void Dispersive::printInfo() const {
std::cout << "--- VolumeDispersive info ---" << std::endl;
Volume::printInfo();
std::cout << "Type: " << "Dispersive material" << std::endl;
std::cout << "Number of pole residue pairs: " << poleResidue_.size()
<< std::endl;
std::cout << "# " << " re_a " << " im_a " << " re_c " << " im_c "
<< std::endl;
for (std::size_t i = 0; i < poleResidue_.size(); i++) {
std::cout << i << " " << getPole(i).real() << " " << getPole(i).imag()
<< " " << getResidue(i).real() << " " << getResidue(i).imag()
<< std::endl;
}
}
Math::Real Dispersive::getElectricConductivity() const {
if (getPoleNumber() > 1) {
std::cout << std::endl << "WARNING @ getElectricConductivity: "
<< "This material is dispersive and its effective "
<< "permittivity depends on several parameters. "
<< "Returning static limit conductivity." << std::endl;
}
for (std::size_t i = 0; i < getPoleNumber(); i++) {
if (std::abs(getPole(i)) == 0) {
return getResidue(i).real() * 2.0 * Math::Constants::eps0;
}
}
return 0.0;
}
const Residue* ResidueDB::getModifiedResidue(const String& modification)
{
// terminal mods. don't apply to residue (side chain), so don't consider them:
const ResidueModification& mod = ModificationsDB::getInstance()->getModification(modification, "", ResidueModification::ANYWHERE);
return getModifiedResidue(getResidue(mod.getOrigin()), mod.getFullId());
}
double
ossimRpcProjection::optimizeFit(const ossimTieGptSet& tieSet, double* /* targetVariance */)
{
#if 1
//NOTE : ignore targetVariance
ossimRefPtr<ossimRpcSolver> solver = new ossimRpcSolver(false, false); //TBD : choices should be part of setupFromString
std::vector<ossimDpt> imagePoints;
std::vector<ossimGpt> groundPoints;
tieSet.getSlaveMasterPoints(imagePoints, groundPoints);
solver->solveCoefficients(imagePoints, groundPoints);
ossimRefPtr< ossimImageGeometry > optProj = solver->createRpcProjection();
if (!optProj)
{
ossimNotify(ossimNotifyLevel_FATAL) << "FATAL ossimRpcProjection::optimizeFit(): error when optimizing the RPC with given tie points"
<< std::endl;
return -1.0;
}
if(optProj->hasProjection())
{
ossimKeywordlist kwl;
optProj->getProjection()->saveState(kwl);
this->loadState(kwl);
}
return std::pow(solver->getRmsError(), 2); //variance in pixel^2
#else
// COPIED from ossimRpcProjection
//
//
//use a simple Levenberg-Marquardt non-linear optimization
//note : please limit the number of tie points
//
//INPUTS: requires Jacobian matrix (partial derivatives with regards to parameters)
//OUTPUTS: will also compute parameter covariance matrix
//
//TBD: use targetVariance!
int np = getNumberOfAdjustableParameters();
int nobs = tieSet.size();
//setup initail values
int iter=0;
int iter_max = 200;
double minResidue = 1e-10; //TBC
double minDelta = 1e-10; //TBC
//build Least Squares initial normal equation
// don't waste memory, add samples one at a time
NEWMAT::SymmetricMatrix A;
NEWMAT::ColumnVector residue;
NEWMAT::ColumnVector projResidue;
double deltap_scale = 1e-4; //step_Scale is 1.0 because we expect parameters to be between -1 and 1
buildNormalEquation(tieSet, A, residue, projResidue, deltap_scale);
double ki2=residue.SumSquare();
//get current adjustment (between -1 and 1 normally) and convert to ColumnVector
ossimAdjustmentInfo cadj;
getAdjustment(cadj);
std::vector< ossimAdjustableParameterInfo >& parmlist = cadj.getParameterList();
NEWMAT::ColumnVector cparm(np), nparm(np);
for(int n=0;n<np;++n)
{
cparm(n+1) = parmlist[n].getParameter();
}
double damping_speed = 2.0;
//find max diag element for A
double maxdiag=0.0;
for(int d=1;d<=np;++d) {
if (maxdiag < A(d,d)) maxdiag=A(d,d);
}
double damping = 1e-3 * maxdiag;
double olddamping = 0.0;
bool found = false;
//DEBUG TBR
cout<<"rms="<<sqrt(ki2/nobs)<<" ";
cout.flush();
while ( (!found) && (iter < iter_max) ) //non linear optimization loop
{
bool decrease = false;
do
{
//add damping update to normal matrix
for(int d=1;d<=np;++d) A(d,d) += damping - olddamping;
olddamping = damping;
NEWMAT::ColumnVector deltap = solveLeastSquares(A, projResidue);
if (deltap.NormFrobenius() <= minDelta)
{
found = true;
} else {
//update adjustment
nparm = cparm + deltap;
for(int n=0;n<np;++n)
{
setAdjustableParameter(n, nparm(n+1), false); //do not update now, wait
}
adjustableParametersChanged();
//check residue is reduced
NEWMAT::ColumnVector newresidue = getResidue(tieSet);
double newki2=newresidue.SumSquare();
double res_reduction = (ki2 - newki2) / (deltap.t()*(deltap*damping + projResidue)).AsScalar();
//DEBUG TBR
cout<<sqrt(newki2/nobs)<<" ";
cout.flush();
if (res_reduction > 0)
{
//accept new parms
cparm = nparm;
ki2=newki2;
deltap_scale = max(1e-15, deltap.NormInfinity()*1e-4);
buildNormalEquation(tieSet, A, residue, projResidue, deltap_scale);
olddamping = 0.0;
found = ( projResidue.NormInfinity() <= minResidue );
//update damping factor
damping *= std::max( 1.0/3.0, 1.0-std::pow((2.0*res_reduction-1.0),3));
damping_speed = 2.0;
decrease = true;
} else {
//cancel parameter update
for(int n=0;n<np;++n)
{
setAdjustableParameter(n, nparm(n+1), false); //do not update right now
}
adjustableParametersChanged();
damping *= damping_speed;
damping_speed *= 2.0;
}
}
} while (!decrease && !found);
++iter;
}
//DEBUG TBR
cout<<endl;
//compute parameter correlation
// use normal matrix inverse
//TBD
return ki2/nobs;
#endif
}
