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New sampler API #70

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New sampler API #70

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8e1eff6
Rollup: New sampler API -> support for emcee (#68)
cdcapano Aug 22, 2018
3f60371
Update plotting (#71)
cdcapano Sep 25, 2018
b29dd38
Update emcee pt (#73)
cdcapano Sep 25, 2018
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336 changes: 62 additions & 274 deletions bin/gwin
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61 changes: 32 additions & 29 deletions bin/gwin_plot_movie
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ from matplotlib import pyplot
import pycbc.results
from pycbc import transforms

from gwin import (__version__, option_utils)
from gwin import (__version__, option_utils, io)
from gwin.results.scatter_histograms import (create_multidim_plot,
get_scale_fac)

Expand Down Expand Up @@ -91,12 +91,12 @@ def integer_logspace(start, end, num):
out[start_idx:len(x)+start_idx] = x
return out

parser = argparse.ArgumentParser()

# we won't add thinning arguments nor iteration, since this is determined by
# the frame number/step options
skip_args = ['thin-start', 'thin-interval', 'thin-end', 'iteration']
parser = io.ResultsArgumentParser(skip_args=skip_args)
parser.add_argument("--version", action="version", version=__version__,
help="show version number and exit")
parser.add_argument("--input-file", type=str, required=True,
help="Results file path.")
parser.add_argument("--start-sample", type=int, default=1,
help="Start sample for the first frame. Note: sample "
"counting starts from 1. Default is 1.")
Expand All @@ -117,10 +117,6 @@ parser.add_argument("--log-steps", action="store_true", default=False,
parser.add_argument("--output-prefix", type=str, required=True,
help="Output path and prefix for the frame files "
"(without extension).")
parser.add_argument("--parameters", type=str, nargs="+",
metavar="PARAM[:LABEL]",
help="Name of parameters to plot in same format "
"as for pycbc_inference_plot_posterior.")
parser.add_argument('--verbose', action='store_true')
parser.add_argument('--dpi', type=int, default=200,
help='Set the dpi for each frame; default is 200')
Expand All @@ -144,10 +140,12 @@ option_utils.add_density_option_group(parser)
opts = parser.parse_args()
pycbc.init_logging(opts.verbose)

if len(opts.input_file) > 1:
raise ValueError("this program can only plot one file at a time")

# Get data
logging.info('Loading parameters')
fp, parameters, labels, _ = option_utils.results_from_cli(opts,
load_samples=False)
fp, parameters, labels, _ = io.results_from_cli(opts, load_samples=False)

if opts.end_sample is None:
opts.end_sample = fp.niterations
Expand Down Expand Up @@ -190,31 +188,29 @@ else:
raise ValueError("At least one of frame-number or frame-step must be "
"provided.")

# get samples from InferenceFile
# get the samples
file_parameters, trans = transforms.get_common_cbc_transforms(
parameters, fp.variable_params)
samples = fp.read_samples(file_parameters, thin_start=thin_start,
thin_interval=thinint, thin_end=thin_end,
iteration=itermask, flatten=False)
samples = fp.samples_from_cli(opts, file_parameters, thin_start=thin_start,
thin_interval=thinint, thin_end=thin_end,
iteration=itermask, flatten=False)
samples = transforms.apply_transforms(samples, trans)
if samples.ndim > 2:
# multi-tempered samplers will return a 3 dims, so flatten
# multi-tempered samplers will return 3 dims, so flatten
_, ii, jj = samples.shape
samples = samples.reshape((ii, jj))

