The line
|
np.asarray(1.0 / np.maximum(np.power(np.fabs(e_list[k]), 2.0 - p_list[k]), eps))[:, 0]) |
can raise the above-mentioned warning, if an element of
e_list[k] is zero and the corresponding element of
p_list[k] is greater than 2. Is it safe to ignore the warning or should it be taken into account?
The line
NormMinimization/normmin.py
Line 74 in db39e48
can raise the above-mentioned warning, if an element of
e_list[k]is zero and the corresponding element ofp_list[k]is greater than 2. Is it safe to ignore the warning or should it be taken into account?