaCpJJbmL70zqQ70U0jRP053Je9uj3458r708Rl+F09pthIfNyEPUMzv0f8Nb9wX3FTl+rtU6IE1I3EcCZAO4E8B6AIxhjdc772EA46Bbf2QQERcYyuWCj6tUfOPgW4PA7zZVw5tf9BpZYIDfv318HnbeZohKd+p4/EV5zG6LSGy//xN++eTaw+A0/vE4KoyVhOK2zHdB7WHBfyWmS8LcPnpjsvK4OWsd0A0ixE/jPbcDv9gl/9+XH5DhDXf9Qo7fVqTicBo0HJu8nPqXxVK7TYN/rwvsq0S5cmB86o4fuq6YYvW5Ak4NsIKTO4GwoMZw8h5MaA2+7j4QtpG7By0SUP8H76GwHbjtI/13HauHYfvqK+NfVQZZP/p5SSJ1jubc+VWipVbIsLt+N3Dj4//p7AScTJ53sK23G+QPfAN59Kl4ZezgYY4MBHA3gOAAvAbgawGYAHERDUpRQzop4rUDHl5aBwN7X6o8rOZxIn5jN+c6AfK/6h3m4hNSp47sqqZBrEn3doRbR9RRuKC0oSO1A75M6mwA/QYgt2qLWqGlIXRKGU4JEMdWE/A1Jogu++itvQ83kJhlOFg2nTF4k6AGAtaf5+02gC8ofvSA+XTJs5lvLC6lrXxVewG3uZ2aClSBD6hRXh4uGE0WfYfH7ZzpHCE0XIuYPuebw4r1rQocqIs6b+zOA73DOTwTwFQDzAfyzKqXqirAZ8iwb9Cz2GSaMi3V3NjeeTIY4nBJWFNlhqJ3Q5P3FJ2U1ff5OmJlSKyr6lAOSDyBJGU4f/Qt48y/hRllaFY0zmSeN/6D/i1eO7oJASJ3m2XHF6KG4/zx/W+dwUldY5DGUTZYkC5oLNj648tcE3ESvde2eZgyp5CofU0I2dL9xne2877LkfepC6jjJguINzPkW4KxXwsfaHG+hkDrleUhDKI5DXj4/W+hrx2rguZ+7XzMK8lmGNJwSOAzLjcOPGqcoVKNavqtjPOatbJerv7Df87+PuJevh4MxdheApwC0ApjNOd+bc3475/x0ACn9Iw5KkgKNnCXWa1P9x4gwuw33NhymcTgBfh+Yb9FP3DY7Ejj4toqUNBLZvDmjlYRafh17Zs5NwWQXKZKhtNAhxwzN2JHJA8u8BT+Tva9jrFcbkSF19dRwamtch1MSRrEMoVN/cxThodgpjll/D+DbnwJruTicNHXQxUmWb/F/YxK7t2NVOHvehB3cdfTK1XBKJHROnpUqch5V/7PNfsbqTY8A9vxpedq6FUKcVrsF5/xRAOACPwXwVfklY2xWpQvXpWBdOVYYTn0oq8bSQYz00s1HUfFYBui3Vni/nPirFU12MG1KGB3VnQJqS0VPmnVKiobHdTi94K0s0mwdAHE4xegg5IA1dIPK0ia7EmhdUVljSz8gVFbNgEM7T11InfpupZFNGU6m91WVkLoKhAm51Hfds6CDeVUcwhaHk8xgxzJ2DSdw/x3RvkdnpFnfj6PDKY7GXanuWMJPOlZVdjWIqQwn79r1EDMOhHYrRoxaHlM9H7qe+JR95YpFEfds5Al/w+FazvmGnPNLOOcBtV/O+bQeb2fFQSkEowE1nCRkG5Nh0aaylhYEVIeT1wZzBobTpN3FhLAWyGSj+00Xh1OKCiHCTtnmTKHVuPRD8b+aFQwA9vm5SCRSa9QypE43PlkZTquTOZyqqWdo6h9cIOeJ6rlqRmIVn77s37epNdpBpfsu2wwMN4QA0vcdYDglcd4UwlEwLk7LcTPF54Sdgvtr7XAcvYWIBBrl6YVF1aVsHhi/vdAJ3PtnwPTjBHu0znD2KHDOl2n2zSf/XlaREnUV7HoJ6CWdYQAAIABJREFUcMQ9/v82ozqTCxr61FuazQG7X64/b9b3RepNXdpOiu99ARz15/B+OdlTyyYNEzWMrrWMDCWVgpwErb+X2/FJQ+ooa2bDr4b3J2U49VTQ56WGT/3xaOA5Q6gAEDQ6dYNVu8nhVAOGU7XgwlTRhtSReltNHQMbpT1DQup0DkTO/XdDB7komnzoOurkysRwcjSyHv0B8LEnpGpjOHWucUvv7QqVnWDTOqs2Rm3ib3cq6YtdDWKa6Q8QWoQ2pA4nZ3DOH4s4pGfZWeVA1tNGHQMo5Hhg6tM3PVx8Dp4Q3F9y7DfrHU61bHtJQupMGqYpyge3jNEbzAZm/QDoN9J/ZzJDMQB87VXgwN+JelcPh21kSF0Fy6RzHlgdTm3xdWmB6mYJMzEgXVDqI5TyyWs+8A3gH4q0xOqlwLKPguLbLhE5L94c/H+XH5odIQHRcDJnTtqfqwvXLnVo5++LTIQqGaMWWkiqPTblAP85RD0Dee6oTarr6IyJSo7EsX4VY2wQY+xhxth879OoosgY68cY+5gxZpm11hhbnyIoeRK2ypvJ2mmD04/T78/mhWfTBc2ahIGmkDrZwbYvD+5vhNWmo+4Tnwf+TjT0KORbxO95/1lg2SfRx0tQw2gfUq1KujBJOpT6p52sG2j9V43KqLT1dDBZqslIGGI4ee+OUmRNOgONurotn9Gk3aOPCeyrY0hdIEtdhGi4juEU2+FUYYbTUz/1tyMZThXM6KFqOCURO68U+q8thDxbB/tisXEhf498H19+GHF86nCqIBrHemx0xNVKqwvUZA0Wh9OFXwJ9RwT3l/rZvL4/qSVLPZsXfYJtYp0ynGoHdSGGvhcZGUBZrnLxFhD1bENPb7Meovu6e9J2XMk2rXMeWUXDEzKcqomxM8QnfYeuMDGTqG322MXB7yRZgWoZlewCi+0ktXclbGFetC/MtZD+PGF9VCN6XBxX2VzYyV9PlPrPrmkGVLIniTvb/iaARznnEwE86v1vwg8BxMkhW3vECakLfV+B16DL7mEKqSs5nBSGk85pVWvQTFguDV2u7L37JHBNVHpSgoAWDpkQFRMwnNTJek8EjSFXB+uovpGucv5Go92gOpwke4bex+S4MXn3d74wolBVhhw4dOlgJSI1nKoxkddkqRswxttHGAPWkDrEcDiVEVJX2p/AORSl4VTRkDqSvQUgIXUJHE6VWq3KNoUzdDqXwXuPusymOjRilrCuix48yMSEbGeNzHBSbYe4E+mS87pJ35/UcsHFJaSGLg7kejW4M7CLQ9Z/nV0qF+hkVtJci3nRrh4LBlEhdZVs0zoBaNv4X2hPpodTTabJrpcAJz8nFpTiQvYbqi1ne8ZynrQnWcSLozksr23TQqJ2Qybjly9pfVz1mXL9mH3Pyc8lu29SbHOm0E2dSpLbcI193oVQz5F4HwCSX3cziB4UBWNscwDDATxUo3IlQ1T2n2qvZusGC9mRqA1Udpaqx7cRVpvidia5Zv/3qKJwJnw0D3jncXJP8m4S6asoq5Q9ERni3Aw5IUjnqDN+olaL1HBJNWvGoAnmSa2pY17X4ujpl2DQjgv5jGwZOqIYTq6Tia/+Etj8aPsxGcU5HdDVQnBfhjCcPn8nfK1ASB35fZVmOJWOS+Bw6mwLhhBI5Fo8h1MlQ+oMGk71TFGbzSdnOMWdxKYMpxT1QJ/h4lOm+e4KiDuRpo59LcOphg4deX9TVisgOKal4XTVRSikjoynsp7Jd9BiDDAxOH+qXK+iRMMryfDQMpwKwMLXgT8eEw6vL3Qkm89Vc0E61wQM3zDZuSoDWyLwjpWyy4VP+hxU5rMOQyaJLJSlrHqODCcAGLgOsNUpwCG3m8+xQWZjLF0/Zl+b9PkmRb9RQionoAtsiUDoAogsNWNsOmNsBPn/SMbYvYyxaxhj9Em8F/Pew6Uopvc5TD2AMZYB8FMA58a8du1hDanLua1mb3VKGffXdMDZqJC6BnQ4uQxkdAJDHU4u4By4Yadowek4A+rgCcD4HYB9fuF+TndDhgwgIYaTg8CdDSoTL6Svk2Agt3XYZ78W/3pxUXI4WepupTScNjkUmH21/Zj19wS2Pk2slAGKw6kY3FcsAK/eBXSsAR67SHOxaoXUGRxLSz8wX8OEQntYNBsQfeDyBcDH//L3HXRr/OtTlPQVvPIXEmg4DfN0/PqOKq8sEsUi8MV7yc6Na+ykDqdIVNHO6