#include <MultiGaussianStateCombiner1D.h>
Public Member Functions | |
SingleGaussianState1D | combine (const MultiGaussianState1D &theState) const |
SingleGaussianState1D | combine (const VSC &theComponents) const |
Private Types | |
typedef std::vector < SingleGaussianState1D > | VSC |
Class to collapse (combine) a Gaussian mixture of states into one. (c.f. R. Fruewirth et.al., Comp.Phys.Comm 100 (1997) 1
Definition at line 13 of file MultiGaussianStateCombiner1D.h.
typedef std::vector<SingleGaussianState1D> MultiGaussianStateCombiner1D::VSC [private] |
Definition at line 16 of file MultiGaussianStateCombiner1D.h.
SingleGaussianState1D MultiGaussianStateCombiner1D::combine | ( | const MultiGaussianState1D & | theState | ) | const |
Definition at line 9 of file MultiGaussianStateCombiner1D.cc.
References MultiGaussianState1D::components().
Referenced by MultiGaussianState1D::checkCombinedState().
{ return combine(theState.components()); }
SingleGaussianState1D MultiGaussianStateCombiner1D::combine | ( | const VSC & | theComponents | ) | const |
Definition at line 15 of file MultiGaussianStateCombiner1D.cc.
References gather_cfg::cout, Exception, and histoStyle::weight.
{ if (theComponents.empty()) { throw cms::Exception("LogicError") << "MultiGaussianStateCombiner1D:: state container to collapse is empty"; // return SingleState(SingleState::Vector(),SingleState::Matrix(),0.); // return SingleState(SingleState::Vector(), // SingleState::Matrix(),0.); return SingleGaussianState1D(); } const SingleGaussianState1D firstState(theComponents.front()); if (theComponents.size()==1) return firstState; // int size = firstState.mean().num_row(); double meanMean(0.); double weightSum(0.); // double weight; double measCovar1(0.); double measCovar2(0.); for ( VSC::const_iterator mixtureIter1 = theComponents.begin(); mixtureIter1 != theComponents.end(); mixtureIter1++ ) { double weight = mixtureIter1->weight(); weightSum += weight; double mean1 = mixtureIter1->mean(); meanMean += weight * mean1; measCovar1 += weight * mixtureIter1->variance(); for ( VSC::const_iterator mixtureIter2 = mixtureIter1+1; mixtureIter2 != theComponents.end(); mixtureIter2++ ) { double posDiff = mean1 - mixtureIter2->mean(); // SingleState::Matrix s(1,1); //stupid trick to make CLHEP work decently // measCovar2 +=weight * (*mixtureIter2).weight() * // s.similarity(posDiff.T().T()); // SingleState::Matrix mat; // for ( unsigned int i1=0; i1<N; i1++ ) { // for ( unsigned int i2=0; i2<=i1; i2++ ) mat(i1,i2) = posDiff(i1)*posDiff(i2); // } // measCovar2 += weight * (*mixtureIter2).weight() * mat; // // TensorProd yields a general matrix - need to convert to a symm. matrix double covGen = posDiff*posDiff; // double covSym(covGen.LowerBlock()); measCovar2 += weight * mixtureIter2->weight() * covGen; } } double measCovar; if (weightSum<DBL_MIN){ std::cout << "MultiGaussianStateCombiner1D:: New state has total weight of 0." << std::endl; // meanMean = SingleState::Vector(size,0); meanMean = 0.; measCovar = 0.; weightSum = 0.; } else { meanMean /= weightSum; measCovar1 *= (1./weightSum); measCovar2 *= (1./weightSum/weightSum); measCovar = measCovar1 + measCovar2; // measCovar = measCovar1/weightSum + measCovar2/weightSum/weightSum; } return SingleGaussianState1D(meanMean, measCovar, weightSum); }