File	Date	Author	Commit
ID_MAPS	2014-02-24	Colin Mclean	[174d09] Initial commit
OUT	2014-02-24	Colin Mclean	[c2066e] added OUT/ dir
testData	2014-02-24	Colin Mclean	[174d09] Initial commit
Headers.h	2014-02-24	Colin Mclean	[174d09] Initial commit
Helper.h	2014-02-24	Colin Mclean	[174d09] Initial commit
Makefile	2014-02-24	Colin Mclean	[c2066e] added OUT/ dir
README	2014-02-24	Colin Mclean	[174d09] Initial commit
communityDetection.C	2014-02-24	Colin Mclean	[174d09] Initial commit
edge.h	2014-02-24	Colin Mclean	[174d09] Initial commit
eigen_sym.h	2014-02-24	Colin Mclean	[174d09] Initial commit
ludcmp.h	2014-02-24	Colin Mclean	[174d09] Initial commit
node.h	2014-02-24	Colin Mclean	[174d09] Initial commit
nr3.h	2014-02-24	Colin Mclean	[174d09] Initial commit
ran.h	2014-02-24	Colin Mclean	[174d09] Initial commit
readInputFile.h	2014-02-24	Colin Mclean	[174d09] Initial commit

Read Me

------------------------------------------------------
### Community Detection using Modulairty (2013)    ###
### Suite of Modualrity based community detection  ###
### algorithms                                     ###
### Dr. Colin Mclean <cmclean5@staffmail.ed.ac.uk> ###
------------------------------------------------------


----------------------------
*** TO INSTALL AND BUILD ***
----------------------------

(1) Build clustering package within a convienient location,  by running the Makefile. 

 > make

This should create the executable 'run'.


----------------------------
***       TO RUN         ***
----------------------------

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