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PaulWAyers avatar PaulWAyers commented on August 22, 2024

I think there is no choice here. It bothers me that under-the-hood the SVD is the iterative SVD that can fail due to "lack of convergence" and this is a problem we've observed happens sometimes, as opposed to the rigorous factorization of a matrix which is always fine. But with current versions, scipy.pinv, scipy.pinv2, and numpy.pinv are all the same. No need to distinguish.

See the discussion scipy/scipy#8861 (comment)

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PaulWAyers avatar PaulWAyers commented on August 22, 2024

We need to remember this: if we end up with "SVD did not converge" errors we will need to add in a brute strength implementation using the dgesvd SVD driver (accessible in scipy).

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