GPReg< TInput > Class Template Reference

#include <gpRegression.hpp>

List of all members.

Public Member Functions
void	buildGP (bool useTargets=true)
void	buildTargets ()
void	evalGP (const TInput &x, double &mean)
void	evalGP (const TInput &x, double &mean, double &var)
double	getAvgVariance ()
double	getComplexity ()
double	getDataFit ()
double	getDataLikelihood ()
void	getDerivative (std::vector< double > *r)
double	getMarginalDataLikelihood ()
void	getParameters (std::vector< double > *r)
	GPReg (GPReg< TInput > *copyFromGP)
	GPReg (CovFunc< TInput > *covFunc, double *sigmaNoise, GPReg< TInput > *noiseGP=NULL)
	GPReg (CovFunc< TInput > *covFunc, double sigmaNoise, GPReg< TInput > *noiseGP=NULL)
bool	minimizeGSL (unsigned maxIt)
void	setDataPoints (TVector< TInput > &dataPoints, TVector< double > &dataTargets)
void	setParameters (std::vector< double > *r)
void	setSigmaNoise (double sigma)
	~GPReg ()
Static Public Member Functions
static void	gsl_my_df (const gsl_vector *v, void *params, gsl_vector *df)
static double	gsl_my_f (const gsl_vector *v, void *params)
static void	gsl_my_fdf (const gsl_vector *v, void *params, double *f, gsl_vector *df)
Public Attributes
TMatrix< double > *	m_C
GPReg< TInput > *	m_copyFromGP
CovFunc< TInput > *	m_covFunc
TVector< TInput > *	m_dataPoints
TMatrix< double > *	m_iC
TVector< double > *	m_iCt
GPReg< TInput > *	m_noiseGP
int	m_numDataPoints
double	m_ownSigmaNoise
double *	m_sigmaNoise
TVector< double > *	m_t

---

Detailed Description

template<class TInput>
class GPReg< TInput >

Definition at line 18 of file gpRegression.hpp.

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Constructor & Destructor Documentation

template<class TInput>

GPReg< TInput >::GPReg	(	CovFunc< TInput > *	covFunc,
		double	sigmaNoise,
		GPReg< TInput > *	noiseGP = NULL
	)

template<class TInput>

GPReg< TInput >::GPReg	(	CovFunc< TInput > *	covFunc,
		double *	sigmaNoise,
		GPReg< TInput > *	noiseGP = NULL
	)

template<class TInput>

GPReg< TInput >::GPReg

(

GPReg< TInput > *

copyFromGP

)

template<class TInput>

GPReg< TInput >::~GPReg

(

)

---

Member Function Documentation

template<class TInput>

void GPReg< TInput >::buildGP

(

bool

useTargets = true

)

template<class TInput>

void GPReg< TInput >::buildTargets

(

)

template<class TInput>

void GPReg< TInput >::evalGP	(	const TInput &	x,
		double &	mean
	)

template<class TInput>

void GPReg< TInput >::evalGP	(	const TInput &	x,
		double &	mean,
		double &	var
	)

template<class TInput>

double GPReg< TInput >::getAvgVariance

(

)

template<class TInput>

double GPReg< TInput >::getComplexity

(

)

template<class TInput>

double GPReg< TInput >::getDataFit

(

)

template<class TInput>

double GPReg< TInput >::getDataLikelihood

(

)

template<class TInput>

void GPReg< TInput >::getDerivative

(

std::vector< double > *

r

)

template<class TInput>

double GPReg< TInput >::getMarginalDataLikelihood

(

)

template<class TInput>

void GPReg< TInput >::getParameters

(

std::vector< double > *

r

)

template<class TInput>

static void GPReg< TInput >::gsl_my_df	(	const gsl_vector *	v,
		void *	params,
		gsl_vector *	df
	)			[static]

template<class TInput>

static double GPReg< TInput >::gsl_my_f	(	const gsl_vector *	v,
		void *	params
	)			[static]

template<class TInput>

static void GPReg< TInput >::gsl_my_fdf	(	const gsl_vector *	v,
		void *	params,
		double *	f,
		gsl_vector *	df
	)			[static]

template<class TInput>

bool GPReg< TInput >::minimizeGSL

(

unsigned

maxIt

)

template<class TInput>

void GPReg< TInput >::setDataPoints	(	TVector< TInput > &	dataPoints,
		TVector< double > &	dataTargets
	)

template<class TInput>

void GPReg< TInput >::setParameters

(

std::vector< double > *

r

)

template<class TInput>

void GPReg< TInput >::setSigmaNoise

(

double

sigma

)

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Member Data Documentation

template<class TInput>

TMatrix<double>* GPReg< TInput >::m_C

Definition at line 58 of file gpRegression.hpp.

template<class TInput>

GPReg<TInput>* GPReg< TInput >::m_copyFromGP

Definition at line 52 of file gpRegression.hpp.

template<class TInput>

CovFunc<TInput>* GPReg< TInput >::m_covFunc

Definition at line 62 of file gpRegression.hpp.

template<class TInput>

TVector<TInput>* GPReg< TInput >::m_dataPoints

Definition at line 56 of file gpRegression.hpp.

template<class TInput>

TMatrix<double>* GPReg< TInput >::m_iC

Definition at line 60 of file gpRegression.hpp.

template<class TInput>

TVector<double>* GPReg< TInput >::m_iCt

Definition at line 61 of file gpRegression.hpp.

template<class TInput>

GPReg<TInput>* GPReg< TInput >::m_noiseGP

Definition at line 66 of file gpRegression.hpp.

template<class TInput>

int GPReg< TInput >::m_numDataPoints

Definition at line 54 of file gpRegression.hpp.

template<class TInput>

double GPReg< TInput >::m_ownSigmaNoise

Definition at line 64 of file gpRegression.hpp.

template<class TInput>

double* GPReg< TInput >::m_sigmaNoise

Definition at line 63 of file gpRegression.hpp.

template<class TInput>

TVector<double>* GPReg< TInput >::m_t

Definition at line 57 of file gpRegression.hpp.

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The documentation for this class was generated from the following file:

• /opt/ros/diamondback/stacks/freiburg_tools/gaussian_process/include/gaussian_process/gpRegression.hpp