code: def funcGauss1D(x, mu, sig):
      
      arrOut = np.exp(-np.power((x - mu)/sig, 2.)/2)
      # normalize
  #    arrOut = arrOut/(np.sqrt(2.*np.pi)*sig)
      # normalize (laternative)
      arrOut = arrOut/np.sum(arrOut)
      return arrOut
docs: Create 1D Gaussian. Source:
      http://mathworld.wolfram.com/GaussianFunction.html