[SciPy-User] leastsq interface and features

[Charles R Harris]

On Fri, May 28, 2010 at 10:47 PM, bowie_22 <m.boumans at gmx.net> wrote:

> Hello,
>
> at the moment am I am evaluating scipy as a subsitute for Matlab.
> One important use case for me is to fit a model to measured data.
>
> In Matlab I use lsqnonlin from the Optimization Toolbox.
> In Scipy I would use leastsq.
>
> By comparing the 2 approaches with a "daily use" point of view I see the
> following improvements for the scipy module
>
> 1) setting the options for the algorithm:
>   ML uses a structure together with optimset optimget
>   --> lsqnonlin has a quite short signature
> IMPROVEMENT: introduce a common options structure for all optimization
> algos
>
>
I hate the options structure. It's a hidden super-huge signature with poorly
chosen defaults.


> 2) there is the possibilty to set an output function that is called in each
> iteration step in ML. That can be used for displaying the current status of
> the
> optimization. For me a quite important point as my customers want to "see"
> what
> happens (not just throwing measured data to an algorithm and get back a set
> of
> numbers)
>  IMPROVEMENT: introduce a output function that can be called each iteration
>
>
Possible, I think.


> 3) give lower and upper bounds for the optimization variables. Also quite
> important as in my uses cases you have normally an idea in which range your
> parameter should be (mass of a car 1200 - 1800 kg). In ML you can provide
> this
> knowledge as lower bounds and upper bounds to lsqnonlin.
> IMPROVEMENT: introduce lower and upper bounds
>
>
Suggest using a different function for this. Matlab tends to over-overload
it's functions.


> My problem:
> How can I help to get this improvements to scipy? Is this the correct
> address to
> ask?
>
>
Yes.

Chuck
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