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PoissonLikelihoodFCN.h
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1// @(#)root/mathcore:$Id$
2// Author: L. Moneta Fri Aug 17 14:29:24 2007
3
4/**********************************************************************
5 * *
6 * Copyright (c) 2007 LCG ROOT Math Team, CERN/PH-SFT *
7 * *
8 * *
9 **********************************************************************/
10
11// Header file for class PoissonLikelihoodFCN
12
13#ifndef ROOT_Fit_PoissonLikelihoodFCN
14#define ROOT_Fit_PoissonLikelihoodFCN
15
16#include "Fit/BasicFCN.h"
17
18#include "Math/IParamFunction.h"
19
20#include "Fit/BinData.h"
21
22#include "Fit/FitUtil.h"
23
24
25#include <memory>
26
27//#define PARALLEL
28// #ifdef PARALLEL
29// #ifndef ROOT_Fit_FitUtilParallel
30// #include "Fit/FitUtilParallel.h"
31// #endif
32// #endif
33
34namespace ROOT {
35
36 namespace Fit {
37
38
39//___________________________________________________________________________________
40/**
41 class evaluating the log likelihood
42 for binned Poisson likelihood fits
43 it is template to distinguish gradient and non-gradient case
44
45 @ingroup FitMethodFunc
46*/
47template<class DerivFunType, class ModelFunType = ROOT::Math::IParamMultiFunction>
48class PoissonLikelihoodFCN : public BasicFCN<DerivFunType,ModelFunType,BinData> {
49
50public:
51 typedef typename ModelFunType::BackendType T;
53
54 typedef ::ROOT::Math::BasicFitMethodFunction<DerivFunType> BaseObjFunction;
56
57 typedef ::ROOT::Math::IParamMultiFunctionTempl<T> IModelFunction;
59
60 /**
61 Constructor from unbin data set and model function (pdf)
62 */
63 PoissonLikelihoodFCN (const std::shared_ptr<BinData> & data, const std::shared_ptr<IModelFunction> & func, int weight = 0, bool extended = true, const ::ROOT::Fit::ExecutionPolicy &executionPolicy = ::ROOT::Fit::ExecutionPolicy::kSerial ) :
64 BaseFCN( data, func),
65 fIsExtended(extended),
66 fWeight(weight),
67 fNEffPoints(0),
68 fGrad ( std::vector<double> ( func->NPar() ) ),
69 fExecutionPolicy(executionPolicy)
70 { }
71
72 /**
73 Constructor from unbin data set and model function (pdf) managed by the users
74 */
75 PoissonLikelihoodFCN (const BinData & data, const IModelFunction & func, int weight = 0, bool extended = true, const ::ROOT::Fit::ExecutionPolicy &executionPolicy = ::ROOT::Fit::ExecutionPolicy::kSerial ) :
76 BaseFCN(std::shared_ptr<BinData>(const_cast<BinData*>(&data), DummyDeleter<BinData>()), std::shared_ptr<IModelFunction>(dynamic_cast<IModelFunction*>(func.Clone() ) ) ),
77 fIsExtended(extended),
78 fWeight(weight),
79 fNEffPoints(0),
80 fGrad ( std::vector<double> ( func.NPar() ) ),
81 fExecutionPolicy(executionPolicy)
82 { }
83
84
85 /**
86 Destructor (no operations)
87 */
89
90 /**
91 Copy constructor
92 */
96 fWeight( f.fWeight ),
98 fGrad( f.fGrad),
100 { }
101
102 /**
103 Assignment operator
104 */
106 SetData(rhs.DataPtr() );
109 fGrad = rhs.fGrad;
111 fWeight = rhs.fWeight;
113 }
114
115
116 /// clone the function (need to return Base for Windows)
117 virtual BaseFunction * Clone() const { return new PoissonLikelihoodFCN(*this); }
118
119 // effective points used in the fit
120 virtual unsigned int NFitPoints() const { return fNEffPoints; }
121
122 /// i-th likelihood element and its gradient
123 virtual double DataElement(const double * x, unsigned int i, double * g) const {
124 if (i==0) this->UpdateNCalls();
126 }
127
128 /// evaluate gradient
129 virtual void Gradient(const double *x, double *g) const
130 {
131 // evaluate the Poisson gradient
134 }
135
136 /// get type of fit method function
138
139 bool IsWeighted() const { return (fWeight != 0); }
140
141 // Use the weights in evaluating the likelihood
143 if (fWeight == 0) return; // do nothing if it was not weighted
144 fWeight = 1;
145 }
146
147 // Use sum of the weight squared in evaluating the likelihood
148 // (this is needed for calculating the errors)
149 void UseSumOfWeightSquare(bool on = true) {
150 if (fWeight == 0) return; // do nothing if it was not weighted
151 if (on) fWeight = 2;
152 else fWeight = 1;
153 }
154
155
156protected:
157
158
159private:
160
161 /**
162 Evaluation of the function (required by interface)
163 */
164 virtual double DoEval (const double * x) const {
165 this->UpdateNCalls();
168 }
169
170 // for derivatives
171 virtual double DoDerivative(const double * x, unsigned int icoord ) const {
172 Gradient(x, &fGrad[0]);
173 return fGrad[icoord];
174 }
175
176
177 //data member
178
179 bool fIsExtended; // flag to indicate if is extended (when false is a Multinomial lieklihood), default is true
180 int fWeight; // flag to indicate if needs to evaluate using weight or weight squared (default weight = 0)
181
182 mutable unsigned int fNEffPoints; // number of effective points used in the fit
183
184 mutable std::vector<double> fGrad; // for derivatives
185
187};
188
189 // define useful typedef's
192
193
194 } // end namespace Fit
195
196} // end namespace ROOT
197
198
199#endif /* ROOT_Fit_PoissonLikelihoodFCN */
#define f(i)
Definition: RSha256.hxx:104
#define g(i)
Definition: RSha256.hxx:105
BasicFCN class: base class for the objective functions used in the fits It has a reference to the dat...
