+++ /dev/null
-/*
- * Copyright (c) 2003-2005 The BISON Project
- *
- * This program is free software; you can redistribute it and/or modify
- * it under the terms of the GNU Lesser General Public License version 2 as
- * published by the Free Software Foundation.
- *
- * This program is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public License
- * along with this program; if not, write to the Free Software
- * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
- *
- */
-
-package peersim.reports;
-
-import peersim.config.Configuration;
-import peersim.graph.GraphAlgorithms;
-import peersim.util.IncrementalStats;
-
-/**
-* Prints reports on the graph like average clustering and average path length,
-* based on random sampling of the nodes.
-* In fact its functionality is a subset of the union of {@link Clustering}
-* and {@link BallExpansion}, and therefore is redundant,
-* but it is there for historical reasons.
-* @see BallExpansion
-* @see Clustering
-*/
-public class GraphStats extends GraphObserver {
-
-
-// ===================== fields =======================================
-// ====================================================================
-
-/**
-* The number of nodes to use for
-* sampling average path length.
-* Statistics are printed over a set of node pairs.
-* To create the set of pairs, we select the given number of different nodes
-* first, and then pair all these nodes with every other node in the network.
-* If zero is given, then no statistics
-* will be printed about path length. If a negative value is given then
-* the value is the full size of the graph.
-* Defaults to zero.
-* @config
-*/
-private static final String PAR_NL = "nl";
-
-/**
-* The number of nodes to use to sample
-* average clustering.
-* If zero is given, then no statistics
-* will be printed about clustering. If a negative value is given then
-* the value is the full size of the graph.
-* Defaults to zero.
-* @config
-*/
-private static final String PAR_NC = "nc";
-
-private final int nc;
-
-private final int nl;
-
-
-// ===================== initialization ================================
-// =====================================================================
-
-
-/**
- * Standard constructor that reads the configuration parameters.
- * Invoked by the simulation engine.
- * @param name the configuration prefix for this class
- */
-public GraphStats(String name) {
-
- super(name);
- nl = Configuration.getInt(name+"."+PAR_NL,0);
- nc = Configuration.getInt(name+"."+PAR_NC,0);
-}
-
-
-// ====================== methods ======================================
-// =====================================================================
-
-/**
-* Returns statistics over minimal path length and clustering.
-* The output is the average over the set of
-* clustering coefficients of randomly selected nodes, and the
-* set of distances from randomly selected nodes to all the other nodes.
-* The output is always concatenated in one line, containing zero, one or two
-* numbers (averages) as defined by the config parameters.
-* Note that the path length between a pair of nodes can be infinite, in which
-* case the statistics will reflect this (the average will be infinite, etc).
-* See also the configuration parameters.
-* @return always false
-* @see BallExpansion
-* @see Clustering
-*/
-public boolean execute() {
-
- System.out.print(name+": ");
-
- IncrementalStats stats = new IncrementalStats();
- updateGraph();
-
- if( nc != 0 )
- {
- stats.reset();
- final int n = ( nc<0 ? g.size() : nc );
- for(int i=0; i<n && i<g.size(); ++i)
- {
- stats.add(GraphAlgorithms.clustering(g,i));
- }
- System.out.print(stats.getAverage()+" ");
- }
-
- if( nl != 0 )
- {
- stats.reset();
- final int n = ( nl<0 ? g.size() : nl );
- outerloop:
- for(int i=0; i<n && i<g.size(); ++i)
- {
- ga.dist(g,i);
- for(int j=0; j<g.size(); ++j)
- {
- if( j==i ) continue;
- if (ga.d[j] == -1)
- {
- stats.add(Double.POSITIVE_INFINITY);
- break outerloop;
- }
- else
- stats.add(ga.d[j]);
- }
- }
- System.out.print(stats.getAverage());
- }
-
- System.out.println();
- return false;
-}
-
-}
-
