enable testing for PEP8 rule N802

pyproject.toml

@@ -270,6 +270,7 @@ select = [
   "D",
   "E",
   "F",
+  "N802",
   "W"
 ]
 

tests/test_analog.py

@@ -196,7 +196,7 @@ def test_compare_with_matlab(self):
 
 
 class TestKS:
-    def test_1D_ks_2samp(self, random):
+    def test_1D_ks_2samp(self, random):  # noqa: N802
         # Compare with scipy.stats.ks_2samp
         x = random.standard_normal(50) + 1
         y = random.standard_normal(50)
@@ -210,7 +210,7 @@ def test_compare_with_matlab(self):
         assert_almost_equal(dm, 0.96667, 4)
 
 
-def analytical_KLDiv(p, q):
+def analytical_KLDiv(p, q):  # noqa: N802
     """Return the Kullback-Leibler divergence between two distributions.
 
     Parameters

tests/test_cffwis.py

@@ -389,7 +389,7 @@ def test_fire_weather_ufunc_errors(
             ),
         ],
     )
-    def test_fire_season_R(self, open_dataset, key, kwargs):
+    def test_fire_season_R(self, open_dataset, key, kwargs):  # noqa: N802
         expected = self._get_cffdrs_fire_season(key)
         in_ds = open_dataset("FWI/cffdrs_test_wDC.nc")
         nid = int(key[2])

tests/test_indicators.py

@@ -265,8 +265,10 @@ def test_module():
     """Translations are keyed according to the module where the indicators are defined."""
     assert atmos.tg_mean.__module__.split(".")[2] == "atmos"
     # Virtual module also are stored under xclim.indicators
-    assert xclim.indicators.cf.fg.__module__ == "xclim.indicators.cf"
-    assert xclim.indicators.icclim.GD4.__module__ == "xclim.indicators.icclim"
+    assert xclim.indicators.cf.fg.__module__ == "xclim.indicators.cf"  # noqa: F821
+    assert (
+        xclim.indicators.icclim.GD4.__module__ == "xclim.indicators.icclim"
+    )  # noqa: F821
 
 
 def test_temp_unit_conversion(tas_series):
@@ -377,7 +379,7 @@ def test_multiindicator(tas_series):
         compute=uniindtemp_compute,
     )
     with pytest.raises(ValueError, match="Indicator minmaxtemp4 was wrongly defined"):
-        tmin, tmax = ind(tas, freq="YS")
+        _tmin, _tmax = ind(tas, freq="YS")
 
 
 def test_missing(tas_series):
@@ -604,7 +606,7 @@ def test_default_formatter():
     assert default_formatter.format("{month}", month="m3") == "march"
 
 
-def test_AttrFormatter():
+def test_AttrFormatter():  # noqa: N802
     fmt = AttrFormatter(
         mapping={"evil": ["méchant", "méchante"], "nice": ["beau", "belle"]},
         modifiers=["m", "f"],
@@ -655,14 +657,14 @@ def test_input_dataset(open_dataset):
     ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
 
     # Use defaults
-    out = xclim.atmos.daily_temperature_range(freq="YS", ds=ds)
+    _ = xclim.atmos.daily_temperature_range(freq="YS", ds=ds)
 
     # Use non-defaults (inverted on purpose)
     with xclim.set_options(cf_compliance="log"):
-        out = xclim.atmos.daily_temperature_range("tasmax", "tasmin", freq="YS", ds=ds)
+        _ = xclim.atmos.daily_temperature_range("tasmax", "tasmin", freq="YS", ds=ds)
 
     # Use a mix
-    out = xclim.atmos.daily_temperature_range(tasmax=ds.tasmax, freq="YS", ds=ds)
+    _ = xclim.atmos.daily_temperature_range(tasmax=ds.tasmax, freq="YS", ds=ds)
 
     # Inexistent variable:
     dsx = ds.drop_vars("tasmin")
@@ -817,7 +819,7 @@ def test_indicator_call_errors(tas_series):
         uniIndTemp(tas, oups=3)
 