rlo7iPC0LY4vt4lMYOpIXUxJ9L7/FwI2w4cq29ntWQ4yb7e5nCik1odKz9F5SDthw//Adw8W/nSq2dyodrmcNLZGdXOeKW1FWjbqKDzRuf4LHYC95wMvHaXEMcOfNdRH/3FasEUoWEa59tW+HPHgNC8FB+3iYZ7me3kvWyLzbLe7fET7/8MsNslwNBJ5nNsWKMwupM4bQaMAbY4wf34nb7n6+9VAl08pM7FErwOwM4AwBjbDsClAE4HsAmA6wEcAACc8/3UExljjwAYoe4HcL5j+U4B8DfO+YcsYiBmjJ0A4AQAGDNmjOPlKwiraHg2OqzgQs/7+nwFnBbrbAe8+3ei4aSG1EnR8AZ0OLlMojN5whLQMWosePi74X26uhVnkpTNA0feE31cd4Y0bAOC0qUv7edGCTSbstRJJFk5Ug3xC78ELtQwXqoFWWdtlGKtw4k820quXmfzwK4kTj8wGCvhHiu9rGR/PkN/LV7UO5zilldt16aVsz8c6vefrvjgeWDN0vD+fKsvLC6xgWMCAxPk737kQmDAWOC/j3j7Y/QxM88W/brMZlUuOlZGH0OxyWH+djYPTNoNePsBt3NTh5MLEttZKboyygzHH7s1cPRfxLaundWU4RTT4dS7AZLUdGdQW+HdvwODSbY5afNKZ8vAsebr6OpVrsk9oiAJolhVSbNa62ASDZcMaNVOKBaSjWmNGgalMrBL+4kN2LZMsNkHjQcuIRnRAwwnlyx1nsNJ2pQ2+9dUrqRQGd1JWGpnvRLv+Jlnx7+HDXteATx0ATBy4+D+fGv8TO11gEuryXLOP/e2DwJwPef8TgB3Msb+bTuRc26MW2GMLWSMjeScf8oYGwlAl1t5awAzGWOnAOgDoIkxtoJzHtJ74pxfD2GYYdq0abWPbYrScJLQrapXCiwLjN7SN16yhpA62cGGQuoaSMNJYvRWwIfPK8dQMble8TJKuTr00klSPNDnpa5wRK1MqeFLnAfPWbUk+H1IfydBcze11z46/3gV4MRwqlBIXRLQ519iOCn3+++j+nN5DIaT+u5yLb4h6+pwSgKdswkw61iUA/m7paNJIo7Bk8lWztkE2EM5ddj+W/42Y8Cht7s7aFOdFhcktrNSdAeQfnD7b9lDvk3Q9Se1ZDjJyePdJwKH3alfZKVjmgx5TFEd2JyYJQ0dby4waHz0sRRxx4+4iAypqyB0Y36xE+jlzdVUrcNCR7Jw+EbVeG3qA0zcFdjq5OB+9Xlf9xXgW0qCEMr0KjHgLXZaseBJMsg5qk3b2EGEPA5UgkVXZKmNnOon1qJY5yvA2/eLjPeBELzGgksLzjLGZOvaCQBN21vOrPw+AEd520cBuFc9gHN+GOd8DOd8HICvA/idztnUELAynLzvDr8TOCVCeOzI+4BT/pGsDN9dAhx7PzB8svhfDuhGhpOyyt2IDCcdc4h2hLnmeBNR12NTh1M80PcWm+HUGTSM33sq+P2yT5XjNQ6quNAZL+cvAM56Oby/GlCdwtpjNAMt/e21qqNqSJ2E2n/4J/hZ4KI0nELvjhu24TsmZ55jKWyZSJLuOAqmSV89+5i493ZxjtEV9BRxUS07yzkjMGOswBj7t/d3H9m/DmPsH975tzPGqhxP04MwdD3xOZ5kPN7+m8Da0+JfSzeBqinDyevr//cY8NgP9cfQRYS+qcOpqpDMNx3kgtLqL8SnTWxaK9dRj5A6GuZfQeeNluFUIAwnhT1d7OyazgoTMhngsDuCWdflfgpdkhHqeGNM2BVWh1MShlOFHE6qFmw9sgRXCwfcCMx9BNjyBGDKAfUujREuDqfbADzJGLsXwGoATwEAY2xdADHjGAK4FMAsxth8ALO8/8EYm8YYu6GM69YH2jTiXoWWDWfdnaOzCIz/CjBs/YRl8AaGWT8QlU9eJ6Th1MghdarAuaZDogNgXIeTcznSVflYCGSpszGcNCh2iAyJkiaqMu+WfwK0Evp9iLIfYXzs+B1LeQnyLfYBsJKQg6ht0NOG1NEsdTWqo6YMSpRSP/mA4Ip1oU30e/QcreNFeXfUkFSNSilE3nuoU7EToRpCtqZw6noaPLRNHv8YcNLT9uNtDqpZcnJpaIdqeu4UOlTLzgLcMwKv5pxv4v3tTfZfBuBK7/wvAMwtszwpJIZvBJz7v+ikDi6ot2h4jjgh3viz/hg6eWwdXN3y9HSM2kSEPpdA+ucRnq21fIH47BuT2T3jNPG5/43AXlclLqIROptRF+ZfCZgYTs3S4aQ4Wood3SukrhyojrdiJ/CaRV5EOpzUJDXaaxPN0EqA6vYC3WuO19QbGD293qWIRKTDiXN+MYBzANwEYFvOS7OADITGQCJwzpdwznfinE/0Pj/39s/jnB+nOf4mzvlpSe9XdegEEOXktdYr2bmmYOVTOwVZLjWmtRFEHNVnlckA684CDvydv48OPNnmeCF1ScuRwo7NPLLigNEaR4mDhlM2DxzwW/G/rJcrPwNWfS4YTv1G+serDqko22O7r4f31XuwKaV4LcPhVItwiakHmRlOFLv8EAE9El3qYJ3BZVupVEPqpMHQ1RxOpudW11VS8i4GjANGTLEfbusP5UTX9C6rsSDQzVAtO8uDU0ZgHZgQz9wRwJ+SnJ/CAb2HVGYyWnfRcLJYYxpf6eSxERY4uzvoAhrtn6fOEZ9jtxafqiZMFDY9QugmTjkAmHZMeWV0Ba1TldRw0jk91iwFnv+52FYlHAqd8RaLhngsxmE1znJWDTz+o+D/uufw+f/M50uHU//R4n+bXTHjDDH32+zI+OWUoNdXGU7diaXWReAUFMs5f55zfjfnfCXZ9zbn/MXqFa2LQRfT2yiUPWOWugYMqdNNzg7/E7DhPvpjsvnKpjCXSB1O8bDF8cB3vxAsF6uGkwYy64dKYb58AvDjdQTDiWbnWrEAWLGYXCDGapesO7QObXmy/thqoqThZHM4RWg4Vdtpdv4C4Ku/hFMqVpYJZlzqbA+ueAPi+6P/ppzoXXu78zQXVRlOHrNNJzYrnc4umddsTqWqaDiZQurq6PSkTdKF1Werp6W+MnU4lYMq2lmRGYE99GKMzWOMPc8Yk06lwQCWcs7lS/wIwFq6kxljJ3jnz1u8eLHukBTVRL0ZToEEEQb7iToKclXoa1MEQcPFViwMf7/VqcA5b9s1nCTWJ8kz6jF2VUvDiTHh3KBY8Kq/rdphpbAwR6y/B3DSM2LxrqvjycuC/8edJ0nB9akHiv9tc84+w8TcrxxNoikH+tvdOaSui6BKLTgFAGDaseKzGpOYOKANa8gk4nBSmCLNDchwotjBS25IJ3CMVXa1o1SObkS3rAUYE2y0TC6ZhlM25wvqtykRJJLhtOsl4v/lC4DbE6YalXWH1qHdL012rXKQ1OFU6AAm7y9WF6tN0c63eAKPko1laRMs4xuEJYaTxpExbpvg/3LVdf095A7ynYHh1KpxOLWvFNohV28MvPKn8PeAT5GX2fh0RnY1RcND++tJsadhyQ66VeUwnCqlwZDCCMbYI4yxVzV/+0SfXcIYzvk0AIcCuIoxNgH6zlv7ojnn13POp3HOpw0dWkUWYgo96s1wykUliECwL6i3XdwTQBcT3lIXeyBsNhctrW9/Asy52f+/lvWqdM8qaTgBwA7fDv5PbQ91wSRJSN2Iyd00pC7iOdD3tGKxmHNmsiIxwqn/BAZPqG759r4G2Pd6sa1mVUxJBTVH6nCqJnb8DnDBIqCpCmEacSBXntaaBpzyvEU0vE/9aYa2Se24meKzkrH/a2+h31+PAbU7gGWTaThl8sJgzbWERRpXfSayx219ivhc/imw7BP/+zjGh6xf9R78ywmpq3Ub5Y4MJxCG0/vPuAmLyvA43bFGDSeNw6ljlb8q+clL+nt1rgG2OQto8TSTmzVZOasxCWpE53WAJepgeOnq3NF/Ffod8juT4z9lOFUdnPOdOeeTNX/3AljoZQKGJSMwOOefeJ/vAHgCwKYAPgMwgAiarw3gE935KeoM3QSqHqLhprIAQT23aoQvpwjCZTHBBU29g+NEXRhOmsy5lUK