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= facetnet-python-unil =
This is a python implementation of the facetnet algorithm presented in
[Lin, Yu-Ru, et al. "Facetnet: a framework for analyzing communities and their evolutions in dynamic networks." Proceedings of the 17th international conference on World Wide Web. ACM, 2008.](https://doi.org/10.1145/1367497.1367590)
based on the implementation of [blmoistawinde](https://github.com/blmoistawinde/facetnet-python). References in code comments refer to paragraphs in this paper.
== File description ==
# //facetnet_step.py//: performs one time step update of the algorithm. Needs the state of the previous step as an input (`xcap.dat`, `lcap.dat`, `idmap.dat`, `idmap_inv.dat`). If no previous state is supplied, an initialization step is performed with alpha = 1.
# //facetnet_evol.py//: generates an entire evolution of facetnet given a set of edge lists for different snapshot networks.
# //facetnet.py//: python module implementing the algorithm
# //facetnet_exp_4_1_1.py//: reproduces the experiment described in paragraph 4.1.1 of the original paper.
# //paper_experiments/synthetic_dataset_1/0.edgelist//: edgelist for the static graph used for the experiment described before. This file also serves as an example for the input format of edge lists.
The first two scripts can be called from the command line. Type e.g. `python3 facetnet_step.py --help` for a description of the arguments.
== Dependencies ==
* python 3.6
* pandas
* numpy
* tqdm
* matplotlib
* seaborn
To reproduce the paper experiments:
* networkx
* python-louvain
== How to use ==
After cloning the repository, enter the folder (folder that contains setup.py script) and install the package:
```sh
pip install .
```
this should also install all required packages.
== Author and copyright ==
If you use this code, please cite:
@article{richardsonant,
title={Ant behavioural maturation is mediated by a stochastic transition between two fundamental states.},
author={Richardson, TO and Braunschweig, R and Journeau, OA and R{\"u}egg, M and McGregor, S and De Los Rio, P and Keller, L},
journal={Current Biology}
}
Tag v1.0 of this repository refers to the version used for the aforementioned publication.
Please also cite:
@inproceedings{lin2008facetnet,
title={Facetnet: a framework for analyzing communities and their evolutions in dynamic networks},
author={Lin, Yu-Ru and Chi, Yun and Zhu, Shenghuo and Sundaram, Hari and Tseng, Belle L},
booktitle={Proceedings of the 17th international conference on World Wide Web},
pages={685--694},
year={2008},
organization={ACM}
}
Written by Group L. Keller, Université de Lausanne, Departement of Ecology and Evolution. Contact: Matthias Rüegg, matthias.ruegg@unil.ch
Copyright 2019 __UNIL__. All rights reserved.
This file is part of facetnet-python-unil.
facet-python-unil 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.
facet-python-unil 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.
You should have received a copy of the GNU General Public License
along with facet-python-unil. If not, see <https://www.gnu.org/licenses/>.
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