 
-def test_resamplingIndicator_new_error():
+def test_resamplingIndicator_new_error():  # noqa: N802
     with pytest.raises(ValueError, match="ResamplingIndicator require a 'freq'"):
         Daily(
             realm="atmos",

tests/test_indices.py

@@ -3690,42 +3690,42 @@ def test_wet_spell_frequency_op(pr_series):
 
 
 class TestSfcWindMax:
-    def test_sfcWind_max(self, sfcWind_series):
+    def test_sfcWind_max(self, sfcWind_series):  # noqa: N802
         sfcWind = sfcWind_series(np.array([14.11, 15.27, 10.70]))
         out = xci.sfcWind_max(sfcWind)
         np.testing.assert_allclose(out, [15.27])
 
 
 class TestSfcWindMean:
-    def test_sfcWind_mean(self, sfcWind_series):
+    def test_sfcWind_mean(self, sfcWind_series):  # noqa: N802
         sfcWind = sfcWind_series(np.array([14.11, 15.27, 10.70]))
         out = xci.sfcWind_mean(sfcWind)
         np.testing.assert_allclose(out, [13.36])
 
 
 class TestSfcWindMin:
-    def test_sfcWind_min(self, sfcWind_series):
+    def test_sfcWind_min(self, sfcWind_series):  # noqa: N802
         sfcWind = sfcWind_series(np.array([14.11, 15.27, 10.70]))
         out = xci.sfcWind_min(sfcWind)
         np.testing.assert_allclose(out, [10.70])
 
 
 class TestSfcWindmaxMax:
-    def test_sfcWindmax_max(self, sfcWindmax_series):
+    def test_sfcWindmax_max(self, sfcWindmax_series):  # noqa: N802
         sfcWindmax = sfcWindmax_series(np.array([14.11, 15.27, 10.70]))
         out = xci.sfcWindmax_max(sfcWindmax)
         np.testing.assert_allclose(out, [15.27])
 
 
 class TestSfcWindmaxMean:
-    def test_sfcWindmax_mean(self, sfcWindmax_series):
+    def test_sfcWindmax_mean(self, sfcWindmax_series):  # noqa: N802
         sfcWindmax = sfcWindmax_series(np.array([14.11, 15.27, 10.70]))
         out = xci.sfcWindmax_mean(sfcWindmax)
         np.testing.assert_allclose(out, [13.36])
 
 
 class TestSfcWindmaxMin:
-    def test_sfcWindmax_min(self, sfcWindmax_series):
+    def test_sfcWindmax_min(self, sfcWindmax_series):  # noqa: N802
         sfcWindmax = sfcWindmax_series(np.array([14.11, 15.27, 10.70]))
         out = xci.sfcWindmax_min(sfcWindmax)
         np.testing.assert_allclose(out, [10.70])

tests/test_sdba/test_adjustment.py

@@ -101,7 +101,9 @@ def test_time(self, kind, name, series, random):
         np.testing.assert_array_almost_equal(p, ref)
 
     @pytest.mark.parametrize("kind,name", [(ADDITIVE, "tas"), (MULTIPLICATIVE, "pr")])
-    def test_mon_U(self, mon_series, series, mon_triangular, kind, name, random):
+    def test_mon_U(  # noqa: N802
+        self, mon_series, series, mon_triangular, kind, name, random
+    ):
         n = 10000
         u = random.random(n)
 
@@ -209,7 +211,9 @@ def test_quantiles(self, series, kind, name, random):
 
     @pytest.mark.parametrize("kind,name", [(ADDITIVE, "tas"), (MULTIPLICATIVE, "pr")])
     @pytest.mark.parametrize("add_dims", [True, False])
-    def test_mon_U(self, mon_series, series, kind, name, add_dims, random):
+    def test_mon_U(  # noqa: N802
+        self, mon_series, series, kind, name, add_dims, random
+    ):
         """
         Train on
         hist: U
@@ -324,7 +328,7 @@ def test_quantiles(self, series, kind, name, random):
     @pytest.mark.parametrize("use_dask", [True, False])
     @pytest.mark.parametrize("kind,name", [(ADDITIVE, "tas"), (MULTIPLICATIVE, "pr")])
     @pytest.mark.parametrize("add_dims", [True, False])
-    def test_mon_U(
+    def test_mon_U(  # noqa: N802
         self, mon_series, series, mon_triangular, add_dims, kind, name, use_dask, random
     ):
         """
@@ -480,7 +484,9 @@ def test_quantiles(self, series, kind, name, random):
         np.testing.assert_array_almost_equal(p[middle], ref[middle], 1)
 
     @pytest.mark.parametrize("kind,name", [(ADDITIVE, "tas"), (MULTIPLICATIVE, "pr")])
-    def test_mon_U(self, mon_series, series, mon_triangular, kind, name, random):
+    def test_mon_U(  # noqa: N802
+        self, mon_series, series, mon_triangular, kind, name, random
+    ):
         """
         Train on
         hist: U

tests/test_temperature.py

@@ -69,7 +69,7 @@ class TestDTR:
     nc_tasmax = os.path.join("NRCANdaily", "nrcan_canada_daily_tasmax_1990.nc")
     nc_tasmin = os.path.join("NRCANdaily", "nrcan_canada_daily_tasmin_1990.nc")
 
