docs: def runningstd(t, data, width):
      """Compute the running standard deviation of a time series.
  
      Returns `t_new`, `std_r`.
      """
      ne = len(t) - width
      t_new = np.zeros(ne)
      std_r = np.zeros(ne)
      for i in range(ne):
          t_new[i] = np.mean(t[i:i+width+1])
          std_r[i] = scipy.stats.nanstd(data[i:i+width+1])
      return t_new, std_r