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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