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Radatools

Communities detection in complex networks and other tools

Index

• Description
• Download
• Installation
• References

Description

Radatools is a set of freely distributed programs to analyze Complex Networks. In particular, it includes very useful programs for Communities Detection and Mesoscales Determination.

The list of programs included in the current version of Radatools is:

• Communities_Detection:
  It is prepared to work with:
  • unweighted [1] and weighted [2] networks
  • undirected [1] and directed [3] networks
  • positive [1] and signed [4] networks
  Implements several algorithms for the optimization of modularity [1]:
  • exhaustive search
  • tabu search [5]
  • extremal optimization [6]
  • spectral optimization [7]
  • fast algorithm [8]
  • fine-tuning by reposition
  • fine-tuning by bootstrapping based on tabu search [5]
  These heuristics may also be combined to obtain the best results.
  It is possible to add a common self-loop to all nodes to analyze the communities at any resolution level [5].
  Please be kind to cite the corresponding articles when you use these tools.
  
  
• Mesoscales_Search:
  Implements the strategy in [5,9] for the determination of the community structure of complex networks at different resolution levels, thus finding the whole mesoscale, from all nodes in one community (macroscale) to every node forming its own community (microscale). It is based on the addition of a common self-loop to all nodes, and the optimization of modularity [1,2,3] using the same heuristics as in Communities_Detection.
  
  
• Mesoscales_Fine_Tuning:
  Fine-tuning of the mesoscales found by Mesoscales_Search.
  
  
• Size_Reduction:
  Elimination of simple and triangular hairs of a network [3].
  
  
• Size_Reduction_Lol_Expand:
  Convert a partition of a sized reduced network [3] into a partition of the original network.
  
  
• Network_Properties:
  Calculate many global, nodes and edges properties of a network, e.g. degrees, strengths, clustering coefficients, assortativity, connectedness, shortest path lengths, diameter, betweenness, degree distribution, distances, etc. It works with weighted and unweighted, directed and undirected, positive and signed networks.
  
  
• Compare_Partitions:
  Calculate similarity and dissimilarity indices between two partitions, e.g. Jaccard Index, Rand Index, Normalized Mutual Information, Variation of Information, etc.
  
  
• Spanning_Tree:
  Calculate the minimum and maximum spanning tree of a graph.
  
  
• List_To_Net:
  Converts a file with the list of links of a graph into a network file in Pajek format.
  
  
• Matrix_To_Net:
  Converts a file with a graph in matrix form into a network file in Pajek format.
  
  
• Net_To_Matrix:
  Converts a file with a network in Pajek format into a graph file in matrix form.
  
  
• Connected_Subgraphs:
  Splits a network in Pajek format into its weak or strong connected components.
  
  
• Extract_Subgraphs:
  Extract subgraphs from a graph given the lists of nodes which form the subgraphs.
  
  
• Convert_Lol_To_Clu:
  Converts a file with a partition in Lol format into a file with a partition in Pajek format.
  
  
• Convert_Clu_To_Lol:
  Converts a file with a partition in Pajek format into a file with a partition in Lol format.
  
  
• Modularity_Calculation:
  Calculates the modularity of a partition of a network.
  
  
• Reformat_Partitions:
  Reformat partitions in Pajek and Lol formats changing indices of nodes by names of nodes.

Download

• Windows 32 and 64 bits: radatools-3.2-win32.zip
• Linux 32 and 64 bits: radatools-3.2-linux32.tar.gz
• Mac OS X: radatools-3.2-mac.tar.gz
  
  
• README: txt, pdf
• CHANGES: txt, pdf
• LICENSE: txt, pdf

Installation

No installation needed, just uncompress the downloaded file. See the README file for the information to run each program.

References

[1]	M.E.J. Newman and M. Girvan Finding and evaluating community structure in networks Physical Review E 69 (2004) 026113

[2]	M.E.J. Newman Analysis of weighted networks Physical Review E 70 (2004) 056131

[3]	Alex Arenas, Jordi Duch, Alberto Fernández and Sergio Gómez Size reduction of complex networks preserving modularity New Journal of Physics 9 (2007) 176 (pdf) (doi) (IOP open access)

[4]	Sergio Gómez, Pablo Jensen and Alex Arenas Analysis of community structure in networks of correlated data Physical Review E 80 (2009) 016114 (pdf) (doi) (APS)

[5]	Alex Arenas, Alberto Fernández and Sergio Gómez Analysis of the structure of complex networks at different resolution levels New Journal of Physics 10 (2008) 053039 (pdf) (doi) (IOP open access)

[6]	Jordi Duch and Alex Arenas Community detection in complex networks using extremal optimization Physical Review E 72 (2005) 027104 (doi) (APS)

[7]	M.E.J. Newman Modularity and community structure in networks Proc. Nat. Acad. Sci. USA 103 (2006) 8577

[8]	M.E.J. Newman Fast algorithm for detecting community structure in networks Physical Review E 69 (2004) 066133

[9]	Clara Granell, Sergio Gómez and Alex Arenas Mesoscopic analysis of networks: applications to exploratory analysis and data clustering Chaos 21 (2011) 016102 (pdf) (doi) (AIP)