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sgpp::datadriven::OperationDensityMargTo1D Class Reference

Marginalize Probability Density Function. More...

#include <OperationDensityMargTo1D.hpp>

Public Member Functions

virtual void margToDimX (base::DataVector *alpha, base::Grid *&grid_x, base::DataVector *&alpha_x, size_t dim_x)
 Keep applying marginalizes to (Density) Functions, until it's reduced to 1 dimension (dim_x) More...
 
virtual void margToDimXs (base::DataVector *alpha, base::Grid *&grid_x, base::DataVector *&alpha_x, std::vector< size_t > &dim_x)
 Keep applying marginalizes to (Density) Functions, until it's reduced to d dimensions (dim_x) More...
 
 OperationDensityMargTo1D (base::Grid *grid)
 
virtual ~OperationDensityMargTo1D ()
 

Protected Member Functions

void computeMarginalizationIndices (std::vector< size_t > &dim_x, size_t numDims, std::vector< size_t > &margDims)
 
void marg_next_dim (base::Grid *g_in, base::DataVector *a_in, base::Grid *&g_out, base::DataVector *&a_out, std::vector< size_t > margDims, size_t ix)
 

Protected Attributes

base::Grid * grid
 

Detailed Description

Marginalize Probability Density Function.

Constructor & Destructor Documentation

◆ OperationDensityMargTo1D()

sgpp::datadriven::OperationDensityMargTo1D::OperationDensityMargTo1D ( base::Grid *  grid)
inlineexplicit

◆ ~OperationDensityMargTo1D()

virtual sgpp::datadriven::OperationDensityMargTo1D::~OperationDensityMargTo1D ( )
inlinevirtual

References alpha, margToDimX(), and margToDimXs().

Member Function Documentation

◆ computeMarginalizationIndices()

void sgpp::datadriven::OperationDensityMargTo1D::computeMarginalizationIndices ( std::vector< size_t > &  dim_x,
size_t  numDims,
std::vector< size_t > &  margDims 
)
protected

References python.leja::count, and python.statsfileInfo::i.

Referenced by margToDimXs().

◆ marg_next_dim()

void sgpp::datadriven::OperationDensityMargTo1D::marg_next_dim ( base::Grid *  g_in,
base::DataVector *  a_in,
base::Grid *&  g_out,
base::DataVector *&  a_out,
std::vector< size_t >  margDims,
size_t  ix 
)
protected

References sgpp::op_factory::createOperationDensityMarginalize(), and sgpp::datadriven::OperationDensityMarginalize::doMarginalize().

Referenced by margToDimXs().

◆ margToDimX()

void sgpp::datadriven::OperationDensityMargTo1D::margToDimX ( base::DataVector *  alpha,
base::Grid *&  grid_x,
base::DataVector *&  alpha_x,
size_t  dim_x 
)
virtual

Keep applying marginalizes to (Density) Functions, until it's reduced to 1 dimension (dim_x)

Parameters
alphaCoefficient vector for current grid
grid_xoutput 1D grid pointer
alpha_xCoefficient vector for new grid (grid_x). Will be initialized.
dim_xTarget dimension, all other dimensions will be marginalized

References sgpp::base::Grid::getDimension(), grid, and margToDimXs().

Referenced by sgpp::datadriven::OperationDensitySamplingLinear::doSampling(), sgpp::datadriven::OperationDensitySamplingLinear::doSampling_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationBspline::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationModBspline::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationBspline::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationBsplineBoundary::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationLinear::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationBsplineBoundary::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationModPoly::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationModBspline::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationModPoly::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationPoly::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationPoly::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationPolyBoundary::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationPolyBoundary::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationLinear::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationBsplineClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationModPolyClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationModPolyClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationPolyClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationBsplineClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationPolyClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationModBsplineClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationInverseRosenblattTransformationPolyClenshawCurtisBoundary::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationModBsplineClenshawCurtis::doTransformation_in_next_dim(), sgpp::datadriven::OperationRosenblattTransformationPolyClenshawCurtisBoundary::doTransformation_in_next_dim(), and ~OperationDensityMargTo1D().

◆ margToDimXs()

void sgpp::datadriven::OperationDensityMargTo1D::margToDimXs ( base::DataVector *  alpha,
base::Grid *&  grid_x,
base::DataVector *&  alpha_x,
std::vector< size_t > &  dim_x 
)
virtual

Keep applying marginalizes to (Density) Functions, until it's reduced to d dimensions (dim_x)

Parameters
alphaCoefficient vector for current grid
grid_xoutput 1D grid pointer
alpha_xCoefficient vector for new grid (grid_x). Will be initialized.
dim_xTarget dimension, all other dimensions will be marginalized

References sgpp::base::Grid::clone(), computeMarginalizationIndices(), sgpp::base::DataVector::get(), sgpp::base::Grid::getDimension(), sgpp::base::DataVector::getSize(), grid, python.statsfileInfo::i, marg_next_dim(), and sgpp::base::DataVector::set().

Referenced by margToDimX(), and ~OperationDensityMargTo1D().

Member Data Documentation

◆ grid

base::Grid* sgpp::datadriven::OperationDensityMargTo1D::grid
protected

Referenced by python.uq.learner.Interpolant.Interpolant::doLearningIteration(), python.learner.Classifier.Classifier::evalError(), python.uq.learner.Interpolant.Interpolant::evalError(), python.uq.learner.SimulationLearner.SimulationLearner::getCollocationNodes(), python.uq.learner.SimulationLearner.SimulationLearner::getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getLearner(), python.uq.learner.Regressor.Regressor::learnData(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), margToDimX(), margToDimXs(), python.learner.Classifier.Classifier::refineGrid(), python.learner.Regressor.Regressor::refineGrid(), python.uq.learner.Regressor.Regressor::refineGrid(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), python.learner.Classifier.Classifier::updateResults(), python.learner.Regressor.Regressor::updateResults(), and python.uq.learner.Regressor.Regressor::updateResults().

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