[SciPy-user] minpack.error / fsolve problem

Webb Sprague webb.sprague@gmail....
Tue Mar 4 13:31:10 CST 2008

If anybody cares, I resolved the issue by using scipy.optimize.brent()
to minimize ((f(x) - y)**2.  Works great now.

On 3/1/08, Webb Sprague <webb.sprague@gmail.com> wrote:
> Thanks for the response, dmitrey!
> On Sat, Mar 1, 2008 at 12:17 AM, dmitrey <dmitrey.kroshko@scipy.org> wrote:
> > As for me it yields "name LcUtil is not defined" (line 48). Also, there
> >  was some indent problems near try-except block, mb due to space-tab
> >  different numbers from the attached file.
> Sorry but there is a lot of infrastructure you don't have, so it won't
> run as is.  Plus it was cut and paste, etc.  But it works 98% of the
> time in its context.
> >  I would recommend you try using another solver, for example nssolve from
> >  scikits.openopt.
> Sounds reasonable, but why that one?
> >  Do you know exactly what do you need? Solve a system of non-linear
> >  equations via fsolve or to minimize a function?
> >  D.
> I need to fit a scalar (kt in the code) such  that f(kt) = e_0 (a
> scalar which is given from somewhere else).  f() involves a bunch of
> stuff (see the code, but don't bother trying to run it), but it is
> monotonic.
> I think of this as finding kt such that f(kt) - e_0 = 0, so I used a
> root solver.  But I hardly care so long as it works
> Is there a best function for this?
> I am totally unfamiliar with optimization theory, besides one
> assignment on Newton's method in first semester calculus, and some
> handwaving about MLE's

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