fix: remove support for fetch ROSETTA grav and mag to align with goal…

… of only providing common and widespread datasets
mdtanker · Jun 5, 2024 · 4dadc7c · 4dadc7c
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diff --git a/docs/datasets/antarctica/index.md b/docs/datasets/antarctica/index.md
@@ -36,8 +36,6 @@ modis_moa
 ---
 gravity
 magnetics
-rosetta_gravity
-rosetta_magnetics
 ```
 
 ## Geophysically-derived data

diff --git a/docs/datasets/antarctica/rosetta_gravity.ipynb b/docs/datasets/antarctica/rosetta_gravity.ipynb
diff --git a/docs/datasets/antarctica/rosetta_magnetics.ipynb b/docs/datasets/antarctica/rosetta_magnetics.ipynb
diff --git a/docs/datasets/index.md b/docs/datasets/index.md
@@ -33,8 +33,6 @@ antarctica/mass_change
 antarctica/basal_melt
 antarctica/groundingline
 antarctica/ice_boundaries
-antarctica/rosetta_gravity
-antarctica/rosetta_magnetics
 antarctica/geology
 greenland/modis_mog
 greenland/groundingline

diff --git a/docs/tutorial/fetch_walkthrough.ipynb b/docs/tutorial/fetch_walkthrough.ipynb
@@ -89,8 +89,6 @@
       "modis_mog\n",
       "moho\n",
       "rema\n",
-      "rosetta_gravity\n",
-      "rosetta_magnetics\n",
       "sediment_thickness\n"
      ]
     }

diff --git a/src/polartoolkit/fetch.py b/src/polartoolkit/fetch.py
@@ -2859,217 +2859,6 @@ def preprocessing(fname: str, action: str, _pooch2: typing.Any) -> str:
     return typing.cast(xr.DataArray, resampled)
 
 
-def rosetta_gravity(version: str = "gravity") -> pd.DataFrame:
-    """
-    Load either a shapefile of ROSETTA-ice flightlines, a dataframe of ROSETTA-Ice
-    airborne gravity data over the Ross Ice Shelf, or a dataframe of ROSETTA-Ice density
-    values from the density inversion.
-    from :footcite:t:`tintoross2019`.
-    Accessed from https://www.usap-dc.org/view/project/p0010035
-    This is only data from the first 2 of the 3 field seasons.
-    Columns:
-    Line Number: The ROSETTA-Ice survey line number, >1000 are tie lines
-    Latitude (degrees): Latitude decimal degrees WGS84
-    Longitude (degrees): Longitude decimal degrees WGS84
-    unixtime (seconds): The number of seconds that have elapsed since midnight
-    (00:00:00 UTC) on January 1st, 1970
-    Height (meters): Height above WGS84 ellipsoid
-    x (meters): Polar stereographic projected coordinates true to scale at 71° S
-    y (meters): Polar stereographic projected coordinates true to scale at 71° S
-    FAG_levelled (mGal): Levelled free air gravity
-
-    Parameters
-    ----------
-    version : str, optional
-
-    Returns
-    -------
-    pd.DataFrame
-        Returns a dataframe containing the gravity, density, or flightline data
-
-    References
-    ----------
-    .. footbibliography::
-    """
-
-    if version == "shapefile":
-        path = pooch.retrieve(
-            url="http://wonder.ldeo.columbia.edu/data/ROSETTA-Ice/GridInformation/Shapefile/ROSETTA-Ice_Grid_Flown_Shapefile.zip",
-            fname="ROSETTA-Ice_Grid_Flown_Shapefile.zip",
-            path=f"{pooch.os_cache('pooch')}/polartoolkit/gravity",
-            known_hash="17e0026fe386503d74c679a6091235e2394fb269030f5555372e55bdf61f6946",
-            progressbar=True,
-            processor=pooch.Unzip(),
-        )
-        # path to shapefile
-        fname = next(p for p in path if p.endswith(".shp"))
-
-        # read the file into a geodataframe
-        df = pyogrio.read_dataframe(fname)
-    elif version == "gravity":
-        path = pooch.retrieve(
-            url="http://wonder.ldeo.columbia.edu/data/ROSETTA-Ice/Gravity/rs_2019_grav.csv",
-            fname="ROSETTA_2019_grav.csv",
-            path=f"{pooch.os_cache('pooch')}/polartoolkit/gravity",
-            known_hash="d4fdfcc293ac13e6222938bfa9e1e9ccc781ea7556a13d356e9f1b4aba809928",
-            progressbar=True,
-        )
-
-        df = pd.read_csv(path)
-
-        # convert line numbers into float format (L200 -> 200)
-        df.Line = df.Line.str[1:]
-        df["Line"] = pd.to_numeric(df["Line"])
-
-    elif version == "density":
-        path = pooch.retrieve(
-            url="http://wonder.ldeo.columbia.edu/data/ROSETTA-Ice/DerivedProducts/Density/rs_2019_density.csv",
-            fname="rs_2019_density.csv",
-            path=f"{pooch.os_cache('pooch')}/polartoolkit/gravity",
-            known_hash="8c3d6f69087095ab1a184d0517a136ebd59e4761110601b30da1ef3685883617",
-            progressbar=True,
-        )
-
-        df = pd.read_csv(path)
-
-        # convert line numbers into float format (L200 -> 200)
-        df.Line = df.Line.str[1:]
-        df["Line"] = pd.to_numeric(df["Line"])
-
-    return df
-
-
-def rosetta_magnetics() -> pd.DataFrame:
-    """
-    Load  a dataframe of ROSETTA-Ice airborne magnetics data over the Ross Ice Shelf
-    from :footcite:t:`tintoross2019`.
