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test: replace deprecated spatial_neighbors with mode-specific functions #1219

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4472c86
test: replace deprecated spatial_neighbors with mode-specific functions
selmanozleyen Jun 19, 2026
ed8b954
Merge branch 'main' into tests/drop-deprecated-spatial-neighbors
selmanozleyen Jun 20, 2026
98c9f28
fix: remove unused spatial_neighbors_knn import in conftest
selmanozleyen Jun 20, 2026
7b1f598
Merge branch 'main' into tests/drop-deprecated-spatial-neighbors
selmanozleyen Jun 20, 2026
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8 changes: 4 additions & 4 deletions tests/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@

import squidpy as sq
from squidpy._constants._pkg_constants import Key
from squidpy.gr import spatial_neighbors
from squidpy.gr import spatial_neighbors_grid
from squidpy.im._container import ImageContainer

HERE: Path = Path(__file__).parent
Expand Down Expand Up @@ -59,7 +59,7 @@ def adata_hne() -> AnnData:
@pytest.fixture(scope="session")
def adata_hne_concat() -> AnnData:
adata1 = sq.datasets.visium_hne_adata_crop()
spatial_neighbors(adata1)
spatial_neighbors_grid(adata1)
adata2 = adata1[:100, :].copy()
adata2.uns["spatial"] = {}
adata2.uns["spatial"]["V2_Adult_Mouse_Brain"] = adata1.uns["spatial"]["V1_Adult_Mouse_Brain"]
Expand Down Expand Up @@ -101,7 +101,7 @@ def nhood_data(adata: AnnData) -> AnnData:
sc.pp.pca(adata)
sc.pp.neighbors(adata)
sc.tl.leiden(adata, key_added="leiden")
sq.gr.spatial_neighbors(adata)
sq.gr.spatial_neighbors_grid(adata)

return adata

Expand All @@ -112,7 +112,7 @@ def dummy_adata() -> AnnData:
adata = AnnData(r.rand(200, 100), obs={"cluster": r.randint(0, 3, 200)})

adata.obsm[Key.obsm.spatial] = np.stack([r.randint(0, 500, 200), r.randint(0, 500, 200)], axis=1)
sq.gr.spatial_neighbors(adata, spatial_key=Key.obsm.spatial, n_rings=2)
sq.gr.spatial_neighbors_knn(adata, spatial_key=Key.obsm.spatial)

return adata

Expand Down
8 changes: 4 additions & 4 deletions tests/graph/test_nhood.py
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Expand Up @@ -10,7 +10,7 @@
centrality_scores,
interaction_matrix,
nhood_enrichment,
spatial_neighbors,
spatial_neighbors_grid,
)

_CK = "leiden"
Expand All @@ -25,22 +25,22 @@ def _assert_common(self, adata: AnnData):
assert adata.uns[key]["count"].shape[0] == adata.obs.leiden.cat.categories.shape[0]

def test_nhood_enrichment(self, adata: AnnData):
spatial_neighbors(adata)
spatial_neighbors_grid(adata)
nhood_enrichment(adata, cluster_key=_CK)

self._assert_common(adata)

@pytest.mark.parametrize("backend", ["threading", "multiprocessing", "loky"])
def test_parallel_works(self, adata: AnnData, backend: str):
spatial_neighbors(adata)
spatial_neighbors_grid(adata)

nhood_enrichment(adata, cluster_key=_CK, n_jobs=2, n_perms=20, backend=backend)

self._assert_common(adata)

