[SciPy-User] fitting data

Johann Cohen-Tanugi cohen@lpta.in2p3...
Thu Jul 30 02:34:36 CDT 2009

```Bala, I think that you are mistyping your problem : the second equation
looks a lot like one of the 2 solutions of a second order polynom a0*X^2
-2*(a0+x+b0)*X+b0
Is that right?
In any case, replace a  by  (f-f0)/(fb-f0) in eq.2  and then  you have
an implicit function g(x,b0)
Johann

Bala subramanian wrote:
> Sorry for not giving clear info. in my previous mail.
>
> Actually, i have two equations 1) f = a * fb + (1-a) fo, where f, fb,
> fo are known
>
> and 2) a = 1/2ao[ (ao + x + bo) - { (ao + x + bo)2 - 4 ao bo }0.5 ]
>
> From eq 1, i should get 'a' and then i use this in eq 2 to find bo.
>
> On Thu, Jul 30, 2009 at 7:49 AM, Johann Cohen-Tanugi
> <cohen@lpta.in2p3.fr <mailto:cohen@lpta.in2p3.fr>> wrote:
>
>     I thinkk he means that f0 and fb are two known function of x, and
>     he is
>     interested in the weight parameter a.
>     You can try :
>     from scipy import optimize
>     def func(x,a): return a * fb(x) + (1-a) fo(x)
>     fitp,cov=optimize.curve_fit(func,x,p)
>
>     that is one of many options....
>     Johann
>
>
>
>     Chris Colbert wrote:
>     > maybe i don't understand what you are asking, but if (a) is your
>     only
>     > unknown, just do:
>     >
>     > a = (f - f0) / (fb - f0)
>     >
>     >
>     >
>     > On Thu, Jul 30, 2009 at 1:32 AM, Bala
>     > subramanian<bala.biophysics@gmail.com
>     <mailto:bala.biophysics@gmail.com>> wrote:
>     >
>     >> Friends,
>     >>
>     >> I am new and just joined the scipy community. I want to fit
>     (least sq. fit)
>     >> my data to the following equation. I would greatly appreciate
>     if someone
>     >> could help me with a sample code on how fitting is done with scipy.
>     >>
>     >> The function is : f = a * fb + (1-a) fo, where f, fb, fo are known.
>     >>
>     >> Regards,
>     >> Bala
>     >>
>     >>
>     >>
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```