第一次用python：计算概率矩阵

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于 2013-01-07 16:39:44 发布 · 3.3k 阅读

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CC 4.0 BY-SA版权

这篇博客介绍了作者初次使用Python进行概率矩阵的计算，展示了计算得到的概率矩阵及其特征，并给出了相关的重要概率和一些关键数值。通过矩阵运算，作者得出了一些关键的序列和总概率，展示了Python在数据分析领域的应用。

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# -*- coding: utf-8 -*-
"""
Spyder Editor

This temporary script file is located here:
C:\Documents and Settings\chen\.spyder2\.temp.py
"""
from numpy import *
from scipy import *
from itertools import *
a=array([[0, 0.0433, 0.1740, 0.0136, 0.0095, 0.0049 , 0.0377],
         [ 0.0433 , 0 , 0.0407,  0.0033,  0.0027,  0.0012 ,0.0316],
         [0.2179, 0.0394 ,  0,  0.2654,    0.0629,    0.0075,    0.0332],
         [0.0197 , 0.0045 ,0.1506 ,  0, 0.2505, 0.0036,  0.0026],
         [0.0155 , 0.0040 , 0.0790,  0.2699 ,   0  ,0.0602,  0.0026],
         [0.0134 , 0.0035, 0.0140 , 0.0169 ,   0.0337 ,   0  , 0.0023],
         [0.2893 , 0.3503,  0.3052 ,  0.0292 ,   0.0184 ,   0.0063 ,  0]])  
    
print 'matrix: '
print a
v=[0 for x in range(35)]
gg = combinations(range(0,7),3)
gs=set(range(0,7))
i=0;
gaa=zeros((35,3))
for g_a in gg:
    gaa[i,:]=g_a
    g_as=set(g_a)
    g_bs=gs-g_as
    g_b=tuple(g_bs)
    s1=0
    s2=0
    f