Inconsistency of dimensions in QR decomposition

[alois-bissuel]

Doing a reduced QR decomposition may give different dimensions when calling qr.reduced.justR(A) instead of qr.reduced(A).r

Explanation:
If M is an m x n matrix, and m<n, then M=QR where Q is m x m and R is m x n.
In doQr, is skipQ is true, then upperTriangular(A(0 until mn, ::) is called to output R, which implicitly outputs a square n x n matrix instead of a rectangular m x n matrix. If skipQ is set to false, then the code correctly erases the lower triangular part of the matrix A (which is the array on which Lapack is called).

[alois-bissuel]

I have created a small commit to fix this in my forked version of Breeze : see pull request here alois-bissuel#1
Sorry if it is not the right way to do it, it is my first tries on GitHub !

[dlwh]

hi alois, sorry for being so slow. The best way to do this is to open a PR against scalanlp/breeze, not your own repository.

thanks

[alois-bissuel]

Sure, will do!

[alois-bissuel]

Done, see PR 736.