great another object array
np.asarray([round(x_i.item()) for x_i in np.array([1, 2.5, 2e20, 2e200])])
array([1, 2, 200000000000000000000,
199999999999999993946624442502072331894900655091004725296483501900693696871108151068392676809412503736055024831947764816364271468736556969278770082094479755742047182133579963622363626612334257709776896],
dtype=object)
I would rather have numpy consistent with numpy than with python
Since round() (and the __round__() interface) is part of Python and not numpy, there is nothing in numpy to be consistent with. We only implement __round__() for the scalar types.
Maybe I misunderstand
I'm using np.round a lot. So maybe it's a question whether and how it will affect np.round.
Does the following change with the proposal?
np.round(np.array([1, 2.5, 2e20, 2e200]))
array([1.e+000, 2.e+000, 2.e+020, 2.e+200])
np.round(np.array([1, 2.5, 2e20, 2e200])).astype(int)
array([ 1, 2, -2147483648, -2147483648])
np.round(np.array([2e200])[0])
2e+200
np.round(2e200)
2e+200
round(2e200)
199999999999999993946624442502072331894900655091004725296483501900693696871108151068392676809412503736055024831947764816364271468736556969278770082094479755742047182133579963622363626612334257709776896
Josef
"around 100" sounds like "something all_close(100)"
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