[SciPy-user] fmin

[Stephen Walton]

On Mon, 2004-11-22 at 20:57 +0100, Reik Börger wrote:

> Now, I additionally provide the gradient of the objective function and 
> use optimize.fmin_bfgs. But when I run the program, the optimizer 
> always stops after 2 or 3 iterations and returns a value close to my 
> starting value as the optimal solution - doesn't matter, where I start, 
> it is always very close to the starting value.

I am only asking this because I've made the same mistake myself many
times:  how sure are you that your analytic gradient is correct?  I
would write a test to compare the analytic gradient against a
numerically computed one before doing anything else.

Moreover, if the function you're optimizing is itself a Fortran or C
routine with a complicated or even non-analytic gradient, you might look
at the automatic differentiators out there:
http://www-unix.mcs.anl.gov/autodiff/AD_Tools/

-- 
Stephen Walton <stephen.walton at csun.edu>
Dept. of Physics & Astronomy, CSU Northridge
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