+BRg4Tn99KtlRLIrvUnaMQNRzoGP/T9YVnywr3uXQSdUrl0Q27ztUO1QNp9ThVGukDqdysf+NwCF/0H/HWO1EiG2QXuSP54mBImvScOoNnPtfocdDs6bUErZOQDKybCsycZwPwzYCjrg7uG8tmR2mQVOYNjoyGQ2jIcK588affbprr35hkUbAb0d9R3hCl5ZsZjZQR2I9BxwnhpPJ4VTjcpccTo4MJwD47G1g2UfR1z7sj8Dsa4Qjkd5L/ONd67/Awtd9LQUdDduYMc9DsSjOz7f4Rriur6ilhlM9EdfhqhM+H7et0O+QbdM01qWi4fVGZEZgxthAxliztz0EwDYAXve0pB4HcIDt/BQNgHqH1NF7me5LJ/Ipw6n6qHQ2uU09Znk9xrSA/VEF+5zaA/Mf9Ldpkhppk6XOCoGoxU+dDVvrZyfLqDKcUqdhzZG2mnLRwCkIS5DMIIlsTnTecpK297XAkv+KwSnXLGiI9YKtM2rxYnkn7gq884T+mOULggLTNgydFA4jlIZSpTIj9DRkcmERd9vkdvVSMaAv9xbNe/UPM5wA/730HSkcGdRwTcJw4hw4+81wWGmtUGI4Weq70eFU49VFF9FwxiL9ilr0GwlsfpSfnll332s3F587XiA+daF67Svs9UyG4+V6ESNcU2+qkYCgIdmSFWT4bbiPYJWN3x649QBg1KZBllnKcKo3LgVwB2NsLoAPAMwBREZgACd5SVo2AHAdY6wIsRB5Kef8de/8bwD4A2PsIgAvAbix1j8ghQN0k79a9j10HDZqOKUhdXXH0IRZsAGxOLTbpbVjiK/zFX+b2h+jt6zCzQx2ZCcRDZd6sanDSSAOw0mi5g4n734hhlPqcKo10lbTE6Cj1WabRBgKIDrvzY6obZlMsE1q195chAQOXR948Fv6Y955XGQ26OOgIWEz0FLdkWToPxp4/T4R8tZPCn1bjBO6egQIHSedw0nWi74jgLfvD34Xh15dql/cqyOGelIrZ5RtBVL3u2RGv5rCM8SiNJzigoaz0veC8CYAz/Bj+t8fxXCSDLp8K2E4aY776AX7dZKgOzCcbMjmhS7Wx/8S/6sOYLk/RV3AOV8CYCfN/nkAjvO2nwWgTVXohdgZYs9TNAzqzXCiNpPJ0VVMHU41hWpDtA4G5j6U/HqZrD4UvRr45ofBuYscR1sGEtuygjAtXFIbVS5IpewYgSjnkdbhVOMFOBkKGmI4pe6PWqMBLeEUFYfO4ZRr8ifUjdTwoiZCwzYIH7PXVcCAsWL7npP9WOEo0I5vvxuAw+9MGU7lYtxMYXh++bG/T31fa74ElnipU+UAvsHe4rNXf6BNE1InjY1yMlYAwMG3AhvMFtn0bOg3Ehgysbx7uSB2SF2hDiF1LgynjLtj5diHgF0uEhpA9PzwjYP/fv6udywDNj86mIHkjT/bmW7S2Mj3Iv0hB0Yoc+xqrJzqwtHqjWo4wUqi8cok53+PVv5eKVKkCEI3kaslw6kfSV7oElJXKX2hFGZ8+WHw/6Eb+NmAGx29+umF6CstGC7h4nCS84KUHSMQyXAqBD+BOjKcVNHw9B3WGg1oCaeoOPIGhlO7x3Dq6g1v2jFmHS1XTJ0DrLszMHGW+L+/NvNziijIVctOSl9VHE6/3QP42WZiWzpVJu0qPnuZGE6eAasLp4oTzz96S+CgWxpHyDmRaHi9NJxcRcMjMGZLYMbp0VmNVMfFq39C6V3PvhrY7lz/u3/8yn5PynCiWdXmPiJWUiV2udjpJ8SC7rdteXLl7xMLVQiJ0LHUJDrbw/tSpEhRXdRynBswGug9zLuvQ0hdUwNkRe7u2F7JvqabC3QV1Mtm04bUNYj9WHModoNqv844Pfi/XFCmzp56aTiFHE4NRLToIUgdTj0B2pC65u4Vj5yE4qqbCM44Q4RT6VKmp4iGrGt0kFYZTgtf9bdLIoze+zNpOMl3lXPIZmZDo+np0Ho7+QCgL6GKax1OCVLylouS3lQM0fC40DqcIt5rHKNPGhu5XkHHSL6XcHJKVMMg19W5WmRosaEaGhy2Feh6aaWlSNGTUetw3pYB3n0N/YtMIDD7GmBYGVpCKdwwfEMhMSHRlVllsi5XTT/KxHDqCG/31JA61fZUo2MGrhP8X9qO9XQ4ZQ0Op576DuuI1OHUE6BrWHRfV2x4J/4dOOEJ/3+XyedrSkY63So/Y+6i4ynCkA6hzjX24wBBsy0N4N4glO8dHhgAPyxJq3kUx+FUI7FLV9C2t+91wDlv+OGhz1wdzvBV7KyfhpN18sLKe7ZaZ0XEe40zmVr9ufhsavXLWS1qvgpdOevu+PSewcnP2g/b+jRgsGOIsimkDkgdTilS1AprT/e367WYaNJVlPuHb1S7svR4kHGuEbJmJ0W1nafLP9XvL1CGk7JA2tOw4T7B/3OKDps6D5OMRqqfVGt2mLyfOifpDkSLLobU4dRTQQeertjwRm4ssiFJuPyGPx4d/L/BfA/dAiWGE+ncTY6IzjbCsvMG8FyzOHfBq8Fjmc3hFAON5nCihov8jWe97O8rktW1YlEY7HXTcIoSDS/H4SSvTUXDNZMWmakO0BguFgfSO0+KZ73W5n7YZ5Tw6Hp7AgffZj/GBToDq96UfFen264XA6e7in7LaxaBuQ8Hv4oSdU+RIkX5OO9doY0nx5V69TNGh5M3AW3ERAo9AaqDoCuh2gtFzR7Tud/awf2dOodTF5wzVQLqYqfqwFTbdSMwnGhIXZ8R/v6uSLTo4kh7/Z6Krs5wUpGoE2sw50N3gByA6CBtes6da/wBXNbBXC+x73d7B48thdRpVuhqxVSpBuiEQCcuHRCsrJOx4ywaXo7DyTtXaoAA+vca+O3K/Url1JTji/eAAWNEyOag8SJJwP43+N/vdhkwcFzwnEN+D6y/h+MPsKARGU42vaXE1yQTgtFKUrPU4ZQiRfXROsgbIyUrtcb9zFQvkUOLIblHSXS53gzPHgTeXRhOVa4zxz8GHHlv+BnRkLqSDdZD66/qSFZtLfUdlRxOq/x99RIN54Ug07qnOg3riNTh1FOR7eIMJxVRv+FCTWaOviPC+1KUh1gMpzVAQXGilELyFJHhSomGl4Mdzgdm/bAy15Jhc1FOmoCxUyfNNWmwRmk4lePAzWSBr/5SSdmsczjlzd8HnJwKViwKtvepc4IZD7c6CTjzP3FK7A6tw6neQy9hI1XskhYnVhpSlyJF7VHrfmbm14Hm/kBzX/33LosXKSoM6nDqBhpO1cLgCcD47cPPiNqyJYdpN5gzJQEvivZtgvqOpCQEtWNr/eyaevvbqcOprkifeE8FDU3qDvHISTqPqQdXvhw9HXEYTv+5zR+ISg4nb7APraTIkDpNXa3kpNmGbb9WOTbgcY8An82PPk7HcGoUDadz3wEu98T1WZkaTgCwyaHKbTXvlf529ft5vzFfe8VCYMTk5GWrNOq9QjpxFrDwFaD30Mpds4/HTptyYPi7ttThlCJFzbDvdcATl9Z+rGAMaO4TzEZHUQqp66EMkXqAMpzyXTmkrkZOSpXhRB1OPT0klBeBPkOBNk1iH0Cj4aRzONW47dOkMBTlynOkiI3U4dRTsP+NQJ/h/v+SScIy+lCeWqPXAGDN0uTnx3U4DZ8CDHEUw03hjjgMp0d/4G9Lw1gOAlS7CPAHqaQhdcMnB7PjJUEljYw+w/wJug2BDCl11g8o/X4GgAO9B5PvWOWNsMiQOgUrFpq/W/UZ0Dqk/DIlQdvy8L56G6w7XgBMPy5axyoOWgYC5y8Mt9HdLgWGbVC5+6RIkcKOKQeIv3qAZcPJLiTSkLr6gs4BuhpqNWaqTrl2Eg7mkrG3O4MXo6UV1OOBoD0/cuPKlysJurLztYsidTj1FKjGhwxNahR20xkv6SdmrogzCR+6PnDo7cnvlcKMbAyGE0WGaDgBQWYPYE+57oJj/gYsX5DsXLUMtYRWw6lOxo6873nvGMLXlPd80tNl3lDzrumK/YCxwDZnAYteB+Y/FD6WotBRP/2KYRuG99XbYM1kgf5rVf66eU3IxlYnV/4+KVKkaExkMhaGk0vG0xSVBRlHu3IG5lqNmaqdQPWHij08JLRYSOZwkoulu/8YGLpedcpmw8nPAf/5PdBvLeCBb4p9XTm8tIsidTj1VJQYJQ3icGodFNRUiYs4DqdtzqzOZCuFMDazTW4Mp8B5MqTO4BQoOZw0hqwq9qxDr/7irxzUI8OdVsOpTm1WvgNTO1Wfz/AyQ9h0IXW0nTMGzPo+8OXHwJXUqaN5T4UO9z7itHmVDdPMNQlD6/7z/H091WBNkSJF9wbL+kwmFT09JKne6NuFHU41C6lTmC80w5pLxt7uDF60//ZQSJ3X3qXtuvb06pQrCsM3BHa5SGxLh1PKcKo50l6/p0JO7Ou90l4pxHE49R9dvXKkECsHcRlOWUeHk86QPfzOWMWLDSnwXUtIJ1ojZKmT0BkagbZE3nMmV76DThtSp3G29V8rnMpYRbHD3bk+ZGLlV+FUvYCeYrCOmVHvEqRIkaKWyGTNDKc0pK72oOPo8I3qV45yUbOQOoX50rHKf4Ylh2kPzXDNuSfDkhNsIRVGhpPncGoUggPQtTM2dlGkDKeeCjkBapSQunIRR4cqZTdVF7lmoEAcTk4Mp4h6WGI4KcyT4VOA3lXW5pn7ELDgleoremhFAAAgAElEQVTeQ8XuPwZ+f6DCcPKMnXoN2rpJwnGPAkv+K7bpa66EU0zncMoarmt7JsWiqDf17OsaydCqFc57F8i31rsUKVKkqCVsDCep05n2C7XHQbd0E1ZHlbMSh0KtuGDs51tShykvCnv+25/q7Xp1Ia3kcPIWThtpvqky2VJUHSnDqadCOpya+9S3HPXAgHH1LkH3RiKGkzcQrVmm/14O8FIPZ+vTvC+qbHwAQN8RIqtXLSGfBxVbLGX0q5Oxo1th7DscGLdN+PuKOJx0IXUGg8WWcaRY5+cGaJ5HDeptvdE6SK/plCJFiu6LTNYckvz+s4K965IwI0WF4I01TV3c1q8Vq0in7SPD6ngP13CSouG5Jv0imvpcpOZV3TIsW5DaJjVHD201KUoTtKa+9S1HrTH9+MbIytedkWtOruHUOlj/vRzIhm8IfPNDYOODxf9JRcQbHbJ93n4EsPA1sV0KqauzhpP5AH+zImF/EaLhgf0Wh1Mj0LnV51FJjagUKVKkaBSwjJnhtHppdPhzisqiJNTeQ8PA4kLncGpfKT5LIXU9meFksQNDGk6NHFKXOpxqjbrNvBljgxhjDzPG5nufAw3HjWGMPcQYe4Mx9jpjbFxtS9pNIeNXm3uYw6mnUmFriSQMJzkhn7QrMH57sd0y0NcIooNcr35u1+zKkA6UlYuAu04U2yWmTr00nCKeOauww0mr4WS47kIS8qiWs95i60DY0EodTilSpOiOsGk4Fdoaa9LZo9DNbaZKQcd8kSFhctzuqfMIHpWlTqljN+4MLPu0MWwwFT31HdYR9aR6fBPAo5zziQAe9f7X4XcALuecbwBgCwCLalS+7g056Pc0h1NPXZmoJZIwnGR9ZAyYsKPY5tw/1/jeuinDSc3GBtRfwykSlXY4FYHX7w3uS3LdQgPQuUMMp25ab1OkSNGzYdNw6mxLxXpTJEOvAcAWJwJH3lfd+9icIsU0pM7qqNHZ6e8+2Rg2WIq6o56tZh8AN3vbNwP4qnoAY2xDADnO+cMAwDlfwTlfVbsidmNkvUG/qXd9y1FrpOF01UeI4eQAOsjLbZkRAwgP8NIJ010n7jRETP72emk4bXyo23GVZjitXAQ8dlFwX5Lr1psZBmiM2G5ab1OkSNGzYWU4tdvDn1NUD109pI4xYI8fA6M2qe59dIlJJLOppOHUQxeui1EMJ813d5/YGDaYxLRj612CHot6zr6Hc84/BQDvU6ciOAnAUsbYXYyxlxhjlzPWU1t6hSE9zd0ia0UM9NSViVpCZTi5OIXoIC/rJo0XDzkKpfHUTSfuOodTvWjJ+/wcuMCBWLrFif52pZxin70d/F+Kd8ZBIwhWmrQNUqRIkaI7IWU4NRa666JctaCbYspnWNJw6uLOu6R47yngg+fM35vsvkbScNrrSuDCL+tdih6Jqs6+GWOPMMZe1fzt43iJHICZAL4OYDqA8QCONtzrBMbYPMbYvMWLF1ek/N0actDvrqtNT/4YWPK/8P7UX1l95HopDieHyXWA4SSdTz2Z4USeh/ztnZ6OQK0N9kzG7Z4bHwRsc5bYrla/0uZgKKxaAlzYH3jdo94XGkA/IKTh1E3rbYoUKXo2dFnqikXgicuAZR/77PoUNYIca3qokyQudE4TleHUY/R/YtYZ04J+I2o4pag5qupw4pzvzDmfrPm7F8BCxthIAPA+dUvoHwF4iXP+Due8E8A9ADYz3Ot6zvk0zvm0oUOHVusndR/IjqG7rjY9fjFw65zw/h4zUNQRuWYlpM5hck2ptnKbF1Ea8EIDWTc3nrQhdW3h7xoNsn1Vul/J5IC+I4F1vhJ97OK3xOc/rhOfpex+dWz7qqGVOpxSpEjRHaHLUvfBc8ATPxIhdbkGHr+6I9IsdfFAbc3px3kb3jOU9TqNlNDDtKDfSAynFHVDPVvNfQCO8raPAnCv5ph/AhjIGJMepB0BvF6DsnV/dHaByWtcrDsr+L8u/CZlOFUfJoaTLQ0pHYiyOg0n5b31HSE+NzuyvLI2KnQMJ5kppZHbrHxPlS7jiKnAOW8CvYe4FML79IzERjB2QtoFqcMpRYoU3RA6DSfJcABShlPdkDqcnECdSdKeKTGcCsH93R1xnZQmR1yhQ9hAqdOzR6OeDqdLAcxijM0HMMv7H4yxaYyxGwCAc16ACKd7lDH2CkSP+es6lbd7QU5ebU6ArobD/wRsdlR4f5HQu1OGU/WRawY6aJY675kPXV9/PMvqBaephpM6kLUMAL63FJhxWmXK3GgIOJy8Z1OvkLo4yFTJ4RSFLU7wt9Vwy0agc6tCpD0tO2iKFCl6BnItwfEfCDI6U5ZDjZEubsQCtTWlPVPScOphIXVxmVy2kLo0nK7Ho24OJ875Es75Tpzzid7n597+eZzz48hxD3POp3LOp3DOj+act9erzN0KkuHU3ejNwzb0t0sTT+JwSqmw1UeuJchw6uMRFA+9XX+8aoCW/icMJ90A351XSwIOG+93doWQOulcrHg2kgijeY/LaSGC3zVCSl75XIZMAva9Dpi0W/3KkiJFihTVQlMrsPpz4KN5wJplwPyHgbtP8r9v5AWT7ojWweKzOy0uVxMBhpO3LecQcvG6p8wj4jK5uOH5FDpTR3MKNECOwhR1Qcnh1M0GIV2nxlOGU02R7xUMZ+QA+q3lh8GpUJ0TGU2Wup4ywEtoNZy6QEidzCaoSy1cK0hH5AfPAoveaIyUvCXHaR7Y+OD6lSNFihQpqol8ixAHv2En/fdpSF1tsc+1wPjtgbW08rcpVOgcTlAYTj3FHo37O2XIYbYpuOhc7Kiv/ZWiIdBDWk2KEPqNEp/9R9e3HJVGYPVMMpyInkBPib2uJ/Kt/9/evUfLVZZ5Hv/9Tm4kREgCyCUQAxi5ioBnIMgo3YhyGRYBFjhcluA0im2LLXgDFz0tPWt0ofaIo4tmOqKCMyxAaBBEbBpobBxHwGAjBCJNAMU0ASKXcAshl2f+2LvOqVNnn3Pq1G1X1fv9rHVW1d77rTpvvWtX1VvPft73zb5gKpkl1YGjIrVfRFOqA075vn7OZipS3SajhtR1ccCpXRlOk5pku+pcuf6s7pjDqfZKKdAhtufZvt32Y/nt3IIyf2r7gaq/N2wfnx+7wvaTVcf27/yrQM+YtuX4x7v5+6sfzZwrHfSx9PpQjRoxvcNYczgl8tN5shfoKwu01F4U3bieDCcQcErW4k9Ip14r7b2k7Jq0VlH2B0PqOquSNbcxz3J6fuXoVWuq1X4RDc3hVDWkLrUJL6s7PaNWqeviK8QD7RpSNwkjMhoHqlapK7FOQx3Xcd4HQHtcIOnOiFgk6c58e4SIuCsi9o+I/ZUtzvK6pH+qKvL5yvGIeKAjtUZvmjZz/OPd/P0FVF+UdupzODUacKrp029YxxxOIOCUrIEp0h5H9d9