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

/*
 This file is part of ELKI:
 Environment for Developing KDD-Applications Supported by Index-Structures

 Copyright (C) 2015
 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.outlier.OutlierAlgorithm;
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.datastore.DataStoreFactory;
import de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil;
import de.lmu.ifi.dbs.elki.database.datastore.WritableDoubleDataStore;
import de.lmu.ifi.dbs.elki.database.ids.DBIDIter;
import de.lmu.ifi.dbs.elki.database.relation.DoubleRelation;
import de.lmu.ifi.dbs.elki.database.relation.MaterializedDoubleRelation;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.logging.Logging;
import de.lmu.ifi.dbs.elki.result.outlier.OutlierResult;
import de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta;
import de.lmu.ifi.dbs.elki.result.outlier.ProbabilisticOutlierScore;

/**
 * Trivial method that claims to find no outliers. Can be used as reference
 * algorithm in comparisons.
 * 
 * @author Erich Schubert
 * @since 0.4.0
 */
public class TrivialNoOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
  /**
   * Our logger.
   */
  private static final Logging LOG = Logging.getLogger(TrivialNoOutlier.class);

  /**
   * Constructor.
   */
  public TrivialNoOutlier() {
    super();
  }

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

  /**
   * Run the actual algorithm.
   * 
   * @param relation Relation
   * @return Result
   */
  public OutlierResult run(Relation<?> relation) {
    WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT);
    for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
      scores.putDouble(iditer, 0.0);
    }
    DoubleRelation scoreres = new MaterializedDoubleRelation("Trivial no-outlier score", "no-outlier", scores, relation.getDBIDs());
    OutlierScoreMeta meta = new ProbabilisticOutlierScore();
    return new OutlierResult(meta, scoreres);
  }

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