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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