Definition: BasicFCN.h:40
void SetData(const std::shared_ptr< BinData > &data)
Set the data pointer.
Definition: BasicFCN.h:88
std::shared_ptr< IModelFunction > ModelFunctionPtr() const
access to function pointer
Definition: BasicFCN.h:80
void SetModelFunction(const std::shared_ptr< IModelFunction > &func)
Set the function pointer.
Definition: BasicFCN.h:91
virtual const DataType & Data() const
access to const reference to the data
Definition: BasicFCN.h:71
std::shared_ptr< BinData > DataPtr() const
access to data pointer
Definition: BasicFCN.h:74
virtual const IModelFunction & ModelFunction() const
access to const reference to the model function
Definition: BasicFCN.h:77
Class describing the binned data sets : vectors of x coordinates, y values and optionally error on y ...
Definition: BinData.h:53
class evaluating the log likelihood for binned Poisson likelihood fits it is template to distinguish ...
virtual unsigned int NFitPoints() const
PoissonLikelihoodFCN(const BinData &data, const IModelFunction &func, int weight=0, bool extended=true, const ::ROOT::Fit::ExecutionPolicy &executionPolicy=::ROOT::Fit::ExecutionPolicy::kSerial)
Constructor from unbin data set and model function (pdf) managed by the users.
::ROOT::Math::IParamMultiFunctionTempl< T > IModelFunction
virtual double DoDerivative(const double *x, unsigned int icoord) const
virtual double DataElement(const double *x, unsigned int i, double *g) const
i-th likelihood element and its gradient
::ROOT::Math::BasicFitMethodFunction< DerivFunType > BaseObjFunction
PoissonLikelihoodFCN(const PoissonLikelihoodFCN &f)
Copy constructor.
virtual BaseFunction * Clone() const
clone the function (need to return Base for Windows)
virtual ~PoissonLikelihoodFCN()
Destructor (no operations)
virtual double DoEval(const double *x) const
Evaluation of the function (required by interface)
PoissonLikelihoodFCN(const std::shared_ptr< BinData > &data, const std::shared_ptr< IModelFunction > &func, int weight=0, bool extended=true, const ::ROOT::Fit::ExecutionPolicy &executionPolicy=::ROOT::Fit::ExecutionPolicy::kSerial)
Constructor from unbin data set and model function (pdf)
BaseObjFunction::BaseFunction BaseFunction
virtual void Gradient(const double *x, double *g) const
evaluate gradient
::ROOT::Fit::ExecutionPolicy fExecutionPolicy
PoissonLikelihoodFCN & operator=(const PoissonLikelihoodFCN &rhs)
Assignment operator.
BasicFCN< DerivFunType, ModelFunType, BinData > BaseFCN
virtual BaseObjFunction::Type_t Type() const
get type of fit method function
Type_t
enumeration specyfing the possible fit method types
virtual void UpdateNCalls() const
update number of calls
IParamFunction interface (abstract class) describing multi-dimensional parameteric functions It is a ...
Double_t x[n]
Definition: legend1.C:17
TFitResultPtr Fit(FitObject *h1, TF1 *f1, Foption_t &option, const ROOT::Math::MinimizerOptions &moption, const char *goption, ROOT::Fit::DataRange &range)
Definition: HFitImpl.cxx:134
PoissonLikelihoodFCN< ROOT::Math::IMultiGradFunction, ROOT::Math::IParamMultiFunction > PoissonLLGradFunction
PoissonLikelihoodFCN< ROOT::Math::IMultiGenFunction, ROOT::Math::IParamMultiFunction > PoissonLLFunction
Namespace for new ROOT classes and functions.
Definition: StringConv.hxx:21
static double EvalPoissonBinPdf(const IModelFunctionTempl< double > &func, const BinData &data, const double *p, unsigned int i, double *g)
evaluate the pdf (Poisson) contribution to the logl (return actually log of pdf) and its gradient
Definition: FitUtil.h:1437
static double EvalPoissonLogL(const IModelFunctionTempl< double > &func, const BinData &data, const double *p, int iWeight, bool extended, unsigned int &nPoints, ::ROOT::Fit::ExecutionPolicy executionPolicy, unsigned nChunks=0)
Definition: FitUtil.h:1412
static void EvalPoissonLogLGradient(const IModelFunctionTempl< double > &func, const BinData &data, const double *p, double *g, unsigned int &nPoints, ::ROOT::Fit::ExecutionPolicy executionPolicy=::ROOT::Fit::ExecutionPolicy::kSerial, unsigned nChunks=0)
Definition: FitUtil.h:1442