numpy协方差矩阵numpy.cov [英] Numpy Covariance Matrix numpy.cov

问题描述

我正在使用numpy并想计算ndarray的协方差矩阵.我正在尝试使用numpy.cov()，但没有得到正确的结果.下面有更多详细信息.

I am using numpy and want to compute the covariance matrix for an ndarray. I am trying to use numpy.cov() but am not getting the correct results. More details below.

我的ndarray是768x8，其中8是我的数据集中的数字特征.

My ndarray is 768x8 for where 8 is the numbers features in my data set.

当我使用MATLAB计算协方差矩阵时，得到的是8x8(这是我所需要的)，但是当我使用np.cov()时，得到的是768x768，这是不正确的.我尝试将rowvar参数更改为true，这是行不通的.

When I use MATLAB to compute the covariance matrix, I get a 8x8 (which is what I require), but when I use np.cov(), I get a 768x768 which is incorrect. I tried changing the rowvar argument to true and this does not work.

对numpy.cov()的正确调用是什么?换句话说，我该如何使用numpy从MATLAB中重现cov()结果.

What would be the correct call to numpy.cov()? In other words, how would I reproduce the cov() results from MATLAB using numpy.

推荐答案

令人惊讶的是，文档可能会告诉您.您应该传递rowvar=False来指示列代表变量.

Amazingly, the documentation might tell you. You should pass rowvar=False to indicate that columns represent variables.

>>> data.shape
(768, 8)
>>> numpy.cov(data, rowvar=False).shape
(8, 8)

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