[SciPy-dev] Why does orth use svd instead of QR ?
Thu Feb 4 21:45:42 CST 2010
I wanted to know if there was a rationale for using svd to
orthonormalize the columns of a matrix (in scipy.linalg). QR-based
methods are likely to be much faster, and I thought this was the
standard, numerically-stable method to orthonormalize a basis ? If the
reason is to deal with rank-deficient matrices, maybe we could add an
option to choose between them ?
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