A class for handling vector Gaussian random fields (GRF). More...

#include <VectorGaussianRandomField.h>

Public Member Functions
Constructor/Destructor methods
	VectorGaussianRandomField (const char *prefix, const VectorSet< P_V, P_M > &indexSet, const VectorSet< Q_V, Q_M > &imageSetPerIndex, const BaseVectorFunction< P_V, P_M, Q_V, Q_M > &meanFunction, const BaseMatrixCovarianceFunction< P_V, P_M, Q_V, Q_M > &covarianceFunction)
	Constructor. More...

	VectorGaussianRandomField (const VectorGaussianRandomField &obj)
	TODO: Copy constructor. More...

	~VectorGaussianRandomField ()
	Destructor. More...

Set methods
VectorGaussianRandomField &	operator= (const VectorGaussianRandomField &rhs)
	TODO: Assignment operator; it copies `rhs` to `this`. More...

Math methods
const VectorSet< P_V, P_M > &	indexSet () const
	Index set; access to protected attribute m_indexSet. More...

const BaseVectorFunction< P_V, P_M, Q_V, Q_M > &	meanFunction () const
	Mean function; access to protected attribute m_meanFunction. More...

const BaseMatrixCovarianceFunction < P_V, P_M, Q_V, Q_M > &	covarianceFunction () const
	Covariance function; access to protected attribute m_covarianceFunction. More...

void	sampleFunction (const std::vector< P_V * > &fieldPositions, Q_V &sampleValues)
	Function that samples from a Gaussian PDF. More...

Protected Member Functions
void	copy (const VectorGaussianRandomField &src)
	Copy method. More...

Protected Attributes
const BaseEnvironment &	m_env
	Environment. More...

std::string	m_prefix
	Prefix. More...

const VectorSet< P_V, P_M > &	m_indexSet
	Index set. More...

const VectorSet< Q_V, Q_M > &	m_imageSetPerIndex
	Image set of the RV, per index. More...

const BaseVectorFunction< P_V, P_M, Q_V, Q_M > &	m_meanFunction
	Mean function. More...

const BaseMatrixCovarianceFunction < P_V, P_M, Q_V, Q_M > &	m_covarianceFunction
	Covariance function. More...

std::vector< P_V * >	m_savedPositions
	Saved positions. More...

VectorSpace< Q_V, Q_M > *	m_savedRvImageSpace
	Image set of the RV. More...

Q_V *	m_savedRvLawExpVector
	Vector of the mean value of the RV. More...

Q_M *	m_savedRvLawCovMatrix
	Covariance matrix of the RV. More...

GaussianVectorRV< Q_V, Q_M > *	m_savedRv
	My RV. More...

Detailed Description

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>
class QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >

A class for handling vector Gaussian random fields (GRF).

This class implements a vector Gaussian random field (GRF); i.e. a random field involving vector Gaussian probability density functions (PDFs) of the variables.

Definition at line 48 of file VectorGaussianRandomField.h.

Constructor & Destructor Documentation

template<class P_V , class P_M , class Q_V , class Q_M >

QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::VectorGaussianRandomField	(	const char *	prefix,
		const VectorSet< P_V, P_M > &	indexSet,
		const VectorSet< Q_V, Q_M > &	imageSetPerIndex,
		const BaseVectorFunction< P_V, P_M, Q_V, Q_M > &	meanFunction,
		const BaseMatrixCovarianceFunction< P_V, P_M, Q_V, Q_M > &	covarianceFunction
	)

Constructor.

Constructs a new object, given a prefix, an index set, and both a mean and a covariance function. This method deletes the previous saved positions.

Definition at line 31 of file VectorGaussianRandomField.C.

References QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_savedPositions.

   :
   m_env                (indexSet.env()),
   m_prefix             ((std::string)(prefix)+"grf_"),
   m_indexSet           (indexSet),
   m_imageSetPerIndex   (imageSetPerIndex),
   m_meanFunction       (meanFunction),
   m_covarianceFunction (covarianceFunction),
   m_savedRvImageSpace  (NULL),
   m_savedRvLawExpVector(NULL),
   m_savedRvLawCovMatrix(NULL),
   m_savedRv            (NULL)
 {
   m_savedPositions.clear();
 }

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::VectorGaussianRandomField ( const VectorGaussianRandomField< P_V, P_M, Q_V, Q_M > & obj )

TODO: Copy constructor.

Todo:: : implement me!

template<class P_V , class P_M , class Q_V , class Q_M >

QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::~VectorGaussianRandomField ( )

Destructor.

Definition at line 53 of file VectorGaussianRandomField.C.

54 {

55 }

Member Function Documentation

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

void QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::copy ( const VectorGaussianRandomField< P_V, P_M, Q_V, Q_M > & src )

protected

Copy method.

template<class P_V , class P_M , class Q_V , class Q_M >

const BaseMatrixCovarianceFunction< P_V, P_M, Q_V, Q_M > & QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::covarianceFunction ( ) const

Covariance function; access to protected attribute m_covarianceFunction.

Definition at line 73 of file VectorGaussianRandomField.C.

 {
   return m_covarianceFunction;
 }

template<class P_V , class P_M , class Q_V , class Q_M >

const VectorSet< P_V, P_M > & QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::indexSet ( ) const

Index set; access to protected attribute m_indexSet.

Definition at line 59 of file VectorGaussianRandomField.C.

 {
   return m_indexSet;
 }

template<class P_V , class P_M , class Q_V , class Q_M >

const BaseVectorFunction< P_V, P_M, Q_V, Q_M > & QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::meanFunction ( ) const

Mean function; access to protected attribute m_meanFunction.

Definition at line 66 of file VectorGaussianRandomField.C.

 {
   return m_meanFunction;
 }

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

VectorGaussianRandomField& QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::operator= ( const VectorGaussianRandomField< P_V, P_M, Q_V, Q_M > & rhs )

TODO: Assignment operator; it copies rhs to this.

Todo:: : implement me!

template<class P_V , class P_M , class Q_V , class Q_M >

void QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::sampleFunction	(	const std::vector< P_V * > &	fieldPositions,
		Q_V &	sampleValues
	)

Function that samples from a Gaussian PDF.

Given the field positions, this method performs a number of tests, calculates the mean vector, the covariance matrix and then it samples from a Gaussian random vector as many positions as required.

Definition at line 80 of file VectorGaussianRandomField.C.

References QUESO::queso_require_equal_to_msg.

 {
   if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
     *m_env.subDisplayFile() << "Entering VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                             << std::endl;
   }
 
   queso_require_equal_to_msg(( sampleValues.sizeLocal() % fieldPositions.size() ), 0, "input data is not multiple of each other");
 
   unsigned int numberOfImageValuesPerIndex = sampleValues.sizeLocal()/fieldPositions.size();
 
   queso_require_equal_to_msg(numberOfImageValuesPerIndex, m_imageSetPerIndex.vectorSpace().dimLocal(), "invalid input data dimension");
 
   if ((m_savedPositions.size() == 0   ) &&
       (m_savedRvImageSpace     == NULL) &&
       (m_savedRvLawExpVector   == NULL) &&
       (m_savedRvLawCovMatrix   == NULL) &&
       (m_savedRv               == NULL)) {
     // Ok
   }
   else if ((m_savedPositions.size() != 0   ) &&
            (m_savedRvImageSpace     != NULL) &&
            (m_savedRvLawExpVector   != NULL) &&
            (m_savedRvLawCovMatrix   != NULL) &&
            (m_savedRv               != NULL)) {
     // Ok
   }
   else {
     queso_error_msg("invalid combination of pointer values");
   }
 