@pytest.mark.parametrize("n_jobs", [1, 2])
def test_reproducibility(self, adata: AnnData, n_jobs: int):
spatial_neighbors(adata)
spatial_neighbors_grid(adata)

res1 = nhood_enrichment(adata, cluster_key=_CK, seed=42, n_jobs=n_jobs, n_perms=20, copy=True)
res2 = nhood_enrichment(adata, cluster_key=_CK, seed=42, n_jobs=n_jobs, n_perms=20, copy=True)
Expand Down
8 changes: 4 additions & 4 deletions tests/graph/test_niche.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
from pandas.testing import assert_frame_equal
from scipy.sparse import issparse

from squidpy.gr import calculate_niche, spatial_neighbors
from squidpy.gr import calculate_niche, spatial_neighbors_knn
from squidpy.gr._niche import _calculate_neighborhood_profile, _utag

SPATIAL_CONNECTIVITIES_KEY = "spatial_connectivities"
Expand All @@ -14,7 +14,7 @@

def test_niche_calc_nhood(adata_seqfish: AnnData):
"""Check whether niche calculation using neighborhood profile approach works as intended."""
spatial_neighbors(adata_seqfish, coord_type="generic", delaunay=False, n_neighs=N_NEIGHBORS)
spatial_neighbors_knn(adata_seqfish, n_neighs=N_NEIGHBORS)
calculate_niche(
adata_seqfish,
groups=GROUPS,
Expand Down Expand Up @@ -53,7 +53,7 @@ def test_niche_calc_nhood(adata_seqfish: AnnData):

def test_niche_calc_utag(adata_seqfish: AnnData):
"""Check whether niche calculation using UTAG approach works as intended."""
spatial_neighbors(adata_seqfish, coord_type="generic", delaunay=False, n_neighs=N_NEIGHBORS)
spatial_neighbors_knn(adata_seqfish, n_neighs=N_NEIGHBORS)
calculate_niche(adata_seqfish, flavor="utag", n_neighbors=N_NEIGHBORS, resolutions=[0.1, 1.0])

niches = adata_seqfish.obs["utag_niche_res=1.0"]
Expand All @@ -71,7 +71,7 @@ def test_niche_calc_utag(adata_seqfish: AnnData):
assert new_feature_matrix.shape == adata_seqfish.X.shape
assert issparse(new_feature_matrix)

spatial_neighbors(adata_seqfish, coord_type="generic", delaunay=False, n_neighs=40)
spatial_neighbors_knn(adata_seqfish, n_neighs=40)
new_feature_matrix_more_neighs = _utag(
adata_seqfish,
normalize_adj=True,
Expand Down
8 changes: 4 additions & 4 deletions tests/graph/test_sepal.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,14 +4,14 @@
from anndata import AnnData
from pandas.testing import assert_frame_equal

from squidpy.gr import sepal, spatial_neighbors
from squidpy.gr import sepal, spatial_neighbors_grid, spatial_neighbors_radius

UNS_KEY = "sepal_score"


def test_sepal_seq_par(adata: AnnData):
"""Check whether sepal results are the same for seq. and parallel computation."""
spatial_neighbors(adata, coord_type="grid")
spatial_neighbors_grid(adata)
rng = np.random.default_rng(42)
adata.var["highly_variable"] = rng.choice([True, False], size=adata.var_names.shape, p=[0.005, 0.995])

Expand All @@ -37,7 +37,7 @@ def test_sepal_seq_par(adata: AnnData):
def test_sepal_square_seq_par(adata_squaregrid: AnnData):
"""Test sepal for square grid."""
adata = adata_squaregrid
spatial_neighbors(adata, radius=1.0)
spatial_neighbors_radius(adata, radius=1.0)
rng = np.random.default_rng(42)
adata.var["highly_variable"] = rng.choice([True, False], size=adata.var_names.shape)

Expand All @@ -60,7 +60,7 @@ def test_sepal_square_seq_par(adata_squaregrid: AnnData):

def test_sepal_dense(adata: AnnData):
"""Check whether sepal results are identical for sparse and dense data."""
spatial_neighbors(adata, coord_type="grid")
spatial_neighbors_grid(adata)
rng = np.random.default_rng(42)
adata.var["highly_variable"] = rng.choice([True, False], size=adata.var_names.shape, p=[0.05, 0.95])

