Python基于matplotlib绘制栈式直方图的方法

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#http://www.jb51.net/article/100363.htm
# numpy array intorduction
#http://matplotlib.org/examples/statistics/histogram_demo_multihist.html
importnumpy as np
importpylab as P
importmatplotlib
d1=np.array([18.46,19.15,18.13,18.30,18.07,18.24,18.26,
     17.14,18.44,18.06,17.44,16.57,16.34,17.21])
d1=d1//1+(d1-d1//1)/0.6
d2=np.array([19.33,19.06,18.10,17.55,19.55,19.13,18.54,
     18.30,18.36,19.59,20.01,19.17,19.30,18.54,18.35,20.04])
d2=d2//1+(d2-d2//1)/0.6
d3=np.array([20.52,20.41,19.20,19.04,19.09,19.01,17.49,19.18,20.01,20.11])
d3=d3//1+(d3-d3//1)/0.6
d4=np.array([22.02,21.03,21.06,20.46,19.46,20.15,19.49,19.43,
       19.51,19.39,19.33,19.18,19.13,19.22,18.46,19.07,
       18.57,18.45,19.17,18.41,18.30])
d4=d4//1+(d4-d4//1)/0.6
x=([d1,d2,d3,d4])
P.figure()
#normed is False is good
n, bins, patches=P.hist(x,12, [16.5,22.5],normed=0, histtype='barstacked',
              color=['blue','green','red','yellow'],
             label=['   ','   ','   ','   '])
printtype(x)
P.legend()#legend should be signed after set down the information
P.show()