mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-21 00:18:11 +08:00
Bruce MartinandColin Megill
e2a12ba9bb
* warning on maxCount for diffexp * cleanup logging * clarification * make the limits configurable * make diff exp limit work * danger! * remove debugging code * fix merge with master * fix unit tests Co-authored-by: Colin Megill <colinmegill@gmail.com>
81 lines
3.4 KiB
Python
81 lines
3.4 KiB
Python
import pytest
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import unittest
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import warnings
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import math
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import server.test.decode_fbs as decode_fbs
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from server.data_anndata.anndata_adaptor import AnndataAdaptor
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from server.common.errors import FilterError
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from server.common.data_locator import DataLocator
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from server.common.app_config import AppConfig
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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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"embeddings__names": ["umap"],
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"presentation__max_categories": 100,
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"single_dataset__obs_names": None,
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"single_dataset__var_names": None,
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"diffexp__lfc_cutoff": 0.01,
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"limits__diffexp_cellcount_max": None,
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"limits__column_request_max": None,
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}
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config = AppConfig()
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config.update(**self.args)
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locator = DataLocator("test/test_datasets/nan.h5ad")
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config.update(single_dataset__datapath=locator.path)
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config.complete_config()
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=UserWarning)
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self.data = AnndataAdaptor(locator, config)
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self.data._create_schema()
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def test_load(self):
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with self.assertWarns(UserWarning):
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config = AppConfig()
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config.update(**self.args)
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locator = DataLocator("test/test_datasets/nan.h5ad")
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config.update(single_dataset__datapath=locator.path)
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config.complete_config()
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self.data = AnndataAdaptor(locator, config)
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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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def test_dataframe(self):
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data_frame_var = decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "var"))
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self.assertIsNotNone(data_frame_var)
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self.assertEqual(data_frame_var["n_rows"], 100)
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self.assertEqual(data_frame_var["n_cols"], 100)
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self.assertTrue(math.isnan(data_frame_var["columns"][3][3]))
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with pytest.raises(FilterError):
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self.data.data_frame_to_fbs_matrix("an erroneous filter", "var")
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with pytest.raises(FilterError):
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filter_ = {"filter": {"obs": {"index": [1, 99, [200, 300]]}}}
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self.data.data_frame_to_fbs_matrix(filter_["filter"], "var")
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def test_dataframe_obs_not_implemented(self):
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with self.assertRaises(ValueError) as cm:
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decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "obs"))
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self.assertIsNotNone(cm.exception)
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def test_annotation(self):
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annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("obs"))
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obs_index_col_name = self.data.schema["annotations"]["obs"]["index"]
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self.assertEqual(annotations["col_idx"], [obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain"])
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self.assertEqual(annotations["n_rows"], 100)
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self.assertTrue(math.isnan(annotations["columns"][2][0]))
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annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("var"))
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var_index_col_name = self.data.schema["annotations"]["var"]["index"]
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self.assertEqual(annotations["col_idx"], [var_index_col_name, "n_cells", "var_with_nans"])
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self.assertEqual(annotations["n_rows"], 100)
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self.assertTrue(math.isnan(annotations["columns"][2][0]))
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