On Mon, May 28, 2018 at 7:36 PM Eric Wieser <wieser.eric+nu...@gmail.com> wrote:
> which ensure that it is still well defined (as the identity) on 1d arrays. > > This strikes me as a bad idea. There’s already enough confusion from > beginners that array_1d.T is a no-op. If we introduce a matrix-transpose, > it should either error on <1d inputs with a useful message, or insert the > extra dimension. I’d favor the former. > To be clear: matrix transpose is an example use-case rather than a serious proposal in this discussion. But given that idiomatic NumPy code uses 1D arrays in favor of explicit row/column vectors with shapes (1,n) and (n,1), I do think it does make sense for matrix transpose on 1D arrays to be the identity, because matrix transpose should convert back and forth between row and column vectors representations. Certainly, matrix transpose should error on 0d arrays, because it doesn't make sense to transpose a scalar.
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