#multired *
- Copyright (C) 2015 Vincenzo (Enzo) Nicosia katolaz@yahoo.it
- This program 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.
- This program 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
- long with this program. If not, see http://www.gnu.org/licenses/.
This is multired-0.2
This is a Python implementation of the algorithm for structural reduction of multi-layer networks based on the Von Neumann Entropy and on the Quantum Jensen-Shannon divergence of graphs, as explained in:
M. De Domenico. V. Nicosia, A. Arenas, V. Latora "Structural reducibility of multilayer networks", Nat. Commun. 6, 6864 (2015) doi:10.1038/ncomms7864
If you happen to find any use of this code please do not forget to cite that paper ;-)
INFO
The package "multired" provides the class "MultiplexRed", which implements the algorithm to reduce a multilayer network described in the paper cited above.
In order to use it, you just need to
from multired import MultiplexRed
m = MultiplexRed(layer_list_filename, verbose=True)
part = m.compute_partitions()
m.dump_partitions()
m.draw_dendrogram()
where layer_list_filename is a text file containing the list of the files describing the multiplex layers (see example in multired/sample_data/file_list)
The constructor requires as its first argument the path of a file which in turn contains a list of files (one for each line) where the graph of each layer is to be found.
The class provides one set of methods which perform the exact evaluation of the Von Neumann entropy, and another set of methods (those whose name end with the suffix "_approx") which rely on a polynomial approximation of the Von Neumann entropy. By default the approximation is based on a 10th order polynomial fit of x log(x) in [0,1], but the order of the polynomial can be set through the parameter "fit_degree" of the constructor.
Several sample scripts can be found in the "test/" directory. You also find a sample data set in the folder "sample_data/". That is the 4-layer Noordin Top Terrorist multiplex network, originally provided in:
N. Roberts, S. F. Everton, Roberts and Everton "Terrorist Data: Noordin Top Terrorist Network" (Subset) (2011).
and extensively studied in:
F. Battiston, V. Nicosia, V. Latora, "Structural measures for multiplex networks", Phys. Rev. E 89, 032804 (2014).
Please consider citing those papers if you use that data set in a scientific work.
DEPENDENCIES
The dependencies are listed in requirements.txt
The module has been tested on a Debian GNU/Linux system, using:
- Python 3.x,
- SciPy
- Numpy
- matplotlib
but it will almost surely work on other platforms and/or with other versions of those packages. If you would like to report a working configuration, just email me (the address is at the beginning of this file).