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aisa 1.0.0
Auto-Information State Aggregation
This is a python module aimed at partitioning networks through the maximization of Auto-Information.
If you use this code, please cite the following paper:
State aggregations in Markov chains and block models of networks,
Faccin, Schaub and Delvenne,
ArXiv 2005.00337
The module provides also a function to compute the Entrogram of a network with a suitable partition.
The Entrogram provides a concise, visual characterization of the Markovianity of the dynamics projected to the partition space.
In case you use this, please cite the following paper:
Entrograms and coarse graining of dynamics on complex networks,
Faccin, Schaub and Delvenne,
Journal of Complex Networks, 6(5) p. 661-678 (2018),
ArXiv 1711.01987
Getting the code
Requirements
The following modules are required to aisa to work properly:
numpy and scipy
networkx
tqdm (optional)
Install
Download the code here and unzip locally or clone the git repository from Github.
On the terminl run:
pip install --user path/to/module
Uninstall
On the terminl run:
$ pip uninstall aisa
Usage
Read the online documentation that describes all classes and functions of the module.
Some simple notebook examples on module usage are provided in the examples subfolder:
a simple example of computing and drawing the entrogram and detecting the partition that maximize the auto-information in a well know small social network, see in nbviewer
an example on how to build a range dependent network and find the partition that maximize auto-nformation, see in nbviewer
License
Copyright: Mauro Faccin (2020)
AISA is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
AISA is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
Check LICENSE.txt for details.
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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