From 3aee2fd43e3059a699af2b63c6f2395e5a55e515 Mon Sep 17 00:00:00 2001
From: KatolaZ <katolaz@freaknet.org>
Date: Wed, 27 Sep 2017 15:06:31 +0100
Subject: First commit on github -- NetBunch 1.0

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+bb_fitness(1) -- Grow a random graph with the fitness model
+======
+
+## SYNOPSIS
+
+`bb_fitness` <N> <m> <n0> [SHOW]
+
+## DESCRIPTION
+
+`bb_fitness` grows an undirected random scale-free graph with <N>
+nodes using the fitness model proposed by Bianconi and Barabasi. The
+initial network is a clique of <n0> nodes, and each new node creates
+<m> new edges. The probability that a new node create an edge to node
+`j` is proportional to
+
+        a_j * k_j
+
+where `a_j` is the attractiveness (fitness) of node `j`. The values of
+node attractiveness are sampled uniformly in the interval [0,1].
+
+## PARAMETERS
+
+* <N>:
+    Number of nodes of the final graph.
+
+* <m>:
+    Number of edges created by each new node.
+    
+* <n0>:
+    Number of nodes in the initial (seed) graph. 
+
+* SHOW:
+    If the fourth parameter is equal to `SHOW`, the values of node
+    attractiveness are printed on STDERR.
+
+## OUTPUT
+
+`bb_fitness` prints on STDOUT the edge list of the final graph. 
+
+## EXAMPLES
+
+The following command:
+
+        $ bb_fitness 10000 3 4 > bb_fitness_10000_3_4.txt
+
+uses the fitness model to create a random graph with <N=10000> nodes,
+where each new node creates <m=3> new edges and the initial seed
+network is a ring of <n0=5> nodes. The edge list of the resulting
+graph is saved in the file `bb_fitness_10000_3_4.txt` (notice the
+redirection operator `>`). The command:
+
+        $ bb_fitness 10000 3 4 SHOW > bb_fitness_10000_3_4.txt 2> bb_fitness_10000_3_4.txt_fitness
+
+will do the same as above, but it will additionally save the values of
+node fitness in the file `bb_fitness_10000_3_4.txt_fitness` (notice
+the redirection operator `2>`, that redirects the STDERR to the
+specified file).
+
+## SEE ALSO
+
+ba(1), dms(1)
+
+## REFERENCES
+
+* G\. Bianconi, A.-L. Barabasi, " Competition and multiscaling in
+  evolving networks". EPL-Europhys. Lett. 54 (2001), 436.
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Chapter 6, Cambridge University Press
+  (2017)
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Appendix 13, Cambridge University Press
+  (2017)
+
+
+## AUTHORS
+
+(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 `<v.nicosia@qmul.ac.uk>`.
+
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