Initial tests for the rest v2 refactor

testing the annotations and the data format validation

.travis.yml

@@ -14,6 +14,3 @@ script:
   - set -eo pipefail
   - flake8 server/app/
   - pytest -s server/test/test_filter.py server/test/test_scanpy_engine.py
-  - cellxgene scanpy example-dataset/ &
-  - for i in {1..90}; do if http :5005/api/v0.1/initialize > /dev/null; then break; else echo "Waiting for server..."; sleep 1; fi; done
-  - pytest server/test/test_api.py

pytest.ini

@@ -0,0 +1,3 @@
+[pytest]
+filterwarnings =
+    ignore::UserWarning

server/app/scanpy_engine/scanpy_engine.py

@@ -9,6 +9,7 @@ from scipy import stats
 from server.app.app import cache
 from server.app.driver.driver import CXGDriver
 
+
 class ScanpyEngine(CXGDriver):
 
     def __init__(self, data, graph_method="umap", diffexp_method="ttest"):
@@ -49,7 +50,8 @@ class ScanpyEngine(CXGDriver):
 
     def _validatate_data_types(self):
         if self.data.X.dtype != 'float32':
-            warnings.warn(f"Scanpy data matrix is in {self.data.X.dtype} format not float32. Precision may be truncated.")
+            warnings.warn(f"Scanpy data matrix is in {self.data.X.dtype} format not float32. "
+                          f"Precision may be truncated.")
 
     def cells(self):
         return list(self.data.obs.index)

server/test/test_scanpy_engine.py

@@ -5,7 +5,7 @@ from server.app.scanpy_engine.scanpy_engine import ScanpyEngine
 
 class UtilTest(unittest.TestCase):
     def setUp(self):
-        self.data = ScanpyEngine("example-dataset/", schema="data_schema.json")
+        self.data = ScanpyEngine("example-dataset/")
 
     def test_init(self):
         self.assertEqual(self.data.cell_count, 2638)
@@ -13,57 +13,15 @@ class UtilTest(unittest.TestCase):
         epsilon = 0.000005
         self.assertTrue(self.data.data.X[0,0] - -0.17146951 < epsilon)
 
-    def test_schema(self):
-        self.assertEqual(self.data.schema, {'CellName': {'type': 'string', 'variabletype': 'categorical', 'displayname': 'Name', 'include': True}, 'n_genes': {'type': 'int', 'variabletype': 'continuous', 'displayname': 'Num Genes', 'include': True}, 'percent_mito': {'type': 'float', 'variabletype': 'continuous', 'displayname': 'Mitochondrial Percentage', 'include': True}, 'n_counts': {'type': 'float', 'variabletype': 'continuous', 'displayname': 'Num Counts', 'include': True}, 'louvain': {'type': 'string', 'variabletype': 'categorical', 'displayname': 'Louvain Cluster', 'include': True}})
-
-    def test_cells(self):
-        cells = self.data.cells()
-        self.assertIn("AAACATACAACCAC-1", cells)
-        self.assertEqual(len(cells), 2638)
-
-    def test_genes(self):
-        genes = self.data.genes()
-        self.assertIn("SEPT4", genes)
-        self.assertEqual(len(genes), 1838)
-
-    def test_filter_categorical(self):
-        filter = {"louvain": {"variable_type": "categorical", "value_type": "string", "query": ["B cells"]}}
-        filtered_data = self.data.filter_cells(filter)
-        self.assertEqual(filtered_data.shape, (342, 1838))
-        louvain_vals = filtered_data.obs['louvain'].tolist()
-        self.assertIn("B cells", louvain_vals)
-        self.assertNotIn("NK cells", louvain_vals)
-
-    def test_filter_continuous(self):
-        # print(self.data.data.obs["n_genes"].tolist())
-        filter = {"n_genes": {"variable_type": "continuous", "value_type": "int", "query": {"min": 300, "max": 400}}}
-        filtered_data = self.data.filter_cells(filter)
-        self.assertEqual(filtered_data.shape, (71, 1838))
-        n_genes_vals = filtered_data.obs['n_genes'].tolist()
-        for val in n_genes_vals:
-            self.assertTrue(300 <= val <= 400)
-
-    def test_metadata(self):
-        metadata = self.data.metadata(df=self.data.data)
-        self.assertEqual(len(metadata), 2638)
-        self.assertIn('louvain', metadata[0])
-
-    @unittest.skip("Umap not producing the same graph on different systems, even with the same seed. Skipping for now")
-    def test_create_graph(self):
-        graph = self.data.create_graph(df=self.data.data)
-        self.assertEqual(graph[0][1], 0.5545382653143183)
-        self.assertEqual(graph[0][2], 0.6021833809031731)
-
-    def test_diffexp(self):
-        diffexp = self.data.diffexp(["AAACATACAACCAC-1", "AACCGATGGTCATG-1"], ["CCGATAGACCTAAG-1", "GGTGGAGAAGTAGA-1"], 0.5, 7)
-        self.assertEqual(diffexp["celllist1"]["topgenes"], ['EBNA1BP2', 'DIAPH1', 'SLC25A11', 'SNRNP27', 'COMMD8', 'COTL1', 'GTF3A'])
-
-    def test_expression(self):
-        expression = self.data.expression(cells=["AAACATACAACCAC-1"])
-        data_exp = self.data.data[["AAACATACAACCAC-1"], :].X
-        for idx in range(len(expression["cells"][0]["e"])):
-            self.assertEqual(expression["cells"][0]["e"][idx], data_exp[idx])
+    def test_mandatory_annotations(self):
+        self.assertIn("name", self.data.data.obs)
+        self.assertEqual(list(self.data.data.obs.index), list(range(2638)))
+        self.assertIn("name", self.data.data.var)
+        self.assertEqual(list(self.data.data.var.index), list(range(1838)))
 
+    def test_data_type(self):
+        self.data.data.X = self.data.data.X.astype("float64")
+        self.assertWarns(UserWarning, self.data._validatate_data_types())
 
 if __name__ == '__main__':
     unittest.main()