Symbolic regression tools.
Project description
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.
Installation
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
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
Documentation
The online documentation is available at glyph.readthedocs.io.
Bugs, feature requests, contributions
Please use the issue tracker and the mailing list. For contributions have a look at out contribution guide.
Project details
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