BayesO Benchmarks: Benchmark Functions for Bayesian Optimization

This repository provides the implementation of benchmark functions for Bayesian optimization. The details of benchmark functions can be found in these notes.

• https://bayeso.org

Installation

We recommend installing it with virtualenv. You can choose one of three installation options.

• Using PyPI repository (for user installation)

To install the released version in PyPI repository, command it.

$ pip install bayeso-benchmarks

• Using source code (for developer installation)

To install bayeso-benchmarks from source code, command

$ pip install .

in the bayeso-benchmarks root.

• Using source code (for editable development mode)

To use editable development mode, command

$ pip install -r requirements.txt
$ python setup.py develop

in the bayeso-benchmarks root.

• Uninstallation

If you would like to uninstall bayeso-benchmarks, command it.

$ pip uninstall bayeso-benchmarks

Required Packages

Mandatory pacakges are inlcuded in requirements.txt. The following requirements files include the package list, the purpose of which is described as follows.

• requirements-dev.txt: It is for developing the bayeso-benchmarks package.

Simple Example

A simple example on Branin function is shown below.

from bayeso_benchmarks import Branin

obj_fun = Branin()
bounds = obj_fun.get_bounds()

X = obj_fun.sample_uniform(100)

Y = obj_fun.output(X)
Y_noise = obj_fun.output_gaussian_noise(X)

License

MIT License