def test_set_subset_varm(adata, subset_func): init_hash = joblib.hash(adata) orig_varm_val = adata.varm["o"].copy() while True: subset_idx = slice_subset(adata.var_names) if (adata[:, subset_idx]).shape[1] > 2: break subset = adata[:, subset_idx] internal_idx = _normalize_index( subset_func(np.arange(subset.varm["o"].shape[0])), subset.var_names) assert subset.is_view subset.varm["o"][internal_idx] = 1 assert not subset.is_view assert np.all(adata.varm["o"] == orig_varm_val) assert init_hash == joblib.hash(adata)
def test_not_set_subset_X(matrix_type, subset_func): adata = ad.AnnData(matrix_type(asarray(sparse.random(20, 20)))) init_hash = joblib.hash(adata) orig_X_val = adata.X.copy() while True: subset_idx = slice_subset(adata.obs_names) if len(adata[subset_idx, :]) > 2: break subset = adata[subset_idx, :] subset = adata[:, subset_idx] internal_idx = _normalize_index(subset_func(np.arange(subset.X.shape[1])), subset.var_names) assert subset.is_view subset.X[:, internal_idx] = 1 assert not subset.is_view assert not np.any(asarray(adata.X != orig_X_val)) assert init_hash == joblib.hash(adata)