Rondall, Are you familiar with the lmfit project? I am not an expert, but it seems like your algorithms may be useful there. I recommend checking with Matt Newville via the mailing list.
Regards, Joe On Fri, Jun 5, 2020, 17:00 Ralf Gommers <ralf.gomm...@gmail.com> wrote: > > > On Fri, Jun 5, 2020 at 9:48 PM rondall jones <rejon...@msn.com> wrote: > >> Hello! I have supported constrained solvers for linear matrix problems >> for about 10 years in C++, but have now switched to Python. I am going to >> submit a couple of new routines for linalg called autoreg(A,b) and >> autoregnn(A,b). They work just like lstsq(A,b) normally, but when they >> detect that the problem is dominated by noise they revert to an automatic >> regularization scheme that returns a better behaved result than one gets >> from lstsq. In addition, autoregnn enforces a nonnegativity constraint on >> the solution. I have put on my web site a slightly fuller featured version >> of these same two algorithms, using a Class implementation to facilitate >> retuning several diagnostic or other artifacts. The web site contains >> tutorials on these methods and a number of examples of their use. See >> http://www.rejones7.net/autorej/ . I hope this community can take a look >> at these routines and see whether they are appropriate for linalg or should >> be in another location. >> > > Hi Ron, thanks for proposing this. It seems out of scope for NumPy; > scipy.linalg or scipy.optimize seem like the most obvious candidates. > > If you propose inclusion into SciPy, it would be good to discuss whether > the algorithm is based on a publication showing usage via citation stats or > some other way. There's more details at > http://scipy.github.io/devdocs/dev/core-dev/index.html#deciding-on-new-features > > Cheers, > Ralf > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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