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 Copyright Developer Manual On this page, we describe best coding practices for SG++ ▼Usage Examples This is a collection of examples from all modules ▼C++ Examples This is a list of all C++ examples Using the DataMatrix object This example shows how to initialize a DataMatrix object, store it to a file and then to restore it back Using the DataVector object This example shows how to initialize a DataVector object, store it to a file and then to restore it back Detect the configuration of OpenCL platforms This code detects the configuration of the OpenCL platforms available on the machine and outputs it to a file Interaction-Term aware sparse grids. This example shows how grids with more interaction terms differ from simpler grids Generalised Sparse Grids This example creates a generalised grid Using JSON This example demonstrates how to use the basic functionality of SG++ JSON API Spatially-Dimension-Adaptive Refinement in C++ We compute the sparse grid interpolant of the function $$f(x) = \sin(\pi x).$$ We perform spatially-dimension-adaptive refinement of the sparse grid model, which means we refine a particular grid point (locality) only in some dimensions (dimensionality) Quadrature in C++ The following example shows how to integrate in SG++, using both direct integration of a sparse grid function and the use of Monte Carlo integration Refinement Example Here we demonstrate how to refine a grid tutorial.cpp (Start Here) To be able to quickly start with a toolkit, it is often advantageous (not only for the impatient users), to look at some code examples first Grid unserialization In this example we show how to store a grid into a file and how to load it back into a sgpp::base::Grid object List of different Grid Types This example is supposed to simply demonstrate the available grid, boundary and basis function types bspline_pce.cpp This example can be found under combigrid/examples/bspline_pce.cpp Stochastic Collocation with B-Spline Combigrids gettingStarted.cpp (Start Here) This tutorial contains examples with increasing complexity to introduce you to the combigrid module interpolation.cpp This example can be found under combigrid/examples/interpolation.cpp PCE with Combigrids This simple example shows how to create a Polynomial Chaos Expansion from an adaptively refined combigrid performance.cpp This example can be found under combigrid/examples/performance.cpp Stochastic Collocation with Combigrids This simple example shows how to create a Stochastic Collocation surrogate from a regular combigrid benchmark_OrthoAdapt.cpp This example can be found under datadriven/examples/benchmark_OrthoAdapt.cpp buildMats.cpp This example can be found under datadriven/examples/buildMats.cpp Classification Example This example shows how classification specific refinement strategies are used Learner Classification Test This represents a small example how to use sparse grids for classification problems Regression Learner This example demonstrates sparse grid regression learning Learner SGDE Online This example shows how to perform online-classification using sparse grid density estimation and conjugate gradients method Learner SGDE OnOff This example shows how to perform offline/online-classification using sparse grid density estimation and matrix decomposition methods learner SGDE This examples demonstrates density estimation learner SGDE This examples demonstrates density estimation Learner SGD This example shows how to perform online-classification using sparse grids and averaged stochastic gradient descent method Learner SVM This example shows how to perform online-classification using the support vector machine with sparse grid kernels Classification Example MultipleClassRefinement Helper to create learner new_sgde.cpp This example can be found under datadriven/examples/new_sgde.cpp optimize_kde_bandwidth.cpp This example can be found under datadriven/examples/optimize_kde_bandwidth.cpp constrainedOptimization.cpp This example demonstrates the optimization of an objective function $$f$$ with additional constraints optimization.cpp On this page, we look at an example application of the sgpp::optimization module FISTA Solver This example demonstrates the FISTA solver for a toy dataset using using the elastic net regularization method with various regularization penalties ▼Python Examples This is a list of all Python examples Using the DataMatrix object This example shows how to initialize a DataMatrix object, store it to a file and then to restore it back Using the DataVector object This example shows how to initialize a DataVector object, store it to a file and then to restore it back Generalised Sparse Grids This example creates a generalised grid Spatially-Dimension-Adaptive Refinement of ANOVA Components in Python We compute the sparse grid interpolant of the function $$f(x) = \sin(10x_0)+x_1.$$ We perform spatially-dimension-adaptive refinement of the sparse grid model, which means we refine a particular grid point (locality) only in some dimensions (dimensionality) Spatially-Dimension-Adaptive Refinement in Python We compute the sparse grid interpolant of the function $$f(x) = \sin(\pi x).$$ We perform spatially-dimension-adaptive refinement of the sparse grid model, which means we refine a particular grid point (locality) only in some dimensions (dimensionality) Quadrature in Python The following example shows how to integrate in SG++, using both direct integration of a sparse grid function and the use of Monte Carlo integration refinement.py Here we demonstrate how to refine a grid Dimension-Adaptive Refinement in Python We compute the sparse grid interpolant of the function $$f(x) = \sin(10x_0)+x_1.$$ We perform dimension-adaptive refinement of the sparse grid model, which means we add a complete hierarchical subspace in some dimensions tutorial.py (Start Here) To be able to quickly start with a toolkit, it is often advantageous (not only for the impatient users), to look at some code examples first bSplines.py Plots anisotropic full grids that form part of the combination technique convergence.py Simple code that provides convergence plots for various analytic models example_comparison.py gettingStarted.py (Start Here) This tutorial contains examples with increasing complexity to introduce you to the combigrid module gridConverter.py This tutorial contains examples on how to convert sparse grids with a hierarchical basis to a sparse grid defined on the combination of anisotropic full grids (combination technique) PCE with Combigrids (Python) This simple example shows how to create a Polynomial Chaos Expansion from an adaptively refined combigrid plot_2d_sparse_grids.py Plots anisotropic full grids that form part of the combination technique Point Distributions (Python) This simple example demonstrates the different types of 1-D point distributions available in the combigrid module Gaussian Weight Priors This example compares two different Gaussian priors for sparse grid regression Generalised Sparse Grids This example tests generalised sparse grids Interaction Terms Aware Sparse Grids This example compares standard sparse grids with sparse grids that only contain a subset of all possible interaction terms learnerExample.py This example can be found under datadriven/examples/learnerExample.py learnerSGDETest.py This example can be found under datadriven/examples/learnerSGDETest.py positive_density.py This example can be found under datadriven/examples/positive_density.py Calculating the regularization path This example generates a regularization path for sparsity-inducing penalties test_Rosenblatt.py This example can be found under datadriven/examples/test_Rosenblatt.py test_sgdeLaplace.py This example can be found under datadriven/examples/test_sgdeLaplace.py resumingLearningProcess.py This is an example of how to resume the learning process from a checkpoint without recalculating the last iteration optimization.py On this page, we look at an example application of the sgpp::optimization module LTwoDotTest.py This example can be found under pde/examples/LTwoDotTest.py ▼Java Examples This is a list of all Java examples Refinement Example Here we demonstrate how to refine a grid tutorial.java (Start Here) To be able to quickly start with a toolkit, it is often advantageous (not only for the impatient users), to look at some code examples first Learner SGDE This tutorial demostrates the sparse grid density estimation optimization.java On this page, we look at an example application of the sgpp::optimization module ▼MATLAB Examples This is a list of all MATLAB examples tutorial.m (Start Here) To be able to quickly start with a toolkit, it is often advantageous (not only for the impatient users), to look at some code examples first optimization.m On this page, we look at an example application of the sgpp::optimization module Integrate Dakota Install and enable Dakota for sgpp::combigrid module Todo List Deprecated List