var=pd.DataFrame({"genes": 'g1 g2 g3'.split()}).set_index('genes'),
)
a.obs['foo'] = a.obs['foo'].astype('category')
sc.pl.heatmap(
a, var_names=a.var_names, groupby='foo', swap_axes=True, figsize=(4, 4)
)
save_and_compare_images('master_heatmap_small_swap_alignment')
sc.pl.heatmap(
a, var_names=a.var_names, groupby='foo', swap_axes=False, figsize=(4, 4)
)
save_and_compare_images('master_heatmap_small_alignment')
@pytest.mark.skipif(
pkg_version("matplotlib") < version.parse('3.1'),
reason="https://github.com/mwaskom/seaborn/issues/1953",
)
@pytest.mark.parametrize(
"obs_keys,name",
[(None, "master_clustermap"), ("cell_type", "master_clustermap_withcolor")],
)
def test_clustermap(image_comparer, obs_keys, name):
save_and_compare_images = image_comparer(ROOT, FIGS, tol=15)
adata = sc.datasets.krumsiek11()
sc.pl.clustermap(adata, obs_keys)
save_and_compare_images(name)
@pytest.mark.parametrize(
"id,fn",
@pytest.mark.parametrize('n', [3, 4])
def test_neighbors_defaults(adatas, n):
adata_ref = adatas[0].copy()
adata_new = adatas[1].copy()
sc.pp.neighbors(adata_ref, n_neighbors=n)
ing = sc.tl.Ingest(adata_ref)
ing.fit(adata_new)
ing.neighbors()
assert ing._indices.shape[1] == n
@pytest.mark.skipif(
pkg_version("anndata") < sc.tl._ingest.ANNDATA_MIN_VERSION,
reason=
"`AnnData.concatenate` does not concatenate `.obsm` in old anndata versions",
)
def test_ingest_function(adatas):
adata_ref = adatas[0].copy()
adata_new = adatas[1].copy()
sc.tl.ingest(
adata_new,
adata_ref,
obs='bulk_labels',
embedding_method=['umap', 'pca'],
inplace=True,
)
