SG++-Doxygen-Documentation
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keep applying marginalize to function until it's reduced to only 1 dimension More...
#include <OperationRosenblattTransformationPolyClenshawCurtisBoundary.hpp>
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... | |
OperationRosenblattTransformationPolyClenshawCurtisBoundary (base::Grid *grid) | |
virtual | ~OperationRosenblattTransformationPolyClenshawCurtisBoundary () |
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 |
keep applying marginalize to function until it's reduced to only 1 dimension
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inlineexplicit |
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inlinevirtual |
References alpha, doTransformation(), and python.leja::points.
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virtual |
Transformation with mixed starting dimensions.
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 ~OperationRosenblattTransformationPolyClenshawCurtisBoundary().
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virtual |
Transformation with specified starting dimension.
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().
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protectedvirtual |
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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().
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References doTransformation_in_next_dim(), and sgpp::base::DataVector::getSize().
Referenced by doTransformation().
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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().