On Sat, Sep 17, 2011 at 2:52 PM, Charles R Harris <charlesr.har...@gmail.com> wrote: > Hi All, > > I'd like to start a discussion about modifications to lstsq to accommodate > the new masked arrays and move weights, scaling, and covariance > determination down to a lower common level. This is motivated by Travis' > recent changes to polyfit as well as my own various polynomial fits that > also allow weights. Also, once these features are pushed down to lstsq, it > should be possible to push them down further into a c-wrapper for the LAPACK > routines, which is where I really think they belong in the long run. > > Because missing values will effect the std/var/cov in the same way as > weights of zero, I think support for missing values and weights go naturally > together. Support for scaling and covariance are less closely tied, but they > are both features I use all the time in practice and having them available > will be useful. It might also be nice to change the return signature, > though this would require a new function. I rather like the idea of > returning the coefficients and a dictionary, where everything not a > coefficient gets stuffed into the dictionary. In this regard see also Denis > Laxalde's proposal, something we might want to be consistent with. > > Thoughts?
What's the speed penalty if we just want to use numpy/scipy linalg as a library and don't need any of the extra features? As some of the discussions have shown it can be pretty expensive to use linalg in loops. Josef > > Chuck > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
