def test_cloudupdrs_data(self): self.wrong_data = './tests/data/kinetic_tremor_wrong_format.csv' ts = pdkit.TremorTimeSeries().load(self.wrong_data, 'cloudupdrs') validator = CloudUPDRSDataFrameValidator() # print('---> ', validator.is_valid(self.tp.data_frame)) # print(self.tp.data_frame) self.assertEqual(False, validator.is_valid(ts))
def __get_tremor_measurements(self, data_frame, directory, files_list): """ Convenience method that gets the finger tapping measurements :param data_frame: the dataframe where the features will be added :type data_frame: pandas.DataFrame :param directory: the directory name that contains the files :type features: str :param files_list: the list of files :type files_list: str :return data_frame: the dataframe :rtype data_frame: pandas.DataFrame """ abr_measurement_type = 'T' tp = pdkit.TremorProcessor() for f in files_list: if f.startswith(abr_measurement_type): tts = pdkit.TremorTimeSeries().load( join(self.__build_folder_path(directory), f)) features = tp.extract_features( tts, self.__get_measurement_name(abr_measurement_type, f)) if features is not None: data_frame = self.__save_features_to_dataframe( features, data_frame, f) else: print('file error: ' + f) return data_frame
def test_tremor_freq_welch_cloudupdrs(self): ts = pdkit.TremorTimeSeries().load(self.filename_cloudupdrs, 'cloudupdrs') amplitude, frequency = self.tp.bradykinesia(ts, 'welch') self.assertEqual(float("{0:.5f}".format(frequency)), float("{0:.5f}".format(2.34375)))
def test_tremor_amplitude_welch_cloudupdrs(self): ts = pdkit.TremorTimeSeries().load(self.filename_cloudupdrs, 'cloudupdrs') amplitude, frequency = self.tp.bradykinesia(ts, 'welch') self.assertEqual(float("{0:.14f}".format(amplitude)), float("{0:.14f}".format(5.0055189177887085)))
def test_bradykinesia_amplitude_cloudupdrs(self): ts = pdkit.TremorTimeSeries().load(self.filename_cloudupdrs, 'cloudupdrs') amplitude, frequency = self.tp.bradykinesia(ts) self.assertEqual(float("{0:.14f}".format(amplitude)), float("{0:.14f}".format(1.525984985866312)))
def test_cloudupdrs_data(self): self.wrong_data = './tests/data/pronation_supination_wrong_format.csv' ts = pdkit.TremorTimeSeries().load(self.wrong_data, 'cloudupdrs') validator = CloudUPDRSDataFrameValidator() self.assertEqual(False, validator.is_valid(ts))
def test_tremor_freq_welch_mpower(self): ts = pdkit.TremorTimeSeries().load(self.filename_mpower, 'mpower') amplitude, frequency = self.tp.amplitude(ts, 'welch') self.assertEqual(float("{0:.5f}".format(frequency)), float("{0:.5f}".format(5.859375)))
def test_tremor_amplitude_welch_mpower(self): ts = pdkit.TremorTimeSeries().load(self.filename_mpower, 'mpower') amplitude, frequency = self.tp.amplitude(ts, 'welch') self.assertEqual(float("{0:.14f}".format(amplitude)), float("{0:.14f}".format(0.16300804916508932)))
def test_tremor_amplitude_welch_cloudupdrs(self): ts = pdkit.TremorTimeSeries().load(self.filename_cloudupdrs, 'cloudupdrs') amplitude, frequency = self.tp.amplitude(ts, 'welch') self.assertEqual(float("{0:.14f}".format(amplitude)), float("{0:.14f}".format(6.39553002855188)))
def test_tremor_amplitude_mpower(self): ts = pdkit.TremorTimeSeries().load(self.filename_mpower, 'mpower') amplitude, frequency = self.tp.amplitude(ts) self.assertEqual(float("{0:.14f}".format(amplitude)), float("{0:.14f}".format(0.4186992556201507)))
def test_tremor_amplitude_cloudupdrs(self): ts = pdkit.TremorTimeSeries().load(self.filename_cloudupdrs, 'cloudupdrs') amplitude, frequency = self.tp.amplitude(ts) self.assertEqual(float("{0:.14f}".format(amplitude)), float("{0:.14f}".format(2.390463750531757)))