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diff --git a/doc/clust.md b/doc/clust.md new file mode 100644 index 0000000..36cc6c4 --- /dev/null +++ b/doc/clust.md @@ -0,0 +1,105 @@ +clust(1) -- Compute the graph and node clustering coefficients +====== + +## SYNOPSIS + +`clust` <graph_in> [SHOW] + +## DESCRIPTION + +`clust` computes the clustering coefficient of the undirected graph +given as input in the file <graph_in>. If `SHOW` is provided as a +second parameter, the program prints on STDERR the label, degree, and +clustering coefficient of all the nodes in <graph_in>. + +## PARAMETERS + +* <graph_in>: + undirected input graph (edge list). If is equal to `-` (dash), read + the edge list from STDIN. + +* SHOW: + If the second (optional) parameter is equal to `SHOW`, the program + will dump on the standard error the label, degree, and clustering + coefficient of each node in <graph_in>. + +## OUTPUT + +If only <graph_in> is specified, then the output is a single line, +containing the clustering coefficient of the undirected graph provided +as input. If `SHOW` is specified, the program will print on the +standard output one line for each node, in the format: + + node_1 k_1 c_1 + node_2 k_2 c_2 + node_3 k_3 c_3 + .... + +where `node_1` is the label of the node, `k_1` is its degree, and +`c_1` is its node clustering coefficient. + +## EXAMPLES + +The most simple way of using `clust` is to compute only the clustering +coefficient of a graph. For instance: + + $ clust er_1000_5000.txt + 0.01034196 + $ + +will show on output the clustering coefficient of the graph +`er_1000_5000.txt`. In order to obtain the clustering coefficient of +all the nodes, we should use: + + $ clust er_1000_5000.txt SHOW + 0 10 0.0222222 + 1 3 0 + 2 7 0 + 3 5 0 + 4 10 0 + 5 17 0 + 6 14 0 + 7 8 0 + 8 6 0 + 9 11 0 + 10 9 0 + 11 10 0 + 12 13 0.0128205 + .... + 998 10 0.0222222 + 999 9 0 + 0.01034196 + $ + +The last line printed on output is still the value of the clustering +coefficient of the graph, while the previous 1000 lines (which are +printed on STDERR) contain the label, degree, and clustering +coefficient of all the nodes. For instance, the first line indicates +that node `0` has degree equal to `10` and clustering coefficient +equal to `0.0222222`. It is more convenient to save the values of node +clustering coefficients in a file, e.g.: + + $ clust er_1000_5000.txt SHOW 2> er_1000_5000.txt_node_clust + 0.01034196 + $ + +In this case, the program prints on output only the graph clustering +coefficient `0.01034196`, while the node clustering coefficients are +saved on the file `er_1000_5000.txt_node_clust` (notice the syntax `2> +er_1000_5000.txt_node_clust`, which redirects the STDERR to the file +`er_1000_5000.txt_node_clust`). + +## SEE ALSO + +clust_w(1) + +## REFERENCES + +* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles, + Methods and Applications", Chapter 4, Cambridge University Press + (2017) + + +## AUTHORS + +(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 `<v.nicosia@qmul.ac.uk>`. |