[SciPy-user] optimization question
Volker Lorrmann
lorrmann@physik.uni-wuerzburg...
Tue Jul 3 17:18:23 CDT 2007
Hello list,
i wanna fit a function to some measured datapoints T_m(x_i). The
function i wanna fit is something like that,T_fit(a,b,c,d,x_i), where
a,b,c are the fitting-parameters. Fitting this with
scipy.optimize.leastsq would be easy (btw. is there anoterh way to fit
this, like fmin, fmin_powell, ...?).
The problem is, that a is a and b are _fixed_ scalar parameters. But c
and d are variables, that depend on x_i, c=c(x_i) and d=d(x_i). And in
fact, c(x_i) and d(x_i) are the variables i´m mainly interested in. (a
and b are nearly exactly known, so i can reduce the fitting_function to
T(c(x_i),d(x_i),x_i)).
I hope you can see what my problem is, its late here and i´m tired, so
maybe i haven´t explained very well.
Maybe the following will help
---
\ 2
minimize | {T_meas(x_i) - T(a,b,c(x_i),d(x_i),x_i)}
/
---
i
is what i´m lookig for. Is this possible with scipy.optimize.leastsq, or
should i use some other routine therefor? And if so, which on?
Thanks so far
Volker
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