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, )