text: import scipy.stats
  import numpy
  import pylab
  import scipy.stats, scipy
  import matplotlib.pyplot as plt
  import math
  
  
  class NormalProb(object):
      
      def __init__(self):
          pass
      
      def model(self,position, width, height, dx):
          return  height * math.sqrt(2*math.pi) * width * scipy.stats.norm.pdf(dx, position, width)
      
      def test1(self):
          x = numpy.linspace(0, 1, 400)
          position = 0.5
          height = 1.0
          width = 0.1
          dx = numpy.linspace(0, 1, 400)
          gauss = self.model(position, width, height,dx)
          plt.plot(x,gauss, '+', color='red')
          plt.show()
      
      def test2(self):
          pass
          b1 = scipy.stats.norm(10, 9)
          b2 = scipy.stats.norm(25, 49)
          m = scipy.stats.norm(17.5, 25)
          print ("b1.15", b1.pdf(15))
          print ("b2.15", b2.pdf(15))
          print ("m.15", m.pdf(15))
  
      def start(self):
          self.test1()
  
  npb = NormalProb()
  npb.start()
  