LinearSolve default handling for non-square

[alex-s-gardner]

If I want to solve a 12 parameter model:

A = rand(100,12)
b = rand(100,1)
x = A\b

works just fine in Julia or matlab. But the following does not work in LinearSolve:

using LinearSolve
prob = LinearProblem(A,b)
sol = solve(prob)

as it requires A to be a square matrix.

I'm just curious why this is.

[vpuri3]

what \ is doing is a linear least squares solve.

[ChrisRackauckas]

The default algorithm choice is just forgetting to check for square before choosing lu. We should add that bit.

[ChrisRackauckas]

sol = solve(prob, QRFactorization())