[SciPy-User] Alternatives to scipy.optimize

Erik Petigura eptune@gmail....
Sat Feb 25 20:21:43 CST 2012


Thanks for getting back to me!

I'd like to minimize p1 and p2 together.  Let me try to describe my problem a little better:

I'm trying to fit an exoplanet transit light curve.  My model is a box + a polynomial trend.

https://gist.github.com/1912265

The polynomial coefficients and the depth of the box are linear parameters, so I want to fit them using linear least squares.  The center and width of the transit are non-linear so I need to fit them with an iterative approach like optimize.fmin.  Here's how I implemented it.

https://gist.github.com/1912281

There is a lot unpacking and repacking the parameter array as it gets passed around between functions.  One option that might work would be to define functions based on a "parameter object".  This parameter object could have attributes like float/fix, linear/non-linear.  I found a more object oriented optimization module here:

http://newville.github.com/lmfit-py/

However, it doesn't allow for linear fitting.

Erik

-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/scipy-user/attachments/20120225/04c340bc/attachment.html 


More information about the SciPy-User mailing list