如何使numpy数组列的总和为1 [英] How to make numpy array column sum up to 1

问题描述

我正在构建用于实现PageRank算法的转换矩阵.我该如何使用numpy来确保这些列加起来.

I am working on building a transition matrix for implementing the PageRank algorithm. How could I use numpy to make sure that the columns add up to one.

例如:

1 1 1   
1 1 1  
1 1 1

应标准化为

.33 .33 .33  
.33 .33 .33  
.33 .33 .33

推荐答案

按列总和来划分各列的元素-

Divide the elements of each column by their column-summations -

a/a.sum(axis=0,keepdims=1) # or simply : a/a.sum(0)

为使行总和统一，请更改轴输入-

For making the row-summations unity, change the axis input -

a/a.sum(axis=1,keepdims=1)

样品运行-

In [78]: a = np.random.rand(4,5)

In [79]: a
Out[79]: 
array([[ 0.37,  0.74,  0.36,  0.41,  0.44],
       [ 0.51,  0.86,  0.91,  0.03,  0.76],
       [ 0.56,  0.46,  0.01,  0.86,  0.38],
       [ 0.72,  0.66,  0.56,  0.84,  0.69]])

In [80]: b = a/a.sum(axis=0,keepdims=1)

In [81]: b.sum(0) # Verify
Out[81]: array([ 1.,  1.,  1.,  1.,  1.])

要确保它也适用于Python 2.x的int数组，请使用from __future__ import division或使用

To make sure it works on int arrays as well for Python 2.x, use from __future__ import division or use np.true_divide.

对于添加到0

For columns adding upto 0

对于加到0的列，假设我们可以保留它们原样，我们可以将总和设置为1，而不用像这样除以0-

For columns that add upto 0, assuming that we are okay with keeping them as they are, we can set the summations to 1, rather than divide by 0, like so -

sums = a.sum(axis=0,keepdims=1); 
sums[sums==0] = 1
out = a/sums

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