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Network propagation models for networkx.

Project description

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.. .. |experinet_icon| image::

Synthetic network theory experiment.

.. code-block:: python

'entry': {
'type': 'generate',
'model': 'ba',
'd': 2,

.. contents::

.. section-numbering::


.. code-block:: bash

pip install experinet


* Pure python.
* Supports Python 3.5+.
* Fully tested.




Package author and maintainer is Shay Palachy (; You are more than welcome to approach him for help. Contributions are very welcomed.

Installing for development


.. code-block:: bash

git clone

Install in development mode, including test dependencies:

.. code-block:: bash

cd experinet
pip install -e '.[test]'

Running the tests

To run the tests use:

.. code-block:: bash

cd experinet

Adding documentation

The project is documented using the `numpy docstring conventions`_, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings. When documenting code you add to this project, follow `these conventions`_.

.. _`numpy docstring conventions`:
.. _`these conventions`:

Additionally, if you update this ``README.rst`` file, use ``python checkdocs`` to validate it compiles.


Created by Shay Palachy (

.. |PyPI-Status| image::

.. |PyPI-Versions| image::

.. |Build-Status| image::

.. |LICENCE| image::


.. |Codecov| image::

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