def __getitem__(self, idx):
batch_x = []
for i in range(self.context*2+1):
batch_x.append(np.zeros((self.batch_size, self.win_length, 1)))
batch_y = np.zeros((self.batch_size, self.win_length, 1))
x_w = self.x[idx].reshape(len(self.x[idx]))
y_w = self.y[idx].reshape(len(self.y[idx]))
x_w = slicing(x_w, self.win_length, self.hop_length, windowing = self.win_input)
x_w = np.pad(x_w, ((self.context, self.context),(0, 0)), 'constant', constant_values=(0))
a = []
for i in range(x_w.shape[0]):
a.append(x_w[i:i+self.context*2+1])
del a[-self.context*2:]
a = np.asarray(a)
y_w = slicing(y_w, self.win_length, self.hop_length, windowing = self.win_output)
for i in range(self.batch_size):
for j in range(self.context*2+1):
batch_x[j][i] = a[:,j,:][i].reshape(self.win_length,1)
batch_y[i] = y_w[i].reshape(self.win_length,1)
batch_x = np.swapaxes(np.asarray(batch_x), 0, 1)
return batch_x, batch_y
def __getitem__(self, idx):
batch_x = np.zeros((self.batch_size, self.in_length, 1))
batch_y = np.zeros((self.batch_size, self.out_length, 1))
x_w = self.x[idx].reshape(len(self.x[idx]))
y_w = self.y[idx].reshape(len(self.y[idx]))
x_w = slicing(x_w, self.in_length, self.hop_length, windowing=self.win)
y_w = slicing(y_w, self.in_length, self.hop_length, windowing=self.win)
for i in range(self.batch_size):
batch_x[i] = x_w[i].reshape(self.in_length, 1)
batch_y[i] = y_w[i].reshape(
self.in_length, 1)[self.trim:self.trim + self.out_length]
return batch_x, batch_y