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fix: remove unused parameters in co_occurence #1121

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fix: remove unused parameters in co_occurence #1121

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27893ad
remove the params
selmanozleyen Feb 23, 2026
1b19494
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Feb 23, 2026
7de00ca
Merge branch 'main' into fix/co-occurence-unused-params
selmanozleyen Feb 24, 2026
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12 changes: 1 addition & 11 deletions src/squidpy/gr/_ppatterns.py
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Original file line number Diff line number Diff line change
Expand Up @@ -348,10 +348,6 @@ def co_occurrence(
spatial_key: str = Key.obsm.spatial,
interval: int | NDArrayA = 50,
copy: bool = False,
n_splits: int | None = None,
n_jobs: int | None = None,
backend: str = "loky",
show_progress_bar: bool = True,
) -> tuple[NDArrayA, NDArrayA] | None:
"""
Compute co-occurrence probability of clusters.
Expand All @@ -365,10 +361,6 @@ def co_occurrence(
Distances interval at which co-occurrence is computed. If :class:`int`, uniformly spaced interval
of the given size will be used.
%(copy)s
n_splits
Number of splits in which to divide the spatial coordinates in
:attr:`anndata.AnnData.obsm` ``['{spatial_key}']``.
%(parallelize)s

Returns
-------
Expand Down Expand Up @@ -406,9 +398,7 @@ def co_occurrence(

# Compute co-occurrence probabilities using the fast numba routine.
out = _co_occurrence_helper(spatial_x, spatial_y, interval, labs)
start = logg.info(
f"Calculating co-occurrence probabilities for `{len(interval)}` intervals using `{n_jobs}` core(s) and `{n_splits}` splits"
)
start = logg.info(f"Calculating co-occurrence probabilities for `{len(interval)}` intervals")

if copy:
logg.info("Finish", time=start)
Expand Down
8 changes: 3 additions & 5 deletions tests/graph/test_ppatterns.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,12 +137,10 @@ def test_co_occurrence(adata: AnnData):
assert arr.shape[1] == arr.shape[0] == adata.obs["leiden"].unique().shape[0]


# @pytest.mark.parametrize(("ys", "xs"), [(10, 10), (None, None), (10, 20)])
@pytest.mark.parametrize(("n_jobs", "n_splits"), [(1, 2), (2, 2)])
def test_co_occurrence_reproducibility(adata: AnnData, n_jobs: int, n_splits: int):
def test_co_occurrence_reproducibility(adata: AnnData):
"""Check co_occurrence reproducibility results."""
arr_1, interval_1 = co_occurrence(adata, cluster_key="leiden", copy=True, n_jobs=n_jobs, n_splits=n_splits)
arr_2, interval_2 = co_occurrence(adata, cluster_key="leiden", copy=True, n_jobs=n_jobs, n_splits=n_splits)
arr_1, interval_1 = co_occurrence(adata, cluster_key="leiden", copy=True)
arr_2, interval_2 = co_occurrence(adata, cluster_key="leiden", copy=True)

np.testing.assert_array_equal(sorted(interval_1), sorted(interval_2))
np.testing.assert_allclose(arr_1, arr_2)
Expand Down