Symbolic regression tools.
glyph is a python 3 library based on deap providing abstraction layers for symbolic regression problems.
It comes with batteries included:
- predefined primitive sets
- n-dimensional expression tree class
- symbolic and structural constants
- interfacing constant optimization to scipy.optimize
- easy integration with joblib or dask.distributed
- symbolic constraints
- boilerplate code for logging, checkpointing, break conditions and command line applications
- rich set of algorithms
glyph also includes a plug and play command line application glyph-remote which lets non-domain experts apply symbolic regression to their optimization tasks.
Glyph is a python 3.5+ only package.
You can install the latest stable version from PyPI with pip
pip install pyglyph
or get the bleeding edge
pip install git+git://github.com/ambrosys/glyph.git#egg=glyph
Examples can be found in the repo. To run them you need to:
- Clone the repo.
- make init
- cd examples
- Run any example, e.g. python lorenz.py --help
The online documentation is available at glyph.readthedocs.io.
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|pyglyph-0.3.5-py3-none-any.whl (35.1 kB) Copy SHA256 hash SHA256||Wheel||py3||Jan 22, 2018|
|pyglyph-0.3.5.tar.gz (47.4 kB) Copy SHA256 hash SHA256||Source||None||Jan 22, 2018|