[SciPy-User] optimization routines can not handle infinity values
Wed Sep 15 15:05:58 CDT 2010
i'm aware of SDP solvers but they handle only linear objective functions
and the costraints are not the problem. it is just that the function is not
i will experiment by changing the line search methods as i think they are
part of the methods that needs to be aware of the domain.
thanx for the help, i will post my eventual findings.
On Wed, Sep 15, 2010 at 6:48 PM, Jason Rennie <firstname.lastname@example.org> wrote:
> On Tue, Sep 14, 2010 at 9:55 AM, enrico avventi <email@example.com> wrote:
>> Some of the routines (fmin_cg comes to mind) wants to check the gradient
>> at points where the objective function is infinite. Clearly in such cases
>> the gradient is not defined - i.e the calculations fail - and the algorithm
> IIUC, CG requires that the function is smooth, so you can't use CG for your
> problem. I.e. there's nothing wrong with fmin_cg. You really need a
> semidefinite programming solver, such as yalmip or sedumi. My experience
> from ~5 years ago is that SDP solvers only work on relatively small problems
> (1000s of variables).
> Jason Rennie
> Research Scientist, ITA Software
> SciPy-User mailing list
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