def __augment(self):
'''Applies augmentation incrementally'''
self.X_aug, self.y_aug, self.r_aug = [], [], []
for i in range(len(self.X)):
for _ in range(self.size_factor):
x = np.copy(self.X[i])
if self.permutation != 0:
x = da.permute(x, nPerm=self.permutation)
if self.rotation != 0:
x = da.rotate(x,
rotation=self.rotation,
mask=self.rotation_mask)
if self.time_warping != 0:
x = da.time_warp(x, sigma=self.time_warping)
if self.scale_sigma != 0:
x = da.scale(x, sigma=self.scale_sigma)
if self.mag_warping != 0:
x = da.mag_warp(x, sigma=self.mag_warping)
if self.noise_snr_db != 0:
x = da.jitter(x, snr_db=self.noise_snr_db)
if self.permutation or self.rotation or self.time_warping or self.scale_sigma or self.mag_warping or self.noise_snr_db:
self.X_aug.append(x)
self.y_aug.append(self.y[i])
self.r_aug.append(self.r[i])
self.X_aug.append(self.X[i])
self.y_aug.append(self.y[i])
self.r_aug.append(self.r[i])
def __augment(self):
'''Applies augmentation incrementally'''
self.X_aug, self.y_aug, self.r_aug = [], [], []
for i in range(len(self.X)):
for _ in range(self.size_factor):
x = np.copy(self.X[i])
if self.noise_snr_db != 0:
x = da.jitter(x, snr_db=self.noise_snr_db)
self.X_aug.append(x)
self.y_aug.append(self.y[i])
self.r_aug.append(self.r[i])
self.X_aug.append(self.X[i])
self.y_aug.append(self.y[i])
self.r_aug.append(self.r[i])
def __augment(self):
'''Data augmentation application'''
self.X_aug, self.y_aug, self.r_aug = [], [], []
for i in range(len(self.X)):
for _ in range(self.size_factor):
x = np.copy(self.X[i])
if self.snr_db != 0:
x = da.jitter(x, snr_db=self.snr_db)
if self.time_warping != 0:
x = da.time_warp(x, sigma=self.time_warping)
if self.permutation or self.rotation or self.time_warping or self.scale_sigma or self.mag_warping or self.noise_snr_db:
self.X_aug.append(x)
self.y_aug.append(self.y[i])
self.r_aug.append(self.r[i])
self.X_aug.append(self.X[i])
self.y_aug.append(self.y[i])
self.r_aug.append(self.r[i])