Function Svdcmp-Sf
(
svdcmp-sf < a > < m > < n > < w > < v > &optional < rv1 > )
Given an `m'x`n' matrix `A,' this routine computes its singular value
decomposition, A = U W V^T. The matrix U replaces `A' on output. The diagonal
matrix of singular values W is output as a vector `W' of length `n.' The matrix
`V' -- not the transpose V^T -- is output as an `n'x`n' matrix `V.' The row
dimension `m' must be greater or equal to `n'; if it is smaller, then `A' should
be filled up to square with zero rows. See the discussion in Numerical Recipes
in C, section 2.6.
This routine returns no values, storing the results in `A,' `W,' and `V.' It
does use some auxiliary storage, which can be passed in as `rv1,' a single-float
array of length `n,' if you want to avoid consing. All input arrays should be
of single-floats.