def process_raw_gyro_data(self, data):
""" Calculate 160 features
:param data:
:return:
"""
filt_gyro = util.butter_lowpass(data, 20, 50, 3)
j2 = np.insert(filt_gyro, filt_gyro.shape[0], np.zeros(3), 0)
j1 = np.insert(filt_gyro, 0, np.zeros(3), 0)
gyro_jerk = np.delete((j2 - j1) / self._dt, -1, axis=0)
gyro_mag = np.sqrt(np.sum(filt_gyro ** 2, axis=1))
gyro_jerk_mag = np.sqrt(np.sum(gyro_jerk ** 2, axis=1))
# 24 features x 2 = 48
features = self.process_3d_signal(filt_gyro)
features = np.vstack((features, self.process_3d_signal(gyro_jerk)))
# 8 features x 2 = 16
features = np.vstack((features, self.process_mag_signal(gyro_mag)))
features = np.vstack((features, self.process_mag_signal(gyro_jerk_mag)))
# FFT 71 + 12 + 12 = 96
features = np.vstack((features, self.process_fft_3D_signal(filt_gyro)))
features = np.vstack((features, self.process_fft_1d_signal(gyro_mag)))
features = np.vstack((features, self.process_fft_1d_signal(gyro_jerk_mag)))
# print("Gyro features extracted" + str(features.shape))
# np.savetxt("..\\Tmp\\features.txt", features.T)
return features, filt_gyro
def process_raw_acc_data(self, data):
""" Calculate 274 features
:param data: num.examples * nuum_col. Num_cal is 3 axes and optionally number of seconds
:return:
"""
# remove noise
body_acc = util.butter_lowpass(data, 20, 50, 3)
# split into gravity and body signal with lowpass filter
grav_acc = util.butter_lowpass(body_acc, 0.3, 50, 3)
body_acc = body_acc - grav_acc
# print(data.shape)
j1 = np.insert(body_acc, body_acc.shape[0], np.zeros(3), 0)
j2 = np.insert(body_acc, 0, np.zeros(3), 0)
body_acc_jerk = np.delete((j2 - j1) / self._dt, -1, axis=0)
body_acc_mag = np.sqrt(np.sum(body_acc**2, axis=1))
grav_acc_mag = np.sqrt(np.sum(grav_acc**2, axis=1))
body_acc_jerk_mag = np.sqrt(np.sum(body_acc_jerk**2, axis=1))
# should be 40 features each but is 40 * 3 = 120
features = self.process_3d_signal(body_acc)
features = np.vstack((features, self.process_3d_signal(grav_acc)))
features = np.vstack((features, self.process_3d_signal(body_acc_jerk)))
# should be 13 features but is 9 * 3 = 33
features = np.vstack((features, self.process_mag_signal(body_acc_mag)))
features = np.vstack((features, self.process_mag_signal(grav_acc_mag)))
features = np.vstack(
(features, self.process_mag_signal(body_acc_jerk_mag)))
# FFT 71 + 71 + 12 + 12 = 166
features = np.vstack((features, self.process_fft_3D_signal(body_acc)))
features = np.vstack(
(features, self.process_fft_3D_signal(body_acc_jerk)))
features = np.vstack(
(features, self.process_fft_1d_signal(body_acc_mag)))
features = np.vstack(
(features, self.process_fft_1d_signal(body_acc_jerk_mag)))
# print("Acc features extracted" + str(features.shape))
return features, body_acc, grav_acc
def process_raw_compas_data(self, data):
""" Calculate 160 features
:param data:
:return:
"""
filt_comp = util.butter_lowpass(data, 20, 50, 1)
# 8 features
features = self.process_mag_signal(filt_comp)
# FFT 12
features = np.vstack((features, self.process_fft_1d_signal(filt_comp)))
return features, filt_comp