[SciPy-User] is it possible to constrain the scipy.optimize.curve_fit function?

servant mathieu servant.mathieu@gmail....
Thu May 17 04:00:15 CDT 2012


Hi David,
That's really dirty but it works thanks :-). More generally, is there a
standard procedure to constrain a specific parameter to fall in a specific
range (e.g., [200, 400]) during the fitting process?

Mathieu

2012/5/16 David Baddeley <david_baddeley@yahoo.com.au>

> The quick and dirty way is to do a variable substitution with the square
> of your parameter and fit, e.g. r + (a**2)*np.power(x, -b**2)
> You can take the sqrt of the parameters later.
>
>   ------------------------------
> *From:* servant mathieu <servant.mathieu@gmail.com>
> *To:* scipy-user@scipy.org
> *Sent:* Thursday, 17 May 2012 4:20 AM
> *Subject:* [SciPy-User] is it possible to constrain the
> scipy.optimize.curve_fit function?
>
> Dear scipy users,
>
> I'm trying to fit to data a power law of the form :
>
>
> def func (x, a,b, r):
>       return r + a*np.power(x,-b)
>
>
> I would like to constrain the curve_fit routine to only allow
> positive parameter values. How is it possible to do so?
>
> Kind regards,
> Mathieu
>
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