-    def test_DTR_3d_data_with_nans(self, open_dataset):
+    def test_DTR_3d_data_with_nans(self, open_dataset):  # noqa: N802
         tasmax = open_dataset(self.nc_tasmax).tasmax
         tasmax_C = open_dataset(self.nc_tasmax).tasmax
         tasmax_C -= K2C
@@ -176,7 +176,7 @@ class TestTmean:
         os.path.join("NRCANdaily", "nrcan_canada_daily_tasmin_1990.nc"),
     )
 
-    def test_Tmean_3d_data(self, open_dataset):
+    def test_Tmean_3d_data(self, open_dataset):  # noqa: N802
         ds_tmax = open_dataset(self.nc_files[0])
         ds_tmin = open_dataset(self.nc_files[1])
         tas = atmos.tg(ds_tmin.tasmin, ds_tmax.tasmax)
@@ -205,7 +205,7 @@ def test_Tmean_3d_data(self, open_dataset):
 class TestTx:
     nc_file = os.path.join("NRCANdaily", "nrcan_canada_daily_tasmax_1990.nc")
 
-    def test_TX_3d_data(self, open_dataset):
+    def test_TX_3d_data(self, open_dataset):  # noqa: N802
         tasmax = open_dataset(self.nc_file).tasmax
         tasmax_C = open_dataset(self.nc_file).tasmax
         tasmax_C.values -= K2C
@@ -255,7 +255,7 @@ def test_TX_3d_data(self, open_dataset):
 class TestTn:
     nc_file = os.path.join("NRCANdaily", "nrcan_canada_daily_tasmin_1990.nc")
 
-    def test_TN_3d_data(self, open_dataset):
+    def test_TN_3d_data(self, open_dataset):  # noqa: N802
         tasmin = open_dataset(self.nc_file).tasmin
         tasmin_C = open_dataset(self.nc_file).tasmin
         tasmin_C.values -= K2C

tests/test_wind.py

@@ -19,7 +19,7 @@ def test_calm_windy_days(self, open_dataset):
 
 
 class TestSfcWindMax:
-    def test_sfcWind_max(self, open_dataset):
+    def test_sfcWind_max(self, open_dataset):  # noqa: N802
         ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
         sfcWind, _ = atmos.wind_speed_from_vector(ds.uas, ds.vas)
 
@@ -29,7 +29,7 @@ def test_sfcWind_max(self, open_dataset):
 
 
 class TestSfcWindMean:
-    def test_sfcWind_mean(self, open_dataset):
+    def test_sfcWind_mean(self, open_dataset):  # noqa: N802
         ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
         sfcWind, _ = atmos.wind_speed_from_vector(ds.uas, ds.vas)
 
@@ -39,7 +39,7 @@ def test_sfcWind_mean(self, open_dataset):
 
 
 class TestSfcWindMin:
-    def test_sfcWind_min(self, open_dataset):
+    def test_sfcWind_min(self, open_dataset):  # noqa: N802
         ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
         sfcWind, _ = atmos.wind_speed_from_vector(ds.uas, ds.vas)
 
@@ -49,7 +49,7 @@ def test_sfcWind_min(self, open_dataset):
 
 
 class TestSfcWindmaxMax:
-    def test_sfcWindmax_max(self, open_dataset):
+    def test_sfcWindmax_max(self, open_dataset):  # noqa: N802
         ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
         sfcWindmax, _ = atmos.wind_speed_from_vector(ds.uas, ds.vas)
 
@@ -59,7 +59,7 @@ def test_sfcWindmax_max(self, open_dataset):
 
 
 class TestSfcWindmaxMean:
-    def test_sfcWindmax_mean(self, open_dataset):
+    def test_sfcWindmax_mean(self, open_dataset):  # noqa: N802
         ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
         sfcWindmax, _ = atmos.wind_speed_from_vector(ds.uas, ds.vas)
 
@@ -69,7 +69,7 @@ def test_sfcWindmax_mean(self, open_dataset):
 
 
 class TestSfcWindmaxMin:
-    def test_sfcWindmax_mean(self, open_dataset):
+    def test_sfcWindmax_mean(self, open_dataset):  # noqa: N802
         ds = open_dataset("ERA5/daily_surface_cancities_1990-1993.nc")
         sfcWindmax, _ = atmos.wind_speed_from_vector(ds.uas, ds.vas)
 

xclim/indices/_simple.py

@@ -535,7 +535,9 @@ def snow_depth(
 
 
 @declare_units(sfcWind="[speed]")
-def sfcWind_max(sfcWind: xarray.DataArray, freq: str = "YS") -> xarray.DataArray:
+def sfcWind_max(  # noqa: N802
+    sfcWind: xarray.DataArray, freq: str = "YS"
+) -> xarray.DataArray:
     r"""Highest daily mean wind speed.
 
