8000 Singular matrix inverse does't throw an error · Issue #6178 · numpy/numpy · GitHub
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rasoolfa opened this issue Aug 7, 2015 · 1 comment
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Singular matrix inverse does't throw an error #6178

rasoolfa opened this issue Aug 7, 2015 · 1 comment

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@rasoolfa
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rasoolfa commented Aug 7, 2015

Hi,
Here is an example of inv that doesn't throw an error when dealing with singular matrix and return wrong results.

import numpy as np
import scipy as si
A=np.array([[1,2,3],[4,5,6],[7,8,9]])
b=np.array([15,15,15])
print np.dot(np.linalg.inv(A),b)
array([-32., 48., -24.] ## wrong result
np.linalg.solve(A,b) # the result of np.dot(np.linalg.inv(A),b) should be same as this.
array([-39., 63., -24.]) # correct result

It is necessary to say that scipy throws an error though.
np.dot(si.linalg.inv(A),b)

My numpy version is '1.9.2' and python 2.7.6.
@rasoolfa rasoolfa changed the title Singular matrix inverse does't throw error Singular matrix inverse does't throw an error Aug 7, 2015
@pv pv mentioned this issue Jan 27, 2018
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@mattip
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mattip commented Jan 21, 2019

A=np.array([[1,2,3],[4,5,6],[7,8,9]]); np.linalg.inv(A) now raises. Closing.

@mattip mattip closed this as completed Jan 21, 2019
@pmli pmli mentioned this issue Feb 23, 2019
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