mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-27 05:38:12 +08:00
Apply yapf to python files
This commit is contained in:
Matt Weiden
@@ -14,6 +14,7 @@ from server.app.util.data_locator import DataLocator
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class WritableAnnotationTest(unittest.TestCase):
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def setUp(self):
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self.tmpDir = tempfile.mkdtemp()
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self.annotations_file = path.join(self.tmpDir, "test_annotations.csv")
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@@ -27,7 +28,8 @@ class WritableAnnotationTest(unittest.TestCase):
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"annotations_file": self.annotations_file,
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"annotations_output_dir": None
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}
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self.data = ScanpyEngine(DataLocator("../example-dataset/pbmc3k.h5ad"), args)
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self.data = ScanpyEngine(DataLocator("../example-dataset/pbmc3k.h5ad"),
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args)
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def tearDown(self):
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shutil.rmtree(self.tmpDir)
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@@ -41,7 +43,9 @@ class WritableAnnotationTest(unittest.TestCase):
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n_rows = self.data.data.obs.shape[0]
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fbs_bad = self.make_fbs({
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'louvain': pd.Series(['undefined' for l in range(0, n_rows)], dtype='category')
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'louvain':
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pd.Series(['undefined' for l in range(0, n_rows)],
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dtype='category')
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})
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# ensure attempt to change VAR annotation
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@@ -56,31 +60,49 @@ class WritableAnnotationTest(unittest.TestCase):
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# verify the file is written as expected
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n_rows = self.data.data.obs.shape[0]
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fbs = self.make_fbs({
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'cat_A': pd.Series(['label_A' for l in range(0, n_rows)], dtype='category'),
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'cat_B': pd.Series(['label_B' for l in range(0, n_rows)], dtype='category')
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'cat_A':
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pd.Series(['label_A' for l in range(0, n_rows)],
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dtype='category'),
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'cat_B':
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pd.Series(['label_B' for l in range(0, n_rows)],
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dtype='category')
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})
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res = self.data.annotation_put_fbs("obs", fbs)
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self.assertEqual(res, json.dumps({"status": "OK"}))
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self.assertTrue(path.exists(self.annotations_file))
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df = pd.read_csv(self.annotations_file, index_col=0, header=0, comment='#')
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df = pd.read_csv(self.annotations_file,
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index_col=0,
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header=0,
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comment='#')
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self.assertEqual(df.shape, (n_rows, 2))
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self.assertEqual(set(df.columns), set(['cat_A', 'cat_B']))
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self.assertTrue(self.data.original_obs_index.equals(df.index))
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self.assertTrue(np.all(df['cat_A'] == ['label_A' for l in range(0, n_rows)]))
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self.assertTrue(np.all(df['cat_B'] == ['label_B' for l in range(0, n_rows)]))
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self.assertTrue(
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np.all(df['cat_A'] == ['label_A' for l in range(0, n_rows)]))
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self.assertTrue(
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np.all(df['cat_B'] == ['label_B' for l in range(0, n_rows)]))
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# verify complete overwrite on second attempt, AND rotation occurs
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fbs = self.make_fbs({
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'cat_A': pd.Series(['label_A1' for l in range(0, n_rows)], dtype='category'),
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'cat_C': pd.Series(['label_C' for l in range(0, n_rows)], dtype='category')
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'cat_A':
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pd.Series(['label_A1' for l in range(0, n_rows)],
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dtype='category'),
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'cat_C':
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pd.Series(['label_C' for l in range(0, n_rows)],
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dtype='category')
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})
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res = self.data.annotation_put_fbs("obs", fbs)
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self.assertEqual(res, json.dumps({"status": "OK"}))
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self.assertTrue(path.exists(self.annotations_file))
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df = pd.read_csv(self.annotations_file, index_col=0, header=0, comment='#')
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df = pd.read_csv(self.annotations_file,
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index_col=0,
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header=0,
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comment='#')
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self.assertEqual(set(df.columns), set(['cat_A', 'cat_C']))
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self.assertTrue(np.all(df['cat_A'] == ['label_A1' for l in range(0, n_rows)]))
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self.assertTrue(np.all(df['cat_C'] == ['label_C' for l in range(0, n_rows)]))
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self.assertTrue(
