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

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