Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Array API fixes for astype #7847

Merged
merged 3 commits into from
May 19, 2023
Merged

Array API fixes for astype #7847

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
a0a03b2
array API fixes for astype
TomNicholas May 4, 2023
927b893
Merge branch 'main' into array_API_astype2
TomNicholas May 19, 2023
e69c4fa
whatsnew
TomNicholas May 19, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
73 changes: 43 additions & 30 deletions xarray/core/accessor_str.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -51,6 +51,7 @@

import numpy as np

from xarray.core import duck_array_ops
from xarray.core.computation import apply_ufunc
from xarray.core.types import T_DataArray

Expand Down Expand Up @@ -2085,13 +2086,16 @@ def _get_res_multi(val, pat):
else:
# dtype MUST be object or strings can be truncated
# See: https://github.com/numpy/numpy/issues/8352
return self._apply(
func=_get_res_multi,
func_args=(pat,),
dtype=np.object_,
output_core_dims=[[dim]],
output_sizes={dim: maxgroups},
).astype(self._obj.dtype.kind)
return duck_array_ops.astype(
self._apply(
func=_get_res_multi,
func_args=(pat,),
dtype=np.object_,
output_core_dims=[[dim]],
output_sizes={dim: maxgroups},
),
self._obj.dtype.kind,
)

def extractall(
self,
Expand Down Expand Up @@ -2258,15 +2262,18 @@ def _get_res(val, ipat, imaxcount=maxcount, dtype=self._obj.dtype):

return res

return self._apply(
# dtype MUST be object or strings can be truncated
# See: https://github.com/numpy/numpy/issues/8352
func=_get_res,
func_args=(pat,),
dtype=np.object_,
output_core_dims=[[group_dim, match_dim]],
output_sizes={group_dim: maxgroups, match_dim: maxcount},
).astype(self._obj.dtype.kind)
return duck_array_ops.astype(
self._apply(
# dtype MUST be object or strings can be truncated
# See: https://github.com/numpy/numpy/issues/8352
func=_get_res,
func_args=(pat,),
dtype=np.object_,
output_core_dims=[[group_dim, match_dim]],
output_sizes={group_dim: maxgroups, match_dim: maxcount},
),
self._obj.dtype.kind,
)

def findall(
self,
Expand Down Expand Up @@ -2385,13 +2392,16 @@ def _partitioner(

# dtype MUST be object or strings can be truncated
# See: https://github.com/numpy/numpy/issues/8352
return self._apply(
func=arrfunc,
func_args=(sep,),
dtype=np.object_,
output_core_dims=[[dim]],
output_sizes={dim: 3},
).astype(self._obj.dtype.kind)
return duck_array_ops.astype(
self._apply(
func=arrfunc,
func_args=(sep,),
dtype=np.object_,
output_core_dims=[[dim]],
output_sizes={dim: 3},
),
self._obj.dtype.kind,
)

def partition(
self,
Expand Down Expand Up @@ -2510,13 +2520,16 @@ def _dosplit(mystr, sep, maxsplit=maxsplit, dtype=self._obj.dtype):

# dtype MUST be object or strings can be truncated
# See: https://github.com/numpy/numpy/issues/8352
return self._apply(
func=_dosplit,
func_args=(sep,),
dtype=np.object_,
output_core_dims=[[dim]],
output_sizes={dim: maxsplit},
).astype(self._obj.dtype.kind)
return duck_array_ops.astype(
self._apply(
func=_dosplit,
func_args=(sep,),
dtype=np.object_,
output_core_dims=[[dim]],
output_sizes={dim: maxsplit},
),
self._obj.dtype.kind,
)

def split(
self,
Expand Down
6 changes: 3 additions & 3 deletions xarray/core/variable.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1421,7 +1421,7 @@ def _shift_one_dim(self, dim, count, fill_value=dtypes.NA):
pads = [(0, 0) if d != dim else dim_pad for d in self.dims]

data = np.pad(
trimmed_data.astype(dtype),
duck_array_ops.astype(trimmed_data, dtype),
pads,
mode="constant",
constant_values=fill_value,
Expand Down Expand Up @@ -1570,7 +1570,7 @@ def pad(
pad_option_kwargs["reflect_type"] = reflect_type

array = np.pad(
self.data.astype(dtype, copy=False),
duck_array_ops.astype(self.data, dtype, copy=False),
pad_width_by_index,
mode=mode,
**pad_option_kwargs,
Expand Down Expand Up @@ -2438,7 +2438,7 @@ def rolling_window(
"""
if fill_value is dtypes.NA: # np.nan is passed
dtype, fill_value = dtypes.maybe_promote(self.dtype)
var = self.astype(dtype, copy=False)
var = duck_array_ops.astype(self, dtype, copy=False)
else:
dtype = self.dtype
var = self
Expand Down