如何在python中获得两个向量的相关性
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How to get correlation of two vectors in python
提问by Luke Makk
In matlab I use
在matlab中我使用
a=[1,4,6]
b=[1,2,3]
corr(a,b)
which returns .9934. I've tried numpy.correlatebut it returns something completely different. What is the simplest way to get the correlation of two vectors?
返回 0.9934。我试过了，numpy.correlate但它返回了完全不同的东西。获得两个向量的相关性的最简单方法是什么？
回答by Hooked
The docs indicate that numpy.correlateis not what you are looking for:
文档表明这numpy.correlate不是您要查找的内容：
numpy.correlate(a, v, mode='valid', old_behavior=False)[source]
Cross-correlation of two 1-dimensional sequences.
This function computes the correlation as generally defined in signal processing texts:
z[k] = sum_n a[n] * conj(v[n+k])
with a and v sequences being zero-padded where necessary and conj being the conjugate.
Instead, as the other comments suggested, you are looking for a Pearson correlation coefficient. To do this with scipy try:
相反，正如其他评论所建议的那样，您正在寻找Pearson 相关系数。要做到这一点 scipy 尝试：
from scipy.stats.stats import pearsonr
a = [1,4,6]
b = [1,2,3]
print pearsonr(a,b)
This gives
这给
(0.99339926779878274, 0.073186395040328034)
You can also use numpy.corrcoef:
您还可以使用numpy.corrcoef：
import numpy
print numpy.corrcoef(a,b)
This gives:
这给出：
[[ 1. 0.99339927]
[ 0.99339927 1. ]]
