User Tools

Site Tools


Elementary fitting

Top: Frida handbook
Up: Tutorial
Previous: Simple manipulations
Next: Fitting with convolution

In this tutorial session, we learn how to fit parametrized curves to given data, and how to extract the fitted parameters.

Basic example

Let us fit the instrumental resolution gly180 by a Gaussian:

command action
? > fl gly180 load data file
0 > mr! abs(x)<2 restrict frequency range (the modified '!' means: operate “in place”, overwrite the input file)
0 > p 7 plot spectrum 7
0 > cc p0*exp(-(t-p1)^2/2/p2^2) create the fit curve (will be file 1)
1 > a 7 add to plot, with default initial values p0=p1=..=1
1 > cf fit (by default, the curve refers to data file 0)
1 > 0,1 p 7 replot data and fit
0,1 > 1 cp inform about curve, print parameters
1 > oi p2 create file containing p2 vs z0
2 > g4 new lin-lin plot window
2 > p plot p2 vs z0

Instead of the explicit formula p0*exp(-(t-p1)^2/2/p2^2), one could use the shorthand p0*gnn(t-p1,p2), where gnn stands for “gauss, not normalized”. The expression gauss(t,p2) is equivalent to the normal form 1/sqrt(2*pi)/p2*exp(-t^2/2/p2^2).

Fixing and setting parameters

Assume file 1 is a curve.

command action
1 > cx 2 fix parameter p2 to the current value
1 > op2 1.234 set parameter p2 to 1.234
1 > op2 pi/z0 arbitrary expressions may be used
1 > cf now fit, with p2 kept fixed at the previously set value
1 > cu 2 unfix p2

Last updated for Frida2.3.0c.