Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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91 lines
2.3 KiB
91 lines
2.3 KiB
4 years ago
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"""
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**************
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Pickled Graphs
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**************
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Read and write NetworkX graphs as Python pickles.
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"The pickle module implements a fundamental, but powerful algorithm
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for serializing and de-serializing a Python object
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structure. "Pickling" is the process whereby a Python object hierarchy
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is converted into a byte stream, and "unpickling" is the inverse
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operation, whereby a byte stream is converted back into an object
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hierarchy."
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Note that NetworkX graphs can contain any hashable Python object as
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node (not just integers and strings). For arbitrary data types it may
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be difficult to represent the data as text. In that case using Python
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pickles to store the graph data can be used.
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Format
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------
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See https://docs.python.org/3/library/pickle.html
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"""
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__all__ = ["read_gpickle", "write_gpickle"]
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from networkx.utils import open_file
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import pickle
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@open_file(1, mode="wb")
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def write_gpickle(G, path, protocol=pickle.HIGHEST_PROTOCOL):
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"""Write graph in Python pickle format.
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Pickles are a serialized byte stream of a Python object [1]_.
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This format will preserve Python objects used as nodes or edges.
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Parameters
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----------
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G : graph
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A NetworkX graph
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path : file or string
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File or filename to write.
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Filenames ending in .gz or .bz2 will be compressed.
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protocol : integer
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Pickling protocol to use. Default value: ``pickle.HIGHEST_PROTOCOL``.
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Examples
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--------
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>>> G = nx.path_graph(4)
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>>> nx.write_gpickle(G, "test.gpickle")
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References
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----------
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.. [1] https://docs.python.org/3/library/pickle.html
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"""
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pickle.dump(G, path, protocol)
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@open_file(0, mode="rb")
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def read_gpickle(path):
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"""Read graph object in Python pickle format.
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Pickles are a serialized byte stream of a Python object [1]_.
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This format will preserve Python objects used as nodes or edges.
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Parameters
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----------
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path : file or string
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File or filename to write.
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Filenames ending in .gz or .bz2 will be uncompressed.
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Returns
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-------
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G : graph
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A NetworkX graph
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Examples
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--------
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>>> G = nx.path_graph(4)
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>>> nx.write_gpickle(G, "test.gpickle")
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>>> G = nx.read_gpickle("test.gpickle")
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References
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----------
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.. [1] https://docs.python.org/3/library/pickle.html
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"""
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return pickle.load(path)
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