def test_extract_time_series(self):
# GIVEN
sensorFile = '../data/FallDataSet/209/Testler Export/916/Test_1/340535.txt'
df = pd.DataFrame({'Acc_X': [1.0, 2.0, 3.0], 'Acc_Y': [4.0, 5.0, 6.0]})
time_series_extractor = TimeSeriesExtractor(
sensor_file_2_df=lambda sensor_file: {sensorFile: df}[sensor_file],
columns=['Acc_X', 'Acc_Y'])
# WHEN
X_actual, y_actual = time_series_extractor.extract_time_series(
sensorFile)
# THEN
X_expected = np.array([[1.0, 4.0], [2.0, 5.0], [3.0, 6.0]])
y_expected = isFall(sensorFile)
self.assertEquals(X_expected.tolist(), X_actual.tolist())
self.assertEquals(y_expected, y_actual)
def test_is_fall1(self):
fall = isFall(
'../data/FallDataSet/209/Testler Export/916/Test_1/340535.txt')
self.assertEquals(fall, True)
def sensorFile_and_fall_df(self, sensorFile):
return pd.DataFrame(data={
'sensorFile': [sensorFile],
'fall': isFall(sensorFile)
})
def test_is_fall2(self):
fall = isFall(
'../data/FallDataSet/209/Testler Export/813/Test_6/340535.txt')
self.assertEquals(fall, False)
def extract_time_series(self, sensorFile):
X = extract_time_series(self.sensor_file_2_df(sensorFile),
self.columns)
y = isFall(sensorFile)
return X, y