VjxFDkfLXVh3sSOWLokyVDueGddILT0ir7pNeeXrs8rVfREOBgaqAU8rLyHtAevN16V++lm138xwYZc3hVK12RaTK+78bhtSNF3gF2mOJpCvz+1dKOn6C8idJ+mlEvN7WWqE/TZ81/nH6YOhm400avjm1DKeq17nPiROXHwo41fRRN6wjwwkEnNBniiZbHpHhRGen7aoDTs8/MXH52vl+RqzQxlAkeUD6f9+WNuS//7q5wz6U4dTiOk4m4Lipal2JqTOGs4rKbDfOY5Rn+4hYLUn57VsnKH+KpKtr9n3Z9oO2L7FdGPG2fbbtZbaXrVmzpvlaozdNmyjgxFwu6GIj5nCq9Blq53Dq4j5YK1W3xd7HTVx++uzsdu7bRu7f8DoBJzBpOPpM9fwAleSt2iE2aK/KkLrf/0J6ZfXE5ceaNFwaPWljijzQO1fUhiZ5L7FD9szy4fu//4V04BnZ/TLrVOlsbbFVeXVA37J9h6SiVRkunOTz7CjpnZJuq9r9RUnPSJouaamk8yX9t9rHRsTS/LgGBwcT/sBO3IQBp0R+rKM3jchwqrpQdNHWxWX6WXWfqZ6hsAsWSydeLm23h/T37x3ez5A6iIAT+s2EczjR2Wm7SofzR5+or3ztF9GIjKeCLLXU2NKseWXXoj6V4GGZQ+pqy774u+y2zB86cxZIR10s7VXHVUJgkiLiiLGO2X7W9o4RsToPKD03zlN9SNKNETE0LrWSHSVpve3vS/pcSyqN/jTRHE5kOKGbFa1SV5thnUrQtHDFvgnsd7L0/OMj9214vdyVi9EVEgnTIhlFAadLDxq+n8oXRZmmbTG58rUd0OorpAxFytpgi60nLtdNit6HZemWNPjFn5C2nl9uHZCimyWdmd8/U9JN45Q9VTXD6fIglWxb2fxPywseB2QmGjpT9ucwMJ6iIXWVuYmKyvSz6t9Lk3nNtWXJcIIIOKHfVP/Qfekp6YUnpdefH95HZ6f9Jkqpr1U7cf283Ybv1y5Lm6LqL+8jv1JePerxxtrsduac1j5vMwN0hua+4gobknSxpA/YfkzSB/Jt2R60fXmlkO2FknaR9C81j7/K9kOSHpK0raT/3oE6o1dNNPSGi37oZkWThr/56thl+tmI4NskFpiqfY8zaTjEkDr0m9rMih/UDGGhs9N+U+vIcDr2EumW87L7tVePBqZIp14rzdpG+sU38319/FG1y2Jp47qxj3tgeHWUdxzVmTo1at2L2e3MuS1+4iYiThvytmX+NiQoIp6X9P6C/cskfbRq+3eSRqXgRcTh7awf+sxE2a30wdDNBgoynNa/UlMmkXO40YDTqAyn1/q7D4+6cAagv9QuGV/JuKhI5cpEmerJcBr8syyg9MMzsky0WnvkgZXjvi3tcnD216/Oum384/bwSmvdfv6ueyG7bXnAqQkb3shuyW4EgPaaOkHAic9hdLOiDKf1L49dpp+NeJ3NBJzWddc0CygFASf0l9q0zdqoOmmd7VfvHE7b7ZXdzh5nle5Z86RD/7L5OvWy6gynbr+yts2i7Hb7fZp/rhlbS+vzgHHtpJ1FpkyXNr05en8le4wrbADQXhMOqeNzGF1spwOG71cCJ7UZTqkETWvncDrqYmm7PSd+XG37bHyD314g4IQ+U9vZqR2uNXv7ztUlVfXO4bTtIun4y6Tt921vfXqdB6oynLq8o3PIJ6XdDpN2fFfzzzXZ4Nqn7pe++c7R+4eG1HV52wFAr2NIHXrZ3IXZIi1vrK3KcEp1DqfqgJOzhU/qelxB+xBoTh5nAPpLbWfnzddGbr9lh87VJVXjzeHkgapVwyztf1pn6tTLeinDaWBKa4JNlecaUkeG05wFxfsrk4Z3e7AOAHodQ+rQLyrn6sY3Ru7v9n5Yq7RqSJ00+rcYkpNImBbJqO3szNp25PZsAk5tN23m2MfOXS597K7O1aUvuCpIl0hHRxr5WusZUlfrpO9lt5U5nFLpJAJAWchwQr+oBE5qV0lOJcOpdkhd3Y8rKPsE/f7UkeGE/lLb2Xn1meH7Cw6Rptc53AuNG69DufX87A/166UMp1ZqNgV723dktxsZUgcAHUHACf2icq7WTs0xmRXbeln162xmlTpAZDih34zX2Tn4zztXD6BZA/kkiyPmcEroI3vEVbIGMpwqc4lV5nBKKTsMAMowYcCJ69zoEZU+Q+WC3477l1eXMrjRDKf8PV49omTe7q2pE3pWQr9ekITxovBcWUMvqXTcU81waiRA9F//OHx/+uzsliF1ANAZUydYpY7AP3pFpc9QueB37Dekv36xvPp0WqMXOKdvKX3859J//j/D+z58Q2vqhJ5FwAnpSCk7pGwXrZWmbVl2LXrblKIMp4Q669VXwuudw2nKNOm066Szbh+ez41JwwGgMyZa/pzAP3pF5TfD5qoM86L5ifpV9Xu1dh6riey4n7TFVsPbM7YauyySkNA7B8kj4NRZk/2CwkiVDKfYnGaG02RXqat4xwelXQ4abr/KCjMM5QCA9hog4IQ+UZvhlNpviN0PH77fSH++us81jflzU5fYuwdJm7uw7BqkpfIljcZsu2j4fuqr1DViSk2GU0pXJgGgDNNnSSd+R/rMiuLjKX2HoUflU3MUZTil5LALpLm7ZvcbCThVZztONNQWfS+xdw+Stt2eZdcgLZsJODWlMv59y23IcKp3SN2Ix+dX12IzP3IAoFP2+5C01U7Fx8g0Ra+onKtDfdlEVqerGBiQ5izI7jeU4VQVcEplZT+MqbSAk+15tm+3/Vh+O3eMcl+z/bDtFba/ZXPWogEXreUDr9MYUtecWfOyebAi8mwxp3UONxtcs6UpM1rzXACAyfn4z0evTsVnMXqFEx9SJw2/5mYznJC8Mt89F0i6MyIWSboz3x7B9nskHSppP0n7SvoPkg7rZCUBNKqBrBSMtOE1adn3sytsqXXU3eAcTtUqw+o2vdl0dQAAk7DjftKRXxm5j2xT9IrUh9RJVQGnJrLMAZUbcFoi6cr8/pWSji8oE5K2kDRd0gxJ0yQ925HaoX986Adl1yBNi/+i7Br0hw2vSasfSK+j3sgqdaOeI8EOIgB0i9oLJaldOEHvqvQfhjKcEsowryDDCS1SZm98+4hYLUn57VtrC0TELyXdJWl1/ndbRBTORGj7bNvLbC9bs2ZNG6uNnrPbn5RdgzQd+RXpr18ouxb9YcO69DrqrXi9G95o/jkAAI2p/ZGe2vcYelflIt/myqItCV7AGlqpr8k5nJC8tua72b5D0g4Fhy6s8/Fvl7SXpJ3zXbfbfl9E3F1bNiKWSloqSYODg4zlSdlW8yVZenlVts2HXjns9LJy2mXzpvTackTnrsGP9E3rW1IVAEADar+3UvseQ++qBFs2b8x3JJjhVHnNZDihSW0NOEXEEWMds/2s7R0jYrXtHSU9V1DsBEn3RMSr+WN+KmmxpFEBJ2DIeQ9nt38zJ7tlHDF6XWxKZ3jYx+6SVv1KevSnZdcEANCM2qwQ+mPoFaMmDU8w4NTMkLoU2wtjKvMXzM2SzszvnynppoIyT0k6zPZU29OUTRheOKQOGOKa1bzo4JTr809IX3iy7Fr0tticzpXh+QdKB3985NCLRudwAgCUhzmc0KuGMpxSnjS8iQwnoEqZ756LJX3A9mOSPpBvy/ag7cvzMtdLelzSQ5J+I+k3EfHjMiqLHpZKZki32nIbada8smvR21JcpW5E+joBJwDoeVNnlF0DYHyVIIuZNFzb75Pdzt6+scfveax04ndaVx/0rNJSPyLieUnvL9i/TNJH8/ubJH28w1UDgO6SUoZTOxx4Rtk1AID0DM1/k5u2ZTn1AOpVyaiuBJxSnjT8sPOzhZcWLG7s8adc1craoIcl+O4BgB6zeWN6GU7VVxObHVJ39NebezwAYPI21QScyDhHrxgaTpbwkLqBKdLb3lN2LdAHEnz3AECPSXGVuhGaDDhN26I11QAA1G/zhrJrAEzO0MWu/LYyh1OSq9QBrUHACQC6XUqr1AEA+sMmAk7oUaPmcKIPBjSKdw8AdLtNG6Up08uuRXkaTXDaepeWVgPoNbZPtv2w7c22B8cpd5TtR22vtH1B1f5dbd9r+zHb19pO+IMIk0aGE3pVJdOpMg8ZASegYbx7AKDbbXxDmsLqPpP2yfukC54quxZAmZZLOlHS3WMVsD1F0qWSjpa0t6RTbe+dH/6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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from