sgpp::datadriven::OperationDensitySamplingLinear Class Reference

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

#include <OperationDensitySamplingLinear.hpp>

Inheritance diagram for sgpp::datadriven::OperationDensitySamplingLinear:

Public Member Functions
void	doSampling (base::DataVector *alpha, base::DataMatrix *&samples, size_t num_samples)
	Sampling with mixed starting dimensions. More...
void	doSampling (base::DataVector *alpha, base::DataMatrix *&samples, size_t num_samples, size_t dim_x)
	Sampling with specified starting dimension. More...
	OperationDensitySamplingLinear (base::Grid *grid)
virtual	~OperationDensitySamplingLinear ()
Public Member Functions inherited from sgpp::datadriven::OperationDensitySampling
	OperationDensitySampling ()
virtual	~OperationDensitySampling ()

Protected Member Functions
void	doSampling_in_next_dim (base::Grid *g_in, base::DataVector *a_in, size_t dim_x, base::DataVector *&sampleVec, size_t &curr_dim, unsigned int *seedp)
void	doSampling_start_dimX (base::Grid *g_in, base::DataVector *a_in, size_t dim_start, base::DataVector *&sampleVec, unsigned int *seedp)

Protected Attributes
base::Grid *	grid

Detailed Description

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

Constructor & Destructor Documentation

OperationDensitySamplingLinear()

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

inlineexplicit

~OperationDensitySamplingLinear()

virtual sgpp::datadriven::OperationDensitySamplingLinear::~OperationDensitySamplingLinear ( )

inlinevirtual

References alpha, doSampling(), and parabolasimple::samples.

Member Function Documentation

doSampling() [1/2]

void sgpp::datadriven::OperationDensitySamplingLinear::doSampling ( base::DataVector *  alpha, base::DataMatrix *&  samples, size_t  num_samples  )

virtual

Sampling with mixed starting dimensions.

Parameters

alpha	Coefficient vector for current grid
samples	Output DataMatrix (rows: # of samples, columns: # of dims)
num_samples	# of samples to draw

Implements sgpp::datadriven::OperationDensitySampling.

References chess::b, sgpp::op_factory::createOperationDensityMargTo1D(), sgpp::op_factory::createOperationDensitySampling1D(), sgpp::datadriven::OperationDensitySampling1D::doSampling1D(), doSampling_start_dimX(), sgpp::base::DataVector::get(), sgpp::base::Grid::getDimension(), sgpp::base::DataVector::getSize(), grid, python.statsfileInfo::i, python.utils.statsfile2gnuplot::j, sgpp::datadriven::OperationDensityMargTo1D::margToDimX(), sgpp::base::DataVector::set(), and sgpp::base::DataMatrix::set().

Referenced by ~OperationDensitySamplingLinear().

doSampling() [2/2]

void sgpp::datadriven::OperationDensitySamplingLinear::doSampling ( base::DataVector *  alpha, base::DataMatrix *&  samples, size_t  num_samples, size_t  dim_x  )

virtual

Sampling with specified starting dimension.

Parameters

alpha	Coefficient vector for current grid
samples	Output DataMatrix (rows: # of samples, columns: # of dims)
num_samples	# of samples to draw
dim_x	Starting dimension

Implements sgpp::datadriven::OperationDensitySampling.

References chess::b, sgpp::op_factory::createOperationDensityMargTo1D(), sgpp::op_factory::createOperationDensitySampling1D(), sgpp::datadriven::OperationDensitySampling1D::doSampling1D(), doSampling_start_dimX(), sgpp::base::DataVector::get(), sgpp::base::Grid::getDimension(), grid, python.statsfileInfo::i, python.utils.statsfile2gnuplot::j, sgpp::datadriven::OperationDensityMargTo1D::margToDimX(), sgpp::base::DataVector::set(), and sgpp::base::DataMatrix::set().

doSampling_in_next_dim()

void sgpp::datadriven::OperationDensitySamplingLinear::doSampling_in_next_dim ( base::Grid *  g_in, base::DataVector *  a_in, size_t  dim_x, base::DataVector *&  sampleVec, size_t &  curr_dim, unsigned int *  seedp  )

protected

References sgpp::op_factory::createOperationDensityConditional(), sgpp::op_factory::createOperationDensityMargTo1D(), sgpp::op_factory::createOperationDensitySampling1D(), sgpp::datadriven::OperationDensityConditional::doConditional(), sgpp::datadriven::OperationDensitySampling1D::doSampling1D(), sgpp::base::DataVector::get(), sgpp::base::Grid::getDimension(), sgpp::base::DataVector::getSize(), sgpp::datadriven::OperationDensityMargTo1D::margToDimX(), and sgpp::base::DataVector::set().

Referenced by doSampling_start_dimX().

doSampling_start_dimX()

void sgpp::datadriven::OperationDensitySamplingLinear::doSampling_start_dimX ( base::Grid *  g_in, base::DataVector *  a_in, size_t  dim_start, base::DataVector *&  sampleVec, unsigned int *  seedp  )

protected

References doSampling_in_next_dim(), and sgpp::base::DataVector::getSize().

Referenced by doSampling().

Member Data Documentation

grid

base::Grid* sgpp::datadriven::OperationDensitySamplingLinear::grid

protected

Referenced by python.uq.learner.Interpolant.Interpolant::doLearningIteration(), doSampling(), 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(), 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().

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

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