Source: python-bayesian-optimization
Section: python
Priority: optional
Maintainer: Adam Cecile <acecile@le-vert.net>
Build-Depends: debhelper (>= 9),
 dh-python,
 python3-all,
 python3-setuptools,
 python3-pytest <!nocheck>,
 python3-numpy <!nocheck>,
 python3-scipy <!nocheck>,
 python3-sklearn <!nocheck>,
 lsb-release,
Standards-Version: 4.1.3
Homepage: https://github.com/fmfn/BayesianOptimization
X-Python-Version: >= 2.7
X-Python3-Version: >= 3.4

Package: python3-bayes-opt
Architecture: all
Depends: ${python3:Depends}, ${misc:Depends}
Suggests: python-bayes-opt-doc
Description: Python implementation of optimization with gaussian processes (Python 3)
 This is a constrained global optimization package built upon bayesian
 inference and gaussian process, that attempts to find the maximum value of
 an unknown function in as few iterations as possible.
 .
 This technique is particularly suited for optimization of high cost
 functions, situations where the balance between exploration and
 exploitation is important.
 .
 This package installs the library for Python 3.

Package: python-bayes-opt-doc
Architecture: all
Section: doc
Depends: ${sphinxdoc:Depends}, ${misc:Depends}
Description: Python implementation of optimization with gaussian processes (common doc)
 This is a constrained global optimization package built upon bayesian
 inference and gaussian process, that attempts to find the maximum value of
 an unknown function in as few iterations as possible.
 .
 This technique is particularly suited for optimization of high cost
 functions, situations where the balance between exploration and
 exploitation is important.
 .
 This is the common documentation package.
