def test_reproducibility(self, adata: AnnData, n_jobs: int):
spatial_neighbors(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)
res3 = nhood_enrichment(adata,
cluster_key=_CK,
seed=43,
n_jobs=n_jobs,
n_perms=20,
copy=True)
assert len(res1) == len(res2)
assert len(res2) == len(res3)
for key in range(len(res1)):
np.testing.assert_array_equal(res2[key], res1[key])
if key == 0: # z-score
with pytest.raises(AssertionError):
np.testing.assert_array_equal(res3[key], res2[key])
else: # counts
np.testing.assert_array_equal(res3[key], res2[key])
def test_plot_nhood_enrichment_dendro(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)
# use count to avoid nan for scipy.cluster.hierarchy
pl.nhood_enrichment(adata,
cluster_key=C_KEY,
mode="count",
method="single")
def test_parallel_works(self, adata: AnnData, backend: str):
spatial_neighbors(adata)
nhood_enrichment(adata,
cluster_key=_CK,
n_jobs=2,
n_perms=20,
backend=backend)
self._assert_common(adata)
def test_plot_cbar_kwargs(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)
pl.nhood_enrichment(adata,
cluster_key=C_KEY,
cbar_kwargs={
"label": "FOOBARBAZQUUX",
"filled": False
})
def test_nhood_enrichment(self, adata: AnnData):
spatial_neighbors(adata)
nhood_enrichment(adata, cluster_key=_CK)
self._assert_common(adata)
def test_plot_cbar_vmin_vmax(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)
pl.nhood_enrichment(adata, cluster_key=C_KEY, vmin=10, vmax=20)
def test_plot_nhood_enrichment(self, adata: AnnData):
gr.spatial_neighbors(adata)
gr.nhood_enrichment(adata, cluster_key=C_KEY)
pl.nhood_enrichment(adata, cluster_key=C_KEY)