[SciPy-Dev] GSOC Optimization Project

[Nikolay Mayorov]

Hi! I want to clarify some things about GSOC project idea related to Levenberg-Marquardt algorithm.
1) Why do we want anything but current leastsq based on MINPACK?
Looks like it is answered here: https://github.com/scipy/scipy/pull/90 
"When we call python from FORTRAN, a lot of magic has to be done. This magic prevents us, for example, to properly pass exceptions through the FORTRANcode."
Could you comment more on that perhaps?
2) What's wrong with https://github.com/scipy/scipy/pull/90? Why it is stalled? What do you expect from GSOC student to do better / different?
Again partially answered in PR: "It's stalled: the algorithmic part is OK, the new interfaces proposed controversial.", "However, this could perhaps be extended to Levenberg-Marquardt supporting sparse Jacobians"

3) Based on 2: how GSOC student should proceed with interface issue? I mean there weren't any strong opinions and it was on the list for so long. I have no idea how to come up with a good solution all of a sudden.

4) Do you believe that code written during GSOC should be based on PR mentioned?
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That's what I come up so far about the work during GSOC:
- Decide on interface part- Add new features to the PR from pv (probably just one of them):    Sparse Jacobians support   Constraints support- Implement a solid test suite

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I would appreciate your answers,
Nikolay.

 		 	   		  
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