Abstract observation base class implementation. More...

#include "GTools.hpp"
#include "GException.hpp"
#include "GIntegral.hpp"
#include "GDerivative.hpp"
#include "GVector.hpp"
#include "GVectorSparse.hpp"
#include "GMatrixSparse.hpp"
#include "GObservation.hpp"
#include "GResponse.hpp"
#include "GEventCube.hpp"
#include "GEventList.hpp"
#include "GEventBin.hpp"
#include "GModel.hpp"
#include "GModels.hpp"
#include "GModelPar.hpp"
#include "GModelSky.hpp"
#include "GModelData.hpp"

Macros
#define	G_LIKELIHOOD

#define	G_MODEL1 "GObservation::model(GModels&, GEvent&, GVector*)"

#define	G_MODEL2 "GObservation::model(GModels&, GMatrixSparse*)"

#define	G_EVENTS "GObservation::events()"

#define	G_NPRED "GObservation::npred(GModel&)"

#define	G_NPRED_SPEC "GObservation::npred_spec(GModel&, GTime&)"

#define	G_LN_ENERGY_INT
	ln(E) variable substitution for integration

#define	G_MODEL_COLUMN_FILL
	Use column fill for sparse matrix.

#define	G_MODEL_SPARSE_VECTOR
	Use sparse vector for sparse matrix.

#define	G_LIKELIHOOD_SPARSE_VECTOR
	Use sparse vector for sparse matrix.

Variables
const double	minmod = 1.0e-100
	Minimum model value.

const double	minerr = 1.0e-100
	Minimum statistical error.

Detailed Description

Abstract observation base class implementation.

Author: Juergen Knoedlseder

Definition in file GObservation.cpp.

Macro Definition Documentation

◆ G_EVENTS

#define G_EVENTS "GObservation::events()"

Definition at line 54 of file GObservation.cpp.

Referenced by GObservation::events(), and GObservation::events().

◆ G_LIKELIHOOD

#define G_LIKELIHOOD

Value:

"GObservation::likelihood(GModels&, GVector*,"\

" GMatrixSparse*, double*)"

Definition at line 50 of file GObservation.cpp.

Referenced by GCTAOnOffObservation::likelihood(), and GObservation::likelihood().

◆ G_LIKELIHOOD_SPARSE_VECTOR

#define G_LIKELIHOOD_SPARSE_VECTOR

Use sparse vector for sparse matrix.

Definition at line 68 of file GObservation.cpp.

◆ G_LN_ENERGY_INT

#define G_LN_ENERGY_INT

ln(E) variable substitution for integration

Definition at line 65 of file GObservation.cpp.

◆ G_MODEL1

#define G_MODEL1 "GObservation::model(GModels&, GEvent&, GVector*)"

Definition at line 52 of file GObservation.cpp.

Referenced by GObservation::model().

◆ G_MODEL2

#define G_MODEL2 "GObservation::model(GModels&, GMatrixSparse*)"

Definition at line 53 of file GObservation.cpp.

Referenced by GObservation::model().

◆ G_MODEL_COLUMN_FILL

#define G_MODEL_COLUMN_FILL

Use column fill for sparse matrix.

Definition at line 66 of file GObservation.cpp.

◆ G_MODEL_SPARSE_VECTOR

#define G_MODEL_SPARSE_VECTOR

Use sparse vector for sparse matrix.

Definition at line 67 of file GObservation.cpp.

◆ G_NPRED

#define G_NPRED "GObservation::npred(GModel&)"

Definition at line 55 of file GObservation.cpp.

◆ G_NPRED_SPEC

#define G_NPRED_SPEC "GObservation::npred_spec(GModel&, GTime&)"

Definition at line 56 of file GObservation.cpp.

Variable Documentation

◆ minerr

const double minerr = 1.0e-100

Minimum statistical error.

Definition at line 60 of file GObservation.cpp.

Referenced by GObservation::likelihood_gaussian_binned().

◆ minmod

const double minmod = 1.0e-100

Minimum model value.

Definition at line 59 of file GObservation.cpp.

Referenced by GCTAOnOffObservation::likelihood_cstat(), GObservation::likelihood_gaussian_binned(), GObservation::likelihood_poisson_binned(), and GObservation::likelihood_poisson_unbinned().

Macros

Variables