analysis.utils import sample\n", "from scipy.stats import norm\n", @@ -137272,42 +533,18 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.026914897987428098" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "np.mean(residuals)" ] }, { "cell_type": "code", - "execution_count": 46, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from scipy.stats import norm\n", "t0 = t(6)\n", @@ -137331,7 +568,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -137345,7 +582,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.5" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/src/gz21_ocean_momentum/analysis/utils.py b/src/gz21_ocean_momentum/analysis/utils.py index 63dce58b..b6bd7c23 100755 --- a/src/gz21_ocean_momentum/analysis/utils.py +++ b/src/gz21_ocean_momentum/analysis/utils.py @@ -18,7 +18,9 @@ from scipy.ndimage import gaussian_filter from gz21_ocean_momentum.data.pangeo_catalog import get_patch, get_whole_data from cartopy.crs import PlateCarree +import yaml +from gz21_ocean_momentum.data.utils import load_training_datasets from enum import Enum @@ -166,7 +168,12 @@ def onClick(event): fig.canvas.mpl_connect("button_press_event", onClick) -def sample(data: np.ndarray, step_time: int = 1, nb_per_time: int = 5, random_state: Optional[int] = None): +def sample( + data: np.ndarray, + step_time: int = 1, + nb_per_time: int = 5, + random_state: Optional[int] = None, +): """Samples points from the data, where it is assumed that the data is 4-D, with the first dimension representing time , the second the channel, and the others representing spatial dimensions. @@ -186,7 +193,7 @@ def sample(data: np.ndarray, step_time: int = 1, nb_per_time: int = 5, random_st :nb_per_time: int, Number of points used (chosen randomly according to a uniform distribution over the spatial domain) for each image. - + :random_state: int, optional, Random state used for the random number generator. @@ -583,7 +590,6 @@ def apply_complete_mask(array, pred, uv_plotter): def plot_training_subdomains( - run_id, global_plotter: GlobalPlotter, alpha=0.5, bg_variable=None, @@ -595,15 +601,13 @@ def plot_training_subdomains( **plot_kwd_args, ): """ - Plots the training subdomains used for a given training run. Retrieves - those subdomains from the run's parameters. Additionally, provide the + Plots the training subdomains used for a training run. Retrieves + those subdomains from the training_subdomains.yaml file. Additionally, provide the latex code of a table with the latitudes and longitudes of each subdomain. Parameters ---------- - run_id : str - Id of the training run. global_plotter : GlobalPlotter DESCRIPTION. alpha : TYPE, optional @@ -618,10 +622,6 @@ def plot_training_subdomains( None. """ - # First retrieve the run's data - run = mlflow.get_run(run_id) - run_params = run.data.params - data_ids = run_params["source.run_id"].split("/") # retrieve the latex code for the table from file with open("analysis/latex_table.txt") as f: lines = f.readlines() @@ -632,32 +632,39 @@ def plot_training_subdomains( subdomain_names = "ABCDE" # Plot the map ax = global_plotter.plot(bg_variable, *plot_args, **plot_kwd_args) - for i, data_id in enumerate(data_ids): - # Recover the coordinates of the rectangular subdomain - run = mlflow.get_run(data_id) - run_params = run.data.params - lat_min, lat_max = run_params["lat_min"], run_params["lat_max"] - lon_min, lon_max = run_params["long_min"], run_params["long_max"] - lat_min, lat_max = float(lat_min), float(lat_max) - lon_min, lon_max = float(lon_min), float(lon_max) - x, y = lon_min, lat_min - width, height = lon_max - lon_min, lat_max - lat_min - ax.add_patch( - Rectangle( - (x, y), - width, - height, - facecolor=facecolor, - edgecolor=edgecolor, - linewidth=linewidth, - fill=fill, - alpha=alpha, + + # Recover