sgpp::datadriven::OperationRosenblattTransformationBspline Class Reference

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

#include <OperationRosenblattTransformationBspline.hpp>

Inheritance diagram for sgpp::datadriven::OperationRosenblattTransformationBspline:

Public Member Functions
void	doTransformation (base::DataVector *alpha, base::DataMatrix *points, base::DataMatrix *pointscdf)
	Transformation with mixed starting dimensions. More...
void	doTransformation (base::DataVector *alpha, base::DataMatrix *points, base::DataMatrix *pointscdf, size_t dim_start)
	Transformation with specified starting dimension. More...
	OperationRosenblattTransformationBspline (base::Grid *grid)
virtual	~OperationRosenblattTransformationBspline ()
Public Member Functions inherited from sgpp::datadriven::OperationRosenblattTransformation
	OperationRosenblattTransformation ()
virtual	~OperationRosenblattTransformation ()

Protected Member Functions
virtual double	doTransformation1D (base::Grid *grid1d, base::DataVector *alpha1d, double coord1d)
void	doTransformation_in_next_dim (base::Grid *g_in, base::DataVector *a_in, size_t dim_x, base::DataVector *coords1d, base::DataVector *cdfs1d, size_t &curr_dim)
void	doTransformation_start_dimX (base::Grid *g_in, base::DataVector *a_in, size_t dim_start, base::DataVector *coords1d, base::DataVector *cdfs1d)

Protected Attributes
base::Grid *	grid

Detailed Description

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

Constructor & Destructor Documentation

OperationRosenblattTransformationBspline()

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

inlineexplicit

~OperationRosenblattTransformationBspline()

virtual sgpp::datadriven::OperationRosenblattTransformationBspline::~OperationRosenblattTransformationBspline ( )

inlinevirtual

References alpha, doTransformation(), and python.leja::points.

Member Function Documentation

doTransformation() [1/2]

void sgpp::datadriven::OperationRosenblattTransformationBspline::doTransformation ( base::DataVector *  alpha, base::DataMatrix *  points, base::DataMatrix *  pointscdf  )

virtual

Transformation with mixed starting dimensions.

Parameters

alpha	Coefficient vector for current grid
points	Input Matrix
pointscdf	Output Matrix

Implements sgpp::datadriven::OperationRosenblattTransformation.

References sgpp::op_factory::createOperationDensityMargTo1D(), doTransformation1D(), doTransformation_start_dimX(), sgpp::base::DataMatrix::get(), sgpp::base::Grid::getDimension(), sgpp::base::DataMatrix::getNrows(), sgpp::base::DataMatrix::getRow(), grid, python.statsfileInfo::i, sgpp::base::DataMatrix::set(), and sgpp::base::DataMatrix::setRow().

Referenced by ~OperationRosenblattTransformationBspline().

doTransformation() [2/2]

void sgpp::datadriven::OperationRosenblattTransformationBspline::doTransformation ( base::DataVector *  alpha, base::DataMatrix *  points, base::DataMatrix *  pointscdf, size_t  dim_start  )

virtual

Transformation with specified starting dimension.

Parameters

alpha	Coefficient vector for current grid
points	Input Matrix
pointscdf	Output Matrix
dim_start	Starting dimension

Implements sgpp::datadriven::OperationRosenblattTransformation.

References sgpp::op_factory::createOperationDensityMargTo1D(), doTransformation1D(), doTransformation_start_dimX(), sgpp::base::DataMatrix::get(), sgpp::base::DataMatrix::getNcols(), sgpp::base::DataMatrix::getNrows(), sgpp::base::DataMatrix::getRow(), grid, python.statsfileInfo::i, sgpp::base::DataMatrix::set(), and sgpp::base::DataMatrix::setRow().

doTransformation1D()

double sgpp::datadriven::OperationRosenblattTransformationBspline::doTransformation1D ( base::Grid *  grid1d, base::DataVector *  alpha1d, double  coord1d  )

protectedvirtual

References sgpp::op_factory::createOperationRosenblattTransformation1D().

Referenced by doTransformation(), and doTransformation_in_next_dim().

doTransformation_in_next_dim()

void sgpp::datadriven::OperationRosenblattTransformationBspline::doTransformation_in_next_dim ( base::Grid *  g_in, base::DataVector *  a_in, size_t  dim_x, base::DataVector *  coords1d, base::DataVector *  cdfs1d, size_t &  curr_dim  )

protected

References sgpp::op_factory::createOperationDensityConditional(), sgpp::op_factory::createOperationDensityMargTo1D(), sgpp::datadriven::OperationDensityConditional::doConditional(), doTransformation1D(), sgpp::base::DataVector::get(), sgpp::base::Grid::getDimension(), sgpp::base::DataVector::getSize(), sgpp::datadriven::OperationDensityMargTo1D::margToDimX(), and sgpp::base::DataVector::set().

Referenced by doTransformation_start_dimX().

doTransformation_start_dimX()

void sgpp::datadriven::OperationRosenblattTransformationBspline::doTransformation_start_dimX ( base::Grid *  g_in, base::DataVector *  a_in, size_t  dim_start, base::DataVector *  coords1d, base::DataVector *  cdfs1d  )

protected

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

Referenced by doTransformation().

Member Data Documentation

grid

base::Grid* sgpp::datadriven::OperationRosenblattTransformationBspline::grid

protected

Referenced by python.uq.learner.Interpolant.Interpolant::doLearningIteration(), doTransformation(), 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/OperationRosenblattTransformationBspline.hpp
• datadriven/src/sgpp/datadriven/operation/hash/simple/OperationRosenblattTransformationBspline.cpp