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Reference Guide
MCFitter.h
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1// @(#)root/tmva $Id$
2// Author: Andreas Hoecker, Peter Speckmayer, Joerg Stelzer, Helge Voss
3
4/**********************************************************************************
5 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
6 * Package: TMVA *
7 * Class : MCFitter *
8 * Web : http://tmva.sourceforge.net *
9 * *
10 * Description: *
11 * Fitter using Monte Carlo sampling of parameters *
12 * *
13 * Authors (alphabetical): *
14 * Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
15 * Peter Speckmayer <speckmay@mail.cern.ch> - CERN, Switzerland *
16 * Joerg Stelzer <Joerg.Stelzer@cern.ch> - CERN, Switzerland *
17 * Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany *
18 * *
19 * Copyright (c) 2005: *
20 * CERN, Switzerland *
21 * MPI-K Heidelberg, Germany *
22 * *
23 * Redistribution and use in source and binary forms, with or without *
24 * modification, are permitted according to the terms listed in LICENSE *
25 * (http://tmva.sourceforge.net/LICENSE) *
26 **********************************************************************************/
27
28#ifndef ROOT_TMVA_MCFitter
29#define ROOT_TMVA_MCFitter
30
31//////////////////////////////////////////////////////////////////////////
32// //
33// MCFitter //
34// //
35// Fitter using Monte Carlo sampling of parameters //
36// //
37//////////////////////////////////////////////////////////////////////////
38
39#include "TMVA/FitterBase.h"
40
41namespace TMVA {
42
43 class MCFitter : public FitterBase {
44
45 public:
46
47 MCFitter( IFitterTarget& target, const TString& name,
48 const std::vector<TMVA::Interval*>& ranges, const TString& theOption );
49
50 virtual ~MCFitter() {}
51
52 void SetParameters( Int_t cycles );
53
54 Double_t Run( std::vector<Double_t>& pars );
55
56 private:
57
58 void DeclareOptions();
59
60 Int_t fSamples; // number of MC samples
61 Double_t fSigma; // new samples are generated randomly with a gaussian probability with fSigma around the current best value
62 UInt_t fSeed; // Seed for the random generator (0 takes random seeds)
63
64 ClassDef(MCFitter,0); // Fitter using Monte Carlo sampling of parameters
65 };
66
67} // namespace TMVA
68
69#endif
70
71
int Int_t
Definition: RtypesCore.h:41
unsigned int UInt_t
Definition: RtypesCore.h:42
double Double_t
Definition: RtypesCore.h:55
#define ClassDef(name, id)
Definition: Rtypes.h:324
Base class for TMVA fitters.
Definition: FitterBase.h:51
Double_t Run()
estimator function interface for fitting
Definition: FitterBase.cxx:74
Interface for a fitter 'target'.
Definition: IFitterTarget.h:44
Fitter using Monte Carlo sampling of parameters.
Definition: MCFitter.h:43
UInt_t fSeed
Definition: MCFitter.h:62
void SetParameters(Int_t cycles)
set MC fitter configuration parameters
Definition: MCFitter.cxx:78
virtual ~MCFitter()
Definition: MCFitter.h:50
Double_t fSigma
Definition: MCFitter.h:61
MCFitter(IFitterTarget &target, const TString &name, const std::vector< TMVA::Interval * > &ranges, const TString &theOption)
constructor
Definition: MCFitter.cxx:51
void DeclareOptions()
Declare MCFitter options.
Definition: MCFitter.cxx:67
Int_t fSamples
Definition: MCFitter.h:60
Basic string class.
Definition: TString.h:131
Abstract ClassifierFactory template that handles arbitrary types.