void AdaptiveSparseGrid<Scalar,UserVector>::build_diffRule(
CubatureTensorSorted<Scalar> & outRule,
std::vector<int> index,
AdaptiveSparseGridInterface<Scalar,UserVector> & problem_data) {
int numPoints = 0;
int dimension = problem_data.getDimension();
bool isNormalized = problem_data.isNormalized();
std::vector<EIntrepidBurkardt> rule1D; problem_data.getRule(rule1D);
std::vector<EIntrepidGrowth> growth1D; problem_data.getGrowth(growth1D);
for (int i=0; i<dimension; i++) {
// Compute 1D rules
numPoints = growthRule1D(index[i],growth1D[i],rule1D[i]);
CubatureLineSorted<Scalar> diffRule1(rule1D[i],numPoints,isNormalized);
if (numPoints!=1) { // Compute differential rule
numPoints = growthRule1D(index[i]-1,growth1D[i],rule1D[i]);
CubatureLineSorted<Scalar> rule1(rule1D[i],numPoints,isNormalized);
diffRule1.update(-1.0,rule1,1.0);
}
// Build Tensor Rule
outRule = kron_prod<Scalar>(outRule,diffRule1);
}
}
Quadrature<Real>::Quadrature(const int dimension,
const std::vector<int> &numPoints1D,
const std::vector<EQuadrature> &rule1D,
const std::vector<EGrowth> &growth1D,
const bool isNormalized)
: dimension_(dimension) {
TEUCHOS_TEST_FOR_EXCEPTION((dimension!=(int)numPoints1D.size()||
dimension!=(int)rule1D.size()||
dimension!=(int)growth1D.size()),std::out_of_range,
">>> ERROR (Quadrature): Dimension mismatch for inputs.");
accuracy_.clear();
accuracy_.resize(dimension);
std::vector<int> degree(1);
Quadrature<Real> newRule(0,1);
for (int i=0; i<dimension; i++) {
// Compute 1D rules
int numPoints = growthRule1D(numPoints1D[i],growth1D[i],rule1D[i]);
Quadrature<Real> rule1(rule1D[i],numPoints,isNormalized);
rule1.getAccuracy(degree);
accuracy_.push_back(degree[0]);
// Build Tensor Rule
newRule = kron_prod<Real>(newRule,rule1);
}
typename std::map<std::vector<Real>,int>::iterator it;
int loc = 0;
std::vector<Real> node;
for (it=newRule.begin(); it!=newRule.end(); it++) {
node = it->first;
addPointAndWeight(node,newRule.getWeight(node),loc);
loc++;
}
if (isNormalized) {
normalize();
}
}
