merge

xskillscore/core/contingency.py

@@ -15,7 +15,7 @@
 FORECASTS_NAME = "forecasts"
 
 
-def _get_category_bounds(category_edges: XArray | np.array) -> List[str]:
+def _get_category_bounds(category_edges: XArray | np.ndarray) -> List[str]:
     """Return formatted string of category bounds given list of category edges"""
     bounds = [
         f"[{str(category_edges[i])}, {str(category_edges[i + 1])})"
@@ -104,8 +104,8 @@ def __init__(
         self,
         observations: XArray,
         forecasts: XArray,
-        observation_category_edges: xr.DataArray | np.array,
-        forecast_category_edges: xr.DataArray | np.array,
+        observation_category_edges: xr.DataArray | np.ndarray,
+        forecast_category_edges: xr.DataArray | np.ndarray,
         dim: Dim,
     ):
         self._observations = observations.copy()

xskillscore/core/utils.py

@@ -189,7 +189,7 @@ def _helper_bool_to_int(da):
 
 def _check_identical_xr_types(a, b):
     """Check that a and b are both xr.Dataset or both xr.DataArray."""
-    if type(a) != type(b):
+    if not isinstance(a, type(b)):
         raise ValueError(f"a and b must be same type, found {type(a)} and {type(b)}")
     for d in [a, b]:
         if not isinstance(d, (xr.Dataset, xr.DataArray)):

xskillscore/tests/test_probabilistic.py

@@ -72,7 +72,7 @@ def assert_keep_attrs(actual, o, keep_attrs):
 
 
 def assign_type_input_output(actual, o):
-    assert type(o) == type(actual)
+    assert isinstance(o, type(actual))
 
 
 @pytest.mark.parametrize("chunk_bool", [True, False])

xskillscore/tests/test_resampling.py

@@ -148,7 +148,7 @@ def test_resample_inputs(a_1d, func, input, chunk, replace):
     # check dask collection preserved
     assert is_dask_collection(actual) if chunk else not is_dask_collection(actual)
     # input type preserved
-    assert type(actual) == type(a_1d)
+    assert isinstance(a_1d, type(actual))
 
 
 @pytest.mark.parametrize("func", resample_iterations_funcs)