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fitLinear2.C File Reference

## Detailed Description

Fit a 5d hyperplane by n points, using the linear fitter directly

This macro shows some features of the TLinearFitter class A 5-d hyperplane is fit, a constant term is assumed in the hyperplane equation (y = a0 + a1*x0 + a2*x1 + a3*x2 + a4*x3 + a5*x4)

par[0]=0.000069+-0.001011
par[1]=3.999934+-0.000164
par[2]=0.999835+-0.000172
par[3]=1.999892+-0.000178
par[4]=2.999967+-0.000185
par[5]=0.199823+-0.000174
chisquare=70.148012
More Points:
par[0]=0.000551+-0.000712
par[1]=3.999910+-0.000121
par[2]=0.999886+-0.000125
par[3]=2.000067+-0.000123
par[4]=2.999915+-0.000127
par[5]=0.199918+-0.000130
chisquare=145.050322490891915
Without Constant
par[0]=3.999913+-0.000121
par[1]=0.999890+-0.000125
par[2]=2.000057+-0.000123
par[3]=2.999919+-0.000127
par[4]=0.199918+-0.000130
chisquare=145.649621
Fixed Constant:
par[0]=0.000536+-0.000712
par[1]=4.000000+-1.000000
par[2]=0.999884+-0.000125
par[3]=2.000070+-0.000123
par[4]=2.999910+-0.000127
par[5]=0.199920+-0.000130
chisquare=145.602523231222818
#include "TLinearFitter.h"
#include "TF1.h"
#include "TRandom.h"
void fitLinear2()
{
int n=100;
int i;
TRandom randNum;
//The predefined "hypN" functions are the fastest to fit
lf->SetFormula("hyp5");
double *x=new double[n*10*5];
double *y=new double[n*10];
double *e=new double[n*10];
//Create the points and put them into the fitter
for (i=0; i<n; i++){
x[0 + i*5] = randNum.Uniform(-10, 10);
x[1 + i*5] = randNum.Uniform(-10, 10);
x[2 + i*5] = randNum.Uniform(-10, 10);
x[3 + i*5] = randNum.Uniform(-10, 10);
x[4 + i*5] = randNum.Uniform(-10, 10);
e[i] = 0.01;
y[i] = 4*x[0+i*5] + x[1+i*5] + 2*x[2+i*5] + 3*x[3+i*5] + 0.2*x[4+i*5] + randNum.Gaus()*e[i];
}
//To avoid copying the data into the fitter, the following function can be used:
lf->AssignData(n, 5, x, y, e);
//A different way to put the points into the fitter would be to use
//the AddPoint function for each point. This way the points are copied and stored
//inside the fitter
//Perform the fitting and look at the results
lf->Eval();
TVectorD params;
TVectorD errors;
lf->GetParameters(params);
lf->GetErrors(errors);
for (int i=0; i<6; i++)
printf("par[%d]=%f+-%f\n", i, params(i), errors(i));
double chisquare=lf->GetChisquare();
printf("chisquare=%f\n", chisquare);
//Now suppose you want to add some more points and see if the parameters will change
for (i=n; i<n*2; i++) {
x[0+i*5] = randNum.Uniform(-10, 10);
x[1+i*5] = randNum.Uniform(-10, 10);
x[2+i*5] = randNum.Uniform(-10, 10);
x[3+i*5] = randNum.Uniform(-10, 10);
x[4+i*5] = randNum.Uniform(-10, 10);
e[i] = 0.01;
y[i] = 4*x[0+i*5] + x[1+i*5] + 2*x[2+i*5] + 3*x[3+i*5] + 0.2*x[4+i*5] + randNum.Gaus()*e[i];
}
//Assign the data the same way as before
lf->AssignData(n*2, 5, x, y, e);
lf->Eval();
lf->GetParameters(params);
lf->GetErrors(errors);
printf("\nMore Points:\n");
for (int i=0; i<6; i++)
printf("par[%d]=%f+-%f\n", i, params(i), errors(i));
chisquare=lf->GetChisquare();
printf("chisquare=%.15f\n", chisquare);
//Suppose, you are not satisfied with the result and want to try a different formula
//Without a constant:
//Since the AssignData() function was used, you don't have to add all points to the fitter again
lf->SetFormula("x0++x1++x2++x3++x4");
lf->Eval();
lf->GetParameters(params);
lf->GetErrors(errors);
printf("\nWithout Constant\n");
for (int i=0; i<5; i++)
printf("par[%d]=%f+-%f\n", i, params(i), errors(i));
chisquare=lf->GetChisquare();
printf("chisquare=%f\n", chisquare);
//Now suppose that you want to fix the value of one of the parameters
//Let's fix the first parameter at 4:
lf->SetFormula("hyp5");
lf->FixParameter(1, 4);
lf->Eval();
lf->GetParameters(params);
lf->GetErrors(errors);
printf("\nFixed Constant:\n");
for (i=0; i<6; i++)
printf("par[%d]=%f+-%f\n", i, params(i), errors(i));
chisquare=lf->GetChisquare();
printf("chisquare=%.15f\n", chisquare);
//The fixed parameters can then be released by the ReleaseParameter method
delete lf;
}
#define e(i)
Definition RSha256.hxx:103
The Linear Fitter - For fitting functions that are LINEAR IN PARAMETERS.
virtual Double_t GetChisquare()
Get the Chisquare.
virtual void GetErrors(TVectorD &vpar)
Returns parameter errors.
virtual Int_t Eval()
Perform the fit and evaluate the parameters Returns 0 if the fit is ok, 1 if there are errors.
virtual void AssignData(Int_t npoints, Int_t xncols, Double_t *x, Double_t *y, Double_t *e=nullptr)
This function is to use when you already have all the data in arrays and don't want to copy them into...
virtual void GetParameters(TVectorD &vpar)
Returns parameter values.
void FixParameter(Int_t ipar) override
Fixes paramter #ipar at its current value.
virtual void SetFormula(const char *formula)
Additive parts should be separated by "++".
This is the base class for the ROOT Random number generators.
Definition TRandom.h:27
virtual Double_t Gaus(Double_t mean=0, Double_t sigma=1)
Samples a random number from the standard Normal (Gaussian) Distribution with the given mean and sigm...
Definition TRandom.cxx:274
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition TRandom.cxx:672
Double_t y[n]
Definition legend1.C:17
Double_t x[n]
Definition legend1.C:17
const Int_t n
Definition legend1.C:16

Definition in file fitLinear2.C.