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Rename to sliding_window_view_kwargs
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@dcherian
dcherian committed Nov 18, 2024
1 parent 8fb9d2a commit 42f78ff
Showing 1 changed file with 25 additions and 25 deletions.
50 changes: 25 additions & 25 deletions xarray/core/rolling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,7 +187,7 @@ def method(self, keep_attrs=None, **kwargs):
rolling_agg_func=rolling_agg_func,
keep_attrs=keep_attrs,
fillna=fillna,
sliding_window_kwargs=dict(automatic_rechunk=automatic_rechunk),
sliding_window_view_kwargs=dict(automatic_rechunk=automatic_rechunk),
**kwargs,
)

Expand Down Expand Up @@ -329,7 +329,7 @@ def construct(
stride: int | Mapping[Any, int] = 1,
fill_value: Any = dtypes.NA,
keep_attrs: bool | None = None,
sliding_window_kwargs: Mapping[Any, Any] | None = None,
sliding_window_view_kwargs: Mapping[Any, Any] | None = None,
**window_dim_kwargs: Hashable,
) -> DataArray:
"""
Expand All @@ -348,7 +348,7 @@ def construct(
If True, the attributes (``attrs``) will be copied from the original
object to the new one. If False, the new object will be returned
without attributes. If None uses the global default.
sliding_window_kwargs : Mapping
sliding_window_view_kwargs : Mapping
Keyword arguments that should be passed to the underlying array type's
``sliding_window_view`` function.
**window_dim_kwargs : Hashable, optional
Expand All @@ -358,7 +358,7 @@ def construct(
-------
DataArray
a view of the original array. By default, the returned array is not writeable.
For numpy arrays, one can pass ``writeable=True`` in ``sliding_window_kwargs``.
For numpy arrays, one can pass ``writeable=True`` in ``sliding_window_view_kwargs``.
See Also
--------
Expand All @@ -368,7 +368,7 @@ def construct(
Notes
-----
With dask arrays, it's possible to pass the ``automatic_rechunk`` kwarg as
``sliding_window_kwargs={"automatic_rechunk": True}``. This controls
``sliding_window_view_kwargs={"automatic_rechunk": True}``. This controls
whether dask should automatically rechunk the output to avoid
exploding chunk sizes. Automatically rechunking is the default behaviour.
Importantly, each chunk will be a view of the data so large chunk sizes are
Expand Down Expand Up @@ -408,15 +408,15 @@ def construct(
"""

if sliding_window_kwargs is None:
sliding_window_kwargs = {}
if sliding_window_view_kwargs is None:
sliding_window_view_kwargs = {}
return self._construct(
self.obj,
window_dim=window_dim,
stride=stride,
fill_value=fill_value,
keep_attrs=keep_attrs,
sliding_window_kwargs=sliding_window_kwargs,
sliding_window_view_kwargs=sliding_window_view_kwargs,
**window_dim_kwargs,
)

Expand All @@ -428,13 +428,13 @@ def _construct(
stride: int | Mapping[Any, int] = 1,
fill_value: Any = dtypes.NA,
keep_attrs: bool | None = None,
sliding_window_kwargs: Mapping[Any, Any] | None = None,
sliding_window_view_kwargs: Mapping[Any, Any] | None = None,
**window_dim_kwargs: Hashable,
) -> DataArray:
from xarray.core.dataarray import DataArray

if sliding_window_kwargs is None:
sliding_window_kwargs = {}
if sliding_window_view_kwargs is None:
sliding_window_view_kwargs = {}

keep_attrs = self._get_keep_attrs(keep_attrs)

Expand All @@ -456,7 +456,7 @@ def _construct(
window_dims,
center=self.center,
fill_value=fill_value,
**sliding_window_kwargs,
**sliding_window_view_kwargs,
)

