fix up some tests

pydata · dcherian · Nov 26, 2024 · Nov 18, 2024 · Nov 18, 2024 · Nov 18, 2024
commit 6225ae3a70d785047259decda130513d1e5df03a
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
@@ -8679,9 +8679,12 @@ def _integrate_one(self, coord, datetime_unit=None, cumulative=False):
             else:
                 if k in self.data_vars and dim in v.dims:
                     # cast coord data to duck array if needed
-                    coord_data = duck_array_ops.get_array_namespace(v.data).asarray(
-                        coord_var.data
-                    )
+                    if isinstance(v.data, array_type("cupy")):
+                        coord_data = duck_array_ops.get_array_namespace(v.data).asarray(
+                            coord_var.data
+                        )
+                    else:
+                        coord_data = coord_var.data
                     if _contains_datetime_like_objects(v):
                         v = datetime_to_numeric(v, datetime_unit=datetime_unit)
                     if cumulative:

diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
@@ -168,7 +168,8 @@ def isnull(data):
         )
     ):
         # these types cannot represent missing values
-        return full_like(data, dtype=xp.bool, fill_value=False)
+        dtype = xp.bool_ if hasattr(xp, "bool_") else xp.bool
+        return full_like(data, dtype=dtype, fill_value=False)
     else:
         # at this point, array should have dtype=object
         if isinstance(data, np.ndarray) or is_extension_array_dtype(data):

diff --git a/xarray/core/nputils.py b/xarray/core/nputils.py
@@ -236,6 +236,9 @@ def f(values, axis=None, **kwargs):
             # bottleneck does not take care dtype, min_count
             kwargs.pop("dtype", None)
             result = bn_func(values, axis=axis, **kwargs)
+            # bottleneck returns python scalars for reduction over all axes
+            if isinstance(result, float):
+                result = np.float64(result)
         else:
             result = getattr(npmodule, name)(values, axis=axis, **kwargs)
 

diff --git a/xarray/core/variable.py b/xarray/core/variable.py
@@ -1936,17 +1936,17 @@ def quantile(
         if keep_attrs is None:
             keep_attrs = _get_keep_attrs(default=False)
 
-        xp = duck_array_ops.get_array_namespace(self.data)
-
         scalar = utils.is_scalar(q)
-        q = xp.atleast_1d(xp.asarray(q, dtype=float))
+        q = np.atleast_1d(np.asarray(q, dtype=np.float64))
 
         if dim is None:
             dim = self.dims
 
         if utils.is_scalar(dim):
             dim = [dim]
 
+        xp = duck_array_ops.get_array_namespace(self.data)
+
         def _wrapper(npa, **kwargs):
             # move quantile axis to end. required for apply_ufunc
             return xp.moveaxis(_quantile_func(npa, **kwargs), 0, -1)