def get_emg_data_object(self,n_gestures=6):
emg_data = symbionic.EmgData()
for g in range(1,n_gestures+1):
emg_values = self.get_chained_device_data_for_prediction(g)
if emg_values is not None and len(emg_values) > 0:
emg_data.store_emg_values_in_gesture(emg_values,f'g{g}')
return emg_data
def test_list_to_dataframe():
emg_data = symbionic.EmgData()
emg_data.demean_data = False
df = emg_data.convert_emg_values_to_dataframe(raw_emg_data_sample())
assert df.shape == (2,
emg_data.channels + 1), 'Output shape does not match'
assert df[emg_data.channel_names[0]].tolist() == [1.1] * 2
def __init__(self):
emg_data = symbionic.EmgData()
emg_data.load(symbionic.example_data_directory() + "raw3.bin")
emg_array = emg_data.data['g1'].drop('time', axis=1).values
emg_iterator = DataIterator(emg_array)
emg_iterator.step = 80
emg_iterator.size = 500
self.emg_iterator = emg_iterator
''' currently just a script @author: Matthijs Cox ''' import symbionic import numpy as np import matplotlib.pyplot as plt folder = symbionic.example_data_directory() emg_data = symbionic.EmgData() emg_data.load(folder + 'raw1.bin', gesture='g1') emg_data.load(folder + 'raw2.bin', gesture='g2') emg_data.load(folder + 'raw3.bin', gesture='g3') emg_data.load(folder + 'raw4.bin', gesture='g4') emg_data.load(folder + 'raw5.bin', gesture='g5') emg_data.load(folder + 'raw6.bin', gesture='g6') emg_data.label_patterns() emg_data.plot(ylim=(-100, 100)) # get windowed training samples # samples = emg_data.get_training_samples()
def test_data_retrieval():
emg_data = symbionic.EmgData()
emg_data.store_emg_values_in_gesture([1.1] * emg_data.channels * 2, 'g1')
data = emg_data.get_data_from_gesture('g1')
assert isinstance(data, pd.DataFrame)
assert emg_data.get_data_from_gesture('g2') is None
def test_data_retrieval():
emg_data = symbionic.EmgData()
emg_data.store_emg_values_in_gesture(raw_emg_data_sample(), 'g1')
data = emg_data.get_data_from_gesture('g1')
assert isinstance(data, pd.DataFrame)
assert emg_data.get_data_from_gesture('g2') is None
def load_emg_data_single_gesture():
emg_data = symbionic.EmgData()
emg_data.load(data_directory() + 'raw2.bin', gesture='g2')
emg_data.label_patterns()
return emg_data