code: def gaussian_distribution(mean, stdev, num_pts=50):
      
      xstart = mean - (4.0 * stdev)
      xend = mean + (4.0 * stdev)
      x = np.linspace(xstart,xend,num_pts)
      y = (1.0/np.sqrt(2.0*np.pi*stdev*stdev)) * np.exp(-1.0 * ((x - mean)**2)/(2.0*stdev*stdev))
      return x,y
docs: get an x and y numpy.ndarray that spans the +/- 4
      standard deviation range of a gaussian distribution with
      a given mean and standard deviation. useful for plotting
  
      Parameters
      ----------
      mean : float
          the mean of the distribution
      stdev : float
          the standard deviation of the distribution
      num_pts : int
          the number of points in the returned ndarrays.
          Default is 50
  
      Returns
      -------
      x : numpy.ndarray
          the x-values of the distribution
      y : numpy.ndarray
          the y-values of the distribution