fix info

README.md

@@ -1,18 +1,19 @@
-# MCL Clustering
+# MCL algorithm
+
+This module implements the Markov Cluster algorithm created by Stijn van Dongen and 
+described in http://www.library.uu.nl/digiarchief/dip/diss/1895620/inhoud.htm.
 
-Python implementation of Markov Clustering technique.
 This implementation si not yet optimized for large networks.
 
 ## Installation:
 
-    python setup.py install
+python setup.py install
 
 ##Usage:
 
 ###Command line:
 
-    Usage: ./mcl_clustering.py [options] <input_file> <output_file>
-
+    Usage: mcl_clustering.py [options] <input_matrix>
 
     Options:
       -h, --help            show this help message and exit
@@ -21,49 +22,55 @@ This implementation si not yet optimized for large networks.
       -i INFLATE_FACTOR, --inflate_factor=INFLATE_FACTOR
                             inflate factor (default: 2)
       -m MULT_FACTOR, --mult_factor=MULT_FACTOR
-                            multiply factor (default: 1)
+                            multiply factor (default: 2)
       -l MAX_LOOP, --max_loops=MAX_LOOP
                             max loops (default: 60)
+      -o FILE, --output=FILE
+                            output (default: stdout)
+      -v, --verbose         verbose (default: True)
+      -d, --draw-graph      show graph with networkx (default: False)
+
+
+The input matrix must be as comma separated value file representing the 
+adjacency matrix. 
 
+An example is the file example.csv.
+try mcl_clustering.py -e 3 example.csv
 
 
 ###Code:
 
-        numpy adjacency matrix
-
-            from mcl_clustering import mcl
-
-            A = <your matrix>
+####Using numpy adjacency matrix
 
-            M, clusters = mcl(A, expand_factor = options.expand_factor,
-                               inflate_factor = options.inflate_factor,
-                               max_loop = options.max_loop,
-                               mult_factor = options.mult_factor)
+    from mcl_clustering import mcl
 
-        networkx graph
+    A = <your matrix>
 
-            from mcl_clustering import networkx_mcl
+    M, clusters = mcl(A, expand_factor = options.expand_factor,
+                       inflate_factor = options.inflate_factor,
+                       max_loop = options.max_loop,
+                       mult_factor = options.mult_factor)
 
-            G = <your graph>
-
-            M, clusters = networkx_mcl(G, expand_factor = options.expand_factor,
-                               inflate_factor = options.inflate_factor,
-                               max_loop = options.max_loop,
-                               mult_factor = options.mult_factor)
-        
-            
-        Output:
-            M = otuput matrix
-            clusters = dict with keys = [<cluster id>] values = [<vertex id>]
+####Using a networkx graph
 
-##Requirements
-
-        numpy
-        networkx
+    from mcl_clustering import networkx_mcl
 
+    G = <your graph>
 
-##Example:
+    M, clusters = networkx_mcl(G, expand_factor = options.expand_factor,
+                       inflate_factor = options.inflate_factor,
+                       max_loop = options.max_loop,
+                       mult_factor = options.mult_factor)
 
+
+    Output:
+        M = otuput matrix
+        clusters = dict with keys = [<cluster id>] values = [<vertex id>]
+
+##Requirements
+
+    numpy
+    networkx
 
 
 ##Parameters:
@@ -75,14 +82,13 @@ This implementation si not yet optimized for large networks.
     -s --show-graph     show graph with networkx
 
 
-
 ## References
 
-      Stijn van Dongen, Graph Clustering by Flow Simulation.
+[1]   Stijn van Dongen, Graph Clustering by Flow Simulation.
       PhD thesis, University of Utrecht, May 2000.
       ( http://www.library.uu.nl/digiarchief/dip/diss/1895620/inhoud.htm )
 
-      Stijn van Dongen. A cluster algorithm for graphs.  Technical Report
+[2]   Stijn van Dongen. A cluster algorithm for graphs.  Technical Report
       INS-R0010, National Research Institute for Mathematics and Computer
       Science in the Netherlands, Amsterdam, May 2000.
       ( http://www.cwi.nl/ftp/CWIreports/INS/INS-R0010.ps.Z )

setup.py

@@ -12,6 +12,6 @@
     author='koteth',
     install_requires = ['numpy', 'networkx'],
     keywords = "MCL markov clustering graph",
-    author_email='[email protected]',
+    author='Gabriele Lami',
     packages=['mcl'],
-     )
+)