Hi,

I just happened to do the same thing two days ago. If you want  
uncertainties as well, here is some code that uses scipy.optimize. I  
just put up a preliminary example on the scipy wiki:

http://www.scipy.org/Cookbook/FittingData?action=show

Not the cleanest or most sophisticated code in the world, but it  
works for simple things.

Cheers,
Jessica

On Dec 6, 2007, at 8:06 AM, Ryan May wrote:

> Ping Yeh wrote:
>> Hi,
>>
>> I have (x,y) data that I want to fit to the formula
>> y = a * x^b
>> to determine a and b. How can I do it? The current
>> manual only lists linear fit and polynomial fit.
>>
>
> If you just want quick power law fit without turning to the other
> solutions, you can just transform your variables to make it a  
> linear fit
> problem:
>
> log(y) = log(a * x^b) = log(a) + b * log(x)
>
> So just do the linear regression with the logarithms of x and y,  
> and the
> slope you get back will be b, and the intercept will be log(a).
>
> Ryan
>
> -- 
> Ryan May
> Graduate Research Assistant
> School of Meteorology
> University of Oklahoma
>
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