diff --git a/src/squidpy/gr/_ppatterns.py b/src/squidpy/gr/_ppatterns.py
index 292c75994..3e8cb7b04 100644
--- a/src/squidpy/gr/_ppatterns.py
+++ b/src/squidpy/gr/_ppatterns.py
@@ -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.
@@ -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
     -------
@@ -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)
diff --git a/tests/graph/test_ppatterns.py b/tests/graph/test_ppatterns.py
index 226fb2830..01c2e3033 100644
--- a/tests/graph/test_ppatterns.py
+++ b/tests/graph/test_ppatterns.py
@@ -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)