heal-research / pyoperon

Python bindings and scikit-learn interface for the Operon library for symbolic regression.

pyoperon

pyoperon is the python bindings library of Operon, a modern C++ framework for symbolic regression developed by Heal-Research at the University of Applied Sciences Upper Austria.

A scikit-learn regressor is also available:

from pyoperon.sklearn import SymbolicRegressor

The example folder contains sample code for using either the Python bindings directly or the pyoperon.sklearn module.

Installation

Due to ABI incompatiblity, the PyOperon version on PyPI is outdated. The wheels are instead released on github: https://github.com/heal-research/pyoperon/releases/

Building from source

Conda/Mamba

1. Clone the repository

git clone https://github.com/heal-research/pyoperon.git
cd pyoperon

2. Install and activate the environment (replace micromamba with your actual program)

micromamba env create -f environment.yml
micromamba activate pyoperon

3. Install the dependencies

export CC=${CONDA_PREFIX}/bin/clang
export CXX=${CONDA_PREFIX}/bin/clang++
./script/dependencies.sh

4. Install pyoperon

pip install .

Nix

Use this environment created with poetry2nix

nix develop github:foolnotion/poetryenv --no-write-lock-file

This will install operon and dependencies. Modify the flake file if you need additional python libraries (see https://github.com/nix-community/poetry2nix#how-to-guides)

Contributing

See the CONTRIBUTING document.