//#include "countLine.h"
int main(int argc, char** argv)
{
ComputeKernelMatrix(argc, argv);
// step 7. train and test with svm.
//TrainAndTest(argc, argv);
// extra. count the lines of files extracted by step 2.
//countLine(argc, argv);
return 0;
}
void GaussianProcess<TScalarType>::ComputeCoreMatrix(typename GaussianProcess<TScalarType>::MatrixType &C) const{
MatrixType K;
ComputeKernelMatrix(K);
// add noise variance to diagonal
AddNoiseToKernelMatrix(K);
C = InvertKernelMatrix(K, m_InvMethod);
if(debug){
std::cout << "GaussianProcess::ComputeCoreMatrix: inversion error: " << (K*C - MatrixType::Identity(K.rows(),K.cols())).norm() << std::endl;
}
}
typename GaussianProcess<TScalarType>::HighPrecisionType GaussianProcess<TScalarType>::ComputeCoreMatrixWithDeterminant(typename GaussianProcess<TScalarType>::MatrixType &C) const{
typedef typename GaussianProcess<TScalarType>::HighPrecisionType HighPrecisionType;
MatrixType K;
ComputeKernelMatrix(K);
// add noise variance to diagonal
AddNoiseToKernelMatrix(K);
C = InvertKernelMatrix(K, m_InvMethod);
if(debug){
std::cout << "GaussianProcess::ComputeCoreMatrix: inversion error: " << (K*C - MatrixType::Identity(K.rows(),K.cols())).norm() << std::endl;
std::cout << "GaussianProcess::ComputeCoreMatrix: determinant of K: " << K.template cast<HighPrecisionType>().determinant() << std::endl;
}
return K.template cast<HighPrecisionType>().determinant();
}