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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+dms(1) -- Grow a scale-free random graph with tunable exponent
+======
+
+## SYNOPSIS
+
+`dms` <N> <m> <n0> _a_
+
+## DESCRIPTION
+
+`dms` grows an undirected random scale-free graph with <N> nodes using
+the modified linear preferential attachment model proposed by
+Dorogovtsev, Mendes and Samukhin. The initial network is a clique of
+<n0> nodes, and each new node creates <m> new edges. The resulting
+graph will have a scale-free degree distribution, whose exponent
+converges to `gamma=3.0 + a/m` for large <N>.
+
+## 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. 
+
+* _a_:
+    This parameter sets the exponent of the degree distribution
+    (`gamma = 3.0 + a/m`). _a_ must be larger than <-m>.
+
+## OUTPUT
+
+`dms` prints on STDOUT the edge list of the final graph.
+
+## EXAMPLES
+
+Let us assume that we want to create a scale-free network with
+<N=10000> nodes, with average degree equal to 8, whose degree
+distribution has exponent
+
+        gamma = 2.5
+
+Since `dms` produces graphs with scale-free degree sequences with an
+exponent `gamma = 3.0 + a/m`, the command:
+
+        $ dms 10000 4 4 -2.0 > dms_10000_4_4_-2.0.txt
+
+will produce the desired network. In fact, the average degree of the
+graph will be:
+
+        <k> = 2m = 8
+
+and the exponent of the power-law degree distribution will be:
+
+        gamma = 3.0 + a/m = 3.0 -0.5 = 2.5
+
+The following command:
+
+        $ dms 10000 3 5 0 > dms_10000_3_5_0.txt
+
+creates a scale-free 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 degree distribution of the final graph will have
+exponent equal to `gamma = 3.0 + a/m = 3.0`. In this case, `dms`
+produces a Barabasi-Albert graph (see ba(1) for details). The edge
+list of the graph is saved in the file `dms_10000_3_5_0.txt` (thanks
+to the redirection operator `>`).
+
+## SEE ALSO
+
+ba(1), bb_fitness(1)
+
+## REFERENCES
+
+* S\. N. Dorogovtsev, J. F. F. Mendes, A. N. Samukhin. "Structure of
+    Growing Networks with Preferential Linking".  Phys. Rev. Lett. 85
+    (2000), 4633-4636.
+
+* 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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