Community Detection Modularity Suite Files

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### Community Detection using Modulairty (2013)    ###
### Suite of Modualrity based community detection  ###
### algorithms                                     ###
### Dr. Colin Mclean <cmclean5@staffmail.ed.ac.uk> ###
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*** TO INSTALL AND BUILD ***
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(1) Build clustering package within a convienient location,  by running the Makefile. 

 > make

This should create the executable 'run'.


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***       TO RUN         ***
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The user can obtain help on running each of the arguments by typing the following:
 > ./run

> ./run can take the following arguments: 
> -file         : the network file to run 
> -fullNetwork  : Use full network and not the lagrest component 
> -searchK      : run algorithm through K space findKlow = 1, findKhigh = N, Kinterval = 1 
> -findKlow     : run algorithm through K, starting at K = findKlow 
> -findKhigh    : run algorithm through K, ending at K = findKhigh 
> -Kinterval    : run algorithm through K with spacing Kinterval 
> -searchLL     : run algorithm with K = findK first calculating the solution's space LLmean 
> -LLiterations : run algorithm with K = findK first calculating the solution's space LLmean, using LLiterations 
> -LLmean       : run algorithm using Log Likelihood mean = LLmean 
> -findK        : run algorithm with K = findK for max Log Likelihood 
> -geneNames    : can use if running -findK over a Human PPI data
> -----
> EXAMPLE 1
> -----
> ./run -searchK -file testData/karate.txt
> ./run -findK 4 -file testData/karate.txt
> -----
> EXAMPLE 2
> -----
> ./run -findKlow 1 -findKhigh 20 -Kinterval 1 -file testData/karate.txt
> ./run -searchLL -findK 4 -file testData/karate.txt
> -----

Some Example data is included in the testData directory