Hi Sebastian and Chuck, Thanks for the response! (Sorry about the formatting in my original post, I wasn't familiar with how to display code in this setting).
I think keeping + as "logical or" and * as "logical and" on np.bool_ types is fine, although redundant given that | and & provide this functionality and potentially misleading given the different behavior from the native Python bool; however, I could see it being too painful of a migration within v1.* numpy. I think my main point of contention is that division and exponentiation aren't well defined operations on np.bool_, at least as currently defined, and they should raise errors like subtraction. Raising those errors would have caught the problem I ran into when trying to taking the mean of multiple ndarrays of dtype=np.bool_. I'm not sure what the realistic use case is to have division/exp. return a float/int, especially when +/* return np.bool_ and subtraction throws an error. Sebastian, you stated: "N.B.: I have changed that logic. "Future" ufuncs are now reversed. They will default to an error rather than using the `int8` implementation." So is the division/exp. issue that I described with np.bool_ solved in future releases? Happy to help out on implementation/formalizing a proposal! FWIW, I suppose you could change + to XOR. Then np.bool_ would be a field (isomorphic to Z/2Z) and then you could reasonably define - and /. (Although + would be equivalent to - and * would be equivalent to /, which would probably be confusing to most users.) Best, Jacob _______________________________________________ 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
