void InterpolationSurrogateBuilder<V,M>::partition_work()
{
// Convenience
unsigned int n_values = this->get_default_data().n_values();
unsigned int n_workers = this->get_default_data().get_paramDomain().env().numSubEnvironments();
unsigned int n_jobs = n_values/n_workers;
unsigned int n_leftover = this->get_default_data().n_values() % n_workers;
/* If the number of values is evenly divisible over all workers,
then everyone gets the same amount work */
if( n_leftover == 0 )
{
for(unsigned int n = 0; n < n_workers; n++)
this->m_njobs[n] = n_jobs;
}
/* Otherwise, some workers get more work than others*/
else
{
for(unsigned int n = 0; n < n_workers; n++)
{
if( n < n_leftover )
this->m_njobs[n] = n_jobs+1;
else
this->m_njobs[n] = n_jobs;
}
}
// Sanity check
queso_assert_equal_to( (int)n_values, std::accumulate( m_njobs.begin(), m_njobs.end(), 0 ) );
}
void
GaussianJointPdf<V,M>::distributionVariance(M & covMatrix) const
{
queso_assert_equal_to (covMatrix.numCols(), covMatrix.numRowsGlobal());
if (m_diagonalCovMatrix) {
covMatrix.zeroLower();
covMatrix.zeroUpper();
unsigned int n_comp = this->lawVarVector().sizeLocal();
queso_assert_equal_to (n_comp, covMatrix.numCols());
for (unsigned int i = 0; i < n_comp; ++i) {
covMatrix(i,i) = this->lawVarVector()[i];
}
} else {
covMatrix = *this->m_lawCovMatrix;
}
}
virtual void evaluate_model( const V & domainVector, std::vector<double>& values )
{ queso_assert_equal_to( domainVector.sizeGlobal(), 4);
queso_assert_equal_to( values.size(), 2 );
values[0] = four_d_fn_1(domainVector[0],domainVector[1],domainVector[2],domainVector[3]);
values[1] = four_d_fn_2(domainVector[0],domainVector[1],domainVector[2],domainVector[3]);
};
