Gapsplit: efficient random sampling for non-convex constraint-based models.
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ABSTRACT: Summary
Gapsplit generates random samples from convex and non-convex constraint-based models by targeting under-sampled regions of the solution space. Gapsplit provides uniform coverage of linear, mixed-integer and general non-linear models.Availability and implementation
Python and Matlab source code are freely available at http://jensenlab.net/tools.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Keaty TC
PROVIDER: S-EPMC7178416 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
Gapsplit: efficient random sampling for non-convex constraint-based models.
Keaty Thomas C TC Jensen Paul A PA
Bioinformatics (Oxford, England) 20200401 8
<h4>Summary</h4>Gapsplit generates random samples from convex and non-convex constraint-based models by targeting under-sampled regions of the solution space. Gapsplit provides uniform coverage of linear, mixed-integer and general non-linear models.<h4>Availability and implementation</h4>Python and Matlab source code are freely available at http://jensenlab.net/tools.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online. ...[more]
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