void CStoreScalarAggregator<T>::submit_result(CJobResult* result)
{
SG_GCDEBUG("Entering\n")
// check for proper typecast
CScalarResult<T>* new_result=dynamic_cast<CScalarResult<T>*>(result);
if (!new_result)
SG_ERROR("result is not of CScalarResult type!\n");
// aggregate it with previous
m_aggregate+=new_result->get_result();
SG_GCDEBUG("Leaving\n")
}
CConjugateGradientSolver::~CConjugateGradientSolver()
{
SG_GCDEBUG("%s destroyed (%p)\n", this->get_name(), this);
}
CConjugateGradientSolver::CConjugateGradientSolver(bool store_residuals)
: CIterativeLinearSolver<float64_t>(store_residuals)
{
SG_GCDEBUG("%s created (%p)\n", this->get_name(), this);
}
CConjugateGradientSolver::CConjugateGradientSolver()
: CIterativeLinearSolver<float64_t>()
{
SG_GCDEBUG("%s created (%p)\n", this->get_name(), this);
}
CNormalSampler::CNormalSampler()
: CTraceSampler()
{
SG_GCDEBUG("%s created (%p)\n", this->get_name(), this)
}
CNormalSampler::CNormalSampler(index_t dimension)
: CTraceSampler(dimension)
{
SG_GCDEBUG("%s created (%p)\n", this->get_name(), this)
}
CNormalSampler::~CNormalSampler()
{
SG_GCDEBUG("%s destroyed (%p)\n", this->get_name(), this)
}
void CNormalSampler::precompute()
{
m_num_samples=1;
}
SGVector<float64_t> CNormalSampler::sample(index_t idx) const
{
SGVector<float64_t> s(m_dimension);
if (idx>=m_num_samples)
SG_WARNING("idx should be less than %d\n", m_num_samples)
else
{
for (index_t i=0; i<m_dimension; ++i)
