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Reference Guide
exampleFit3D.C
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1/// \file
2/// \ingroup tutorial_fit
3/// \notebook -nodraw
4/// example of fitting a 3D function
5/// Typical multidimensional parametric regression where the predictor
6/// depends on 3 variables
7///
8/// In the case of 1 or 2D one can use the TGraph classes
9/// but since no TGraph3D class exists this tutorial provide
10/// an example of fitting 3D points
11///
12/// \macro_output
13/// \macro_code
14///
15/// \author Lorenzo Moneta
16
17
18#include "TRandom2.h"
19#include "TF3.h"
20#include "TError.h"
21#include "Fit/BinData.h"
22#include "Fit/Fitter.h"
24
25void exampleFit3D() {
26
27 const int n = 1000;
28 double x[n], y[n], z[n], v[n];
29 double ev = 0.1;
30
31 // generate the data
32 TRandom2 r;
33 for (int i = 0; i < n; ++i) {
34 x[i] = r.Uniform(0,10);
35 y[i] = r.Uniform(0,10);
36 z[i] = r.Uniform(0,10);
37 v[i] = sin(x[i] ) + cos(y[i]) + z[i] + r.Gaus(0,ev);
38 }
39
40 // create a 3d binned data structure
41 ROOT::Fit::BinData data(n,3);
42 double xx[3];
43 for(int i = 0; i < n; ++i) {
44 xx[0] = x[i];
45 xx[1] = y[i];
46 xx[2] = z[i];
47 // add the 3d-data coordinate, the predictor value (v[i]) and its errors
48 data.Add(xx, v[i], ev);
49 }
50
51 TF3 * f3 = new TF3("f3","[0] * sin(x) + [1] * cos(y) + [2] * z",0,10,0,10,0,10);
52 f3->SetParameters(2,2,2);
53 ROOT::Fit::Fitter fitter;
54 // wrapped the TF1 in a IParamMultiFunction interface for the Fitter class
56 fitter.SetFunction(wf);
57 //
58 bool ret = fitter.Fit(data);
59 if (ret) {
60 const ROOT::Fit::FitResult & res = fitter.Result();
61 // print result (should be around 1)
62 res.Print(std::cout);
63 // copy all fit result info (values, chi2, etc..) in TF3
64 f3->SetFitResult(res);
65 // test fit p-value (chi2 probability)
66 double prob = res.Prob();
67 if (prob < 1.E-2)
68 Error("exampleFit3D","Bad data fit - fit p-value is %f",prob);
69 else
70 std::cout << "Good fit : p-value = " << prob << std::endl;
71
72 }
73 else
74 Error("exampleFit3D","3D fit failed");
75}
ROOT::R::TRInterface & r
Definition: Object.C:4
void Error(const char *location, const char *msgfmt,...)
Use this function in case an error occurred.
Definition: TError.cxx:187
double cos(double)
double sin(double)
Class describing the binned data sets : vectors of x coordinates, y values and optionally error on y ...
Definition: BinData.h:52
class containg the result of the fit and all the related information (fitted parameter values,...
Definition: FitResult.h:47
void Print(std::ostream &os, bool covmat=false) const
print the result and optionaly covariance matrix and correlations
Definition: FitResult.cxx:428
double Prob() const
p value of the fit (chi2 probability)
Definition: FitResult.cxx:359
Fitter class, entry point for performing all type of fits.
Definition: Fitter.h:77
const FitResult & Result() const
get fit result
Definition: Fitter.h:384
bool Fit(const Data &data, const Function &func, const ROOT::EExecutionPolicy &executionPolicy=ROOT::EExecutionPolicy::kSequential)
fit a data set using any generic model function If data set is binned a least square fit is performed...
Definition: Fitter.h:141
void SetFunction(const IModelFunction &func, bool useGradient=false)
Set the fitted function (model function) from a parametric function interface.
Definition: Fitter.cxx:103
Class to Wrap a ROOT Function class (like TF1) in a IParamMultiFunction interface of multi-dimensions...
virtual void SetFitResult(const ROOT::Fit::FitResult &result, const Int_t *indpar=0)
Set the result from the fit parameter values, errors, chi2, etc... Optionally a pointer to a vector (...
Definition: TF1.cxx:3368
virtual void SetParameters(const Double_t *params)
Definition: TF1.h:644
A 3-Dim function with parameters.
Definition: TF3.h:28
Random number generator class based on the maximally quidistributed combined Tausworthe generator by ...
Definition: TRandom2.h:27
Double_t y[n]
Definition: legend1.C:17
Double_t x[n]
Definition: legend1.C:17
const Int_t n
Definition: legend1.C:16