Cross-correlation 相关

Cross-correlation

how to calculate the corss correlation between two variable using python

cov(X, Y) = (sum (x - mean(X)) * (y - mean(Y)) ) * 1/(n-1)

请看这个博客：

How to Calculate Correlation Between Variables in Python

 https://en.wikipedia.org/wiki/Cross-correlationj

计算两个变量的协方差矩阵时，可以直接调用numpy 的函数

covariance = cov(data1, data2)

构建demo data

# calculate the covariance between two variables
from numpy.random import randn
from numpy.random import seed
from numpy import cov
# seed random number generator
seed(1)
# prepare data
data1 = 20 * randn(1000) + 100
data2 = data1 + (10 * randn(1000) + 50)

# calculate covariance matrix   计算两个变量的协方差
covariance = cov(data1, data2)
print(covariance)

结果如下：

[[385.33297729 389.7545618 ]
 [389.7545618  500.38006058]]

对角线上的是变量data1和data2的方差（就是小学中学的方差）

非对角线的元素，刻画的是data1和data2的协方差，

也就是神经元和神经元之间的协方差，可以用来刻画相关性；

有正相关、负相关和不相关，三种状态；