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_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.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_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_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 test_data_frame(self): fbs = self.data.data_frame_to_fbs_matrix(None, "var") data = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(data["n_rows"], 2638) self.assertEqual(data["n_cols"], 1838) with self.assertRaises(ValueError): self.data.data_frame_to_fbs_matrix(None, "obs")
def test_annotation_var(self): endpoint = "annotations/var" url = f"{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_layout(self): fbs = self.data.layout_to_fbs_matrix() layout = decode_fbs.decode_matrix_FBS(fbs) self.assertEqual(layout["n_cols"], 2) 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_annotation(self): annotations = decode_fbs.decode_matrix_FBS( self.data.annotation_to_fbs_matrix("obs")) self.assertEqual( annotations["col_idx"], ["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")) self.assertEqual(annotations["col_idx"], ["name", "n_cells", "var_with_nans"]) self.assertEqual(annotations["n_rows"], 100) self.assertTrue(math.isnan(annotations["columns"][2][0])) with pytest.raises(JSONEncodingValueError): json.loads(self.data.annotation(None, "obs")) with pytest.raises(JSONEncodingValueError): json.loads(self.data.annotation(None, "var"))
def test_data_put_single_var(self): endpoint = f"data/var" url = f"{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_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.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.schema["annotations"]["var"]["index"] self.assertEqual(annotations["col_idx"], [var_index_col_name, "n_cells"])
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(JSONEncodingValueError): json.loads(self.data.data_frame(None, "obs")) with pytest.raises(JSONEncodingValueError): json.loads(self.data.data_frame(None, "var"))
def test_put_get_roundtrip(self): # verify that OBS PUTs (annotation_put_fbs) are accessible via # GET (annotation_to_fbs_matrix) n_rows = self.data.data.obs.shape[0] fbs = self.make_fbs({ 'cat_A': pd.Series(['label_A' for l in range(0, n_rows)], dtype='category'), 'cat_B': pd.Series(['label_B' for l in range(0, n_rows)], dtype='category') }) # put res = self.data.annotation_put_fbs("obs", fbs) self.assertEqual(res, json.dumps({"status": "OK"})) # get fbsAll = self.data.annotation_to_fbs_matrix("obs") schema = self.data.get_schema() annotations = decode_fbs.decode_matrix_FBS(fbsAll) obs_index_col_name = schema["annotations"]["obs"]["index"] self.assertEqual(annotations["n_rows"], n_rows) self.assertEqual(annotations["n_cols"], 7) self.assertIsNone(annotations["row_idx"]) self.assertEqual(annotations["col_idx"], [ obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain", "cat_A", "cat_B" ]) col_idx = annotations["col_idx"] self.assertEqual(annotations["columns"][col_idx.index('cat_A')], ['label_A' for l in range(0, n_rows)]) self.assertEqual(annotations["columns"][col_idx.index('cat_B')], ['label_B' for l in range(0, n_rows)]) # verify the schema was updated all_col_schema = { c["name"]: c for c in schema["annotations"]["obs"]["columns"] } self.assertEqual( all_col_schema["cat_A"], { "name": "cat_A", "type": "categorical", "categories": ["label_A"], "writable": True }) self.assertEqual( all_col_schema["cat_B"], { "name": "cat_B", "type": "categorical", "categories": ["label_B"], "writable": True })
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 test_data_put_fbs(self): endpoint = f"data/var" url = f"{URL_BASE}{endpoint}" header = {"Accept": "application/octet-stream"} result = self.session.put(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'], 1838) self.assertIsNotNone(df['columns']) self.assertListEqual(df['col_idx'].tolist(), []) self.assertIsNone(df['row_idx']) self.assertEqual(len(df['columns']), df['n_cols'])
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_obs_keys_fbs(self): endpoint = "annotations/obs" query = "annotation-name=n_genes&annotation-name=percent_mito" url = f"{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'], 2) self.assertIsNotNone(df['columns']) self.assertIsNotNone(df['col_idx']) self.assertIsNone(df['row_idx']) self.assertEqual(len(df['columns']), df['n_cols']) self.assertListEqual(df['col_idx'], ['n_genes', 'percent_mito'])
def test_get_layout_fbs(self): endpoint = "layout/obs" url = f"{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.assertListEqual(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_get_annotations_var_fbs(self): endpoint = "annotations/var" url = f"{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'], 1838) self.assertEqual(df['n_cols'], 2) self.assertIsNotNone(df['columns']) self.assertIsNotNone(df['col_idx']) self.assertIsNone(df['row_idx']) self.assertEqual(len(df['columns']), df['n_cols']) self.assertListEqual(df['col_idx'], ['name', 'n_cells'])
def test_get_annotations_obs_fbs(self): endpoint = "annotations/obs" url = f"{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'], 5) self.assertIsNotNone(df['columns']) self.assertIsNotNone(df['col_idx']) self.assertIsNone(df['row_idx']) self.assertEqual(len(df['columns']), df['n_cols']) obs_index_col_name = self.schema["schema"]["annotations"]["obs"]["index"] self.assertListEqual(df['col_idx'], [obs_index_col_name, 'n_genes', 'percent_mito', 'n_counts', 'louvain'])
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)
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)