Numpy and Scipy matrix inversion functions differences

Question

My question is rather simple : What is the difference between the numpy.linalg.inv and the scipy.linalg.inv functions for matrices inversion

Is the Scipy function just a wrapper of the Numpy one ? Efficiency, numerical stability, speed ... which one should I prefer ?

Thanks !

tmdavison · Accepted Answer · 2015-08-25 13:03:09Z

9

From the SciPy Documentation you get the following information:

scipy.linalg vs numpy.linalg
scipy.linalg contains all the functions in numpy.linalg. plus some other more advanced ones not contained in numpy.linalg Another advantage of using scipy.linalg over numpy.linalg is that it is always compiled with BLAS/LAPACK support, while for numpy this is optional. Therefore, the scipy version might be faster depending on how numpy was installed.

Therefore, unless you don’t want to add scipy as a dependency to your numpy program, use scipy.linalg instead of numpy.linalg

I hope this helps!

edited Aug 25, 2015 at 13:03

tmdavison

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answered Aug 25, 2015 at 12:57

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