td_data_prep.py

def data_transform(data, timesteps, var='x'):
  m = []
  s = data.to_numpy()
  for i in range(s.shape[0]-timesteps):
      m.append(s[i:i+timesteps].tolist())

  if var == 'x':
      t = np.zeros((len(m), len(m[0]), len(m[0][0])))
      for i, x in enumerate(m):
          for j, y in enumerate(x):
              for k, z in enumerate(y):
                  t[i, j, k] = z
  else:
      t = np.zeros((len(m), len(m[0])))
      for i, x in enumerate(m):
          for j, y in enumerate(x):
              t[i, j] = y

  return t

all_y_rnn = data_transform(all_y, HOURS_AHEAD, var='y')
all_X_rnn = data_transform(all_X, HOURS_AHEAD, var='x')