You can use numpy to compute the covariance of two list of numbers:
sage: x = [random() for _ in range(10)]
sage: y = [random() for _ in range(10)]
sage: import numpy as np
sage: np.cov(x,y)
array([[ 0.09306006, -0.04053014],
[-0.04053014, 0.10647864]])
The numpy array can be converted back into a SageMath matrix:
sage: matrix(_)
[ 0.09306006427535807 -0.04053014267978353]
[-0.04053014267978353 0.10647864456311205]
More usage examples can be found in the numpy doc.
Indeed, doing search_src('covariance') seems to confirm there is nothing in the sage library to do that. I think as SageMath users, it is not a bad thing that we learn how to use python libraries such as numpy, pandas, matplotlib, etc.
Asked: 2020-04-02 21:06:16 +0200
Seen: 693 times
Last updated: Apr 02 '20
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