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NetworkX-Temporal


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Python package to build and manipulate temporal graphs using NetworkX as backend.

Requirements

  • Python>=3.7
  • networkx>=2.1
  • pandas>=1.1.0

Install

Package is available to install on PyPI:

$ pip install 'networkx-temporal[draw]'

The [draw] extra includes additional libraries required to plot graphs with NetworkX.

Quick example

For detailed information on using the package, please refer to its official documentation.

An interactive Jupyter notebook with more examples is also available here (open on Colab).

>>> import networkx_temporal as tx
>>>
>>> # Build directed temporal graph.
>>> TG = tx.TemporalDiGraph()
>>> TG.add_edge("a", "b", time=0)
>>> TG.add_edge("c", "b", time=1)
>>> TG.add_edge("d", "c", time=2)
>>> TG.add_edge("d", "e", time=2)
>>> TG.add_edge("a", "c", time=2)
>>> TG.add_edge("f", "e", time=3)
>>> TG.add_edge("f", "a", time=3)
>>> TG.add_edge("f", "b", time=3)
>>>
>>> # Slice it into snapshots.
>>> TG = TG.slice(attr="time")
>>>
>>> # Plot resulting object.
>>> tx.draw(TG, layout="kamada_kawai", figsize=(8,2))

Plot

Contributing

Contributions are welcome! If you find any bugs or have any suggestions, feel free to open a ticket, fork the repository and create a pull request, or simply send an e-mail. Please keep in mind that any out-of-scope contributions (not regarding temporal networks) should instead be directed to the NetworkX repository.

License

This package is released under the BSD License.

Cite

In case this package is useful for your research, please kindly consider citing it.

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Python package to build and manipulate temporal graphs.

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  • Python 71.0%
  • Jupyter Notebook 29.0%