class evaluating the log likelihood for binned Poisson likelihood fits it is template to distinguish gradient and non-gradient case
Definition at line 46 of file PoissonLikelihoodFCN.h.
Public Types | |
typedef BasicFCN< DerivFunType, ModelFunType, BinData > | BaseFCN |
typedef BaseObjFunction::BaseFunction | BaseFunction |
typedef ::ROOT::Math::BasicFitMethodFunction< DerivFunType > | BaseObjFunction |
typedef ::ROOT::Math::IParamMultiFunctionTempl< T > | IModelFunction |
typedef ModelFunType::BackendType | T |
typedef BaseObjFunction::Type_t | Type_t |
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typedef FunctionType::BaseFunc | BaseFunction |
enum | Type_t |
enumeration specifying the possible fit method types More... | |
Public Member Functions | |
PoissonLikelihoodFCN (const BinData &data, const IModelFunction &func, int weight=0, bool extended=true, const ::ROOT::EExecutionPolicy &executionPolicy=::ROOT::EExecutionPolicy::kSequential) | |
Constructor from unbin data set and model function (pdf) managed by the users. | |
PoissonLikelihoodFCN (const PoissonLikelihoodFCN &f) | |
Copy constructor. | |
PoissonLikelihoodFCN (const std::shared_ptr< BinData > &data, const std::shared_ptr< IModelFunction > &func, int weight=0, bool extended=true, const ::ROOT::EExecutionPolicy &executionPolicy=::ROOT::EExecutionPolicy::kSequential) | |
Constructor from unbin data set and model function (pdf) | |
virtual | ~PoissonLikelihoodFCN () |
Destructor (no operations) | |
virtual BaseFunction * | Clone () const |
clone the function (need to return Base for Windows) | |
virtual double | DataElement (const double *x, unsigned int i, double *g, double *h, bool fullHessian) const |
i-th likelihood element and its gradient | |
virtual void | Gradient (const double *x, double *g) const |
evaluate gradient | |
bool | IsWeighted () const |
virtual unsigned int | NFitPoints () const |
PoissonLikelihoodFCN & | operator= (const PoissonLikelihoodFCN &rhs) |
Assignment operator. | |
virtual BaseObjFunction::Type_t | Type () const |
Computes the full Hessian. | |
void | UseSumOfWeights () |
void | UseSumOfWeightSquare (bool on=true) |
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virtual const DataType & | Data () const |
access to const reference to the data | |
std::shared_ptr< DataType > | DataPtr () const |
access to data pointer | |
virtual bool | HasHessian () const |
flag to indicate if can compute Hessian | |
virtual const IModelFunction & | ModelFunction () const |
access to const reference to the model function | |
std::shared_ptr< IModelFunction > | ModelFunctionPtr () const |
access to function pointer | |
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BasicFitMethodFunction (int dim, int npoint) | |
~BasicFitMethodFunction () override | |
Virtual Destructor (no operations) | |
virtual bool | G2 (const double *, double *) const |
Computes the Second derivatives. | |
virtual bool | Hessian (const double *x, double *hess) const |
Computes the full Hessian. | |
bool | IsAGradFCN () |
virtual unsigned int | NCalls () const |
return the total number of function calls (override if needed) | |
unsigned int | NDim () const override |
Number of dimension (parameters) . | |
virtual unsigned int | NPoints () const |
return the number of data points used in evaluating the function | |
virtual void | ResetNCalls () |
reset number of function calls | |
virtual void | UpdateNCalls () const |
update number of calls | |
Private Member Functions | |
virtual double | DoDerivative (const double *x, unsigned int icoord) const |
virtual double | DoEval (const double *x) const |
Evaluation of the function (required by interface) | |
Private Attributes | |
::ROOT::EExecutionPolicy | fExecutionPolicy |
Execution policy. | |
std::vector< double > | fGrad |
for derivatives | |
bool | fIsExtended |
flag to indicate if is extended (when false is a Multinomial likelihood), default is true | |
unsigned int | fNEffPoints |
number of effective points used in the fit | |
int | fWeight |
flag to indicate if needs to evaluate using weight or weight squared (default weight = 0) | |
Additional Inherited Members | |
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static bool | IsAGradFCN () |
Static function to indicate if a function is supporting gradient. | |
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typedef BaseObjFunction::BaseFunction | BaseFunction |
typedef ::ROOT::Math::BasicFitMethodFunction< DerivFunType > | BaseObjFunction |
typedef ::ROOT::Math::IParametricGradFunctionMultiDimTempl< T > | IGradModelFunction |
typedef ::ROOT::Math::IParamMultiFunctionTempl< T > | IModelFunction |
typedef ModelFunType::BackendType | T |
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BasicFCN (const std::shared_ptr< DataType > &data, const std::shared_ptr< IModelFunction > &func) | |
Constructor from data set and model function. | |
virtual | ~BasicFCN () |
Destructor (no operations) | |
void | SetData (const std::shared_ptr< DataType > &data) |
Set the data pointer. | |
void | SetModelFunction (const std::shared_ptr< IModelFunction > &func) |
Set the function pointer. | |
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std::shared_ptr< DataType > | fData |
std::shared_ptr< IModelFunction > | fFunc |
#include <Fit/PoissonLikelihoodFCN.h>
typedef BasicFCN<DerivFunType,ModelFunType,BinData> ROOT::Fit::PoissonLikelihoodFCN< DerivFunType, ModelFunType >::BaseFCN |
Definition at line 50 of file PoissonLikelihoodFCN.h.
