numpy covariance matrix

covariance, numpy, python

Solution

You have two vectors, not 25. The computer I'm on doesn't have python so I can't test this, but try:

z = zip(x,y)
np.cov(z)

Of course.... really what you want is probably more like:

n=100 # number of points in each vector
num_vects=25
vals=[]
for _ in range(num_vects):
    vals.append(np.random.normal(size=n))
np.cov(vals)

This takes the covariance (I think/hope) of `num_vects` 1x`n` vectors

Problem

Suppose I have two vectors of length 25, and I want to compute their covariance matrix. I try doing this with numpy.cov, but always end up with a 2x2 matrix. ``` >>> import numpy as np >>> x=np.random.normal(size=25) >>> y=np.random.normal(size=25) >>> np.cov(x,y) array([[ 0.77568388, 0.15568432], [ 0.15568432, 0.73839014]]) ``` Using the rowvar flag doesn't help either - I get exactly the same result. ``` >>> np.cov(x,y,rowvar=0) array([[ 0.77568388, 0.15568432], [ 0.15568432, 0.73839014]]) ``` How can I get the 25x25 covariance matrix?

Original source