BUG: numpy.linalg.inv returning different values on consecutive calls with some nan elements #20233
Description
Describe the issue:
I have a calculus of an inverse matrix in the middle of my code (some module developed by me) and debugging I found that numpy could not provide and inverse matrix. Also, only a few elements where reported as nan (don´t know if this is as expected or the complete matrix should be nan).
Anyway, if I stop the calculus at this point, and call again the inverse, it does provide an inverse matrix. Seems that something is changed in the numpy module in the first call, and not restored, so the next calls I have a different output.
The code I provide as an example does not work stand alone. I tried executing at the beginning of my complete code and it does provide the same result. So, something in my code previously has an effect on how numpy gets configured to the place where it does fail.
Sorry I cant provide the complete code and libraries. Don’t know how can I provide some stand alone code to reproduce this failure. Can I help the debugging of this issue in an other way?
Regards
Leonardo
Reproduce the code example:
a = np.array([[ 1.06902137e-08+1.03397577e-25j, -8.29800043e-09+1.46316136e-09j,
1.06153905e-08+7.03229683e-10j, -8.26255952e-09+1.45691217e-09j],
[-8.29800043e-09-1.46316136e-09j, 1.06902137e-08+0.00000000e+00j,
-8.26255952e-09-1.45691217e-09j, 1.06153905e-08-7.03229683e-10j],
[ 1.06153905e-08-7.03229683e-10j, -8.26255952e-09+1.45691217e-09j,
1.06902137e-08+7.23783036e-25j, -8.29800043e-09+1.46316136e-09j],
[-8.26255952e-09-1.45691217e-09j, 1.06153905e-08+7.03229683e-10j,
-8.29800043e-09-1.46316136e-09j, 1.06902137e-08-7.23783036e-25j]])
print(np.linalg.inv(a))
print(np.linalg.inv(a))
[[ nan +nanj -3.75115133e+11-5.40693281e+10j
-3.79340139e+11-1.19099169e+11j 3.72964747e+11-6.57637077e+10j]
[ nan +nanj 3.98070598e+11-1.64825002e-01j
3.72964747e+11+6.57637077e+10j -3.79340139e+11+1.19099169e+11j]
[ nan +nanj 3.72964747e+11-6.57637077e+10j
3.98070588e+11-1.88123676e-01j -3.34000150e+11+1.79105405e+11j]
[ nan+6.57637077e+10j -3.79340139e+11-1.19099169e+11j
-3.34000150e+11-1.79105405e+11j 3.98070588e+11-1.64492045e-01j]]
[[ 3.98070598e+11-1.88316777e-01j -3.75115133e+11-5.40693281e+10j
-3.79340139e+11-1.19099169e+11j 3.72964747e+11-6.57637077e+10j]
[-3.75115133e+11+5.40693281e+10j 3.98070598e+11-1.64825002e-01j
3.72964747e+11+6.57637077e+10j -3.79340139e+11+1.19099169e+11j]
[-3.79340139e+11+1.19099169e+11j 3.72964747e+11-6.57637077e+10j
3.98070588e+11-1.88123676e-01j -3.34000150e+11+1.79105405e+11j]
[ 3.72964747e+11+6.57637077e+10j -3.79340139e+11-1.19099169e+11j
-3.34000150e+11-1.79105405e+11j 3.98070588e+11-1.64492045e-01j]]Error message:
No response
NumPy/Python version information:
numpy version 1.20.1