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Try cleaning up some expected_groups logic #175

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Merged
merged 3 commits into from
Nov 27, 2022
Merged

Try cleaning up some expected_groups logic #175

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23d3602
Try cleaning up some expected_groups logic
dcherian Oct 17, 2022
318d856
Fix _extract_unknown_groups
dcherian Oct 19, 2022
6d8f209
Fixes
dcherian Nov 27, 2022
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23 changes: 8 additions & 15 deletions flox/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1164,7 +1164,7 @@ def subset_to_blocks(
return dask.array.Array(graph, name, chunks, meta=array)


def _extract_unknown_groups(reduced, group_chunks, dtype) -> tuple[DaskArray]:
def _extract_unknown_groups(reduced, dtype) -> tuple[DaskArray]:
import dask.array
from dask.highlevelgraph import HighLevelGraph

Expand All @@ -1180,7 +1180,7 @@ def _extract_unknown_groups(reduced, group_chunks, dtype) -> tuple[DaskArray]:
dask.array.Array(
HighLevelGraph.from_collections(groups_token, layer, dependencies=[reduced]),
groups_token,
chunks=group_chunks,
chunks=((np.nan,),),
meta=np.array([], dtype=dtype),
),
)
Expand Down Expand Up @@ -1293,14 +1293,7 @@ def dask_groupby_agg(
name=f"{name}-chunk-{token}",
)

if expected_groups is None:
if is_duck_dask_array(by_input):
expected_groups = None
else:
expected_groups = _get_expected_groups(by_input, sort=sort)
group_chunks: tuple[tuple[Union[int, float], ...]] = (
(len(expected_groups),) if expected_groups is not None else (np.nan,),
)
group_chunks: tuple[tuple[Union[int, float], ...]]
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@Illviljan the only float value that is valid here is np.nan. Is there a way to narrow this to just np.nan? A simple Literal[np.nan] does not work.

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yeah, I am sad about that as well. :(

Thought a little about this in dask/dask#9255 but came to the conclusion that adding float with a reminder comment was the most practical solution. Here's a relevant typing thread: python/typing#1160

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ah too bad. Thanks!


if method in ["map-reduce", "cohorts"]:
combine: Callable[..., IntermediateDict]
Expand Down Expand Up @@ -1333,13 +1326,13 @@ def dask_groupby_agg(
aggregate=partial(aggregate, expected_groups=expected_groups, reindex=reindex),
)
if is_duck_dask_array(by_input) and expected_groups is None:
groups = _extract_unknown_groups(reduced, group_chunks=group_chunks, dtype=by.dtype)
groups = _extract_unknown_groups(reduced, dtype=by.dtype)
group_chunks = ((np.nan,),)
else:
if expected_groups is None:
expected_groups_ = _get_expected_groups(by_input, sort=sort)
else:
expected_groups_ = expected_groups
groups = (expected_groups_.to_numpy(),)
expected_groups = _get_expected_groups(by_input, sort=sort)
groups = (expected_groups.to_numpy(),)
group_chunks = ((len(expected_groups),),)

elif method == "cohorts":
chunks_cohorts = find_group_cohorts(
Expand Down