multiNetX v1.0

By nkoub / November 4, 2015 / Multiplex networks, Networks, software / No Comments

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multiNetX is a python package for the manipulation and visualization of multilayer networks. The core of this package is a MultilayerGraph, a class that inherits all the features of networkx.Graph(). multiNetX inheriths all features from NetworkX Features:

  • Creating networks with weighted or unweighted links
  • Visualizing multiplex networks and dynamical processes on them
  • Analysing the spectral properties of adjacency or Laplacian matrices
  • All features of NetworkX
  • Benefits from Python: fast prototyping, easy to use, multi-platform Please download or clone the source code with the brief tutorial and examples from

https://github.com/nkoub/multinetx Any feedback or contribution to the code is more than welcome! multiNetX is part of the deliverables of the LASAGNE project (multi-LAyer SpAtiotemporal Generalized NEtworks), EU/FP7-2012-STREP-318132 (http://complex.ffn.ub.es/~lasagne/) and is distributed under the GNU General Public License.

##Import standard libraries

import numpy as np
import matplotlib.pyplot as plt

##Import the package MultiNetX

import multinetx as mx

##Create three Erd"os- R'enyi networks with N nodes for each layer

N = 50
g1 = mx.erdos_renyi_graph(N,0.07,seed=218)
g2 = mx.erdos_renyi_graph(N,0.07,seed=211)
g3 = mx.erdos_renyi_graph(N,0.07,seed=208)

##Define the type of interconnection between the layers

adj_block = mx.lil_matrix(np.zeros((N*3,N*3)))

adj_block[0:  N,  N:2*N] = np.identity(N)    # L_12
adj_block[0:  N,2*N:3*N] = np.identity(N)    # L_13
#adj_block[N:2*N,2*N:3*N] = np.identity(N)    # L_23
adj_block += adj_block.T

##Create an instance of the MultilayerGraph class

mg = mx.MultilayerGraph(list_of_layers=[g1,g2,g3],
                        inter_adjacency_matrix=adj_block)

mg.set_edges_weights(inter_layer_edges_weight=4)

mg.set_intra_edges_weights(layer=0,weight=1)
mg.set_intra_edges_weights(layer=1,weight=2)
mg.set_intra_edges_weights(layer=2,weight=3)

##Plot the adjacency matrix and the multiplex networks

fig = plt.figure(figsize=(15,5))
ax1 = fig.add_subplot(121)
ax1.imshow(mx.adjacency_matrix(mg,weight='weight').todense(),
          origin='upper',interpolation='nearest',cmap=plt.cm.jet_r)
ax1.set_title('supra adjacency matrix')

ax2 = fig.add_subplot(122)
ax2.axis('off')
ax2.set_title('regular interconnected network')
pos = mx.get_position(mg,
                      mx.fruchterman_reingold_layout(mg.get_layer(0)),
                      layer_vertical_shift=1.4,
                      layer_horizontal_shift=0.0,
                      proj_angle=7)
mx.draw_networkx(mg,pos=pos,ax=ax2,node_size=50,with_labels=False,
                 edge_color=[mg[a][b]['weight'] for a,b in mg.edges()],
                 edge_cmap=plt.cm.jet_r)
plt.show()

output_51_0 More examples are available at https://github.com/nkoub/multinetx