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Symbolic regression tools.

Project description

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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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0.3.5

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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

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