Python isFall Examples

Example #1

File: test_time_series_extractor.py Project: KnollFrank/MLND-Capstone-Detecting-Falls-with-Wearable-Sensors

    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)

Example #2

File: test_fall_predicate.py Project: KnollFrank/MLND-Capstone-Detecting-Falls-with-Wearable-Sensors

 def test_is_fall1(self):
     fall = isFall(
         '../data/FallDataSet/209/Testler Export/916/Test_1/340535.txt')
     self.assertEquals(fall, True)

Example #3

File: feature_extractor_workflow.py Project: KnollFrank/MLND-Capstone-Detecting-Falls-with-Wearable-Sensors

 def sensorFile_and_fall_df(self, sensorFile):
     return pd.DataFrame(data={
         'sensorFile': [sensorFile],
         'fall': isFall(sensorFile)
     })

Example #4

File: test_fall_predicate.py Project: KnollFrank/MLND-Capstone-Detecting-Falls-with-Wearable-Sensors

 def test_is_fall2(self):
     fall = isFall(
         '../data/FallDataSet/209/Testler Export/813/Test_6/340535.txt')
     self.assertEquals(fall, False)

Example #5

File: time_series_extractor.py Project: KnollFrank/MLND-Capstone-Detecting-Falls-with-Wearable-Sensors

 def extract_time_series(self, sensorFile):
     X = extract_time_series(self.sensor_file_2_df(sensorFile),
                             self.columns)
     y = isFall(sensorFile)
     return X, y