package org.activityinfo.server.report.generator.map.cluster.genetic;
/*
* #%L
* ActivityInfo Server
* %%
* Copyright (C) 2009 - 2013 UNICEF
* %%
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as
* published by the Free Software Foundation, either version 3 of the
* License, or (at your option) any later version.
*
* 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public
* License along with this program. If not, see
* <http://www.gnu.org/licenses/gpl-3.0.html>.
* #L%
*/
import org.activityinfo.server.report.generator.map.RadiiCalculator;
import org.activityinfo.server.report.generator.map.cluster.Cluster;
import java.util.ArrayList;
import java.util.List;
public class UpperBoundsCalculator {
public interface Tracer {
void onSubgraph(int nodeCount);
void incremented(int count, List<Cluster> clusters, double fitness);
}
public static List<Integer> calculate(MarkerGraph graph, RadiiCalculator radiiCalculator) {
return calculate(graph, radiiCalculator, null);
}
/**
* Calculates the upper bound of the number of clusters per subgraph based
* on a minimum possible radius
*/
public static List<Integer> calculate(MarkerGraph graph, RadiiCalculator radiiCalculator, Tracer tracer) {
List<Integer> bounds = new ArrayList<Integer>();
List<List<MarkerGraph.Node>> subgraphs = graph.getSubgraphs();
FitnessFunctor ftor = new BubbleFitnessFunctor();
for (List<MarkerGraph.Node> subgraph : subgraphs) {
if (tracer != null) {
tracer.onSubgraph(subgraph.size());
}
bounds.add(calcUpperBound(subgraph, radiiCalculator, ftor, tracer));
}
return bounds;
}
private static int calcUpperBound(List<MarkerGraph.Node> subgraph,
RadiiCalculator radiiCalculator,
FitnessFunctor ftor,
Tracer tracer) {
for (int i = 2; i <= subgraph.size(); ++i) {
List<Cluster> clusters = KMeans.cluster(subgraph, i);
radiiCalculator.calculate(clusters);
double fitness = ftor.score(clusters);
if (tracer != null) {
tracer.incremented(i, clusters, fitness);
}
if (fitness <= 0) {
return i - 1;
}
}
return subgraph.size();
}
}