code: def Gaussian_filter(x, sigma, norm=True):
      r
  
      x = check_float(x)
      sigma = check_float(sigma)
  
      val = np.exp(-0.5 * (x / sigma) ** 2)
  
      if norm:
          return val / (np.sqrt(2 * np.pi) * sigma)
  
      else:
          return val
docs: r"""Gaussian filter
  
      This method implements a Gaussian filter.
  
      Parameters
      ----------
      x : float
          Input data point
      sigma : float
          Standard deviation (filter scale)
      norm : bool
          Option to return normalised data. Default (norm=True)
  
      Returns
      -------
      float Gaussian filtered data point
  
      Examples
      --------
      >>> from modopt.signal.filter import Gaussian_filter
      >>> Gaussian_filter(1, 1)
      0.24197072451914337
  
      >>> Gaussian_filter(1, 1, False)
      0.60653065971263342