This repository provides the implementation of benchmark functions for Bayesian optimization. The details of benchmark functions can be found in these notes.
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 the following in the bayeso-benchmarks
root.
pip install .
- Using source code (for editable development mode)
To use editable development mode, command the following in the bayeso-benchmarks
root.
pip install -e .
If you want to install the packages required for development, you can simply add [dev]
.
For example, pip install .[dev]
or pip install -e .[dev]
.
- Uninstallation
If you would like to uninstall bayeso-benchmarks
, command it.
pip uninstall bayeso-benchmarks
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)
@misc{KimJ2023software,
author={Kim, Jungtaek},
title={{BayesO Benchmarks}: Benchmark Functions for {Bayesian} Optimization},
doi={10.5281/zenodo.7577330},
url={https://github.com/jungtaekkim/bayeso-benchmarks},
howpublished={\url{https://doi.org/10.5281/zenodo.7577330}},
year={2023}
}