attrs = obj.attrs if keep_attrs else {}
Expand All @@ -477,7 +477,7 @@ def reduce(
func: Callable,
keep_attrs: bool | None = None,
*,
sliding_window_kwargs: Mapping[Any, Any] | None = None,
sliding_window_view_kwargs: Mapping[Any, Any] | None = None,
**kwargs: Any,
) -> DataArray:
"""Reduce each window by applying `func`.
Expand All @@ -494,7 +494,7 @@ def reduce(
If True, the attributes (``attrs``) will be copied from the original
object to the new one. If False, the new object will be returned
without attributes. If None uses the global default.
sliding_window_kwargs
sliding_window_view_kwargs
Keyword arguments that should be passed to the underlying array type's
``sliding_window_view`` function.
**kwargs : dict
Expand All @@ -513,7 +513,7 @@ def reduce(
Notes
-----
With dask arrays, it's possible to pass the ``automatic_rechunk`` kwarg as
``sliding_window_kwargs={"automatic_rechunk": True}``. This controls
``sliding_window_view_kwargs={"automatic_rechunk": True}``. This controls
whether dask should automatically rechunk the output to avoid
exploding chunk sizes. Automatically rechunking is the default behaviour.
Importantly, each chunk will be a view of the data so large chunk sizes are
Expand Down Expand Up @@ -568,7 +568,7 @@ def reduce(
window_dim=rolling_dim,
keep_attrs=keep_attrs,
fill_value=fillna,
sliding_window_kwargs=sliding_window_kwargs,
sliding_window_view_kwargs=sliding_window_view_kwargs,
)

dim = list(rolling_dim.values())
Expand Down Expand Up @@ -844,7 +844,7 @@ def reduce(
self,
func: Callable,
keep_attrs: bool | None = None,
sliding_window_kwargs: Mapping[Any, Any] | None = None,
sliding_window_view_kwargs: Mapping[Any, Any] | None = None,
**kwargs: Any,
) -> DataArray:
"""Reduce the items in this group by applying `func` along some
Expand All @@ -860,7 +860,7 @@ def reduce(
If True, the attributes (``attrs``) will be copied from the original
object to the new one. If False, the new object will be returned
without attributes. If None uses the global default.
sliding_window_kwargs : Mapping
sliding_window_view_kwargs : Mapping
Keyword arguments that should be passed to the underlying array type's
``sliding_window_view`` function.
**kwargs : dict
Expand All @@ -879,7 +879,7 @@ def reduce(
Notes
-----
With dask arrays, it's possible to pass the ``automatic_rechunk`` kwarg as
``sliding_window_kwargs={"automatic_rechunk": True}``. This controls
``sliding_window_view_kwargs={"automatic_rechunk": True}``. This controls
whether dask should automatically rechunk the output to avoid
exploding chunk sizes. Automatically rechunking is the default behaviour.
Importantly, each chunk will be a view of the data so large chunk sizes are
Expand All @@ -888,7 +888,7 @@ def reduce(
return self._dataset_implementation(
functools.partial(DataArrayRolling.reduce, func=func),
keep_attrs=keep_attrs,
sliding_window_kwargs=sliding_window_kwargs,
sliding_window_view_kwargs=sliding_window_view_kwargs,
**kwargs,
)

Expand Down Expand Up @@ -924,7 +924,7 @@ def construct(
stride: int | Mapping[Any, int] = 1,
fill_value: Any = dtypes.NA,
keep_attrs: bool | None = None,
sliding_window_kwargs: Mapping[Any, Any] | None = None,
sliding_window_view_kwargs: Mapping[Any, Any] | None = None,
**window_dim_kwargs: Hashable,
) -> Dataset:
"""
Expand All @@ -940,7 +940,7 @@ def construct(
size of stride for the rolling window.
fill_value : Any, default: dtypes.NA
Filling value to match the dimension size.
sliding_window_kwargs
sliding_window_view_kwargs
Keyword arguments that should be passed to the underlying array type's
``sliding_window_view`` function.
**window_dim_kwargs : {dim: new_name, ...}, optional
Expand All @@ -950,7 +950,7 @@ def construct(
-------
Dataset
Dataset with views of the original arrays. By default, the returned arrays are not writeable.
For numpy arrays, one can pass ``writeable=True`` in ``sliding_window_kwargs``.
For numpy arrays, one can pass ``writeable=True`` in ``sliding_window_view_kwargs``.
See Also
--------
Expand All @@ -960,7 +960,7 @@ def construct(
Notes
-----
With dask arrays, it's possible to pass the ``automatic_rechunk`` kwarg as
``sliding_window_kwargs={"automatic_rechunk": True}``. This controls
``sliding_window_view_kwargs={"automatic_rechunk": True}``. This controls
whether dask should automatically rechunk the output to avoid
exploding chunk sizes. Automatically rechunking is the default behaviour.
Importantly, each chunk will be a view of the data so large chunk sizes are
Expand Down Expand Up @@ -996,7 +996,7 @@ def construct(
fill_value=fill_value,
stride=st,
keep_attrs=keep_attrs,
sliding_window_kwargs=sliding_window_kwargs,
sliding_window_view_kwargs=sliding_window_view_kwargs,
)
else:
dataset[key] = da.copy()
Expand Down

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