VOPy 0.1.1

A framework for black-box vector optimization

Vector Optimization with Active Learning

What is VOPy?

VOPy is an open-source Python library built to address noisy black-box vector optimization problems, where the user preferences are encoded with a cone order.

What to do with VOPy?

VOPy includes several pre-implemented algorithms, models, orders, and problems from the literature for black-box vector optimization, allowing users to select and utilize components based on their specific needs. Specifically, you can:

• Using existing methods for novel problems
• Benchmark novel algorithms with literature
• ... and anything in between utilizing wide range of existing tools!

How To Start?

Visit our website to see tutorials, examples and API references on how to use VOPy.

Setup

Installation using pip:

pip install vopy

Latest (Unstable) Version

To upgrade to the latest (unstable) version, run

pip install --upgrade git+https://github.com/Bilkent-CYBORG/VOPy.git

Manual installation (for development)

If you are contributing a pull request, it is best to perform a manual installation:

git clone https://github.com/Bilkent-CYBORG/VOPy.git
cd VOPy
mamba env create --name vopy --file environment.yml  # To setup a proper development environment
pip install -e .

For all development requirements, see requirements.txt or environment.yml.

Further, installing the pre-commit hooks are highly encouraged.

# Inside the package folder
pre-commit install