Metadata-Version: 2.1
Name: pygom
Version: 0.1.7
Summary: ODE modeling in Python
Home-page: https://github.com/PublicHealthEngland/pygom
Author: Thomas Finnie
Author-email: Thomas.Finnie@phe.gov.uk
License: GPL2
Description: ===============================
        pygom - ODE modelling in Python
        ===============================
        
        |Build status|  |Github actions|  |Documentation Status|  |pypi version|  |licence|
        
        .. |pypi version| image:: https://img.shields.io/pypi/v/pygom.svg
           :target: https://pypi.python.org/pypi/pygom
        .. |Build status| image:: https://travis-ci.org/PublicHealthEngland/pygom.svg?branch=master
           :target: https://travis-ci.org/PublicHealthEngland/pygom
        .. |Documentation Status| image:: https://readthedocs.org/projects/pygom/badge/?version=master
           :target: https://pygom.readthedocs.io/en/master/?badge=master
        .. |licence| image:: https://img.shields.io/pypi/l/pygom?color=green   :alt: PyPI - License
           :target: https://raw.githubusercontent.com/PublicHealthEngland/pygom/master/LICENSE.txt
        .. |Github actions| image:: https://github.com/PublicHealthEngland/pygom/workflows/pygom/badge.svg
           :target: https://github.com/PublicHealthEngland/pygom/actions/
        
        A generic framework for ode models, specifically compartmental type problems.
        
        This package depends on::
        
            dask
            matplotlib
            enum34
            pandas
            python-dateutil
            numpy
            scipy
            sympy
        
        and they should be installed if not already available.  Alternatively, the easier way
        to use a minimal (and isolated) setup is to use `conda <https://conda.io/docs/>`_ and
        create a new environment via::
        
          conda env create -f conda-env.yml
        
        Installation of this package can be performed via::
        
        $ python setup.py install
        
        and tested via::
        
        $ python setup.py test
        
        A reduced form of the documentation may be found on ReadTheDocs_.
        
        .. _ReadTheDocs: https://pygom.readthedocs.io/en/master/
        
        You may get the full documentation, including the lengthy examples by locally
        building the documentation found in the folder::
        
        $ doc
        
        Note that building the documentation can be extremely slow depending on the
        setup of the system.  Further details can be found at it's own read me::
        
        $ doc/README.rst
        
        Please be aware that if the module tests fails, then the documentation for the
        package will not compile.
        
        Please be aware that there may be redundant files within the package as it is
        under active development.
        
        Contributors
        ============
        Thomas Finnie (Thomas.Finnie@phe.gov.uk)
        
        Edwin Tye
        
        Hannah Williams
        
        Jonty Carruthers
        
        Martin Grunnill
        
        Version
        =======
        0.1.7 Add Approximate Bayesian Computation (ABC) as a method of fitting to data 
        
        0.1.6 Bugfix scipy API, pickling, print to logging and simulation
        
        0.1.5 Remove auto-simplification for much faster startup
        
        0.1.4 Much faster Tau leap for stochastic simulations
        
        0.1.3 Defaults to python built-in unittest and more in sync with conda
        
Platform: UNKNOWN
Description-Content-Type: text/x-rst
