import json from os import path import pytest import time import unittest import argparse import numpy as np from pandas import Series from server.app.scanpy_engine.scanpy_engine import ScanpyEngine class UtilTest(unittest.TestCase): def setUp(self): args = {'layout': 'umap', 'diffexp': 'ttest', 'max_category_items': 100, 'obs_names': None, 'var_names': None} self.data = ScanpyEngine("example-dataset/pbmc3k.h5ad", args) self.data._create_schema() def test_init(self): self.assertEqual(self.data.cell_count, 2638) self.assertEqual(self.data.gene_count, 1838) epsilon = 0.000005 self.assertTrue(self.data.data.X[0, 0] - -0.17146951 < epsilon) 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))) @pytest.mark.filterwarnings("ignore:Scanpy data matrix") def test_data_type(self): self.data.data.X = self.data.data.X.astype("float64") with self.assertWarns(UserWarning): self.data._validate_data_types() def test_filter_idx(self): filter_ = { "filter": { "var": { "index": [1, 99, [200, 300]] }, "obs": { "index": [1, 99, [1000, 2000]] } } } data = self.data.filter_dataframe(filter_["filter"]) self.assertEqual(data.shape, (1002, 102)) def test_filter_annotation(self): filter_ = { "filter": { "obs": { "annotation_value": [ {"name": "louvain", "values": ["NK cells", "CD8 T cells"]}, ] } } } data = self.data.filter_dataframe(filter_["filter"]) self.assertEqual(data.shape, (470, 1838)) filter_ = { "filter": { "obs": { "annotation_value": [ {"name": "n_counts", "min": 3000}, ] } } } data = self.data.filter_dataframe(filter_["filter"]) self.assertEqual(data.shape, (497, 1838)) def test_filter_annotation_no_uns(self): filter_ = { "filter": { "var": { "annotation_value": [ {"name": "name", "values": ["RER1"]}, ] } } } data = self.data.filter_dataframe(filter_["filter"]) self.assertEqual(data.shape[1], 1) def test_filter_complex(self): filter_ = { "filter": { "var": { "index": [1, 99, [200, 300]] }, "obs": { "annotation_value": [ {"name": "louvain", "values": ["NK cells", "CD8 T cells"]}, {"name": "n_counts", "min": 3000}, ], "index": [1, 99, [1000, 2000]] } } } data = self.data.filter_dataframe(filter_["filter"]) self.assertEqual(data.shape, (15, 102)) def test_obs_and_var_names(self): self.assertEqual(np.sum(self.data.data.var["name"].isna()), 0) self.assertEqual(np.sum(self.data.data.obs["name"].isna()), 0) def test_schema(self): with open(path.join(path.dirname(__file__), "schema.json")) as fh: schema = json.load(fh) self.assertEqual(self.data.schema, schema) def test_schema_produces_error(self): self.data.data.obs["time"] = Series(list([time.time() for i in range(self.data.cell_count)]), dtype="datetime64[ns]") with pytest.raises(TypeError): self.data._create_schema() def test_config(self): self.assertEqual(self.data.features["layout"]["obs"], {'available': True, 'interactiveLimit': 50000}) def test_layout(self): layout = self.data.layout(None) self.assertEqual(layout["ndims"], 2) self.assertEqual(len(layout["coordinates"]), 2638) self.assertEqual(layout["coordinates"][0][0], 0) for idx, val in enumerate(layout["coordinates"]): self.assertLessEqual(val[1], 1) self.assertLessEqual(val[2], 1) def test_annotations(self): annotations = self.data.annotation(None, "obs") self.assertEqual(annotations["names"], ["name", "n_genes", "percent_mito", "n_counts", "louvain"]) self.assertEqual(len(annotations["data"]), 2638) annotations = self.data.annotation(None, "var") self.assertEqual(annotations["names"], ["name", "n_cells"]) self.assertEqual(len(annotations["data"]), 1838) def test_annotation_fields(self): annotations = self.data.annotation(None, "obs", ["n_genes", "n_counts"]) self.assertEqual(annotations["names"], ["n_genes", "n_counts"]) self.assertEqual(len(annotations["data"]), 2638) annotations = self.data.annotation(None, "var", ["name"]) self.assertEqual(annotations["names"], ["name"]) self.assertEqual(len(annotations["data"]), 1838) def test_filtered_annotation(self): filter_ = { "filter": { "obs": { "annotation_value": [ {"name": "n_counts", "min": 3000}, ] }, "var": { "annotation_value": [ {"name": "name", "values": ["ATAD3C", "RER1"]}, ] } } } annotations = self.data.annotation(filter_["filter"], "obs") self.assertEqual(annotations["names"], ["name", "n_genes", "percent_mito", "n_counts", "louvain"]) self.assertEqual(len(annotations["data"]), 497) annotations = self.data.annotation(filter_["filter"], "var") self.assertEqual(annotations["names"], ["name", "n_cells"]) self.assertEqual(len(annotations["data"]), 2) def test_filtered_layout(self): filter_ = { "filter": { "obs": { "annotation_value": [ {"name": "n_counts", "min": 3000}, ] } } } layout = self.data.layout(filter_["filter"]) self.assertEqual(len(layout["coordinates"]), 497) def test_diffexp_topN(self): f1 = { "filter": { "obs": { "index": [[0, 500]] } } } f2 = { "filter": { "obs": { "index": [[500, 1000]] } } } result = self.data.diffexp_topN(f1["filter"], f2["filter"]) self.assertEqual(len(result), 10) var_idx = [i[0] for i in result] self.assertEqual(var_idx, sorted(var_idx)) result = self.data.diffexp_topN(f1["filter"], f2["filter"], 20) self.assertEqual(len(result), 20) def test_data_frame(self): data_frame_obs = self.data.data_frame(None, "obs") self.assertEqual(len(data_frame_obs["var"]), 1838) self.assertEqual(len(data_frame_obs["obs"]), 2638) data_frame_var = self.data.data_frame(None, "var") self.assertEqual(len(data_frame_var["var"]), 1838) self.assertEqual(len(data_frame_var["obs"]), 2638) def test_filtered_data_frame(self): filter_ = { "filter": { "obs": { "annotation_value": [ {"name": "n_counts", "min": 3000}, ] } } } data_frame_obs = self.data.data_frame(filter_["filter"], "obs") self.assertEqual(len(data_frame_obs["var"]), 1838) self.assertEqual(len(data_frame_obs["obs"]), 497) self.assertIsInstance(data_frame_obs["obs"][0], (list, tuple)) self.assertEqual(type(data_frame_obs["var"][0]), int) data_frame_var = self.data.data_frame(filter_["filter"], "var") self.assertEqual(len(data_frame_var["var"]), 1838) self.assertEqual(len(data_frame_var["obs"]), 497) self.assertIsInstance(data_frame_var["var"][0], (list, tuple)) self.assertEqual(type(data_frame_var["obs"][0]), int) def test_data_single_gene(self): for axis in ["obs", "var"]: filter_ = { "filter": { "var": { "annotation_value": [ {"name": "name", "values": ["RER1"]}, ] } } } data_frame_var = self.data.data_frame(filter_["filter"], axis) if axis == "obs": self.assertEqual(type(data_frame_var["var"][0]), int) self.assertIsInstance(data_frame_var["obs"][0], (list, tuple)) elif axis == "var": self.assertEqual(type(data_frame_var["obs"][0]), int) self.assertIsInstance(data_frame_var["var"][0], (list, tuple)) if __name__ == '__main__': unittest.main()