mirror of
https://github.com/chanzuckerberg/cellxgene.git
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86 lines
3.6 KiB
Python
86 lines
3.6 KiB
Python
import json
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import pytest
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import unittest
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import warnings
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from server.app.scanpy_engine.scanpy_engine import ScanpyEngine
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from server.app.util.errors import JSONEncodingValueError
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class NaNTest(unittest.TestCase):
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def setUp(self):
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self.args = {
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"layout": "umap",
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"diffexp": "ttest",
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"max_category_items": 100,
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"obs_names": None,
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"var_names": None,
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"diffexp_lfc_cutoff": 0.01,
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"nan_to_num": False,
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}
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=UserWarning)
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self.data = ScanpyEngine("server/test/test_datasets/nan.h5ad", self.args)
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self.data._create_schema()
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self.args_nan = dict(self.args)
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self.args_nan["nan_to_num"] = True
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=UserWarning)
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self.data_nan = ScanpyEngine(
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"server/test/test_datasets/nan.h5ad", self.args_nan
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)
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self.data_nan._create_schema()
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def test_load(self):
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with self.assertWarns(UserWarning):
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ScanpyEngine("server/test/test_datasets/nan.h5ad", self.args_nan)
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def test_init(self):
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self.assertEqual(self.data.cell_count, 100)
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self.assertEqual(self.data.gene_count, 100)
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epsilon = 0.000_005
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self.assertTrue(self.data.data.X[0, 0] - -0.171_469_51 < epsilon)
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self.assertEqual(self.data_nan.cell_count, 100)
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self.assertEqual(self.data_nan.gene_count, 100)
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epsilon = 0.000_005
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self.assertTrue(self.data_nan.data.X[0, 0] - -0.171_469_51 < epsilon)
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def test_dataframe(self):
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data_frame_obs = json.loads(self.data_nan.data_frame(None, "obs"))
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self.assertEqual(len(data_frame_obs["var"]), 100)
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self.assertEqual(len(data_frame_obs["obs"]), 100)
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data_frame_var = json.loads(self.data_nan.data_frame(None, "var"))
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self.assertEqual(len(data_frame_var["var"]), 100)
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self.assertEqual(len(data_frame_var["obs"]), 100)
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with pytest.raises(JSONEncodingValueError):
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data_frame_obs = json.loads(self.data.data_frame(None, "obs"))
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with pytest.raises(JSONEncodingValueError):
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data_frame_var = json.loads(self.data.data_frame(None, "var"))
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def test_dataframe_nan_to_0(self):
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data_frame_obs = json.loads(self.data_nan.data_frame(None, "obs"))
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self.assertEqual(data_frame_obs["obs"][1][3], 0.0)
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data_frame_var = json.loads(self.data_nan.data_frame(None, "var"))
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self.assertEqual(data_frame_var["var"][1][5], 0.0)
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def test_annotation_nan_to_0(self):
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annotations_obs = json.loads(self.data_nan.annotation(None, "obs"))
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self.assertEqual(annotations_obs["data"][0][3], 0.0)
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annotations_var = json.loads(self.data_nan.annotation(None, "var"))
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self.assertEqual(annotations_var["data"][0][3], 0.0)
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def test_annotation(self):
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annotations = json.loads(self.data_nan.annotation(None, "obs"))
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self.assertEqual(
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annotations["names"],
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["name", "n_genes", "percent_mito", "n_counts", "louvain"],
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)
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annotations = json.loads(self.data_nan.annotation(None, "var"))
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self.assertEqual(annotations["names"], ["name", "n_cells", "var_with_nans"])
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self.assertEqual(len(annotations["data"]), 100)
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with pytest.raises(JSONEncodingValueError):
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annotations = json.loads(self.data.annotation(None, "obs"))
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with pytest.raises(JSONEncodingValueError):
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annotations = json.loads(self.data.annotation(None, "var"))
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