The sparse grids toolkit SG++ SG++ is a collection of numerical algorithms for sparse grids. It contains modules for interpolation, quadrature, data mining (regression, classification, clustering), optimization, PDEs, and more. SG++ implements algorithms for spatially adaptive grids and also provides a module for the combination technique. Many of the implemented algorithms are also available as a high-performance version, often orders of magnitude faster than standard implementations.
SG⁺⁺ is a library and framework for sparse grids in different flavors. SG⁺⁺ supports both hierarchical spatially-adaptive sparse grids and the dimensionally-adaptive sparse grid combination technique.
You are invited to use, contribute, discuss, …
The library is free to use, provided proper credit is given.
For more details and the API documentation, please visit http://sgpp.sparsegrids.org.
You can find binaries for Linux (deb) and MATLAB support in the SG++ releases.
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The sparse grids toolkit SG++ SG++ is a collection of numerical algorithms for sparse grids. It contains modules for interpolation, quadrature, data mining (regression, classification, clustering), optimization, PDEs, and more. SG++ implements algorithms for spatially adaptive grids and also provides a module for the combination technique. Many of the implemented algorithms are also available as a high-performance version, often orders of magnitude faster than standard implementations.
We found that pysgpp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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