code: def gaussian(x, y, xsigma, ysigma):
      
      if xsigma==0.0 or ysigma==0.0:
          return x*0.0
  
      with float_error_ignore():
          x_w = np.divide(x,xsigma)
          y_h = np.divide(y,ysigma)
          return np.exp(-0.5*x_w*x_w + -0.5*y_h*y_h)
docs: Two-dimensional oriented Gaussian pattern (i.e., 2D version of a
      bell curve, like a normal distribution but not necessarily summing
      to 1.0).