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

/*
 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 org.junit.Test;

import de.lmu.ifi.dbs.elki.JUnit4Test;
import de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest;
import de.lmu.ifi.dbs.elki.data.Clustering;
import de.lmu.ifi.dbs.elki.data.DoubleVector;
import de.lmu.ifi.dbs.elki.data.model.SubspaceModel;
import de.lmu.ifi.dbs.elki.database.Database;
import de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.ParameterException;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization;

/**
 * Performs a full CLIQUE run, and compares the result with a clustering derived
 * from the data set labels. This test ensures that CLIQUE performance doesn't
 * unexpectedly drop on this data set (and also ensures that the algorithms
 * work, as a side effect).
 *
 * @author Elke Achtert
 * @author Katharina Rausch
 * @author Erich Schubert
 * @since 0.3
 */
public class CLIQUETest extends AbstractSimpleAlgorithmTest implements JUnit4Test {
  /**
   * Run CLIQUE with fixed parameters and compare the result to a golden
   * standard.
   *
   * @throws ParameterException
   */
  @Test
  public void testCLIQUEResults() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-simple.csv", 600);

    ListParameterization params = new ListParameterization();
    params.addParameter(CLIQUE.TAU_ID, "0.1");
    params.addParameter(CLIQUE.XSI_ID, 20);

    // setup algorithm
    CLIQUE<DoubleVector> clique = ClassGenericsUtil.parameterizeOrAbort(CLIQUE.class, params);
    testParameterizationOk(params);

    // run CLIQUE on database
    Clustering<SubspaceModel> result = clique.run(db);

    // PairCounting is not appropriate here: overlapping clusterings!
    // testFMeasure(db, result, 0.9882);
    testClusterSizes(result, new int[] { 200, 200, 216, 400 });
  }

  /**
   * Run CLIQUE with fixed parameters and compare the result to a golden
   * standard.
   *
   * @throws ParameterException
   */
  @Test
  public void testCLIQUESubspaceOverlapping() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-overlapping-3-4d.ascii", 850);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(CLIQUE.TAU_ID, 0.2);
    params.addParameter(CLIQUE.XSI_ID, 6);
    CLIQUE<DoubleVector> clique = ClassGenericsUtil.parameterizeOrAbort(CLIQUE.class, params);
    testParameterizationOk(params);

    // run CLIQUE on database
    Clustering<SubspaceModel> result = clique.run(db);
    // PairCounting is not appropriate here: overlapping clusterings!
    // testFMeasure(db, result, 0.433661);
    testClusterSizes(result, new int[] { 255, 409, 458, 458, 480 });
  }

  /**
   * Run CLIQUE with fixed parameters and compare the result to a golden
   * standard.
   *
   * @throws ParameterException
   */
  @Test
  public void testCLIQUESubspaceOverlappingPrune() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-overlapping-3-4d.ascii", 850);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(CLIQUE.TAU_ID, 0.2);
    params.addParameter(CLIQUE.XSI_ID, 6);
    params.addFlag(CLIQUE.PRUNE_ID);
    CLIQUE<DoubleVector> clique = ClassGenericsUtil.parameterizeOrAbort(CLIQUE.class, params);
    testParameterizationOk(params);

    // run CLIQUE on database
    Clustering<SubspaceModel> result = clique.run(db);
    // PairCounting is not appropriate here: overlapping clusterings!
    // testFMeasure(db, result, 0.433661);
    testClusterSizes(result, new int[] { 255, 409, 458, 458, 480 });
  }
}