[SciPy-user] Optimization / fitting routines

[Christian Kristukat]

Webb Sprague wrote:
> Hi all,
> 
> (I am a little bit over my head, so if I say things that sound stupid,
> please excuse.)
> 
> (1) Could someone point me toward documentation for optimization
> routines in numpy?  I need the routine to be very general, excepting
> an arbitrary Python function that accepts a test value, and a target
> value for that function. We can assume that the function will be
> monotonic.

An overview of the optimization routines is available in the docstring:

help(optimize)

And each of the routines has some further documentation, e.g.

help(optimize.fmin)

The following code snippet finds the minimum of a parabola:

def func(x):
    return .3*x**2-3.4*x

res = optimize.fmin(func, [7])
Optimization terminated successfully.
         Current function value: -9.633333
         Iterations: 16
         Function evaluations: 32

print res

[ 5.66665039]


> (2)  Could someone point me or recommend a book that clearly describes
> these problems mathematically at an "advanced undergrad" level?

I guess many of them are described in the 'Numercial recipies'.

Hope this helps, Christian