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Revert unproject_layout's action; use shape_touched in column optimization. #317

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Revert unproject_layout's action; use shape_touched in column optimization. #317

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7949baa
make unproject_layout do nothing; check report for shape_touched.
douglasdavis Jul 12, 2023
1482d37
avoid masked array vs raw array mismatch in to_dask_array tests
douglasdavis Jul 12, 2023
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2 changes: 1 addition & 1 deletion src/dask_awkward/lib/optimize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -421,7 +421,7 @@ def _necessary_columns(dsk: HighLevelGraph) -> dict[str, list[str]]:
"""Pair layer names with lists of necessary columns."""
kv = {}
for name, report in _get_column_reports(dsk).items():
cols = {_ for _ in report.data_touched if _ is not None}
cols = {_ for _ in report.data_touched + report.shape_touched if _ is not None}
select = []
for col in sorted(cols):
if col == name:
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7 changes: 4 additions & 3 deletions src/dask_awkward/lib/unproject_layout.py
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Expand Up @@ -401,6 +401,7 @@ def unproject_layout(form: Form | None, layout: Content) -> Content:
not appear in the projected layout will be PlaceholderArrays).

"""
if form is None:
return layout
return _unproject_layout(form, layout, layout.length, layout.backend)
return layout
# if form is None:
# return layout
# return _unproject_layout(form, layout, layout.length, layout.backend)
3 changes: 3 additions & 0 deletions tests/test_io.py
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Expand Up @@ -95,6 +95,7 @@ def test_json_bytes_no_delim_defined(ndjson_points_file: str) -> None:


def test_to_and_from_dask_array(daa: dak.Array) -> None:
daa = dak.from_awkward(daa.compute(), npartitions=3)
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the normal daa fixture is an array that comes from parquet, and the form ends up getting a mask when we do column selection. We avoid the mask by going ahead and computing the parquet-originating collection and creating a new collection from the concrete result via from_awkward. A bit roundabout but we still test what we mean to test here.

computed = ak.flatten(daa.points.x.compute())
x = dak.flatten(daa.points.x)
daskarr = dak.to_dask_array(x)
Expand Down Expand Up @@ -273,6 +274,8 @@ def test_from_lists(caa_p1: ak.Array) -> None:
def test_to_dask_array(daa: dak.Array, caa: dak.Array) -> None:
from dask.array.utils import assert_eq as da_assert_eq

daa = dak.from_awkward(daa.compute(), npartitions=4)
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same as above


da = dak.to_dask_array(dak.flatten(daa.points.x))
ca = ak.to_numpy(ak.flatten(caa.points.x))
da_assert_eq(da, ca)
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