ctMatrix4 ctTransform::GetGlobalTransformMatrix() const
{
// return GetLocalTransformMatrix();
if(!m_parent)
{return GetLocalTransformMatrix();}
else
{
ctMatrix4 tmpMat(m_parent->GetGlobalTransformMatrix());
ctMatrix4 tmpMat1(m_localTransform);
//tmpMat = m_localTransform.Multiply(tmpMat);
return tmpMat1 * tmpMat;
}
}
Matrix operator* (const Matrix& leftSideMatrix, double value)
{
Matrix tmpMat(leftSideMatrix);
tmpMat *= value;
return(tmpMat);
}
Matrix operator* (double value, const Matrix& rightSideMatrix)
{
Matrix tmpMat(rightSideMatrix);
tmpMat *= value;
return(tmpMat);
}
Matrix operator* (const Matrix& leftSideMatrix, const Matrix& rightSideMatrix)
{
Matrix tmpMat(leftSideMatrix);
tmpMat *= rightSideMatrix;
return(tmpMat);
}
Matrix Matrix::operator-() const
{
Matrix tmpMat(*this);
tmpMat.negate();
return(tmpMat);
}
void
VectorGaussianRandomField<P_V,P_M,Q_V,Q_M>::sampleFunction(const std::vector<P_V*>& fieldPositions, Q_V& sampleValues)
{
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;
}
MovingMatrix operator- (const MovingMatrix& leftSideMatrix, const MovingMatrix& rightSideMatrix)
{
MovingMatrix tmpMat(leftSideMatrix);
tmpMat -= rightSideMatrix;
return(tmpMat);
}