the coordinates of the rectangular subdomain + with open("../../training_subdomains.yaml", encoding="utf-8") as config_file: + subdomains = yaml.full_load(config_file) + for i in range(len(subdomains)): + lat_min = dict(subdomains[i][1])["lat_min"] + lat_max = dict(subdomains[i][1])["lat_max"] + lon_min = dict(subdomains[i][1])["lon_min"] + lon_max = dict(subdomains[i][1])["lon_max"] + + lat_min, lat_max = float(lat_min), float(lat_max) + lon_min, lon_max = float(lon_min), float(lon_max) + x, y = lon_min, lat_min + width, height = lon_max - lon_min, lat_max - lat_min + ax.add_patch( + Rectangle( + (x, y), + width, + height, + facecolor=facecolor, + edgecolor=edgecolor, + linewidth=linewidth, + fill=fill, + alpha=alpha, + ) ) - ) - # Add the table line - lat_range = str(lat_min) + "\\degree, " + str(lat_max) + "\\degree" - lon_range = str(lon_min) + "\\degree, " + str(lon_max) + "\\degree" - latex_lines.append(latex_line.format(subdomain_names[i], lat_range, lon_range)) + # Add the table line + lat_range = str(lat_min) + "\\degree, " + str(lat_max) + "\\degree" + lon_range = str(lon_min) + "\\degree, " + str(lon_max) + "\\degree" + latex_lines.append( + latex_line.format(subdomain_names[i], lat_range, lon_range) + ) + latex_lines = "".join(latex_lines) latex = "".join((latex_start, latex_lines, latex_end)) print(latex) diff --git a/src/gz21_ocean_momentum/data/pangeo_catalog.py b/src/gz21_ocean_momentum/data/pangeo_catalog.py index c471acda..2e25a788 100755 --- a/src/gz21_ocean_momentum/data/pangeo_catalog.py +++ b/src/gz21_ocean_momentum/data/pangeo_catalog.py @@ -8,11 +8,6 @@ from intake.config import conf -# TODO variable currently unused? Remove? Or is it setting environment variable? -conf["persist_path"] = "/scratch/ag7531/" -# TODO variable currently unused. Remove? -CACHE_FOLDER = "/scratch/ag7531/cm26_cache" -# TODO: Not sure this should be hard coded here. Isn't it also hard coded in cmip26.py? CATALOG_URL = "https://raw.githubusercontent.com/pangeo-data/pangeo-datastore\ /master/intake-catalogs/master.yaml" @@ -52,12 +47,8 @@ def get_patch( catalog = intake.open_catalog(catalog_url) if CO2_level == 0: source = catalog.ocean.GFDL_CM2_6.GFDL_CM2_6_control_ocean_surface - # TODO variable cache_folder currently unused. Remove? - cache_folder = CACHE_FOLDER elif CO2_level == 1: source = catalog.ocean.GFDL_CM2_6.GFDL_CM2_6_one_percent_ocean_surface - # TODO variable cache_folder currently unused. Remove? - cache_folder = CACHE_FOLDER + "1percent" else: raise ValueError("Unrecognized CO2 level. Should be O or 1.") s_grid = catalog.ocean.GFDL_CM2_6.GFDL_CM2_6_grid @@ -124,8 +115,7 @@ def get_whole_data(url, c02_level): os.environ[ "GOOGLE_APPLICATION_CREDENTIALS" - ] = "/home/arthur/\ -access_key.json" + ] = "~/.config/gcloud/application_default_credentials.json" CATALOG_URL = "https://raw.githubusercontent.com/pangeo-data/pangeo-datastore\ /master/intake-catalogs/master.yaml" retrieved_data = get_whole_data(CATALOG_URL, 0) diff --git a/src/gz21_ocean_momentum/inference/main.py b/src/gz21_ocean_momentum/inference/main.py index a3f72396..25e37b5a 100755 --- a/src/gz21_ocean_momentum/inference/main.py +++ b/src/gz21_ocean_momentum/inference/main.py @@ -94,7 +94,7 @@ "start_time", "params.time_indices", "params.model_cls_name", - "params.source.run_id", + "params.source.run-id", "params.submodel", ] model_run = select_run( @@ -113,7 +113,7 @@ train_split = float(model_run["params.train_split"]) test_split = float(model_run["params.test_split"]) batch_size = batch_size if batch_size else int(model_run["params.batchsize"]) -source_data_id = model_run["params.source.run_id"] +source_data_id = model_run["params.source.run-id"] model_module_name = model_run["params.model_module_name"] model_cls_name = model_run["params.model_cls_name"] loss_cls_name = model_run["params.loss_cls_name"] diff --git a/src/gz21_ocean_momentum/trainScript.py b/src/gz21_ocean_momentum/trainScript.py index 35977150..f7d36e76 100755 --- a/src/gz21_ocean_momentum/trainScript.py +++ b/src/gz21_ocean_momentum/trainScript.py @@ -38,8 +38,8 @@ from inference.utils import create_test_dataset from inference.metrics import MSEMetric, MaxMetric import train.losses -import models.transforms -import models.submodels +from models import transforms, submodels + from utils import TaskInfo @@ -105,10 +105,16 @@ def check_str_is_None(string_in: str): ) parser = argparse.ArgumentParser(description=description) -parser.add_argument("--run-id", type=str, help="MLflow run ID of data step containing forcing data to use") +parser.add_argument( + "--run-id", + type=str, + help="MLflow run ID of data step containing forcing data to use", +) # access input forcing data via absolute filepath -parser.add_argument("--forcing-data-path", type=str, help="Filepath of the forcing data") +parser.add_argument( + "--forcing-data-path", type=str, help="Filepath of the forcing data" +) parser.add_argument("--batchsize", type=int, default=8) parser.add_argument("--n_epochs", type=int, default=100) @@ -165,9 +171,10 @@ def check_str_is_None(string_in: str): ) params = parser.parse_args() + def argparse_get_mlflow_artifact_path_or_direct_or_fail( - mlflow_artifact_name: str, params: dict[str, Any] - ) -> str: + mlflow_artifact_name: str, params: dict[str, Any] +) -> str: """Obtain a filepath either from an MLflow run ID and artifact name, or a direct path if provided. @@ -183,7 +190,9 @@ def argparse_get_mlflow_artifact_path_or_direct_or_fail( if params.run_id is not None and params.run_id != "None": if params.forcing_data_path is not None and params.forcing_data_path != "None": # got run ID and direct path: bad - raise TypeError("overlapping options provided (--forcing-data-path and --exp-id)") + raise TypeError( + "overlapping options provided (--forcing-data-path and --exp-id)" + ) # got only run ID: obtain path via MLflow mlflow.log_param("source.run-id", params.run_id) @@ -197,6 +206,7 @@ def argparse_get_mlflow_artifact_path_or_direct_or_fail( # if we get here, neither options were provided raise TypeError("require one of --run-id or --forcing-data-path") + forcings_path = argparse_get_mlflow_artifact_path_or_direct_or_fail("forcing", params) # -------------------------- @@ -265,7 +275,7 @@ def argparse_get_mlflow_artifact_path_or_direct_or_fail( for xr_dataset in xr_datasets: # TODO this is a temporary fix to implement seasonal patterns - submodel_transform = copy.deepcopy(getattr(models.submodels, submodel)) + submodel_transform = copy.deepcopy(getattr(submodels, submodel)) print(submodel_transform) xr_dataset = submodel_transform.fit_transform(xr_dataset) with ProgressBar(), TaskInfo("Computing dataset"): @@ -336,7 +346,7 @@ def argparse_get_mlflow_artifact_path_or_direct_or_fail( raise type(e)("Could not find the specified model class: " + str(e)) net = model_cls(datasets[0].n_features, criterion.n_required_channels) try: - transformation_cls = getattr(models.transforms, transformation_cls_name) + transformation_cls = getattr(transforms, transformation_cls_name) transformation = transformation_cls() transformation.indices = criterion.precision_indices net.final_transformation = transformation diff --git a/src/gz21_ocean_momentum/utils.py b/src/gz21_ocean_momentum/utils.py index 93af376e..5c678741 100755 --- a/src/gz21_ocean_momentum/utils.py +++ b/src/gz21_ocean_momentum/utils.py @@ -17,7 +17,7 @@ import gz21_ocean_momentum.models as models import sys -sys.modules["models"] = models # what are we doing here anyway +sys.modules["models"] = models # what are we doing here anyway class TaskInfo: @@ -119,7 +119,7 @@ def select_run( the store" ) print(mlflow_runs[cols]) - id_ = int(input("Run id?") or default_selection) + id_ = int(input("Select row number (first column)") or default_selection) if id_ < 0: return 0 return mlflow_runs.loc[id_, :] @@ -135,7 +135,7 @@ def pickle_artifact(run_id: str, path: str): def seed_all(seed: int = 0): random.seed(seed) # seed hash - os.environ['PYTHONHASHSEED'] = str(seed) + os.environ["PYTHONHASHSEED"] = str(seed) # seed numpy np.random.seed(seed) # seed torch