On Mon, Apr 11, 2016 at 5:24 PM Chris Barker <chris.bar...@noaa.gov> wrote:
> On Fri, Apr 8, 2016 at 4:37 PM, Ian Henriksen < > insertinterestingnameh...@gmail.com> wrote: > > >> If we introduced the T2 syntax, this would be valid: >> >> a @ b.T2 >> >> It makes the intent much clearer. >> > > would: > > a @ colvector(b) > > work too? or is T2 generalized to more than one column? (though I suppose > colvector() could support more than one column also -- weird though that > might be.) > > -CHB > Right, so I've opted to withdraw my support for having the T2 syntax prepend dimensions when the array has fewer than two dimensions. Erroring out in the 1D case addresses my concerns well enough. The colvec/rowvec idea seems nice too, but it matters a bit less to me, so I'll leave that discussion open for others to follow up on. Having T2 be a broadcasting transpose is a bit more general than any semantics for rowvec/colvec that I can think of. Here are specific arrays that, in the a @ b.T2 can only be handled using some sort of transpose: a = np.random.rand(2, 3, 4) b = np.random.rand(2, 1, 3, 4) Using these inputs, the expression a @ b.T2 would have the shape (2, 2, 3, 3). All the T2 property would be doing is a transpose that has similar broadcasting semantics to matmul, solve, inv, and the other gufuncs. The primary difference with those other functions is that transposes would be done as views whereas the other operations, because of the computations they perform, all have to return new output arrays. Hope this helps, -Ian Henriksen
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