Hi, We were discussion integer promotion rules amongst the Numba team, and we were wondering about the rationale for Numpy's rules. For example, adding int8 and int8 will give int8 as result (with potential magnitude loss), while adding int8 and uint8 will give int16 as result (promoting to the smallest fitting type). Furthermore, adding int64 and uint64 returns float64.
Is there a rationale somewhere documenting and explaining this behaviour (sorry if I've missed it in a obvious location)? Is it the produce of organic evolution? Also, it is set to stay like this, or will it evolve in the future? Thank you Antoine. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