Expand Down
18 changes: 9 additions & 9 deletions tests/plotting/test_graph.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,45 +29,45 @@

class TestGraph(PlotTester, metaclass=PlotTesterMeta):
def test_plot_interaction(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.interaction_matrix(adata, cluster_key=C_KEY)

pl.interaction_matrix(adata, cluster_key=C_KEY)

def test_plot_interaction_dendro(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.interaction_matrix(adata, cluster_key=C_KEY)

pl.interaction_matrix(adata, cluster_key=C_KEY, method="single")

def test_plot_centrality_scores(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.centrality_scores(adata, cluster_key=C_KEY)

pl.centrality_scores(adata, cluster_key=C_KEY)

def test_plot_centrality_scores_single(self, adata: AnnData):
selected_score = "degree_centrality"
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.centrality_scores(adata, cluster_key=C_KEY)

pl.centrality_scores(adata, cluster_key=C_KEY, score=selected_score, dpi=DPI)

def test_plot_nhood_enrichment(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)

pl.nhood_enrichment(adata, cluster_key=C_KEY)

def test_plot_nhood_enrichment_ax(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)

fig, ax = plt.subplots(figsize=(2, 2), constrained_layout=True)
pl.nhood_enrichment(adata, cluster_key=C_KEY, ax=ax)

def test_plot_nhood_enrichment_dendro(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)

# use count to avoid nan for scipy.cluster.hierarchy
Expand Down Expand Up @@ -110,13 +110,13 @@ def test_tol_plot_co_occurrence_palette(self, adata_palette: AnnData):

class TestHeatmap(PlotTester, metaclass=PlotTesterMeta):
def test_plot_cbar_vmin_vmax(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)

pl.nhood_enrichment(adata, cluster_key=C_KEY, vmin=10, vmax=20)

def test_plot_cbar_kwargs(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.spatial_neighbors_grid(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)

pl.nhood_enrichment(adata, cluster_key=C_KEY, cbar_kwargs={"label": "FOOBARBAZQUUX"})
Expand Down
8 changes: 4 additions & 4 deletions tests/plotting/test_spatial_static.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@

from squidpy import pl
from squidpy._constants._pkg_constants import Key
from squidpy.gr import spatial_neighbors
from squidpy.gr import spatial_neighbors_grid, spatial_neighbors_radius
from squidpy.pl._spatial_utils import _get_library_id
from tests.conftest import PlotTester, PlotTesterMeta

Expand Down Expand Up @@ -80,7 +80,7 @@ def test_plot_spatial_scatter_crop_noorigin(self, adata_hne_concat: AnnData):
)

def test_plot_spatial_scatter_group_multi(self, adata_hne: AnnData):
spatial_neighbors(adata_hne)
spatial_neighbors_grid(adata_hne)
pl.spatial_scatter(
adata_hne,
shape="circle",
Expand Down Expand Up @@ -109,7 +109,7 @@ def test_plot_spatial_scatter_group(self, adata_hne_concat: AnnData):

def test_plot_spatial_scatter_nospatial(self, adata_hne_concat: AnnData):
adata = adata_hne_concat.copy()
spatial_neighbors(adata)
spatial_neighbors_grid(adata)
adata.uns.pop("spatial")
pl.spatial_scatter(
adata_hne_concat,
Expand All @@ -134,7 +134,7 @@ def test_plot_spatial_scatter_axfig(self, adata_hne: AnnData):

@pytest.mark.skipif(platform.system() == "Darwin", reason="Fails on macOS 3.8 CI")
def test_plot_spatial_scatter_novisium(self, adata_mibitof: AnnData):
spatial_neighbors(adata_mibitof, coord_type="generic", radius=50)
spatial_neighbors_radius(adata_mibitof, radius=50)
pl.spatial_scatter(
adata_mibitof,
library_key="library_id",
Expand Down
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