[SciPy-User] Least-squares fittings with bounds: why is scipy not up to the task?
Sat Mar 10 12:24:42 CST 2012
On Saturday, March 10, 2012 11:00:44 AM UTC-6, Pauli Virtanen wrote:
> 09.03.2012 22:13, Matthew Newville kirjoitti:
> > Well, I understand you don't necessarily consider yourself to be a scipy
> > dev, but I'll ask anyway: How many pull requests have been made, and
> > how many have been accepted? Perhaps I am not reading github's Pull
> > Request link correctly, but that seems to indicate that the numbers are
> > 17 and 0. Surely, those cannot be correct. Unless I am counting
> > wrong, 5 of the 17 (total? outstanding?) pull requests listed for
> > scipy/scipy involve optimization.
> Wrong: 17 open, 99 accepted.
Yes, I see that (or more) now.... I've been using git for a while now, but
still learning how to read github pages. I knew 17/0 couldn't be right....
Sorry for that.
> > Well, there was a discussion "Alternative to scipy.optimize" in the past
> > two weeks on scipy-users that mentioned lmfit, and several over the past
> > several months, and apparently requests about mpfit in the more distant
> > past. And yet two scipy contributers (according to github's list, I am
> > counting you) responded to the original request for features **exactly
> > like lmfit** with something reading an awful lot like "Well, you'll have
> > to write one". Perhaps insular is not a fair characterization -- how
> > would you characterize that?
> Come on. The correct characterization is just: "busy". I did not
> remember that your project existed as it was announced half a year ago
> with no proposal that it should be integrated, and did not read the
> recent thread on scipy-user.
OK, I can accept that. We're all busy.
I still take exception with Gael's response to the original question. In
this instance, there was browbeating of outside people for not contributing
coupled with ignoring contributions from outside people. You'll probably
forgive me for thinking that is not so encouraging for outside
Scipy is fantastic project, and I've been relying on it for many years.
But it is also very large and diverse, with lots of great code, and some
mediocre code, and it's sometimes difficult to tell what is well supported
and what is less so. It's also not clear to me what the strategy is for
deciding what belongs in the core and what belongs in outside projects.
The problems of how to organize the scientific python projects, and how to
attract more developers, are challenging. I do not pretend to know how to
do that, and I'm sure you've all thought about and discussed this at
length, but it might be important to give more attention to these issues.
But I also submit that the (self) perception that there is a small group of
people doing all the work and a large group of people who do nothing but
ask for more features is likely to be self-fulfilling. The way out of the
cage is probably not by running harder or screaming louder, but by moving
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