smt


Namesmt JSON
Version 0.8.0 PyPI version JSON
download
home_pagehttps://github.com/SMTorg/smt
SummaryThe Surrogate Modeling Toolbox (SMT)
upload_time2021-01-18 08:43:07
maintainer
docs_urlNone
authorMohamed Amine Bouhlel et al.
requires_python>=3.6
licenseBSD-3
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            
The surrogate modeling toolbox (SMT) is a Python package that contains 
a collection of surrogate modeling methods, sampling techniques, and 
benchmarking functions. This package provides a library of surrogate 
models that is simple to use and facilitates the implementation of additional methods. 

SMT is different from existing surrogate modeling libraries because of 
its emphasis on derivatives, including training derivatives used for 
gradient-enhanced modeling, prediction derivatives, and derivatives 
with respect to the training data. It also includes new surrogate models 
that are not available elsewhere: kriging by partial-least squares reduction 
and energy-minimizing spline interpolation.



            

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