SG++-Doxygen-Documentation
sgpp::base::GaussHermiteQuadRule1D Class Reference

load gauss quadrature points for standard normal weight function. More...

#include <GaussHermiteQuadRule1D.hpp>

Inheritance diagram for sgpp::base::GaussHermiteQuadRule1D:

## Public Member Functions

GaussHermiteQuadRule1D ()

GaussHermiteQuadRule1D (const GaussHermiteQuadRule1D &that)=delete

void getLevelPointsAndWeightsNormalized (size_t level, base::DataVector &coordinates, base::DataVector &weights, double mean=0.0f, double stdd=1.0f)
the coordinates are scaled by sqrt(2) and then normalized with respect to a given mean and standard deviation. More...

~GaussHermiteQuadRule1D () override

Public Member Functions inherited from sgpp::base::QuadRule1D
void getLevelPointsAndWeights (size_t level, base::DataVector &coordinates, base::DataVector &weights)

size_t getMaxSupportedLevel () const

QuadRule1D ()

virtual ~QuadRule1D ()

## Static Public Member Functions

static GaussHermiteQuadRule1DgetInstance ()

## Additional Inherited Members

Public Attributes inherited from sgpp::base::QuadRule1D
std::vector< double > coordinatesWeights

## Detailed Description

load gauss quadrature points for standard normal weight function.

The points and the weights are generated with numpy.polynomial.hermite.hermgauss, the coordinates are scaled by sqrt(2), the weights are normalized to 1.

## Constructor & Destructor Documentation

 sgpp::base::GaussHermiteQuadRule1D::GaussHermiteQuadRule1D ( )
 sgpp::base::GaussHermiteQuadRule1D::~GaussHermiteQuadRule1D ( )
override
 sgpp::base::GaussHermiteQuadRule1D::GaussHermiteQuadRule1D ( const GaussHermiteQuadRule1D & that )
delete

## Member Function Documentation

 GaussHermiteQuadRule1D & sgpp::base::GaussHermiteQuadRule1D::getInstance ( )
static
 void sgpp::base::GaussHermiteQuadRule1D::getLevelPointsAndWeightsNormalized ( size_t level, base::DataVector & coordinates, base::DataVector & weights, double mean = 0.0f, double stdd = 1.0f )

the coordinates are scaled by sqrt(2) and then normalized with respect to a given mean and standard deviation.

The weights are normalized to 1.

Parameters
 level level of quadrature, is equal to the number of quadrature points coordinates returns the x-coordinates in [-infty, infty] weights returns the corresponding weights (scaled by sqrt(2)) mean mean of the normal distribution the coordinates should be transformed to stdd standard deviation of the normal distribution the coordinates should be transformed to

The documentation for this class was generated from the following files: