复杂数网工具包是一款专为处理复杂网络数据设计的软件套件。它集成了多种算法和模型，帮助用户高效地分析、可视化及优化大规模网络结构与模式。
Complex Networks Toolbox for MatLab is designed to analyze large-scale graphs, model them, explore with simulations of dynamic processes and generate appealing and insightful layouts. For example:
The function [BetweenneessCentrality, varargout]= GraphBetweennessCentrality(Graph,SourceNodes) computes the betweenness centrality of each node.
Inputs:
- Graph - A graph structure loaded using GraphLoad.
- SourceNodes (optional) - An array specifying nodes from which paths start. Default: [] (all nodes).
Outputs:
- BetweenneessCentrality - An array containing the betweenness centrality for each node.
- Nodes - If requested, a list of all nodes for which the betweenness centrality is computed.
The algorithm used can be found at http://www.boost.org/libs/graph/doc/betweenness_centrality.html. For optimization purposes, consider using mexGraphBetweennessCentrality.dll instead.
Function checks:
warning(Use the more optimized mexGraphBetweennessCentrality.dll);
error(nargchk(1,2,nargin));
error(nargoutchk(0,2,nargout));
If SourceNodes is not provided or empty:
SourceNodes = unique(Graph.Data(:,1));
Then Nodes are determined as follows:
Nodes = unique(Graph.Data(:,1:2));
The function proceeds to compute the betweenness centrality for each node by calculating shortest paths and their frequencies.
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