# Get z-values
if opts.z_arg is not None:
logging.info("Getting model stats")
z_arg, zlbl = option_utils.parse_parameters_opt([opts.z_arg])
z_arg = z_arg[0]
zlbl = zlbl[z_arg]
model_stats = fp.read_model_stats(thin_start=thin_start,
thin_end=thin_end, thin_interval=thinint, iteration=itermask,
flatten=False)
if model_stats.ndim > 2:
_, ii, jj = model_stats.shape
model_stats = model_stats.reshape((ii, jj))
zvals = model_stats[z_arg]
logging.info("Getting samples for colorbar")
zsamples = fp.samples_from_cli(opts, opts.z_arg, thin_start=thin_start,
thin_interval=thinint, thin_end=thin_end,
iteration=itermask, flatten=False)
zlbl = opts.z_arg_labels[opts.z_arg]
if zsamples.ndim > 2:
_, ii, jj = zsamples.shape
zsamples = zsamples.reshape((ii, jj))
zvals = zsamples[opts.z_arg]
show_colorbar = True
# Set common min and max for colorbar in all plots
if opts.vmin is None:
Expand All @@ -236,17 +232,24 @@ fp.close()
# get injection values if desired
expected_parameters = {}
if opts.plot_injection_parameters:
injections = option_utils.injections_from_cli(opts)
injections = io.injections_from_cli(opts)
for p in parameters:
# check that all of the injections are the same
unique_vals = numpy.unique(injections[p])
try:
vals = injections[p]
except NameError:
# injection doesn't have this parameter, skip
logging.warn("Could not find injection parameter {}".format(p))
continue
unique_vals = numpy.unique(vals)
if unique_vals.size != 1:
raise ValueError("More than one injection found! To use "
"plot-injection-parameters, there must be a single unique "
"injection in all input files. Use the expected-parameters "
"option to specify an expected parameter instead.")
# passed: use the value for the expected
expected_parameters[p] = unique_vals[0]

# get expected parameter values from command line
expected_parameters.update(option_utils.expected_parameters_from_cli(opts))
expected_parameters_color = opts.expected_parameters_color
Expand Down
87 changes: 32 additions & 55 deletions bin/gwin_plot_posterior
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Original file line number Diff line number Diff line change
Expand Up @@ -37,88 +37,62 @@ from matplotlib import (patches, use)
import pycbc
import pycbc.version
from pycbc.results import metadata
from pycbc.results.scatter_histograms import create_multidim_plot

from gwin import (__version__, option_utils)
from gwin import (__version__, option_utils, io)
from gwin.results.scatter_histograms import create_multidim_plot

use('agg')

# add options to command line
parser = argparse.ArgumentParser()
parser = io.ResultsArgumentParser()
# program-specific
parser.add_argument("--version", action="version", version=__version__,
help="Prints version information.")
parser.add_argument("--output-file", type=str, required=True,
help="Output plot path.")
parser.add_argument("--verbose", action="store_true", default=False,
help="Be verbose")
parser.add_argument("--input-file-labels", nargs="+", default=None,
help="Labels to add to plot if using more than one"
"input file.")

# add options for what plots to create
option_utils.add_plot_posterior_option_group(parser)

# scatter configuration
option_utils.add_scatter_option_group(parser)

# density configuration
option_utils.add_density_option_group(parser)

# add standard option utils
option_utils.add_inference_results_option_group(parser)

# parse command line
opts = parser.parse_args()

# set logging
pycbc.init_logging(opts.verbose)

# get parameters
logging.info("Loading parameters")
fp, parameters, labels, samples = option_utils.results_from_cli(opts)
# load the samples
fps, parameters, labels, samples = io.results_from_cli(opts)

# typecast to list so the input files can be iterated over
fp = fp if isinstance(fp, list) else [fp]
parameters = parameters if isinstance(parameters[0], list) else [parameters]
labels = labels if isinstance(labels[0], list) else [labels]
fps = fps if isinstance(fps, list) else [fps]
samples = samples if isinstance(samples, list) else [samples]

# get likelihood statistic values
# if a z-arg is specified, load samples for it
if opts.z_arg is not None:
logging.info("Getting model stats")

z_arg, f_zlbl = option_utils.parse_parameters_opt([opts.z_arg])
z_arg = z_arg[0]
f_zlbl = f_zlbl[z_arg]

# lists to hold z-axis values and labels for each input file
logging.info("Getting samples for colorbar")
zlbl = opts.z_arg_labels[opts.z_arg]
zvals = []
zlbl = []

