Metadata-Version: 1.0
Name: seeds
Version: 1.0.6
Summary: Stochastic Ecological and Evolutionary Dynamics System
Home-page: https://github.com/briandconnelly/seeds
Author: Brian Connelly
Author-email: bdc@msu.edu
License: Apache Version 2
Download-URL: https://github.com/downloads/briandconnelly/seeds/seeds-1.0.6.tar.gz
Description: ==============================================================
        SEEDS - Stochastic Ecological and Evolutionary Dynamics System
        ==============================================================
        
        :Created by:
            Brian Connelly <bdc@msu.edu> and Luis Zaman <zamanlui@msu.edu>
        :Website:
            https://github.com/briandconnelly/seeds
        
        
        Expanded Documentation:
        -----------------------
        The primary source for documentation is the SEEDS Wiki_.  Here, detailed
        installation instructions, how-to guides, code templates, and example
        experiments are provided.
        
        
        Installing SEEDS:
        -------------------
        SEEDS requires Python version 2.6.5 or greater.  Additionally, SEEDS requires
        the NetworkX_ package.
        
        Installation is done using the standard Python Distribution Utilities and can
        be as straightforward as running "python setup.py install".  For further
        instructions on this process, please see the SEEDS Wiki_ or the official
        Distutils documentation at http://docs.python.org/install/index.html.
        
        
        Running SEEDS:
        --------------
        Out of the box, SEEDS includes simple experiments in the examples directory.
        These experiments can be run once SEEDS has been installed on your system.
        See the README.txt file in a specific directory to learn about the experiment,
        how to configure it, and how to perform it.
        
        
        Expanding SEEDS:
        ----------------
        SEEDS is designed as a plugin-based framework.  This means that you can
        create and use your own cell types, topologies, and actions and use these
        immediately without modifying the base SEEDS framework.
        
        To create experiments that model behaviors of interest to you, a Cell type will
        need to be created.  More information on this process can be found on the
        SEEDS website.  Additionally, sample Cell types can be found in the examples
        directory.
        
        Once you have created your additional types or actions, place them in a
        directory called "plugins", and edit seeds.cfg, instructing the experiment to
        use them.  For cell types, change the value of the "cell" parameter in the
        "Experiment" section.  For topologies, change the value of the "topology"
        parameter in the "Experiment" section.  For actions, add it to the
        comma-separated "actions" parameter in the "Experiment" section.  Parameters to
        your plugins can be set in the seeds.cfg file in the section you define in
        your code.
        
        
        Reporting Bugs and Feature Requests:
        ------------------------------------
        SEEDS is under constant development.  To see which features and changes are
        planned or to report bugs, visit http://github.com/briandconnelly/seeds/issues.
        
        
        License:
        --------
        Seeds is released under the `Apache License, Version 2.0`__.  For more
        information, see the files LICENSE.txt_ and NOTICE.txt_.
        
        
        .. _Wiki: https://github.com/briandconnelly/seeds/wiki
        .. _NetworkX: http://networkx.lanl.gov/
        .. _Apache: http://www.apache.org/licenses/LICENSE-2.0
        __ Apache_
        .. _LICENSE.txt: https://github.com/briandconnelly/seeds/blob/master/LICENSE.txt
        .. _NOTICE.txt: https://github.com/briandconnelly/seeds/blob/master/NOTICE.txt
        
Keywords: simulation,evolution,ecology
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Life
