sgpp::datadriven::OperationDensityMargTo1DLinear Class Reference

keep applying marginalize to function until it's reduced to only 1 dimension More...

#include <OperationDensityMargTo1DLinear.hpp>

Inheritance diagram for sgpp::datadriven::OperationDensityMargTo1DLinear:

Public Member Functions
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...
	OperationDensityMargTo1DLinear (base::Grid *grid)
virtual	~OperationDensityMargTo1DLinear ()
Public Member Functions inherited from sgpp::datadriven::OperationDensityMargTo1D
	OperationDensityMargTo1D ()
virtual	~OperationDensityMargTo1D ()

Protected Member Functions
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 Member Functions inherited from sgpp::datadriven::OperationDensityMargTo1D
void	computeMarginalizationIndices (std::vector< size_t > &dim_x, size_t numDims, std::vector< size_t > &margDims)

Protected Attributes
base::Grid *	grid

Detailed Description

keep applying marginalize to function until it's reduced to only 1 dimension

Constructor & Destructor Documentation

sgpp::datadriven::OperationDensityMargTo1DLinear::OperationDensityMargTo1DLinear ( base::Grid *  grid )

inlineexplicit

virtual sgpp::datadriven::OperationDensityMargTo1DLinear::~OperationDensityMargTo1DLinear ( )

inlinevirtual

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

Member Function Documentation

void sgpp::datadriven::OperationDensityMargTo1DLinear::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(), sgpp::datadriven::OperationDensityMarginalize::doMarginalize(), and sgpp::base::Grid::getDimension().

Referenced by margToDimXs().

void sgpp::datadriven::OperationDensityMargTo1DLinear::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

alpha	Coefficient vector for current grid
grid_x	output 1D grid pointer
alpha_x	Coefficient vector for new grid (grid_x). Will be initialized.
dim_x	Target dimension, all other dimensions will be marginalized

Implements sgpp::datadriven::OperationDensityMargTo1D.

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

Referenced by ~OperationDensityMargTo1DLinear().

void sgpp::datadriven::OperationDensityMargTo1DLinear::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

alpha	Coefficient vector for current grid
grid_x	output 1D grid pointer
alpha_x	Coefficient vector for new grid (grid_x). Will be initialized.
dim_x	Target dimension, all other dimensions will be marginalized

Implements sgpp::datadriven::OperationDensityMargTo1D.

References sgpp::datadriven::OperationDensityMargTo1D::computeMarginalizationIndices(), sgpp::base::Grid::getDimension(), grid, and marg_next_dim().

Referenced by margToDimX(), and ~OperationDensityMargTo1DLinear().

Member Data Documentation

base::Grid* sgpp::datadriven::OperationDensityMargTo1DLinear::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::getGrid(), python.uq.learner.Regressor.Regressor::learnData(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), margToDimX(), and margToDimXs().

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

• datadriven/src/sgpp/datadriven/operation/hash/simple/OperationDensityMargTo1DLinear.hpp
• datadriven/src/sgpp/datadriven/operation/hash/simple/OperationDensityMargTo1DLinear.cpp