   unsigned int numberOfPositions = fieldPositions.size();
   bool instantiate = true;
   if (m_savedPositions.size() == numberOfPositions) {
     bool allPositionsAreEqual = true;
     for (unsigned int i = 0; i < numberOfPositions; ++i) {
       queso_require_msg(m_savedPositions[i], "m_savedPositions[i] should not be NULL");
       if ((m_savedPositions[i]->sizeLocal() == fieldPositions[i]->sizeLocal()) &&
           (*(m_savedPositions[i])           == *(fieldPositions[i])          )) {
         // Ok
       }
       else {
         allPositionsAreEqual = false;
         break;
       }
     } // for i
     instantiate = !allPositionsAreEqual;
   }
 
   if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
     *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                             << ": numberOfPositions = " << numberOfPositions
                             << ", instantiate = "       << instantiate
                             << std::endl;
   }
 
   if (instantiate) {
     delete m_savedRv;
     delete m_savedRvLawCovMatrix;
     delete m_savedRvLawExpVector;
     delete m_savedRvImageSpace;
     for (unsigned int i = 0; i < m_savedPositions.size(); ++i) {
       delete m_savedPositions[i];
     }
     m_savedPositions.clear();
 
     // Set m_savedPositions
     m_savedPositions.resize(numberOfPositions,NULL);
     for (unsigned int i = 0; i < m_savedPositions.size(); ++i) {
       m_savedPositions[i] = new P_V(*(fieldPositions[i]));
     }
 
     // Set m_savedRvImageSpace
     m_savedRvImageSpace = new VectorSpace<Q_V,Q_M>(m_env, "grf_", numberOfPositions*numberOfImageValuesPerIndex, NULL);
 
     // Set m_savedRvLawExpVector
     Q_V tmpVec(m_imageSetPerIndex.vectorSpace().zeroVector());
     m_savedRvLawExpVector = new Q_V(m_savedRvImageSpace->zeroVector());
     for (unsigned int i = 0; i < numberOfPositions; ++i) {
       m_meanFunction.compute(*(fieldPositions[i]),NULL,tmpVec,NULL,NULL,NULL);
       for (unsigned int j = 0; j < numberOfImageValuesPerIndex; ++j) {
         (*m_savedRvLawExpVector)[i*numberOfImageValuesPerIndex + j] = tmpVec[j];
       }
     }
 
     // Set m_savedRvLawCovMatrix
     Q_M tmpMat(m_imageSetPerIndex.vectorSpace().zeroVector());
     m_savedRvLawCovMatrix = new Q_M(m_savedRvImageSpace->zeroVector());
     if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
       *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                               << ": m_savedRvLawCovMatrix order = " << m_savedRvLawCovMatrix->numCols()
                               << ", numberOfPositions = "           << numberOfPositions
                               << ", tmpMat order = "                << tmpMat.numCols()
                               << ", numberOfImageValuesPerIndex = " << numberOfImageValuesPerIndex
                               << std::endl;
     }
     for (unsigned int i = 0; i < numberOfPositions; ++i) {
       for (unsigned int j = 0; j < numberOfPositions; ++j) {
         m_covarianceFunction.covMatrix(*(fieldPositions[i]),*(fieldPositions[j]),tmpMat);
 #if 1
         Q_M testMat(tmpMat);
         if (testMat.chol() != 0) {
           *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                                   << ": i = " << i
                                   << ", j = " << j
                                   << ", *(fieldPositions[i]) = " << *(fieldPositions[i])
                                   << ", *(fieldPositions[j]) = " << *(fieldPositions[j])
                                   << ", tmpMat = "               << tmpMat
                                   << ", testMat = "              << testMat
                                   << ", tmpMat is not positive definite"
                                   << std::endl;
           queso_error_msg("tmpMat is not positive definite");
         }
 #endif
         for (unsigned int k1 = 0; k1 < numberOfImageValuesPerIndex; ++k1) {
           for (unsigned int k2 = 0; k2 < numberOfImageValuesPerIndex; ++k2) {
             unsigned int tmpI = i*numberOfImageValuesPerIndex + k1;
             unsigned int tmpJ = j*numberOfImageValuesPerIndex + k2;
             (*m_savedRvLawCovMatrix)(tmpI,tmpJ) = tmpMat(k1,k2);
             if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
               *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                                       << ": i = " << i
                                       << ", j = " << j
                                       << ", k1 = " << k1
                                       << ", k2 = " << k2
                                       << ", tmpI = " << tmpI
                                       << ", tmpJ = " << tmpJ
                                       << ", *(fieldPositions[i]) = " << *(fieldPositions[i])
                                       << ", *(fieldPositions[j]) = " << *(fieldPositions[j])
                                       << ", (*m_savedRvLawCovMatrix)(tmpI,tmpJ) = " << (*m_savedRvLawCovMatrix)(tmpI,tmpJ)
                                       << std::endl;
             }
           }
         }
       }
     }
 
