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svdvals!

svdvals!(A)

Returns the singular values of A, while saving space by overwriting the input.

Examples

1. Compute singular values of a matrix:

   julia> A = [1 2; 3 4; 5 6];
   julia> svdvals!(A)
   2-element Array{Float64,1}:
   7.3484692283495345
   0.3722813232690143

   This example computes the singular values of matrix A and overwrites A with the result.

2. Update singular values of a matrix in-place:

   julia> B = [0.5 1.5; 2.5 3.5];
   julia> svdvals!(B)
   2-element Array{Float64,1}:
   4.541381265149109
   0.258618734850891

   It computes the singular values of matrix B and modifies B in-place.

3. Handle rectangular matrices:

   julia> C = [1 2 3; 4 5 6];
   julia> svdvals!(C)
   2-element Array{Float64,1}:
   8.866068747318506
   0.36621420674709056

   It can handle rectangular matrices and compute their singular values.

Common mistake example:

julia> D = [1 2; 3 4; 5 6];
julia> svdvals!(D')
ERROR: MethodError: no method matching svdvals!(::Adjoint{Int64,Array{Int64,2}})

In this example, the transpose of matrix D is passed to svdvals!, resulting in a MethodError. Make sure to apply svdvals! directly to the matrix and not its transpose.

See Also

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