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np.all(df['cat_A'] == ['label_A1' for l in range(0, n_rows)]))
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self.assertTrue(
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np.all(df['cat_C'] == ['label_C' for l in range(0, n_rows)]))
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# rotation
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name, ext = path.splitext(self.annotations_file)
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@@ -93,8 +115,12 @@ class WritableAnnotationTest(unittest.TestCase):
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# verify we stop rotation at 9
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n_rows = self.data.data.obs.shape[0]
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fbs = self.make_fbs({
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'cat_A': pd.Series(['label_A' for l in range(0, n_rows)], dtype='category'),
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'cat_B': pd.Series(['label_B' for l in range(0, n_rows)], dtype='category')
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'cat_A':
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pd.Series(['label_A' for l in range(0, n_rows)],
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dtype='category'),
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'cat_B':
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pd.Series(['label_B' for l in range(0, n_rows)],
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dtype='category')
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})
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for i in range(0, 11):
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res = self.data.annotation_put_fbs("obs", fbs)
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@@ -112,8 +138,12 @@ class WritableAnnotationTest(unittest.TestCase):
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n_rows = self.data.data.obs.shape[0]
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fbs = self.make_fbs({
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'cat_A': pd.Series(['label_A' for l in range(0, n_rows)], dtype='category'),
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'cat_B': pd.Series(['label_B' for l in range(0, n_rows)], dtype='category')
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'cat_A':
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pd.Series(['label_A' for l in range(0, n_rows)],
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dtype='category'),
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'cat_B':
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pd.Series(['label_B' for l in range(0, n_rows)],
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dtype='category')
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})
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# put
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@@ -129,27 +159,30 @@ class WritableAnnotationTest(unittest.TestCase):
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self.assertEqual(annotations["n_cols"], 7)
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self.assertIsNone(annotations["row_idx"])
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self.assertEqual(annotations["col_idx"], [
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obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain", "cat_A", "cat_B"
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obs_index_col_name, "n_genes", "percent_mito", "n_counts",
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"louvain", "cat_A", "cat_B"
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])
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col_idx = annotations["col_idx"]
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self.assertEqual(annotations["columns"][col_idx.index('cat_A')], [
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'label_A' for l in range(0, n_rows)
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])
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self.assertEqual(annotations["columns"][col_idx.index('cat_B')], [
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'label_B' for l in range(0, n_rows)
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])
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self.assertEqual(annotations["columns"][col_idx.index('cat_A')],
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['label_A' for l in range(0, n_rows)])
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self.assertEqual(annotations["columns"][col_idx.index('cat_B')],
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['label_B' for l in range(0, n_rows)])
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# verify the schema was updated
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all_col_schema = {c["name"]: c for c in schema["annotations"]["obs"]["columns"]}
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self.assertEqual(all_col_schema["cat_A"], {
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"name": "cat_A",
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"type": "categorical",
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"categories": ["label_A"],
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"writable": True
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})
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self.assertEqual(all_col_schema["cat_B"], {
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"name": "cat_B",
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"type": "categorical",
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"categories": ["label_B"],
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"writable": True
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})
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all_col_schema = {
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c["name"]: c for c in schema["annotations"]["obs"]["columns"]
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}
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self.assertEqual(
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all_col_schema["cat_A"], {
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"name": "cat_A",
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"type": "categorical",
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"categories": ["label_A"],
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"writable": True
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})
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self.assertEqual(
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all_col_schema["cat_B"], {
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"name": "cat_B",
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"type": "categorical",
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"categories": ["label_B"],
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"writable": True
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})
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