typedef BaseObjFunction::BaseFunction ROOT::Fit::PoissonLikelihoodFCN< DerivFunType, ModelFunType >::BaseFunction |
Definition at line 53 of file PoissonLikelihoodFCN.h.
typedef ::ROOT::Math::BasicFitMethodFunction<DerivFunType> ROOT::Fit::PoissonLikelihoodFCN< DerivFunType, ModelFunType >::BaseObjFunction |
Definition at line 52 of file PoissonLikelihoodFCN.h.
typedef ::ROOT::Math::IParamMultiFunctionTempl<T> ROOT::Fit::PoissonLikelihoodFCN< DerivFunType, ModelFunType >::IModelFunction |
Definition at line 55 of file PoissonLikelihoodFCN.h.
typedef ModelFunType::BackendType ROOT::Fit::PoissonLikelihoodFCN< DerivFunType, ModelFunType >::T |
Definition at line 49 of file PoissonLikelihoodFCN.h.
typedef BaseObjFunction::Type_t ROOT::Fit::PoissonLikelihoodFCN< DerivFunType, ModelFunType >::Type_t |
Definition at line 56 of file PoissonLikelihoodFCN.h.
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inline |
Constructor from unbin data set and model function (pdf)
Definition at line 61 of file PoissonLikelihoodFCN.h.
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inline |
Constructor from unbin data set and model function (pdf) managed by the users.
Definition at line 73 of file PoissonLikelihoodFCN.h.
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inlinevirtual |
Destructor (no operations)
Definition at line 86 of file PoissonLikelihoodFCN.h.
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inline |
Copy constructor.
Definition at line 91 of file PoissonLikelihoodFCN.h.
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inlinevirtual |
clone the function (need to return Base for Windows)
Definition at line 115 of file PoissonLikelihoodFCN.h.
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inlinevirtual |
i-th likelihood element and its gradient
Implements ROOT::Math::BasicFitMethodFunction< DerivFunType >.
Definition at line 121 of file PoissonLikelihoodFCN.h.
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inlineprivatevirtual |
Definition at line 195 of file PoissonLikelihoodFCN.h.
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inlineprivatevirtual |
Evaluation of the function (required by interface)
Definition at line 188 of file PoissonLikelihoodFCN.h.
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inlinevirtual |
evaluate gradient
Definition at line 127 of file PoissonLikelihoodFCN.h.
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inline |
Definition at line 163 of file PoissonLikelihoodFCN.h.
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inlinevirtual |
Definition at line 118 of file PoissonLikelihoodFCN.h.
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inline |
Assignment operator.
Definition at line 103 of file PoissonLikelihoodFCN.h.
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inlinevirtual |
Computes the full Hessian.
Return false if Hessian is not supported get type of fit method function
Reimplemented from ROOT::Math::BasicFitMethodFunction< DerivFunType >.
Definition at line 161 of file PoissonLikelihoodFCN.h.
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inline |
Definition at line 166 of file PoissonLikelihoodFCN.h.
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inline |
Definition at line 173 of file PoissonLikelihoodFCN.h.
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private |
Execution policy.
Definition at line 210 of file PoissonLikelihoodFCN.h.
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mutableprivate |
for derivatives
Definition at line 208 of file PoissonLikelihoodFCN.h.
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private |
flag to indicate if is extended (when false is a Multinomial likelihood), default is true
Definition at line 203 of file PoissonLikelihoodFCN.h.
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mutableprivate |
number of effective points used in the fit
Definition at line 206 of file PoissonLikelihoodFCN.h.
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private |
flag to indicate if needs to evaluate using weight or weight squared (default weight = 0)
Definition at line 204 of file PoissonLikelihoodFCN.h.