Metadata-Version: 1.1
Name: pyglyph
Version: 0.3.2
Summary: Symbolic regression tools.
Home-page: https://www.github.com/ambrosys/glyph
Author: Markus Abel, Julien Gout, Markus Quade
Author-email: markus.quade@ambrosys.de
License: LGPL
Description: glyph - symbolic regression tools
        =================================
        
        |Build Status| |AppVeyor| |PyPI version| |codecov| |PythonVersion| |Licence| |DOI|
        
        **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 <https://github.com/Ambrosys/glyph/tree/master/examples>`__. 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 <https://glyph.readthedocs.io>`__.
        
        Bugs, feature requests, contributions
        -------------------------------------
        
        Please use the `issue
        tracker <https://github.com/Ambrosys/glyph/issues>`__ and the `mailing
        list <https://groups.google.com/forum/#!forum/pyglyph>`__. For
        contributions have a look at out `contribution
        guide <https://github.com/ambrosys/glyph/blob/master/.github/CONTRIBUTING>`__.
        
        .. |Build Status| image:: https://travis-ci.org/Ambrosys/glyph.svg?branch=master
           :target: https://travis-ci.org/Ambrosys/glyph
        .. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/rbl2b44yfnfk4owi/branch/master?svg=true
           :target: https://ci.appveyor.com/project/Ohjeah/glyph
        .. |PyPI version| image:: https://badge.fury.io/py/pyglyph.svg
           :target: https://badge.fury.io/py/pyglyph
        .. |codecov| image:: https://codecov.io/gh/Ambrosys/glyph/branch/master/graph/badge.svg
           :target: https://codecov.io/gh/Ambrosys/glyph
        .. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/pyglyph.svg
           :target: https://img.shields.io/pypi/pyversions/pyglyph.svg
        .. |Licence| image:: https://img.shields.io/pypi/l/pyglyph.svg
           :target: https://img.shields.io/pypi/l/pyglyph.svg
        .. |DOI| image:: https://zenodo.org/badge/75950324.svg
           :target: https://zenodo.org/badge/latestdoi/75950324
        
Keywords: complex systems,control,machine learning,genetic programming
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
