Update precommit and fix for release (#62)

* Update precommit

* Fix lint complaints

* Add fix for FillValue decoding in xr.decode_cf with numpy 2.0

* Update coverage settings

.coveragerc

@@ -11,6 +11,9 @@ omit =
 	gpm/visualization/animation.py
 	gpm/utils/pyresample.py
 	gpm/utils/collocation.py
+	gpm/utils/gv.py
+	gpm/utils/zonal_stats.py
+	gpm/xradar/*
 	gpm/_version.py
 
 [report]

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 ---
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v4.6.0
     hooks:
       - id: trailing-whitespace
       - id: end-of-file-fixer
@@ -12,12 +12,12 @@ repos:
       - id: check-ast
       - id: check-added-large-files
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.3.5
+    rev: v0.5.7
     hooks:
       - id: ruff
         args: [--fix]
   - repo: https://github.com/psf/black
-    rev: 24.3.0
+    rev: 24.8.0
     hooks:
       - id: black
         language_version: python3
@@ -27,18 +27,18 @@ repos:
       - id: blackdoc
         additional_dependencies: ["black[jupyter]"]
   - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: "v3.1.0"
+    rev: "v4.0.0-alpha.8"
     hooks:
       - id: prettier
         types_or: [yaml, html, css, scss, javascript, json] # markdown to avoid conflicts with mdformat
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.2.6
+    rev: v2.3.0
     hooks:
       - id: codespell
         types_or: [python, markdown, rst]
         additional_dependencies: [tomli]
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.15.2
+    rev: v3.17.0
     hooks:
       - id: pyupgrade
   - repo: https://github.com/MarcoGorelli/madforhooks
@@ -58,7 +58,7 @@ repos:
       - id: nbstripout
         args: [--keep-output]
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.8.5
+    rev: 1.8.7
     hooks:
       - id: nbqa-black
       - id: nbqa-ruff

gpm/checks.py

@@ -94,7 +94,8 @@ def _has_vertical_dim_dataarray(da, strict):
     vertical_dims = list(get_vertical_dimension(da))
     if not vertical_dims:
         return False
-    if strict and len(da.dims) != 1:  # only the vertical dim
+    only_vertical_dim = len(da.dims) == 1
+    if strict and not only_vertical_dim:  # noqa
         return False
     return True
 
@@ -104,7 +105,8 @@ def _has_frequency_dim_dataarray(da, strict):
     frequency_dims = list(get_frequency_dimension(da))
     if not frequency_dims:
         return False
-    if strict and len(da.dims) != 1:  # only the frequency dimension
+    only_frequency_dim = len(da.dims) == 1
+    if strict and not only_frequency_dim:  # noqa
         return False
     return True
 
@@ -114,29 +116,23 @@ def _has_vertical_dim_dataset(ds, strict):
     has_vertical = np.any(
         [_has_vertical_dim_dataarray(ds[var], strict=strict) for var in get_dataset_variables(ds)],
     ).item()
-    if has_vertical:
-        return True
-    return False
+    return bool(has_vertical)
 
 
 def _has_spatial_dim_dataset(ds, strict):
     """Check if at least one xarray.DataArrays of a xarray.Dataset have at least one spatial dimension."""
     has_spatial = np.any(
         [_has_spatial_dim_dataarray(ds[var], strict=strict) for var in get_dataset_variables(ds)],
     ).item()
-    if has_spatial:
-        return True
-    return False
+    return bool(has_spatial)
 
 
 def _has_frequency_dim_dataset(ds, strict):
     """Check if at least one xarray.DataArrays of a xarray.Dataset have a frequency dimension."""
     has_spatial = np.any(
         [_has_frequency_dim_dataarray(ds[var], strict=strict) for var in get_dataset_variables(ds)],
     ).item()
-    if has_spatial:
-        return True
-    return False
+    return bool(has_spatial)
 
 
 def _check_xarray_conditions(da_condition, ds_condition, xr_obj, strict, squeeze):
@@ -207,9 +203,7 @@ def _is_grid_expected_spatial_dims(spatial_dims):
     is_grid = set(spatial_dims) == set(GRID_SPATIAL_DIMS)
     is_lonlat = set(spatial_dims) == {"latitude", "longitude"}
     is_xy = set(spatial_dims) == {"y", "x"}
-    if is_grid or is_lonlat or is_xy:
-        return True
-    return False
+    return bool(is_grid or is_lonlat or is_xy)
 
 
 def _is_orbit_expected_spatial_dims(spatial_dims):
@@ -223,19 +217,14 @@ def _is_orbit_expected_spatial_dims(spatial_dims):
     # Check if spatial_dims is a non-empty subset of ORBIT_SPATIAL_DIMS
     is_orbit = set(spatial_dims).issubset(ORBIT_SPATIAL_DIMS) and bool(spatial_dims)
     is_xy = set(spatial_dims).issubset({"y", "x"}) and bool(spatial_dims)
-
-    if is_orbit or is_xy:
-        return True
-    return False
+    return bool(is_orbit or is_xy)
 
