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        "author": "Pedro C. de Siracusa",
        "author_email": "pedrosiracusa@gmail.com",
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        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "Caryocar\n========\n\nCaryocar is a Python package for building Species-Collector Networks (SCNs) and Collector CoWorking Networks(CWNs) models from species occurrence data, as introduced in my [MSc thesis](https://lncc-netsci.github.io/pedrocs/).\nSCNs and CWNs extend the social network analytics and can be used for understanding the social structure behind biological collections.\nThis package is built on top of [NetworkX](https://github.com/networkx/networkx).\n\n\n### Supporting documents\n* New perspectives on analyzing data from biological collections based on social network analytics [[MSc thesis](https://tede.lncc.br/handle/tede/279)].\n* On the social structure behind biological collections [[Preprint](https://www.biorxiv.org/content/early/2018/06/08/341297)].\n* Package documentation coming soon...\n\n\nExample Usage\n-------------\nCreate a Species-Collector Network (SCN) from a list of collectors and species:\n\n    >>> cols=[ ['col1','col2','col3'],\n               ['col1','col2'],\n               ['col2','col3'],\n               ['col4','col5'],\n               ['col4'],\n               ['col5','col4'] ]\n\n    >>> spp=['sp1','sp2','sp3','sp2','sp3','sp2']\n\n    >>> scn = SpeciesCollectorsNetwork( species=spp, collectors=cols )\n\n    >>> scn.nodes(data=True)\n    { 'sp1': {'bipartite': 1, 'count': 1}, \n      'col1': {'bipartite': 0, 'count': 2}, \n      'col2': {'bipartite': 0, 'count': 3}, \n      'col3': {'bipartite': 0, 'count': 2}, \n      'sp2': {'bipartite': 1, 'count': 3}, \n      'sp3': {'bipartite': 1, 'count': 2}, \n      'col4': {'bipartite': 0, 'count': 3}, \n      'col5': {'bipartite': 0, 'count': 2} }\n\n    >>> scn.edges(data=True)\n    [ ('sp1', 'col1', {'count': 1}), \n      ('sp1', 'col2', {'count': 1}), \n      ('sp1', 'col3', {'count': 1}), \n      ('col1', 'sp2', {'count': 1}), \n      ('col2', 'sp2', {'count': 1}), \n      ('col2', 'sp3', {'count': 1}), \n      ('col3', 'sp3', {'count': 1}), \n      ('sp2', 'col4', {'count': 2}), \n      ('sp2', 'col5', {'count': 2}), \n      ('sp3', 'col4', {'count': 1}) ]    \n\n\n\nCreate a Collector CoWorking Network (CWN) from a list of collector cliques:\n\n\t\t>>> collectors = [ ['a','b','c'], ['d','e'], ['a','c'] ]\n    >>> cwn = CoworkingNetwork(cliques=collectors)\n\n    >>> cwn.nodes(data=True)\n    { 'a': {'count': 2}, \n      'b': {'count': 1}, \n      'c': {'count': 2}, \n      'd': {'count': 1}, \n      'e': {'count': 1} }    \n\n    >>> cwn.edges(data=True)\n    [ ('a', 'b', {'count': 1, 'taxons': None, 'weight_hyperbolic': 0.5}), \n      ('a', 'c', {'count': 2, 'taxons': None, 'weight_hyperbolic': 1.5}), \n      ('b', 'c', {'count': 1, 'taxons': None, 'weight_hyperbolic': 0.5}), \n      ('d', 'e', {'count': 1, 'taxons': None, 'weight_hyperbolic': 1.0}) ]\n\n\nInstall\n-------\n\nThis package is still experimental, and should ideally be run from a conda virtual environment, which is specified in the `environment.yml` file. In order to create the virtual environment clone this repository, make sure you have [conda](https://conda.io/docs/) installed and use one of the following commands, from the root of the repository:\n\n    $ conda env create -f environment.yml\n\nThen you should activate it with the following command:\n\n* On Linux:\n\n\n    $ source activate caryocar\n\n\n* On Windows:\n\n\n    $ activate caryocar\n\n\n\n",
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