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+# 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-0.1.
+
+
+This is a Python implmementation of the algorithm for structural
+reduction of multi-layer networks based on the Von Neumann 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 module "multired.py" provides the class "multiplex_red", which
+implements the algorithm to reduce a multilayer network described in
+the paper cited above. 
+
+In order to use it, you just need to 
+
+ import multired as mr
+
+in your python script and create a multiplex_red object. Please make
+sure that "multired.py" is in PYTHONPATH. 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. 
+
+--------------------
+    DEPENDENCIES
+--------------------
+
+The only strict dependencies are a recent version of Python, Numpy and
+SciPy. The methods "draw_dendrogram" and "draw_dendrogram_approx" will
+work only if matplotlib is installed.
+
+The module has been tested on a Debian GNU/Linux system, using:
+
+ - Python 2.7.8,  
+ - SciPy 0.13.3
+ - Numpy 1.8.2
+ - matplotlib 1.3.1
+
+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).