On Mon, 2023-05-01 at 17:50 +0000, jmsa...@gmail.com wrote: > > I think this example shows that you don't need any special > > infrastructure > > from numpy. I don't think there is going to be much appetite to > > expand our > > API in this direction. > > But I do! I'm looking for something that implements the > multiply_check_ov(X,Y) and similar functionality for addition and > subtraction, for large arrays; I don't know how to do that > efficiently. (Or even correctly for 64-bit operands --- for 8/16/32 I > suppose as a baseline I could do the math in 64-bit arithmetic and if > the answer doesn't match, then use the sign bit of the 64-bit result > for determining overflow.)
There are two things I could imagine. First, improving the warnings and maybe making some overflow errors (or optional). This never happened since it should come with performance impact and that should be low. Second, there could be a `BigInt` dtype that has full precision like Python integers, but I would prefer such development to start outside of NumPy first. But, neither is even what you want probably. So I agree, NumPy is probably not in a position to help you. You can implement the functions that you described yourself (i.e. with overflow return indication). And they will be fully compatible with NumPy (see for example https://github.com/WarrenWeckesser/ufunclab or maybe via jitters like numba). - Sebastian > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: sebast...@sipsolutions.net > _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
