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 process(self, element, *args, **kwargs):
user, mag_sum_accs = element
if user and mag_sum_accs:
ind, vals = zip(*mag_sum_accs)
ser1 = pd.Series([float(v) for v in vals],
index=[pd.Timestamp(i) for i in ind])
tp = pdkit.TremorProcessor()
yield user, tp.spkt_welch_density(ser1)[0][1]
else:
yield user, 0
def CalculatePandasAbsoluteEnergyMap(element):
user, mag_sum_accs = element
if user and mag_sum_accs:
ind, vals = zip(*mag_sum_accs)
ser1 = pd.Series([float(v) for v in vals],
index=[pd.Timestamp(i) for i in ind])
tp = pdkit.TremorProcessor()
return user, tp.abs_energy(ser1)
else:
return user, 0
def setUp(self):
self.tp = pdkit.TremorProcessor(lower_frequency=0.0,
upper_frequency=4.0)
self.filename_cloudupdrs = './tests/data/pronation_supination_left_hand.csv'
def setUp(self):
self.tp = pdkit.TremorProcessor()
self.filename_cloudupdrs = './tests/data/kinetic_tremor_left_hand.csv'
self.filename_mpower = './tests/data/mpower_tremor.json'