     The maximum of daily mean wind speed.
@@ -574,7 +576,9 @@ def sfcWind_max(sfcWind: xarray.DataArray, freq: str = "YS") -> xarray.DataArray
 
 
 @declare_units(sfcWind="[speed]")
-def sfcWind_mean(sfcWind: xarray.DataArray, freq: str = "YS") -> xarray.DataArray:
+def sfcWind_mean(  # noqa: N802
+    sfcWind: xarray.DataArray, freq: str = "YS"
+) -> xarray.DataArray:
     r"""Mean of daily mean wind speed.
 
     Resample the original daily mean wind speed series by taking the mean over each period.
@@ -615,7 +619,9 @@ def sfcWind_mean(sfcWind: xarray.DataArray, freq: str = "YS") -> xarray.DataArra
 
 
 @declare_units(sfcWind="[speed]")
-def sfcWind_min(sfcWind: xarray.DataArray, freq: str = "YS") -> xarray.DataArray:
+def sfcWind_min(  # noqa: N802
+    sfcWind: xarray.DataArray, freq: str = "YS"
+) -> xarray.DataArray:
     r"""Lowest daily mean wind speed.
 
     The minimum of daily mean wind speed.
@@ -654,7 +660,9 @@ def sfcWind_min(sfcWind: xarray.DataArray, freq: str = "YS") -> xarray.DataArray
 
 
 @declare_units(sfcWindmax="[speed]")
-def sfcWindmax_max(sfcWindmax: xarray.DataArray, freq: str = "YS") -> xarray.DataArray:
+def sfcWindmax_max(  # noqa: N802
+    sfcWindmax: xarray.DataArray, freq: str = "YS"
+) -> xarray.DataArray:
     r"""Highest maximum wind speed.
 
     The maximum of daily maximum wind speed.
@@ -696,7 +704,9 @@ def sfcWindmax_max(sfcWindmax: xarray.DataArray, freq: str = "YS") -> xarray.Dat
 
 
 @declare_units(sfcWindmax="[speed]")
-def sfcWindmax_mean(sfcWindmax: xarray.DataArray, freq: str = "YS") -> xarray.DataArray:
+def sfcWindmax_mean(  # noqa: N802
+    sfcWindmax: xarray.DataArray, freq: str = "YS"
+) -> xarray.DataArray:
     r"""Mean of daily maximum wind speed.
 
     Resample the original daily maximum wind speed series by taking the mean over each period.
@@ -738,7 +748,9 @@ def sfcWindmax_mean(sfcWindmax: xarray.DataArray, freq: str = "YS") -> xarray.Da
 
 
 @declare_units(sfcWindmax="[speed]")
-def sfcWindmax_min(sfcWindmax: xarray.DataArray, freq: str = "YS") -> xarray.DataArray:
+def sfcWindmax_min(  # noqa: N802
+    sfcWindmax: xarray.DataArray, freq: str = "YS"
+) -> xarray.DataArray:
     r"""Lowest daily maximum wind speed.
 
     The minimum of daily maximum wind speed.

xclim/indices/stats.py

@@ -514,7 +514,7 @@ def _fit_start(x, dist: str, **fitkwargs: Any) -> tuple[tuple, dict]:
     return (), {}
 
 
-def _dist_method_1D(
+def _dist_method_1D(  # noqa: N802
     *args, dist: str | scipy.stats.rv_continuous, function: str, **kwargs: Any
 ) -> xr.DataArray:
     r"""Statistical function for given argument on given distribution initialized with params.

xclim/sdba/adjustment.py

@@ -1302,7 +1302,7 @@ def _parse(s):
             ]
         )
 
-    def _generate_SBCK_classes():
+    def _generate_SBCK_classes():  # noqa: N802
         classes = []
         for clsname in dir(SBCK):
             cls = getattr(SBCK, clsname)

xclim/sdba/utils.py

@@ -310,7 +310,7 @@ def add_cyclic_bounds(
     return ensure_chunk_size(qmf, **{att: -1})
 
 
-def _interp_on_quantiles_1D(newx, oldx, oldy, method, extrap):
+def _interp_on_quantiles_1D(newx, oldx, oldy, method, extrap):  # noqa: N802
     mask_new = np.isnan(newx)
     mask_old = np.isnan(oldy) | np.isnan(oldx)
     out = np.full_like(newx, np.NaN, dtype=f"float{oldy.dtype.itemsize * 8}")