4573166454

Build Type

push

travis-pro

Committed by LSC2204

Commit Message

fix unit tests

Run Details

6 of 6 new or added lines in 1 file covered. (100.0%)

13515 of 14488 relevant lines covered (93.28%)

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97.44

/tods/tests/sk_interface/detection_algorithm/test_ski_PCAODetector.py

import numpy as np
import pandas as pd
import os
from tods.sk_interface.detection_algorithm.PCAODetector_skinterface import PCAODetectorSKI

from pyod.utils.data import generate_data
import unittest
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from unittest import TestCase
from sklearn.metrics import roc_auc_score

class PCAODetectorSKI_TestCase(unittest.TestCase):
    def setUp(self):

        _dummy = TestCase('__init__')
        self.assert_greater_equal = _dummy.assertGreaterEqual
        self.assert_greater = _dummy.assertGreater
        self.assert_less_equal = _dummy.assertLessEqual
        self.assert_less = _dummy.assertLess
        self.assert_equal = _dummy.assertEqual

        self.maxDiff = None
        self.n_train = 200
        self.n_test = 100
        self.contamination = 0.1
        self.roc_floor = 0.0
        self.window_size = 5
        self.l_s = 5
        self.n_predictions = 1
        self.X_train, self.X_test,self.y_train,  self.y_test = generate_data(
            n_train=self.n_train, n_test=self.n_test, n_features=3,
            contamination=self.contamination, random_state=42)

        self.transformer = PCAODetectorSKI(contamination=self.contamination, window_size=self.window_size)
        
        self.y_test = self.y_test[self.window_size-1:]
        self.transformer.fit(self.X_train)

    def test_prediction_labels(self):
        pred_labels = self.transformer.predict(self.X_test)
        self.assert_equal(pred_labels.shape[0], self.y_test.shape[0])

    def test_prediction_score(self):
        pred_scores = self.transformer.predict_score(self.X_test)
        self.assert_equal(pred_scores.shape[0], self.y_test.shape[0])
        self.assert_greater_equal(roc_auc_score(self.y_test, pred_scores), self.roc_floor)


    if __name__ == '__main__':
        unittest.main()
    

1	import numpy as np	2✔
2	import pandas as pd	2✔
3	import os	2✔
4	from tods.sk_interface.detection_algorithm.PCAODetector_skinterface import PCAODetectorSKI	2✔
5
6	from pyod.utils.data import generate_data	2✔
7	import unittest	2✔
8	from numpy.testing import assert_allclose	2✔
9	from numpy.testing import assert_array_less	2✔
10	from unittest import TestCase	2✔
11	from sklearn.metrics import roc_auc_score	2✔
12
13	class PCAODetectorSKI_TestCase(unittest.TestCase):	2✔
14	def setUp(self):	2✔
15
16	_dummy = TestCase('__init__')	2✔
17	self.assert_greater_equal = _dummy.assertGreaterEqual	2✔
18	self.assert_greater = _dummy.assertGreater	2✔
19	self.assert_less_equal = _dummy.assertLessEqual	2✔
20	self.assert_less = _dummy.assertLess	2✔
21	self.assert_equal = _dummy.assertEqual	2✔
22
23	self.maxDiff = None	2✔
24	self.n_train = 200	2✔
25	self.n_test = 100	2✔
26	self.contamination = 0.1	2✔
27	self.roc_floor = 0.0	2✔
28	self.window_size = 5	2✔
29	self.l_s = 5	2✔
30	self.n_predictions = 1	2✔
31	self.X_train, self.X_test,self.y_train, self.y_test = generate_data(	2✔
32	n_train=self.n_train, n_test=self.n_test, n_features=3,
33	contamination=self.contamination, random_state=42)
34
35	self.transformer = PCAODetectorSKI(contamination=self.contamination, window_size=self.window_size)	2✔
36
37	self.y_test = self.y_test[self.window_size-1:]	2✔
38	self.transformer.fit(self.X_train)	2✔
39
40	def test_prediction_labels(self):	2✔
41	pred_labels = self.transformer.predict(self.X_test)	2✔
42	self.assert_equal(pred_labels.shape[0], self.y_test.shape[0])	2✔
43
44	def test_prediction_score(self):	2✔
45	pred_scores = self.transformer.predict_score(self.X_test)	2✔
46	self.assert_equal(pred_scores.shape[0], self.y_test.shape[0])	2✔
47	self.assert_greater_equal(roc_auc_score(self.y_test, pred_scores), self.roc_floor)	2✔
48
49
50	if __name__ == '__main__':	2✔
51	unittest.main()	×
52

datamllab / tods / 4573166454

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