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)))
