#!/usr/bin/env python
# -*- coding: utf-8 -*-

from random import *    # cf. documentation cf http://docs.python.org/library/random.html 
import numpy as np
import matplotlib.pyplot as plt     # http://matplotlib.sourceforge.net/api/pyplot_api.html#module-matplotlib.pyplot
import matplotlib.mlab as mlab    # http://matplotlib.sourceforge.net/api/mlab_api.html#module-matplotlib.mlab

#seed('ma chaîne personnelle')  # reproducible initialization
seed()

rval = []
for j in range(100000):
    rval.append(randint(0,99))   # append to the list a random (integer) number between 0 and 99

# print rval  # uncomment just to see the list of random numbers

# analysis - histogram  -  see http://matplotlib.sourceforge.net/examples/api/histogram_demo.html
# http://fr.wikipedia.org/wiki/Histogramme
xh = np.array(rval)  # see http://www.scipy.org/Cookbook/BuildingArrays  transforme une liste en un tableau numérique de Numpy
# print(xh)

fig = plt.figure()
ax = fig.add_subplot(111)

n, bins, patches = ax.hist(xh, 50, facecolor='green', alpha=0.75)
print(n)  # les nombres d'occurences par classe
print(bins)  # les classes, de largeur identique

# modifier le nombre de nombres générés, les nombres de classes-bins, 

plt.show()