QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M > Class Template Reference

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

#include <VectorGaussianRandomField.h>

Collaboration diagram for QUESO::VectorGaussianRandomField< P_V, P_M, Q_V, Q_M >:

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, class P_M, class Q_V, class Q_M>
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 45 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 , class P_M , class Q_V , class Q_M >

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.

{
}

Member Function Documentation

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

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 , class P_M , class Q_V , class Q_M >

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 UQ_FATAL_TEST_MACRO.

{
  if ((m_env.subDisplayFile()) && (m_env.displayVerbosity() >= 3)) {
    *m_env.subDisplayFile() << "Entering VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()"
                            << std::endl;
  }

  UQ_FATAL_TEST_MACRO(( sampleValues.sizeLocal() % fieldPositions.size() ) != 0,
                      m_env.fullRank(),
                      "VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()",
                      "input data is not multiple of each other");

  unsigned int numberOfImageValuesPerIndex = sampleValues.sizeLocal()/fieldPositions.size();

  UQ_FATAL_TEST_MACRO(numberOfImageValuesPerIndex != m_imageSetPerIndex.vectorSpace().dimLocal(),
                      m_env.fullRank(),
                      "VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()",
                      "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 {
    UQ_FATAL_TEST_MACRO(true,
                        m_env.fullRank(),
                        "VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()",
                        "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) {
      UQ_FATAL_TEST_MACRO(m_savedPositions[i] == NULL,
                          m_env.fullRank(),
                          "VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()",
                          "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;
          UQ_FATAL_TEST_MACRO(true,
                              m_env.fullRank(),
                              "VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction()",
                              "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 , 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 >::m_covarianceFunction

protected

Covariance function.

Definition at line 111 of file VectorGaussianRandomField.h.

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

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

protected

Environment.

Definition at line 96 of file VectorGaussianRandomField.h.

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

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 105 of file VectorGaussianRandomField.h.

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 >::m_indexSet

protected

Index set.

Definition at line 102 of file VectorGaussianRandomField.h.

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 >::m_meanFunction

protected

Mean function.

Definition at line 108 of file VectorGaussianRandomField.h.

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

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

protected

Prefix.

Definition at line 99 of file VectorGaussianRandomField.h.

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

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

protected

Saved positions.

Definition at line 114 of file VectorGaussianRandomField.h.

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

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

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

protected

My RV.

Definition at line 126 of file VectorGaussianRandomField.h.

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

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 117 of file VectorGaussianRandomField.h.

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

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

protected

Covariance matrix of the RV.

Definition at line 123 of file VectorGaussianRandomField.h.

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

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 120 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