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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+hv_net(1) -- Sample a random graph with an assigned joint degree distribution
+======
+
+## SYNOPSIS
+
+`hv_net` <graph_in> [SHOW]
+
+## DESCRIPTION
+
+`hv_net` samples a random graph whose joint degree distribution is
+equal to that of another graph provided as input, using the
+hidden-variable model proposed by Boguna ans Pastor-Satorras.
+
+## PARAMETERS
+
+* <graph_in>:
+    File containing the edge list of the existing graph. If equal to
+    '-' (dash), read the edge list from STDIN.
+
+* SHOW:
+    If the second parameter is equal to `SHOW`, the program prints on
+    STDERR the hidden variable and actual degree of each node.
+
+## EXAMPLES
+
+Let us assume that we want to create a graph whose joint degree
+distribution is equal to that of the graph contained in
+`AS-20010316.net` (i.e., the graph of the Internet at the AS level in
+March 2001). We can use the command:
+
+        $ hv_net AS-20010316.net > AS-20010316.net_rand
+
+which will sample a random graph with the same joint-degree
+distribution and will save its edge list in the file
+`AS-20010316.net_rand` (notice the STDOUT redirection operator
+`>`). Additionally, we can also save the values of the hidden
+variables and actual degrees of the nodes by specifying `SHOW` as a
+second parameter:
+
+        $ hv_net AS-20010316.net SHOW > AS-20010316.net_rand 2>AS-20010316.net_rand_hv 
+
+In this case, the file `AS-20010316.net_rand_hv` will contain the
+values of the hidden variable of each node and of the actual degree of
+the node in the sampled graph, in the format:
+     
+         h1 k1
+         h2 k2
+         ....
+
+
+## SEE ALSO
+
+conf_model_deg(1), conf_model_deg_nocheck(1)
+
+## REFERENCES
+
+* M\. Boguna and R. Pastor-Satorras. "Class of correlated random
+  networks with hidden variables". Phys. Rev. E 68 (2003), 036112.
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Chapter 7, Cambridge University Press
+  (2017)
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Appendix 14, Cambridge University Press
+  (2017)
+
+
+## AUTHORS
+
+(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 `<v.nicosia@qmul.ac.uk>`.
+
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