-
-    Accessed from https://www.usap-dc.org/view/project/p0010035
-    Columns:
-    Line Number: The ROSETTA-Ice survey line number, >1000 are tie lines
-    Latitude (degrees): Latitude decimal degrees WGS84
-    Longitude (degrees): Longitude decimal degrees WGS84
-    unixtime (seconds): The number of seconds that have elapsed since midnight
-    (00:00:00 UTC) on January 1st, 1970
-    H_Ell (meters): Height above WGS84 ellipsoid
-    x (meters): Polar stereographic projected coordinates true to scale at 71° S
-    y (meters): Polar stereographic projected coordinates true to scale at 71° S
-    Mag_anomaly (nT): magnetic anomaly
-
-    Returns
-    -------
-    pd.DataFrame
-        Returns a dataframe containing the data
-
-    References
-    ----------
-    .. footbibliography::
-    """
-    url = "http://wonder.ldeo.columbia.edu/data/ROSETTA-Ice/Magnetics/rs_2019_mag.csv"
-    fname = "rs_2019_mag.csv"
-
-    path = pooch.retrieve(
-        url=url,
-        fname=fname,
-        path=f"{pooch.os_cache('pooch')}/polartoolkit/magnetics",
-        known_hash="6a87e59b86888a2cd669012c6ad49ea5e563d1a9759da574d5a9f9b5aa978b70",
-        progressbar=True,
-    )
-
-    df = pd.read_csv(path)
-
-    # convert line numbers into float format (L200 -> 200)
-    df.Line = df.Line.str[1:]
-    df["Line"] = pd.to_numeric(df["Line"])
-
-    # drop rows with height or mag data
-    return df.dropna(subset=["H_Ell", "Mag_anomaly"])
-
-
-# def rosetta_radar_data(version: str="basal_melt") -> pd.DataFrame:
-#     """
-#     Load ice thickness, basal melt rate, and basal melt rate errors from the
-#     ROSETTA-Ice radar data.
