def test_data_named_gene(self): var_index_col_name = self.data.get_schema( )["annotations"]["var"]["index"] filter_ = { "filter": { "var": { "annotation_value": [{ "name": var_index_col_name, "values": ["RER1"] }] } } } fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 1) self.assertEqual(data["col_idx"], [4]) filter_ = { "filter": { "var": { "annotation_value": [{ "name": var_index_col_name, "values": ["SPEN", "TYMP", "PRMT2"] }] } } } fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 3) self.assertTrue((data["col_idx"] == [15, 1818, 1837]).all())
def test_annotation(self): annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("obs")) obs_index_col_name = self.data.schema["annotations"]["obs"]["index"] self.assertEqual(annotations["col_idx"], [obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain"]) self.assertEqual(annotations["n_rows"], 100) self.assertTrue(math.isnan(annotations["columns"][2][0])) annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("var")) var_index_col_name = self.data.schema["annotations"]["var"]["index"] self.assertEqual(annotations["col_idx"], [var_index_col_name, "n_cells", "var_with_nans"]) self.assertEqual(annotations["n_rows"], 100) self.assertTrue(math.isnan(annotations["columns"][2][0]))
def test_annotation_fields(self): fbs = self.data.annotation_to_fbs_matrix("obs", ["n_genes", "n_counts"]) annotations = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(annotations["n_rows"], 2638) self.assertEqual(annotations["n_cols"], 2) var_index_col_name = self.data.get_schema( )["annotations"]["var"]["index"] fbs = self.data.annotation_to_fbs_matrix("var", [var_index_col_name]) annotations = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(annotations["n_rows"], 1838) self.assertEqual(annotations["n_cols"], 1)
def test_layout_fields(self): """ X_pca, X_tsne, X_umap are available """ fbs = self.data.layout_to_fbs_matrix(["pca"]) layout = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(layout["n_cols"], 2) self.assertEqual(layout["n_rows"], 2638) self.assertCountEqual(layout["col_idx"], ["pca_0", "pca_1"]) fbs = self.data.layout_to_fbs_matrix(["tsne", "pca"]) layout = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(layout["n_cols"], 4) self.assertEqual(layout["n_rows"], 2638) self.assertCountEqual(layout["col_idx"], ["tsne_0", "tsne_1", "pca_0", "pca_1"])
def test_filtered_data_frame(self): filter_ = { "filter": { "var": { "annotation_value": [{ "name": "n_cells", "min": 100 }] } } } fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 1040) filter_ = { "filter": { "obs": { "annotation_value": [{ "name": "n_counts", "min": 3000 }] } } } with self.assertRaises(FilterError): self.data.data_frame_to_fbs_matrix(filter_["filter"], "var")
def on_start(self): self.client.verify = False self.dataset = random.choice(DataSets) with self.client.get(f"{self.dataset}/{API_SUFFIX}/schema", stream=True, catch_response=True) as schema_response: if schema_response.status_code == 200: self.schema = schema_response.json()["schema"] else: self.schema = None with self.client.get(f"{self.dataset}/{API_SUFFIX}/config", stream=True, catch_response=True) as config_response: if config_response.status_code == 200: self.config = config_response.json()["config"] else: self.config = None with self.client.get( f"{self.dataset}/{API_SUFFIX}/annotations/var?annotation-name={self.var_index_name()}", headers={"Accept": "application/octet-stream"}, catch_response=True, ) as var_index_response: if var_index_response.status_code == 200: df = decode_fbs.decode_matrix_FBS(var_index_response.content) gene_names_idx = df["col_idx"].index(self.var_index_name()) self.gene_names = df["columns"][gene_names_idx] else: self.gene_names = []
def test_annotation_var(self): endpoint = "annotations/var" url = f"{self.url_base}{endpoint}" result = self.session.get(url) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertTrue(math.isnan(df["columns"][2][0]))
def test_data_frame(self): f1 = {"var": {"index": [[0, 10]]}} fbs = self.data.data_frame_to_fbs_matrix(f1, "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 10) with self.assertRaises(ValueError): self.data.data_frame_to_fbs_matrix(None, "obs")
def test_data(self): endpoint = "data/var" url = f"{self.url_base}{endpoint}" filter = {"filter": {"var": {"index": [[0, 20]]}}} result = self.session.put(url, json=filter) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertTrue(math.isnan(df["columns"][3][3]))
def test_layout(self): fbs = self.data.layout_to_fbs_matrix(fields=None) layout = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(layout["n_cols"], 6) self.assertEqual(layout["n_rows"], 2638) X = layout["columns"][0] self.assertTrue((X >= 0).all() and (X <= 1).all()) Y = layout["columns"][1] self.assertTrue((Y >= 0).all() and (Y <= 1).all())
def test_dataframe(self): data_frame_var = decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "var")) self.assertIsNotNone(data_frame_var) self.assertEqual(data_frame_var["n_rows"], 100) self.assertEqual(data_frame_var["n_cols"], 100) self.assertTrue(math.isnan(data_frame_var["columns"][3][3])) with pytest.raises(FilterError): self.data.data_frame_to_fbs_matrix("an erroneous filter", "var") with pytest.raises(FilterError): filter_ = {"filter": {"obs": {"index": [1, 99, [200, 300]]}}} self.data.data_frame_to_fbs_matrix(filter_["filter"], "var")
