Metadata-Version: 1.1
Name: clhs
Version: 1.0.2
Summary: Conditioned Latin Hypercube Sampling in Python
Home-page: https://github.com/wagoner47/clhs_py
Author: Erika Wagoner
Author-email: wagoner47+clhs@email.arizona.edu
License: MIT
Description: ==============================================================================
        cLHS: Conditioned Latin Hypercube Sampling
        ==============================================================================
        
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        Conditioned Latin Hypercube Sampling in Python.
        
        This code is based on the conditioned LHS method of
        `Minasny & McBratney (2006)`_. It follows some of the code from the R package
        clhs_ of Roudier et al.
        
        In short, this code attempts to create a Latin Hypercube sample by selecting
        only from input data. It uses simulated annealing to force the sampling to
        converge more rapidly, and also allows for setting a stopping criterion on
        the objective function described in Minasny & McBratney (2006).
        
        
        
        .. _Minasny & McBratney (2006): https://doi.org/10.1016/j.cageo.2005.12.009
        .. _clhs: https://CRAN.R-project.org/package=clhs
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Astronomy
