def test_exception_in_window_generation(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0], ff[1], ['target1'], 10, 1,
'faulty_loc')
self.assertIsNone(g)
def test_get_win_no_sensors(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[2]
g = data_generator.get_win(ff[0], ff[1], ['missing'], 10, 1,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(61, len(df.loc[0].tolist()))
def test_get_win_binary_mock_other_strides(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0], ff[1], ['target1'], 3, 2,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(49, df.shape[0])
self.assertCountEqual([0] * 4, df['label'].values.tolist()[:4])
def test_get_win_binary_mock_stride_one(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0], ff[1], ['target1'], 10, 1,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(91, df.shape[0])
self.assertCountEqual([0] * 11, df['label'].values.tolist()[:11])
self.assertCountEqual([1] * 29, df['label'].values.tolist()[11:40])
self.assertCountEqual([0] * 11, df['label'].values.tolist()[40:51])
self.assertCountEqual([1] * 29, df['label'].values.tolist()[51:80])
self.assertCountEqual([0] * 11, df['label'].values.tolist()[80:91])
def test_get_files_with_exercise(self):
f1 = os.path.join(self.base, 'data/ex1/ex1.0.real.0.csv')
f2 = os.path.join(self.base, 'data/ex1/ex1.0.mock.0.csv')
ll = data_generator.get_files(self.test_dataset,
self.test_coordinate_file, ['ex1'])
self.assertEqual(3, len(ll))
self.assertEqual(2, len(ll[1][1]))
self.assertEqual(f1, ll[0][0])
self.assertEqual(f2, ll[1][0])
self.assertCountEqual([(319, 644), (788, 1125), (1287, 1598),
(1745, 2086), (2245, 2554), (2690, 3009),
(3121, 3430), (3565, 3852), (3961, 4257),
(4343, 4684)], ll[0][1])
self.assertCountEqual([(20, 40), (60, 80)], ll[1][1])
def test_get_win_mock(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0], ff[1], ['target1'], 10, 1,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(10 * 6 + 1, df.shape[1])
synth = df.values.tolist()
tg = []
for x in range(1, 7):
tg += [x, x + 1] + [x] * 8
tg.append(0)
self.assertCountEqual(tg, synth[0])
def test_get_win_normalize_zscore(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0],
ff[1], ['target1'],
10,
1,
self.gen_path,
normalize='zscore')
df = pd.read_csv(g)
first_win = df.loc[0].tolist()
tg = []
for x in range(1, 7):
tg += [-0.100503781525, 9.949874371] + [-0.100503781525] * 8
tg.append(0.0)
self.assertEqual(61, len(first_win))
self.assertTrue(np.allclose(tg, first_win, rtol=1e-04, atol=1e-08))
def test_get_win_normalize_minmax(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0],
ff[1], ['target1'],
10,
1,
self.gen_path,
normalize='minmax')
df = pd.read_csv(g)
first_win = df.loc[0].tolist()
tg = []
for x in range(1, 7):
tg += [0.0, 1.0] + [0.0] * 8
tg.append(0)
self.assertEqual(61, len(first_win))
self.assertCountEqual(tg, first_win)
self.assertEqual(0.0, first_win[0])
self.assertEqual(1.0, first_win[1])
def test_get_win_count(self):
ff = data_generator.get_files(self.test_dataset,
self.test_coordinate_file)[1]
g = data_generator.get_win(ff[0], ff[1], ['target1'], 10, 1,
self.gen_path)
self.assertEqual(g, os.path.join(self.gen_path, 'ex1.0.mock.0.csv'))
df = pd.read_csv(g)
self.assertEqual(int(((100 - 10) / 1) + 1), df.shape[0])
g = data_generator.get_win(ff[0], ff[1], ['target1'], 20, 1,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(int(((100 - 20) / 1) + 1), df.shape[0])
g = data_generator.get_win(ff[0], ff[1], ['target1'], 20, 5,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(int(((100 - 20) / 5) + 1), df.shape[0])
g = data_generator.get_win(ff[0], ff[1], ['target1'], 18, 7,
self.gen_path)
df = pd.read_csv(g)
self.assertEqual(int(((100 - 18) / 7) + 1), df.shape[0])