def fbs_checks(self, fbs, dims, expected_types, expected_column_idx): d = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(d["n_rows"], dims[0]) self.assertEqual(d["n_cols"], dims[1]) self.assertIsNone(d["row_idx"]) self.assertEqual(len(d["columns"]), dims[1]) for i in range(0, len(d["columns"])): self.assertEqual(len(d["columns"][i]), dims[0]) self.assertIsInstance(d["columns"][i], expected_types[i][0]) if expected_types[i][1] is not None: self.assertEqual(d["columns"][i].dtype, expected_types[i][1]) if expected_column_idx is not None: self.assertSetEqual(set(expected_column_idx), set(d["col_idx"]))
def test_data_get_unknown_filter_fbs(self): index_col_name = self.schema["schema"]["annotations"]["var"]["index"] endpoint = "data/var" query = f"var:{index_col_name}=UNKNOWN" url = f"{self.URL_BASE}{endpoint}?{query}" header = {"Accept": "application/octet-stream"} result = self.session.get(url, headers=header) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 2638) self.assertEqual(df["n_cols"], 0)
def test_annotations(self): fbs = self.data.annotation_to_fbs_matrix("obs") annotations = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(annotations["n_rows"], 2638) self.assertEqual(annotations["n_cols"], 5) obs_index_col_name = self.data.get_schema( )["annotations"]["obs"]["index"] self.assertEqual( annotations["col_idx"], [ obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain" ], ) fbs = self.data.annotation_to_fbs_matrix("var") annotations = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(annotations["n_rows"], 1838) self.assertEqual(annotations["n_cols"], 2) var_index_col_name = self.data.get_schema( )["annotations"]["var"]["index"] self.assertEqual(annotations["col_idx"], [var_index_col_name, "n_cells"])
def test_filter_complex(self): filter_ = { "filter": { "var": { "annotation_value": [{ "name": "n_cells", "min": 10 }], "index": [1, 99, [200, 300]] } } } fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 91)
def test_get_annotations_var_keys_fbs(self): endpoint = "annotations/var" query = "annotation-name=n_cells" url = f"{self.URL_BASE}{endpoint}?{query}" header = {"Accept": "application/octet-stream"} result = self.session.get(url, headers=header) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 1838) self.assertEqual(df["n_cols"], 1) self.assertIsNotNone(df["columns"]) self.assertIsNone(df["row_idx"]) self.assertEqual(len(df["columns"]), df["n_cols"]) self.assertCountEqual(df["col_idx"], ["n_cells"])
def test_data_put_filter_fbs(self): endpoint = "data/var" url = f"{self.URL_BASE}{endpoint}" header = {"Accept": "application/octet-stream"} filter = {"filter": {"var": {"index": [0, 1, 4]}}} result = self.session.put(url, headers=header, json=filter) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 2638) self.assertEqual(df["n_cols"], 3) self.assertIsNotNone(df["columns"]) self.assertIsNone(df["row_idx"]) self.assertEqual(len(df["columns"]), df["n_cols"]) self.assertListEqual(df["col_idx"].tolist(), [0, 1, 4])
def _test_get_user_annotations_obs_keys_fbs(self, annotation_name, columns): endpoint = "annotations/obs" query = f"annotation-name={annotation_name}" url = f"{self.URL_BASE}{endpoint}?{query}" header = {"Accept": "application/octet-stream"} result = self.session.get(url, headers=header) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 2638) self.assertEqual(df["n_cols"], 1) self.assertListEqual(df["col_idx"], [annotation_name]) self.assertEqual(set(df["columns"][0]), columns) self.assertIsNone(df["row_idx"]) self.assertEqual(len(df["columns"]), df["n_cols"])
def test_get_layout_fbs(self): endpoint = "layout/obs" url = f"{self.URL_BASE}{endpoint}" header = {"Accept": "application/octet-stream"} result = self.session.get(url, headers=header) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 2638) self.assertEqual(df["n_cols"], 8) self.assertIsNotNone(df["columns"]) self.assertSetEqual( set(df["col_idx"]), { "pca_0", "pca_1", "tsne_0", "tsne_1", "umap_0", "umap_1", "draw_graph_fr_0", "draw_graph_fr_1" }, ) self.assertIsNone(df["row_idx"]) self.assertEqual(len(df["columns"]), df["n_cols"])
def test_data_put_single_var(self): endpoint = "data/var" url = f"{self.URL_BASE}{endpoint}" header = {"Accept": "application/octet-stream"} index_col_name = self.schema["schema"]["annotations"]["var"]["index"] var_filter = { "filter": { "var": { "annotation_value": [{ "name": index_col_name, "values": ["RER1"] }] } } } result = self.session.put(url, headers=header, json=var_filter) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 2638) self.assertEqual(df["n_cols"], 1)
def test_get_annotations_obs_fbs(self): endpoint = "annotations/obs" url = f"{self.URL_BASE}{endpoint}" header = {"Accept": "application/octet-stream"} result = self.session.get(url, headers=header) self.assertEqual(result.status_code, HTTPStatus.OK) self.assertEqual(result.headers["Content-Type"], "application/octet-stream") df = decode_fbs.decode_matrix_FBS(result.content) self.assertEqual(df["n_rows"], 2638) self.assertEqual(df["n_cols"], 6 if self.ANNOTATIONS_ENABLED else 5) self.assertIsNotNone(df["columns"]) self.assertIsNone(df["row_idx"]) self.assertEqual(len(df["columns"]), df["n_cols"]) obs_index_col_name = self.schema["schema"]["annotations"]["obs"][ "index"] self.assertCountEqual( df["col_idx"], [ obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain" ] + (["cluster-test"] if self.ANNOTATIONS_ENABLED else []), )
def test_dataframe_obs_not_implemented(self): with self.assertRaises(ValueError) as cm: decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "obs")) self.assertIsNotNone(cm.exception)
def test_filter_idx(self): filter_ = {"filter": {"var": {"index": [1, 99, [200, 300]]}}} fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 102)