Split out the local backend (#2052)

This splits the backend into two parts: the local backend for desktop cellxgene and the AWS backend for hosted cellxgene. The local backend is in local_server while the hosted remains in server. The general idea is to copy everything from server to local_server, pull unneeded stuff out of local_server, and keep server as-is for this PR. Not touching server means all the infra and deployment code will continue working just as it did before so we can make those changes incrementally.
2026-10-02 00:18:11 +08:00 · 2021-02-18 12:58:22 -08:00
parent 036b5f8c0f
commit fb61bd6e9c
153 changed files with 14027 additions and 46 deletions
@@ -0,0 +1,62 @@
+import unittest
+
+import numpy as np
+
+from local_server.data_common.matrix_loader import MatrixDataLoader
+from local_server.test import PROJECT_ROOT, app_config
+
+
+class DiffExpTest(unittest.TestCase):
+    """Tests the diffexp returns the expected results for one test case, using different
+    adaptor types and different algorithms."""
+
+    def load_dataset(self, path, extra_server_config={}, extra_dataset_config={}):
+        config = app_config(path, extra_server_config=extra_server_config, extra_dataset_config=extra_dataset_config)
+        loader = MatrixDataLoader(path)
+        adaptor = loader.open(config)
+        return adaptor
+
+    def get_mask(self, adaptor, start, stride):
+        """Simple function to return a mask or rows"""
+        rows = adaptor.get_shape()[0]
+        sel = list(range(start, rows, stride))
+        mask = np.zeros(rows, dtype=bool)
+        mask[sel] = True
+        return mask
+
+    def compare_diffexp_results(self, results, expects):
+        self.assertEqual(len(results), len(expects))
+        for result, expect in zip(results, expects):
+            self.assertEqual(result[0], expect[0])
+            self.assertTrue(np.isclose(result[1], expect[1], 1e-6, 1e-4))
+            self.assertTrue(np.isclose(result[2], expect[2], 1e-6, 1e-4))
+            self.assertTrue(np.isclose(result[3], expect[3], 1e-6, 1e-4))
+
+    def check_1_10_2_10(self, results):
+        """Checks the results for a specific set of rows selections"""
+        expects = [
+            [956, 0.016060986, 0.0008649321884808977, 1.0],
+            [1124, 0.96602094, 0.0011717216548271284, 1.0],
+            [1809, 1.1110606, 0.0019304405196777848, 1.0],
+            [1712, -0.5525154, 0.0051788902660723345, 1.0],
+            [1754, 0.5201581, 0.005691734062127954, 1.0],
+            [948, 1.6390722, 0.006622111055981219, 1.0],
+            [1810, 0.78618884, 0.007055917428377063, 1.0],
+            [779, 1.5241305, 0.007202934422407284, 1.0],
+            [1575, 1.0317602, 0.007830310753043345, 1.0],
+            [576, 0.97873515, 0.008272092578813124, 1.0],
+        ]
+        self.compare_diffexp_results(results, expects)
+
+    def get_X_col(self, adaptor, cols):
+        varmask = np.zeros(adaptor.get_shape()[1], dtype=bool)
+        varmask[cols] = True
+        return adaptor.get_X_array(None, varmask)
+
+    def test_anndata_default(self):
+        """Test an anndata adaptor with its default diffexp algorithm (diffexp_generic)"""
+        adaptor = self.load_dataset(f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad")
+        maskA = self.get_mask(adaptor, 1, 10)
+        maskB = self.get_mask(adaptor, 2, 10)
+        results = adaptor.compute_diffexp_ttest(maskA, maskB, 10)
+        self.check_1_10_2_10(results)