Metadata-Version: 2.1
Name: generations
Version: 1.3.0
Summary: A set of recursive population models for ecologists
Home-page: https://github.com/alfalimajuliett/generations
Author: M. Marek-Spartz
Author-email: patt0335@umn.edu
License: UNKNOWN
Description: # generations
        
        A set of recursive population models for ecologists including:
        
        - Nicholson Bailey host-parasitoid model
        - Weed-herbivore coupled model for an annual plant that forms a seed bank from [Buckley et al. 2005](http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2664.2005.00991.x/epdf)
        - Weed-herbivore model for a biennial plant that forms a seed bank
        
        
        ## Installation
        
        Generations is available from the [Python Package Index](https://pypi.org/project/generations/). It can be installed using `pip`:
        
            pip install generations
        
        
        ## Running
        
        Once installed, the user can run the various models in `generations` by entering the following commands. Python's `-m` flag imports and runs the specified module. Each population model in `generations` is in it's own module:
        
            python -m generations.nicholson_bailey
        
            python -m generations.buckley
        
            python -m generations.biennial
        
        ### Visualization
        
        Generations requires the [Bokeh](https://pypi.org/project/bokeh/) Python package to generate interactive plots of the simulation outputs in the browser. This functionality is attached to each modeling module. When the module runs, it automatically generates a .csv of the population densities for each organism at each time step Bokeh uses that .csv to automatically generate an html page with an interactive plot of the results in the user's browser. 
        
        
        ### Custom parameters
        
        The user can also create a copy of the default configuration file for the population model modules in their working directory. The file will be named `model_parameters.cfg`.
        
            python -m generations.create_config
        
        The user can then edit parameters to fit their desired ecological system. Model parameters will be loaded from the working directory into the population models at runtime.
        
        
        ## Development
        
        Generations source code is available on [GitHub](https://github.com/alfalimajuliett/generations).
        
            git clone https://github.com/alfalimajuliett/generations.git
        
        
        ### Testing
        
            ./test.sh
        
        This will run the unit tests. If you have [pipenv](https://docs.pipenv.org/), it will also run a number of other checks:
        
        - [`yapf`](https://github.com/google/yapf/): reformat the code automatically
        - [`mypy`](http://mypy-lang.org): check for runtime errors like misnamed imports or variables, or incompatible types
        - [`tox`](https://tox.readthedocs.io/en/latest/): run the unit tests against Python 2.7 and 3.7
        - [`coverage`](https://github.com/nedbat/coveragepy): report on lines that are not covered by unit tests
        
        
        ### Uploading to PyPI
        
        Install [pipenv](https://docs.pipenv.org/#install-pipenv-today) if you don't have it.
        
        Increment the version in `setup.py`.
        
        Run the tests one last time:
        
            ./test.sh
        
        Build the distribution files:
        
            pipenv run python3 setup.py sdist bdist_wheel
        
        Upload using [`twine`](https://github.com/pypa/twine). It will prompt for your PyPI password:
        
            pipenv run twine upload dist/*
        
        Commit the version, create a tag, and push tags:
        
            git commit -am "$version"
            git tag $version
            git push --tags
            git push
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Classifier: Environment :: Console
Description-Content-Type: text/markdown