 
 def _is_expected_spatial_dims(spatial_dims):
     """Check that the spatial_dims are the expected two."""
     is_orbit = _is_orbit_expected_spatial_dims(spatial_dims)
     is_grid = _is_grid_expected_spatial_dims(spatial_dims)
-    if is_orbit or is_grid:
-        return True
-    return False
+    return bool(is_orbit or is_grid)
 
 
 def is_orbit(xr_obj):
@@ -255,9 +244,7 @@ def is_orbit(xr_obj):
     # Check that swath coords exists
     # - Swath objects are determined by 1D (nadir looking) and 2D coordinates
     x_coord, y_coord = _get_swath_dim_coords(xr_obj)
-    if x_coord is not None and y_coord is not None:
-        return True
-    return False
+    return bool(x_coord is not None and y_coord is not None)
 
 
 def is_grid(xr_obj):
@@ -278,9 +265,7 @@ def is_grid(xr_obj):
     # - 1D coordinates: projection coordinates
     # - 2D coordinates: lon/lat coordinates of each pixel
     x_coord, y_coord = _get_proj_dim_coords(xr_obj)
-    if x_coord is not None and y_coord is not None:
-        return True
-    return False
+    return bool(x_coord is not None and y_coord is not None)
 
 
 ####-------------------------------------------------------------------------------------
@@ -298,7 +283,7 @@ def _is_spatial_2d_dataarray(da, strict):
     vertical_dims = get_vertical_dimension(da)
     if vertical_dims:
         return False
-    if strict and len(da.dims) != 2:
+    if strict and len(da.dims) != 2:  # noqa
         return False
 
     return True
@@ -313,7 +298,7 @@ def _is_spatial_3d_dataarray(da, strict):
     vertical_dims = get_vertical_dimension(da)
     if not vertical_dims:
         return False
-    if strict and len(da.dims) != 3:
+    if strict and len(da.dims) != 3:  # noqa
         return False
 
     return True
@@ -329,7 +314,7 @@ def _is_transect_dataarray(da, strict):
     if not vertical_dims:
         return False
 
-    if strict and len(da.dims) != 2:
+    if strict and len(da.dims) != 2:  # noqa
         return False
 
     return True
@@ -341,9 +326,7 @@ def _check_dataarrays_condition(condition, ds, strict):
     all_valid = np.all(
         [condition(ds[var], strict=strict) for var in get_dataset_variables(ds)],
     )
-    if all_valid.item():
-        return True
-    return False
+    return bool(all_valid)
 
 
 def _is_spatial_2d_dataset(ds, strict):

gpm/dataset/conventions.py

@@ -148,6 +148,7 @@ def finalize_dataset(ds, product, decode_cf, scan_mode, start_time=None, end_tim
 
     ##------------------------------------------------------------------------.
     # Decode dataset
+    # - With numpy > 2.0, the _FillValue attribute must be a numpy scalar so that CF decoding is applied
     # - _FillValue is moved from attrs to encoding !
     if decode_cf:
         ds = apply_cf_decoding(ds)

gpm/dataset/decoding/cf.py

@@ -27,7 +27,9 @@
 """This module contains functions to CF-decoding the GPM files."""
 import warnings
 
+import numpy as np
 import xarray as xr
+from packaging import version
 
 
 def apply_cf_decoding(ds):
@@ -36,6 +38,13 @@ def apply_cf_decoding(ds):
     For more information on CF-decoding, read:
         https://docs.xarray.dev/en/stable/generated/xarray.decode_cf.html
     """
+    # Take care of numpy 2.0 FillValue CF Decoding issue
+    if version.parse(np.__version__) >= version.parse("2.0.0"):
+        vars_and_coords = list(ds.data_vars) + list(ds.coords)
+        for var in vars_and_coords:
+            if "_FillValue" in ds[var].attrs:
+                ds[var].attrs["_FillValue"] = ds[var].data.dtype.type(ds[var].attrs["_FillValue"])
+
     # Decode with xr.decode_cf
     with warnings.catch_warnings():
         warnings.simplefilter(action="ignore", category=FutureWarning)

gpm/dataset/decoding/coordinates.py

@@ -57,7 +57,7 @@ def add_lh_height(ds):
     # Fixed heights for 2HSLH and 2HCSH
     # - FileSpec v7: p.2395, 2463
     # NOTE: In SLH/CSH, the first row of the array correspond to the surface
-    # Instead, for the other GPM RADAR prodcuts, is the last row that correspond to the surface !!!
+    # Instead, for the other GPM RADAR products, is the last row that correspond to the surface !!!
     height = np.linspace(0.25 / 2, 20 - 0.25 / 2, 80) * 1000  # in meters
     ds = ds.assign_coords({"height": ("range", height)})
     ds["height"].attrs["units"] = "m a.s.l"

gpm/retrievals/retrieval_1b_radar.py

@@ -285,7 +285,7 @@ def get_dielectric_constant(ds, dielectric_constant=None):
         if value == -9999.9:
             value = 0.9255
     else:
-        ValueError("Expecting a radar product.")
+        raise ValueError("Expecting a radar product.")
     return value
 
 
@@ -306,7 +306,7 @@ def get_radar_wavelength(ds):
         elif "PR" in product:
             eqvWavelength = default_dict["PR"]
         else:
-            ValueError("Expecting a radar product.")
+            raise ValueError("Expecting a radar product.")
     return eqvWavelength
 
 

gpm/tests/test_bucket/test_partitioning.py

@@ -1210,7 +1210,7 @@ def test_justified_label_xy(self):
 
     def test_justified_labels_single_level(self):
         """Test labels justification of single-level 2D TilePartitioning."""
-        size = (10, 10)  #
+        size = (10, 10)
         extent = [-180, 180, -90, 90]
         n_levels = 1
         origin = "bottom"

gpm/tests/test_io/test_products.py

@@ -176,18 +176,18 @@ def test_get_sensor_satellite_names():
         },
     }
 
-    assert ["SSMIS"] == _get_sensor_satellite_names(info_dict, key="sensor", combine_with=None)
-    assert ["F18"] == _get_sensor_satellite_names(info_dict, key="satellite", combine_with=None)
-    assert ["SSMIS-F18"] == _get_sensor_satellite_names(
+    assert _get_sensor_satellite_names(info_dict, key="sensor", combine_with=None) == ["SSMIS"]
+    assert _get_sensor_satellite_names(info_dict, key="satellite", combine_with=None) == ["F18"]
+    assert _get_sensor_satellite_names(
         info_dict,
         key="satellite",
         combine_with="sensor",
-    )
-    assert ["SSMIS-F18"] == _get_sensor_satellite_names(
+    ) == ["SSMIS-F18"]
+    assert _get_sensor_satellite_names(
         info_dict,
         key="sensor",
         combine_with="satellite",
-    )
+    ) == ["SSMIS-F18"]
 
 
 @pytest.mark.parametrize("full", [True, False])

gpm/utils/checks.py

@@ -373,9 +373,7 @@ def has_regular_time(xr_obj):
     """Return True if all timesteps are regular. False otherwise."""
     list_discontinuous_slices = get_slices_non_regular_time(xr_obj)
     n_discontinuous = len(list_discontinuous_slices)
-    if n_discontinuous > 0:
-        return False
-    return True
+    return n_discontinuous == 0
 
 
 ####--------------------------------------------------------------------------.
@@ -648,9 +646,7 @@ def has_contiguous_scans(
         cross_track_dim=cross_track_dim,
     )
     n_discontinuous = len(list_discontinuous_slices)
-    if n_discontinuous > 0:
-        return False
-    return True
+    return n_discontinuous == 0
 
 
 ####--------------------------------------------------------------------------.
@@ -830,9 +826,7 @@ def has_valid_geolocation(
         )
         n_invalid_scan_slices = len(list_invalid_slices)
         return n_invalid_scan_slices == 0
-    if is_grid(xr_obj):
-        return True
-    return False
+    return bool(is_grid(xr_obj))
 
 
 def apply_on_valid_geolocation(function):

gpm/utils/slices.py

@@ -296,7 +296,7 @@ def ensure_is_slice(slc):
     elif isinstance(slc, np.ndarray) and slc.size == 1:
         slc = slice(slc.item(), slc.item() + 1)
     else:
-        raise ValueError("Impossibile to convert to a slice object.")
+        raise ValueError("Impossible to convert to a slice object.")
     return slc
 
 

gpm/utils/subsetting.py

@@ -35,9 +35,8 @@ def is_1d_non_dimensional_coord(xr_obj, coord):
         return False
     if xr_obj[coord].ndim != 1:
         return False
-    if xr_obj[coord].dims[0] == coord:  # 1D dimension coordinate
-        return False
-    return True
+    is_1d_dim_coord = xr_obj[coord].dims[0] == coord
+    return not is_1d_dim_coord
 
 
 def _get_dim_of_1d_non_dimensional_coord(xr_obj, coord):

pyproject.toml

@@ -49,6 +49,8 @@ dependencies = [
     "matplotlib>=3.8.3", # introduce pcolormesh rgb
     "cartopy>=0.22.0",
     "pyproj",
+    "numpy",
+    "pandas",
     "scipy",
     "pycolorbar",
 ]