-
-#     from Das et al. (2020). Multi-decadal basal melt rates and structure of the Ross
-#     Ice Shelf, Antarctica using airborne ice penetrating radar. Journal of Geophysical
-#     Research: Earth Surface, 125 (doi:10.1029/2019JF005241)
-
-#     Accessed from https://www.usap-dc.org/view/dataset/601242
-
-#     or from http://wonder.ldeo.columbia.edu/data/ROSETTA-Ice/DerivedProducts/
-
-#     CURRENTLY NOT WORKING DUE TO RECAPTCHA ON USAP-DC WEBSITE
-
-#     Parameters
-#     ----------
-#     version : str, optional
-
-#     Returns
-#     -------
-#     pd.DataFrame
-#         Returns a dataframe containing the data
-#     """
-
-#     if version == "total_thickness":
-#         url = "https://www.usap-dc.org/dataset/usap-dc/601242/2020-01-10T17:37:09.5Z/DICE_Total_IceThickness_Das_JGR2020.txt"  # noqa: E501
-#         fname = "DICE_Total_IceThickness_Das_JGR2020.txt"
-#         # known_hash="md5:615463dbf98d7a44ce1d36b0a66f49a3"
-#         known_hash = None
-
-#         path = pooch.retrieve(
-#             url=url,
-#             fname=fname,
-#             path=f"{pooch.os_cache('pooch')}/polartoolkit/ROSETTA_radar_data",
-#             known_hash=known_hash,
-#             progressbar=True,
-#         )
-#         df = pd.read_csv(path)
-
-#     elif version == "basal_melt":
-#         url = "https://www.usap-dc.org/dataset/usap-dc/601242/2020-01-10T17:37:09.5Z/BasalMelt_Das_JGR2020.txt"  # noqa: E501
-#         fname = "BasalMelt_Das_JGR2020.txt"
-#         # known_hash="md5:08c5ae638cb72cf81ac022d58f7df7a9"
-#         known_hash = None
-
-#         path = pooch.retrieve(
-#             url=url,
-#             fname=fname,
-#             path=f"{pooch.os_cache('pooch')}/polartoolkit/ROSETTA_radar_data",
-#             known_hash=known_hash,
-#             progressbar=True,
-#         )
-#         df = pd.read_csv(
-#             path,
-#             header=None,
-#             delim_whitespace=True,
-#             names=["lon", "lat", "melt"],
-#         )
-
-#         # re-project to polar stereographic
-#         transformer = Transformer.from_crs("epsg:4326", "epsg:3031")
-#         df["easting"], df["northing"] = transformer.transform(
-#             df.lat.tolist(), df.lon.tolist()
-#         )
-
-#     elif version == "basal_melt_error":
-#         url = "https://www.usap-dc.org/dataset/usap-dc/601242/2020-01-10T17:37:09.5Z/ErrorAnalysis_BasalMelt_Das_JGR2020.txt"  # noqa: E501
-#         fname = "ErrorAnalysis_BasalMelt_Das_JGR2020.txt"
-#         # known_hash="md5:23d99479dd6a3d1358b9f3b62c6738c0"
-#         known_hash = None
-
-#         path = pooch.retrieve(
-#             url=url,
-#             fname=fname,
-#             path=f"{pooch.os_cache('pooch')}/polartoolkit/ROSETTA_radar_data",
-#             known_hash=known_hash,
-#             progressbar=True,
-#         )
-#         df = pd.read_csv(path)
-
-#     return df
-
-
 def magnetics(
     version: str,
     region: tuple[float, float, float, float] | None = None,

diff --git a/tests/test_fetch.py b/tests/test_fetch.py
@@ -915,68 +915,6 @@ def test_gravity(test_input, expected):
 # utils.get_grid_info(grid)
 
 
-# %% ROSETTA radar
-
-
-# @pytest.mark.fetch
-# def test_rosetta_radar():
-#     df = fetch.rosetta_radar_data()
-#     # expected = [
-#     #     547.0122703054126,
-#     #     -80.63749846487134,
-#     #     -43.287329630685,
-#     #     1448416752.058848,
-#     #     -100568.55304355593,
-#     #     -987321.56515563,
-#     #     789.0193522081788,
-#     #     -0.6843365719042627,
-#     # ]
-#     print(df.describe().iloc[1].tolist())
-#     # assert df.describe().iloc[1].tolist() == pytest.approx(expected, rel=0.1)
-
-
-# %% ROSETTA magnetics
-
-
-@pytest.mark.fetch()
-def test_rosetta_magnetics():
-    df = fetch.rosetta_magnetics()
-    expected = [
-        547.0122703054126,
-        -80.63749846487134,
-        -43.287329630685,
-        1448416752.058848,
-        -100568.55304355593,
-        -987321.56515563,
-        789.0193522081788,
-        -0.6843365719042627,
-    ]
-    assert df.describe().iloc[1].tolist() == pytest.approx(expected, rel=0.1)
-
-
-# %% ROSETTA gravity
-
-
-@pytest.mark.fetch()
-def test_rosetta_gravity():
-    df = fetch.rosetta_gravity()
-    expected = [
-        661.2195503654474,
-        -80.57119757556714,
-        -36.74185651880941,
-        1457514923.0469708,
-        793.0566192217011,
-        -84278.81094301463,
-        -1000705.4912593851,
-        -40.83496413480705,
-    ]
-    assert df.describe().iloc[1].tolist() == pytest.approx(expected, rel=0.1)
-
-
-# df = fetch.rosetta_gravity()
-# # get mean values of each column
-# df.describe().iloc[1].tolist()
-
 # %% magnetics
 
 magnetics_test = [