Re:Matlab–Python–Julia Cheatsheet
by ChrisRackauckas on Sunday June 09, 2019 @09:57PM
(#20143257)
But in mathematical derivations, when does a transpose which is not an adjoint ever show up? In many derivations we write transpose knowing that it would be the adjoint if complex numbers are used. That's at least true for most of applied mathematics, statistics, physics, etc.
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Re:Matlab–Python–Julia Cheatsheet
by eigenspace on Sunday June 09, 2019 @10:03PM
(#20143284)
My point at least was just that it’s a bad idea to use adjoint to construct a column matrix since in that case you likely didn’t intend to take an adjoint, you just wanted a certain shape.
There’s no math or physics equation here with objects transforming under an adjoint representation, it’s just a constructor.
Re:Matlab–Python–Julia Cheatsheet
by patrick5415 on Monday June 10, 2019 @02:50AM
(#20144448)
Yes, one may keep that in mind when working something on scratch paper. But when it’s possible for things to be complex, the standard notation is something like A^. In my opinion, it is rather sloppy to write A^T and expect the reader to substitute for the complex case. I can’t remeber where at the moment, but I have definitely seen derivations when the authors explicitly wanted A^T on a complex matrix.