We present Glyph - a Python package for genetic programming based symbolic regression. Glyph is designed for usage let by numerical simulations let by real world experiments. For experimentalists, glyph-remote provides a separation of tasks: a ZeroMQ interface splits the genetic programming optimization task from the evaluation of an experimental (or numerical) run. Glyph can be accessed at http://github.com/ambrosys/glyph . Domain experts are be able to employ symbolic regression in their experiments with ease, even if they are not expert programmers. The reuse potential is kept high by a generic interface design. Glyph is available on PyPI and Github.
@article{arxiv.1803.06226,
title = {Glyph: Symbolic Regression Tools},
author = {Markus Quade and Julien Gout and Markus Abel},
journal= {arXiv preprint arXiv:1803.06226},
year = {2018}
}
Comments
Submitted to JOSR. arXiv admin note: text overlap with arXiv:1612.05276