[SciPy-User] Least-squares fittings with bounds: why is scipy not up to the task?
Fri Mar 9 15:36:47 CST 2012
On Fri, Mar 9, 2012 at 1:55 AM, Matthew Newville <email@example.com>wrote:
> On Thursday, March 8, 2012 3:07:22 PM UTC-6, Gael Varoquaux wrote:
> > I am sorry I am going to react to the provocation.
> And I am sorry that I am going to react to your message. I think your
> reaction is unfair.
> > As some one who spends a fair amount of time working on open source
> > software I hear such remarks quite often: 'why is feature foo not
> > implemented in package bar?. I am finding it harder and harder not to
> > react negatively to these emails. Now I cannot consider myself as a
> > contributor to scipy, and thus I can claim that I am not taking your
> > comment personally.
> Where I work (a large scientific user facility), there are lots of
> scientists in what I'll presume is Eric's position -- able and willing to
> work well with scientific programming tools, but unable to devote the extra
> time needed to develop core functionality or maintain much work outside of
> their own area of interest. There are a great many scientists interested
> in learning and using python. Several people there *are* writing
> scientific libraries with python. Similarly in the fields I work in,
> python is widely accepted as an important ecosystem.
> > Why isn't scipy not up to the task? Will, the answer is quite simple:
> > because it's developed by volunteers that do it on their spare time,
> > at night too often, or companies that put some of their benefits in
> > source rather in locking down a market. 90% of the time the reason the
> > feature isn't as good as you would want it is because of lack of time.
> > I personally find that suggesting that somebody else should put more of
> > the time and money they are already giving away in improving a feature
> > that you need is almost insulting.
> Well, in some sense, Eric's message is an expression of interest....
> Perhaps you would prefer that nobody outside the core group of developers
> or mailing list subscribers asked for any new features or clarification of
> existing features.
> > I am aware that people do not realize how small the group of people
> > develop and maintain their toys is. Borrowing from Fernando Perez's
> > at Euroscipy (http://www.euroscipy.org/file/6459?vid=download slide
> > the number of people that do 90% of the grunt work to get the core
> > scientific Python ecosystem going is around two handfuls.
> Well, Fernando's slides indicate there is a small group that dominates
> commits to the projects, then explains, at least partially, why that it
> is. It is *NOT* because scientists expect this work to be done for them by
> volunteers who should just work harder.
> There are very good reasons for people to not be involved. The work is
> rarely funded, is generally a distraction from funded work, and hardly ever
> "counts" as scientific work. That's all on top of being a scientist, not a
> programmer. Now, if you'll allow me, I myself am one of the "lucky"
> scientific software developers, well-recognized in my own small community
> for open source analysis software, and also in a scientific position and in
> a group where building tools for better data collection and analysis can
> easily be interpreted as part of the job. In fact, I spend a very
> significant amount of my time writing open source software, and work nearly
> exclusively in python.
> So, just as as an example of what happens when someone might
> "contribute", I wrote some code (lmfit-py) that could go into scipy and
> posted it to this list several months ago. Many people have expressed
> interest in this module, and it has been discussed on this list a few times
> in the past few months. Though lmfit-py is older than Fernando's slides
> (it was inspired after being asked several times "Is there something like
> IDL's mpfit, only faster and in python?"), it actually follows his
> directions of "get involved" quite closely: it is BSD, at github, with
> decent documentation, and does not depend on packages other than scipy and
> numpy. Though it's been discussed on this list recently, two responses
> from frequent mailing-list responders (you, Paul V) was more along the
> lines of "yes, that could be done, in principle, if someone were up to
> doing the work" instead of "perhaps package xxx would work for you".
> At no point has anyone from the scipy team expressed an interest in
> putting this into scipy. OK, perhaps lmfit-py is not high enough quality.
> I can accept that.
I don't think anyone has doubts about the quality of lmfit. On the
contrary, I've asked you to list it on
http://scipy.org/Topical_Software(which you did) because I thought it
looked interesting, and have directed
some users towards your package. The documentation is excellent, certainly
better than that of many parts of scipy. The worry with your code is that
the maintenance burden may be relatively high, simply because very few
developers are familiar with AST. The same for merging it in scipy - one of
the core developers will have to invest a significant amount of time
wrapping his head around your work.
The ideal scenario from my point of view would be this:
- lmfit keeps being maintained by you as a separate package for a while
(say six months to a year)
- it gains more users, who can discover potential flaws and provide
feedback. The API can still be changed if necessary.
- once it's stabilized a bit more, you propose it again (and more
explicitly) for inclusion in scipy
- one of the developers does a thorough review and merges it into
- you get commit rights and maintain the code within scipy
- bonus points: if you would be interested in improving and reviewing PRs
for related code in optimize.
Scipy is a very good place to add functionality that's of use in many
different fields of science and engineering, but it needs many more active
developers. I think this thread is another reminder of that. Some of the
criticism in this thread about how hard it is to contribute is certainly
justified. I've had the plan for a while (since Fernando's EuroScipy talk
actually) to write a more accessible "how to contribute" document than the
one Pauli linked to. Besides the mechanics (git, Trac, etc.) it should at
least provide some guidance on what belongs in scipy vs. in a scikit, how
to get help, how to move a contribution that doesn't get a response
forward, etc. I'll try to get a first draft ready within the next week or
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