Skip to content

Faster dask unstack #6150

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

Closed
wants to merge 4 commits into from
Closed

Faster dask unstack #6150

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
27c1939
Faster dask unstack
Illviljan Jan 10, 2022
a5a8ee3
Update variable.py
Illviljan Jan 10, 2022
0851bc9
Update dataset.py
Illviljan Jan 10, 2022
c139409
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jan 10, 2022
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
11 changes: 3 additions & 8 deletions xarray/core/dataset.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4196,20 +4196,15 @@ def unstack(
self.variables[k] for k in set(self.variables) - set(self.xindexes)
]
# Notes for each of these cases:
# 1. Dask arrays don't support assignment by index, which the fast unstack
# function requires.
# https://github.com/pydata/xarray/pull/4746#issuecomment-753282125
# 2. Sparse doesn't currently support (though we could special-case it)
# 1. Sparse doesn't currently support (though we could special-case it)
# https://github.com/pydata/sparse/issues/422
# 3. pint requires checking if it's a NumPy array until
# 2. pint requires checking if it's a NumPy array until
# https://github.com/pydata/xarray/pull/4751 is resolved,
# Once that is resolved, explicitly exclude pint arrays.
# pint doesn't implement `np.full_like` in a way that's
# currently compatible.
needs_full_reindex = any(
is_duck_dask_array(v.data)
or isinstance(v.data, sparse_array_type)
or not isinstance(v.data, np.ndarray)
isinstance(v.data, sparse_array_type) or not isinstance(v.data, np.ndarray)
for v in nonindexes
)

Expand Down
14 changes: 10 additions & 4 deletions xarray/core/variable.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1659,11 +1659,11 @@ def _unstack_once(
else:
dtype = self.dtype

if sparse:
if sparse and not is_duck_dask_array(reordered):
# unstacking a dense multitindexed array to a sparse array
from sparse import COO

codes = zip(*index.codes)
codes = zip(*indexer)
if reordered.ndim == 1:
indexes = codes
else:
Expand All @@ -1680,17 +1680,23 @@ def _unstack_once(
)

else:
# dask supports assigning to a list of ints along one axis only.
# So we construct an array with the last dimension flattened,
# assign the values, then reshape to the final shape.
intermediate_shape = reordered.shape[:-1] + (np.prod(new_dim_sizes),)
indexer = np.ravel_multi_index(indexer, new_dim_sizes)
data = np.full_like(
self.data,
fill_value=fill_value,
shape=new_shape,
shape=intermediate_shape,
dtype=dtype,
)

# Indexer is a list of lists of locations. Each list is the locations
# on the new dimension. This is robust to the data being sparse; in that
# case the destinations will be NaN / zero.
data[(..., *indexer)] = reordered
data[(..., indexer)] = reordered
data = data.reshape(new_shape)

return self._replace(dims=new_dims, data=data)

Expand Down