     // Set m_savedRv
     m_savedRv = new GaussianVectorRV<Q_V,Q_M>("grf_",
                                                      *m_savedRvImageSpace,
                                                      *m_savedRvLawExpVector,
                                                      *m_savedRvLawCovMatrix);
 
     if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
       *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                               << ": just instantiated Gaussian RV"
                               << "\n *m_savedRvLawExpVector = " << *m_savedRvLawExpVector
                               << "\n *m_savedRvLawCovMatrix = " << *m_savedRvLawCovMatrix
                               << std::endl;
       for (unsigned int i = 0; i < numberOfPositions; ++i) {
         *m_env.subDisplayFile() << " *(m_savedPositions[" << i
                                 << "]) = "                << *(m_savedPositions[i])
                                 << std::endl;
       }
     }
   } // if (instantiate)
 
   // Generate sample function
   if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
     *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                             << ": about to realize sample values"
                             << std::endl;
   }
   m_savedRv->realizer().realization(sampleValues);
   if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
     *m_env.subDisplayFile() << "In VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                             << ": just realized sample values"
                             << std::endl;
   }
 
   if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
     *m_env.subDisplayFile() << "Leaving VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                             << std::endl;
   }
 
   return;
 }

Member Data Documentation

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

const BaseMatrixCovarianceFunction<P_V,P_M,Q_V,Q_M>& QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_covarianceFunction

protected

Covariance function.

Definition at line 114 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

const BaseEnvironment& QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_env

protected

Environment.

Definition at line 99 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

const VectorSet<Q_V,Q_M>& QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_imageSetPerIndex

protected

Image set of the RV, per index.

Definition at line 108 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

const VectorSet<P_V,P_M>& QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_indexSet

protected

Index set.

Definition at line 105 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

const BaseVectorFunction<P_V,P_M,Q_V,Q_M>& QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_meanFunction

protected

Mean function.

Definition at line 111 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

std::string QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_prefix

protected

Prefix.

Definition at line 102 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

std::vector<P_V*> QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_savedPositions

protected

Saved positions.

Definition at line 117 of file VectorGaussianRandomField.h.

Referenced by QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::VectorGaussianRandomField().

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

GaussianVectorRV<Q_V,Q_M>* QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_savedRv

protected

My RV.

Definition at line 129 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

VectorSpace<Q_V,Q_M>* QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_savedRvImageSpace

protected

Image set of the RV.

Definition at line 120 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

Q_M* QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_savedRvLawCovMatrix

protected

Covariance matrix of the RV.

Definition at line 126 of file VectorGaussianRandomField.h.

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>

Q_V* QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >::m_savedRvLawExpVector

protected

Vector of the mean value of the RV.

Definition at line 123 of file VectorGaussianRandomField.h.

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

src/stats/inc/VectorGaussianRandomField.h
src/stats/src/VectorGaussianRandomField.C

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix> class QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<class P_V = GslVector, class P_M = GslMatrix, class Q_V = GslVector, class Q_M = GslMatrix>
class QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >