Metadata-Version: 1.1
Name: pyam
Version: 0.2.1-alpha
Summary: Python package for solving assortative matching models with two-sided heterogeneity.
Home-page: https://github.com/davidrpugh/pyAM
Author: davidrpugh
Author-email: david.pugh@maths.ox.ac.uk
License: MIT License
Description: pyAM
        ====
        
        |Build Status| |Coverage Status| |Codacy Badge| |GitHub License| |Latest Version| |Downloads| |DOI|
        
        .. |Build Status| image:: https://travis-ci.org/davidrpugh/pyAM.svg?branch=master
           :target: https://travis-ci.org/davidrpugh/pyAM
        .. |Coverage Status| image:: https://coveralls.io/repos/davidrpugh/pyAM/badge.svg?branch=master
           :target: https://coveralls.io/github/davidrpugh/pyAM?branch=master
        .. |Codacy Badge| image:: https://www.codacy.com/project/badge/f051d7b5ccce47cfa3d6907c9a1bd6bf
           :target: https://www.codacy.com/app/drobert-pugh/pyAM
        .. |GitHub license| image:: https://img.shields.io/github/license/davidrpugh/pyAM.svg
           :target: https://img.shields.io/github/license/davidrpugh/pyAM.svg
        .. |Latest Version| image:: https://img.shields.io/pypi/v/pyAM.svg
           :target: https://pypi.python.org/pypi/pyAM/
        .. |Downloads| image:: https://img.shields.io/pypi/dm/pyAM.svg
           :target: https://pypi.python.org/pypi/pyAM/
        .. |DOI| image:: https://zenodo.org/badge/doi/10.5281/zenodo.22396.svg   
           :target: http://dx.doi.org/10.5281/zenodo.22396
        
        Python package for solving assortative matching models with two-sided heterogeneity.  The theoretical framework behind the class of models solved by pyAM is described in `Eeckhout and Kircher (2012)`_.
        
        .. _`Eeckhout and Kircher (2012)`: http://homepages.econ.ed.ac.uk/~pkircher/Papers/Sorting-and-Factor-Intensity.pdf
        
        Installation
        ------------
        
        Assuming you have `pip`_ on your computer (as will be the case if you've `installed Anaconda`_) you can install the latest stable release of ``pyam`` by typing
            
        .. code:: bash
        
            $ pip install pyam
        
        at a terminal prompt.
        
        .. _pip: https://pypi.python.org/pypi/pip
        .. _`installed Anaconda`: http://quant-econ.net/getting_started.html#installing-anaconda
        
        Contributing
        ------------
        If you wish to contribute to the project you will likely want to install from source. First your will need to fork and then clone the source repository.
        
        .. code:: bash
        
            $ git clone https://github.com/YOUR-USERNAME/pyAM.git 
        
        Next create a new `conda` development environment 
        
        .. code:: bash
            
            $ conda create -n pyam-dev python anaconda
        
        activate the newly created development environment
        
        .. code:: bash
        
            $ source activate pyam-dev
        
        and install additional dependencies not available within Anaconda.
        
        .. code:: bash
        
            $ pip install pycollocation
            $ pip install seaborn
        
        Finally, change into your local clone of the `pyam` source directory and install the package in development mode.
        
        .. code:: bash
        
            $ pip install -e .
        
        
        Example notebooks
        -----------------
        At the moment there are two example notebooks, one for `positive assortative matching`_ and one for `negative assortative matching`_ in the `examples` directory.  The positive assortative matching works fine; the negative assortative matching, however, does not yet work (I suspect because of a poor algorithm for the initial guess).
        
        .. _`positive assortative matching`: https://github.com/davidrpugh/pyAM/blob/master/examples/positive-assortative-matching.ipynb
        .. _`negative assortative matching`: https://github.com/davidrpugh/pyAM/blob/master/examples/negative-assortative-matching.ipynb
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering
