Package de.lmu.ifi.dbs.elki.algorithm.clustering.trivial

Source Code of de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.TrivialAllInOne

package de.lmu.ifi.dbs.elki.algorithm.clustering.trivial;

/*
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 de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm;
import de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm;
import de.lmu.ifi.dbs.elki.data.Cluster;
import de.lmu.ifi.dbs.elki.data.Clustering;
import de.lmu.ifi.dbs.elki.data.model.ClusterModel;
import de.lmu.ifi.dbs.elki.data.model.Model;
import de.lmu.ifi.dbs.elki.data.type.TypeInformation;
import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.logging.Logging;
import de.lmu.ifi.dbs.elki.utilities.documentation.Description;
import de.lmu.ifi.dbs.elki.utilities.documentation.Title;

/**
* Trivial pseudo-clustering that just considers all points to be one big
* cluster.
*
* Useful for evaluation and testing.
*
* @author Erich Schubert
*/
@Title("Trivial all-in-one clustering")
@Description("Returns a 'tivial' clustering which just considers all points to be one big cluster.")
public class TrivialAllInOne extends AbstractAlgorithm<Clustering<Model>> implements ClusteringAlgorithm<Clustering<Model>> {
  /**
   * The logger for this class.
   */
  private static final Logging logger = Logging.getLogger(TrivialAllInOne.class);

  /**
   * Constructor, adhering to
   * {@link de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable}
   */
  public TrivialAllInOne() {
    super();
  }

  public Clustering<Model> run(Relation<?> relation) {
    final DBIDs ids = relation.getDBIDs();
    Clustering<Model> result = new Clustering<Model>("All-in-one trivial Clustering", "allinone-clustering");
    Cluster<Model> c = new Cluster<Model>(ids, ClusterModel.CLUSTER);
    result.addCluster(c);
    return result;
  }

  @Override
  public TypeInformation[] getInputTypeRestriction() {
    return TypeUtil.array(TypeUtil.ANY);
  }

  @Override
  protected Logging getLogger() {
    return logger;
  }
}
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