# loop over each input file and append z-axis values and labels to lists
for f in fp:
model_stats = f.read_model_stats(
thin_start=opts.thin_start, thin_end=opts.thin_end,
thin_interval=opts.thin_interval, iteration=opts.iteration)
zvals.append(model_stats[z_arg])
zlbl.append(f_zlbl)
f.close()

# else there are no z-axis values
for fp in fps:
zsamples = fp.samples_from_cli(opts, parameters=opts.z_arg)
zvals.append(zsamples[opts.z_arg])
else:
zvals = None
zlbl = None
for f in fp:
f.close()

# determine if colorbar should be shown
show_colorbar = True if opts.z_arg else False
# closet the files, we don't need them anymore
for fp in fps:
fp.close()

# if no plotting options selected, then the default options are based
# on the number of parameters
plot_options = [opts.plot_marginal, opts.plot_scatter, opts.plot_density]
if not numpy.any(plot_options):
if len(parameters[0]) == 1:
if len(parameters) == 1:
opts.plot_marginal = True
else:
opts.plot_scatter = True
Expand All @@ -132,7 +106,7 @@ if not numpy.any(plot_options):
mins, maxs = option_utils.plot_ranges_from_cli(opts)

# add any missing parameters
for p in parameters[0]:
for p in parameters:
if p not in mins:
mins[p] = numpy.array([s[p].min() for s in samples]).min()
if p not in maxs:
Expand All @@ -141,10 +115,16 @@ for p in parameters[0]:
# get injection values if desired
expected_parameters = {}
if opts.plot_injection_parameters:
injections = option_utils.injections_from_cli(opts)
for p in parameters[0]:
injections = io.injections_from_cli(opts)
for p in parameters:
# check that all of the injections are the same
unique_vals = numpy.unique(injections[p])
try:
vals = injections[p]
except NameError:
# injection doesn't have this parameter, skip
logging.warn("Could not find injection parameter {}".format(p))
continue
unique_vals = numpy.unique(vals)
if unique_vals.size != 1:
raise ValueError("More than one injection found! To use "
"plot-injection-parameters, there must be a single unique "
Expand All @@ -162,7 +142,7 @@ colors = itertools.cycle(["black"] + ["C{}".format(i) for i in range(10)])
# plot each input file
logging.info("Plotting")
hist_colors = []
for i, (p, l, s) in enumerate(zip(parameters, labels, samples)):
for (i, s) in enumerate(samples):

# on first iteration create figure otherwise update old figure
if i == 0:
Expand All @@ -185,13 +165,13 @@ for i, (p, l, s) in enumerate(zip(parameters, labels, samples)):

# plot
fig, axis_dict = create_multidim_plot(
p, s, labels=l, fig=fig, axis_dict=axis_dict,
parameters, s, labels=labels, fig=fig, axis_dict=axis_dict,
plot_marginal=opts.plot_marginal,
marginal_percentiles=opts.marginal_percentiles,
plot_scatter=opts.plot_scatter,
zvals=zvals[i] if zvals is not None else None,
show_colorbar=show_colorbar,
cbar_label=zlbl[i] if zlbl is not None else None,
show_colorbar=opts.z_arg is not None,
cbar_label=zlbl,
vmin=opts.vmin, vmax=opts.vmax,
scatter_cmap=opts.scatter_cmap,
plot_density=opts.plot_density,
Expand All @@ -208,7 +188,7 @@ for i, (p, l, s) in enumerate(zip(parameters, labels, samples)):
expected_parameters_color=opts.expected_parameters_color)

# add legend to upper right for input files
if opts.input_file_labels:
if len(opts.input_file) > 1:
handles = []
for color, label in zip(hist_colors, opts.input_file_labels):
handles.append(patches.Patch(color=color, label=label))
Expand All @@ -218,9 +198,6 @@ if opts.input_file_labels:
# set DPI
fig.set_dpi(200)

# set tight layout
fig.set_tight_layout(True)

# save
metadata.save_fig_with_metadata(
fig, opts.output_file, {},
Expand Down
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