> In 1.15 the call is instead to `_umath_linalg.lstsq_m` and I'm not sure what this actually ends up doing - does this end up being the same as `dgelsd`?
When the arguments are real, yes. What changed is that the dispatching now happens in C, which was done as a step towards the incomplete https://github.com/numpy/numpy/issues/8720. I'm not an expert - but aren't "minimum norm" and "least squares" two ways to state the same thing? Eric On Sun, 18 Nov 2018 at 20:04 Romesh Abeysuriya <romesh.a...@gmail.com> wrote: > Hi all, > > I'm solving an underdetermined system using `numpy.linalg.lstsq` and > trying to track down its behavior for underdetermined systems. In > previous versions of numpy (e.g. 1.14) in `linalg.py` the definition > for `lstsq` calls `dgelsd` for real inputs, which I think means that > the underdetermined system is solved with the minimum-norm solution > (that is, minimizing the norm of the solution vector, in addition to > minimizing the residual). In 1.15 the call is instead to > `_umath_linalg.lstsq_m` and I'm not sure what this actually ends up > doing - does this end up being the same as `dgelsd`? If so, it would > be great if the documentation for `numpy.linalg.lstsq` stated that it > is returning the minimum-norm solution (as it stands, it reads as > undefined, so in theory I don't think one can rely on any particular > solution being returned for an underdetermined system) > > Cheers, > Romesh > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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