Hi All, Following on a PR combining the ability to provide fixed and flexible dimensions [1] (useful for, e.g., 3-vector input with a signature like `(3),(3)->(3)`, and for `matmul`, resp.; based on earlier PRs by Jaime [2] and Matt (Picus) [3]), I've now made a PR with a further enhancement, which allows one can indicate that a core dimension can be broadcast [4].
A particular use case is `all_equal`, a new function suggested in a stalled PR by Matt (Harrigan) [5], which compares two arrays axis-by-axis, but short-circuits if a non-equality is found (unlike what is the case if one does `(a==b).all(axis)`). One thing that would be obviously useful for a routine like `all_equal` is to be able to provide an array as one argument and a constant as another, i.e., if the core dimensions can be broadcast if needed, just like they are in `(a==b).all(axis)`. This is currently not possible: with its signature of `(n),(n)->()`, the two arrays have to have the same trailing size. My PR provides the ability to indicate in the signature that a core dimension can be broadcast, by using a suffix of "|1". Thus, the signature of `all_equal` would become: ``` (n|1),(n|1)->() ``` Comments most welcome (yes, even on the notation - though I think it is fairly self-explanatory)! Marten p.s. There are some similarities to the new "flexible" dimensions implemented for `matmul` [1], but also differences. In particular, for a signature of `(n?),(n?)->()`, one could also pass in an array of trailing size n and a constant, but it would not be possible to pass in an array with trailing size 1: the dimensions with the same name have to be either present and the same or absent. In contrast, for broadcasting, dimensions with the same name can have trailing size n, size 1, or be absent (in which case they count as 1). For broadcasting, any output dimensions with the same name are never affected, while for flexible dimensions those are removed. [1] https://github.com/numpy/numpy/pull/11175 [2] https://github.com/numpy/numpy/pull/5015 [3] https://github.com/numpy/numpy/pull/11132 [4] https://github.com/numpy/numpy/pull/11179 [5] https://github.com/numpy/numpy/pull/8528 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
