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author | KatolaZ <katolaz@freaknet.org> | 2017-09-27 15:06:31 +0100 |
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committer | KatolaZ <katolaz@freaknet.org> | 2017-09-27 15:06:31 +0100 |
commit | 3aee2fd43e3059a699af2b63c6f2395e5a55e515 (patch) | |
tree | 58c95505a0906ed9cfa694f9dbd319403fd8f01d /doc/hv_net.md |
First commit on github -- NetBunch 1.0
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diff --git a/doc/hv_net.md b/doc/hv_net.md new file mode 100644 index 0000000..89bcce1 --- /dev/null +++ b/doc/hv_net.md @@ -0,0 +1,72 @@ +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>`. + |