On 6/27/2017 5:35 PM, Nathaniel Smith wrote:
I remember... The major issue here is that some people want dot(a, b) on Boolean matrices to use these semantics, right?
Yes; this has worked in the past, and loss of this functionality is unexpected. That said, I haven't used this outside of a teaching context, so for me it only affects some course notes. I suppose loss of this behavior could be somewhat mitigated if numpy could provide an optimized general inner product (along the line of the Wolfram Language's `Inner`). But note that numpy.linalg.matrix_power is also lost (e.g., the derived graphs that allow an intuitive representation of transitive closure). fwiw, Alan _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
