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remove --nan-to-num CLI parameter (#548)

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* remove --nan-to-num CLI parameter

* factor tests better

* lint - remove unused variables
This commit is contained in:
Bruce Martin
2019-01-10 15:03:03 -08:00
committed by GitHub
parent f876a0091a
commit 5d60505407
8 changed files with 34 additions and 183 deletions
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server/test/test_nan_scanpy_engine.py
+30 -43
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@@ -2,6 +2,9 @@ import json
import pytest
import unittest
import warnings
import math
import decode_fbs
from server.app.scanpy_engine.scanpy_engine import ScanpyEngine
from server.app.util.errors import JSONEncodingValueError
@@ -16,24 +19,15 @@ class NaNTest(unittest.TestCase):
"obs_names": None,
"var_names": None,
"diffexp_lfc_cutoff": 0.01,
"nan_to_num": False,
}
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
self.data = ScanpyEngine("server/test/test_datasets/nan.h5ad", self.args)
self.data._create_schema()
self.args_nan = dict(self.args)
self.args_nan["nan_to_num"] = True
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
self.data_nan = ScanpyEngine(
"server/test/test_datasets/nan.h5ad", self.args_nan
)
self.data_nan._create_schema()
def test_load(self):
with self.assertWarns(UserWarning):
ScanpyEngine("server/test/test_datasets/nan.h5ad", self.args_nan)
ScanpyEngine("server/test/test_datasets/nan.h5ad", self.args)
def test_init(self):
self.assertEqual(self.data.cell_count, 100)
@@ -41,45 +35,38 @@ class NaNTest(unittest.TestCase):
epsilon = 0.000_005
self.assertTrue(self.data.data.X[0, 0] - -0.171_469_51 < epsilon)
self.assertEqual(self.data_nan.cell_count, 100)
self.assertEqual(self.data_nan.gene_count, 100)
epsilon = 0.000_005
self.assertTrue(self.data_nan.data.X[0, 0] - -0.171_469_51 < epsilon)
def test_dataframe(self):
data_frame_obs = json.loads(self.data_nan.data_frame(None, "obs"))
self.assertEqual(len(data_frame_obs["var"]), 100)
self.assertEqual(len(data_frame_obs["obs"]), 100)
data_frame_var = json.loads(self.data_nan.data_frame(None, "var"))
self.assertEqual(len(data_frame_var["var"]), 100)
self.assertEqual(len(data_frame_var["obs"]), 100)
with pytest.raises(JSONEncodingValueError):
data_frame_obs = json.loads(self.data.data_frame(None, "obs"))
with pytest.raises(JSONEncodingValueError):
data_frame_var = json.loads(self.data.data_frame(None, "var"))
data_frame_var = decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "var"))
self.assertIsNotNone(data_frame_var)
self.assertEqual(data_frame_var["n_rows"], 100)
self.assertEqual(data_frame_var["n_cols"], 100)
self.assertTrue(math.isnan(data_frame_var["columns"][3][3]))
def test_dataframe_nan_to_0(self):
data_frame_obs = json.loads(self.data_nan.data_frame(None, "obs"))
self.assertEqual(data_frame_obs["obs"][1][3], 0.0)
data_frame_var = json.loads(self.data_nan.data_frame(None, "var"))
self.assertEqual(data_frame_var["var"][1][5], 0.0)
with pytest.raises(JSONEncodingValueError):
json.loads(self.data.data_frame(None, "obs"))
with pytest.raises(JSONEncodingValueError):
json.loads(self.data.data_frame(None, "var"))
def test_annotation_nan_to_0(self):
annotations_obs = json.loads(self.data_nan.annotation(None, "obs"))
self.assertEqual(annotations_obs["data"][0][3], 0.0)
annotations_var = json.loads(self.data_nan.annotation(None, "var"))
self.assertEqual(annotations_var["data"][0][3], 0.0)
def test_dataframe_obs_not_implemented(self):
with self.assertRaises(ValueError) as cm:
decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "obs"))
self.assertIsNotNone(cm.exception)
def test_annotation(self):
annotations = json.loads(self.data_nan.annotation(None, "obs"))
annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("obs"))
self.assertEqual(
annotations["names"],
["name", "n_genes", "percent_mito", "n_counts", "louvain"],
annotations["col_idx"],
["name", "n_genes", "percent_mito", "n_counts", "louvain"]
)
annotations = json.loads(self.data_nan.annotation(None, "var"))
self.assertEqual(annotations["names"], ["name", "n_cells", "var_with_nans"])
self.assertEqual(len(annotations["data"]), 100)
self.assertEqual(annotations["n_rows"], 100)
self.assertTrue(math.isnan(annotations["columns"][2][0]))
annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("var"))
self.assertEqual(annotations["col_idx"], ["name", "n_cells", "var_with_nans"])
self.assertEqual(annotations["n_rows"], 100)
self.assertTrue(math.isnan(annotations["columns"][2][0]))
with pytest.raises(JSONEncodingValueError):
annotations = json.loads(self.data.annotation(None, "obs"))
json.loads(self.data.annotation(None, "obs"))
with pytest.raises(JSONEncodingValueError):
annotations = json.loads(self.data.annotation(None, "var"))
json.loads(self.data.annotation(None, "var"))