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package de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2011
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero 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 Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
import java.util.Collection;
import java.util.Iterator;
import de.lmu.ifi.dbs.elki.data.Cluster;
import de.lmu.ifi.dbs.elki.data.Clustering;
import de.lmu.ifi.dbs.elki.data.NumberVector;
import de.lmu.ifi.dbs.elki.data.model.Model;
import de.lmu.ifi.dbs.elki.database.datastore.DataStoreEvent;
import de.lmu.ifi.dbs.elki.database.datastore.DataStoreListener;
import de.lmu.ifi.dbs.elki.database.ids.DBID;
import de.lmu.ifi.dbs.elki.result.HierarchicalResult;
import de.lmu.ifi.dbs.elki.result.Result;
import de.lmu.ifi.dbs.elki.result.ResultUtil;
import de.lmu.ifi.dbs.elki.utilities.exceptions.ObjectNotFoundException;
import de.lmu.ifi.dbs.elki.utilities.iterator.IterableUtil;
import de.lmu.ifi.dbs.elki.visualization.VisualizationTask;
import de.lmu.ifi.dbs.elki.visualization.projector.ScatterPlotProjector;
import de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary;
import de.lmu.ifi.dbs.elki.visualization.style.marker.MarkerLibrary;
import de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisFactory;
import de.lmu.ifi.dbs.elki.visualization.visualizers.Visualization;
/**
* Visualize a clustering using different markers for different clusters.
*
* @author Erich Schubert
*
* @apiviz.has Clustering oneway - - visualizes
*
* @param <NV> Type of the DatabaseObject being visualized.
*/
// TODO: ensure we have the right database for this
public class ClusteringVisualization<NV extends NumberVector<NV, ?>> extends P2DVisualization<NV> implements DataStoreListener {
/**
* The result we visualize
*/
private Clustering<Model> clustering;
/**
* Constructor.
*
* @param task Visualization task
*/
public ClusteringVisualization(VisualizationTask task) {
super(task);
this.clustering = task.getResult();
context.addDataStoreListener(this);
incrementalRedraw();
}
@Override
public void destroy() {
super.destroy();
context.removeDataStoreListener(this);
}
@Override
public void redraw() {
MarkerLibrary ml = context.getStyleLibrary().markers();
double marker_size = context.getStyleLibrary().getSize(StyleLibrary.MARKERPLOT);
// draw data
Iterator<Cluster<Model>> ci = clustering.getAllClusters().iterator();
for(int cnum = 0; cnum < clustering.getAllClusters().size(); cnum++) {
Cluster<?> clus = ci.next();
for(DBID objId : clus.getIDs()) {
try {
final NV vec = rel.get(objId);
double[] v = proj.fastProjectDataToRenderSpace(vec);
ml.useMarker(svgp, layer, v[0], v[1], cnum, marker_size);
}
catch(ObjectNotFoundException e) {
// ignore.
}
}
}
}
@Override
public void contentChanged(DataStoreEvent e) {
synchronizedRedraw();
}
/**
* Visualization factory
*
* @author Erich Schubert
*
* @apiviz.stereotype factory
* @apiviz.uses ClusteringVisualization oneway - - «create»
*
* @param <NV> Type of the DatabaseObject being visualized.
*/
public static class Factory<NV extends NumberVector<NV, ?>> extends AbstractVisFactory {
/**
* A short name characterizing this Visualizer.
*/
private static final String NAME = "Cluster Markers";
/**
* Constructor, adhering to
* {@link de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable}
*/
public Factory() {
super();
}
@Override
public Visualization makeVisualization(VisualizationTask task) {
return new ClusteringVisualization<NV>(task);
}
@Override
public void processNewResult(HierarchicalResult baseResult, Result result) {
// Find clusterings we can visualize:
Collection<Clustering<?>> clusterings = ResultUtil.filterResults(result, Clustering.class);
for(Clustering<?> c : clusterings) {
if(c.getAllClusters().size() > 0) {
Iterator<ScatterPlotProjector<?>> ps = ResultUtil.filteredResults(baseResult, ScatterPlotProjector.class);
for(ScatterPlotProjector<?> p : IterableUtil.fromIterator(ps)) {
final VisualizationTask task = new VisualizationTask(NAME, c, p.getRelation(), this);
task.put(VisualizationTask.META_LEVEL, VisualizationTask.LEVEL_DATA);
baseResult.getHierarchy().add(c, task);
baseResult.getHierarchy().add(p, task);
}
}
}
}
}
}
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