本文整理汇总了C++中DataVector::getSize方法的典型用法代码示例。如果您正苦于以下问题：C++ DataVector::getSize方法的具体用法？C++ DataVector::getSize怎么用？C++ DataVector::getSize使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类DataVector的用法示例。
在下文中一共展示了DataVector::getSize方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: mult_transpose
/**
* Performs a transposed mass evaluation
*
* @param storage GridStorage object that contains the grid's points information
* @param basis a reference to a class that implements a specific basis
* @param source the coefficients of the grid points
* @param x the d-dimensional vector with data points (row-wise)
* @param result the result vector of the matrix vector multiplication
*/
void mult_transpose(GridStorage* storage, BASIS& basis, DataVector& source,
DataMatrix& x, DataVector& result) {
result.setAll(0.0);
size_t source_size = source.getSize();
#pragma omp parallel
{
DataVector privateResult(result.getSize());
privateResult.setAll(0.0);
DataVector line(x.getNcols());
AlgorithmEvaluationTransposed<BASIS> AlgoEvalTrans(storage);
privateResult.setAll(0.0);
#pragma omp for schedule(static)
for (size_t i = 0; i < source_size; i++) {
x.getRow(i, line);
AlgoEvalTrans(basis, line, source[i], privateResult);
}
#pragma omp critical
{
result.add(privateResult);
}
}
}示例2: parabola
SGPP::float_t parabola(DataVector& input) {
SGPP::float_t result = 1.;
for (size_t i = 0; i < input.getSize(); i++) {
result *= input[i] * (1. - input[i]) * 4.;
}
return result;
}示例3: parabolaBoundary
SGPP::float_t parabolaBoundary(DataVector& input) {
SGPP::float_t result = 1.;
for (size_t i = 0; i < input.getSize(); i++) {
result *= 0.25 * (input[i] - 0.7) * (input[i] - 0.7) + 2;
}
return result;
}示例4: doQuadrature
float_t OperationQuadraturePoly::doQuadrature(DataVector& alpha) {
float_t res = 0;
float_t tmpres = 0;
GridIndex* gp;
for (size_t i = 0; i < alpha.getSize(); i++) {
gp = storage->get(i);
tmpres = 1.;
for (size_t d = 0; d < storage->dim(); d++) {
tmpres *= base.getIntegral(gp->getLevel(d), gp->getIndex(d));
}
res += alpha[i] * tmpres;
}
return res;
}示例5: mult
/**
* Performs a mass evaluation
*
* @param storage GridStorage object that contains the grid's points information
* @param basis a reference to a class that implements a specific basis
* @param source the coefficients of the grid points
* @param x the d-dimensional vector with data points (row-wise)
* @param result the result vector of the matrix vector multiplication
*/
void mult(GridStorage* storage, BASIS& basis, DataVector& source, DataMatrix& x,
DataVector& result) {
result.setAll(0.0);
size_t result_size = result.getSize();
#pragma omp parallel
{
DataVector line(x.getNcols());
AlgorithmEvaluation<BASIS> AlgoEval(storage);
#pragma omp for schedule(static)
for (size_t i = 0; i < result_size; i++) {
x.getRow(i, line);
result[i] = AlgoEval(basis, line, source);
}
}
}