aggregationmeasure.java

一个数据挖掘软件ALPHAMINERR的整个过程的JAVA版源代码

/*
 *    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 2 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, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/**
 * <p>Title: XELOPES</p>
 * <p>Description: Java Data Mining API. Supported standarts: <a href="http://www.dmg.org">Predictive Model Markup Language (PMML 2.0) </a>;  <a href="http://www.omg.org/cwm">DataMining specification for Common Warehouse Metamodel (OMG)</a>.</p>
 * <p>Copyright: Copyright (c) 2002-2004 prudsys AG</p>
 * <p>Company: prudsys, ZSoft</p>
 * @authorv Michael Thess
 * @version 1.2
 */

package com.prudsys.pdm.Olap.Metadata.Measures;

import javax.olap.OLAPException;

import com.prudsys.pdm.Core.MiningAttribute;
import com.prudsys.pdm.Core.MiningException;
import com.prudsys.pdm.Models.Statistics.SimpleStats;
import com.prudsys.pdm.Olap.Metadata.Measure;

/**
 * Measure which is aggregated over an attribute.
 */
public class AggregationMeasure extends Measure
{
  // -----------------------------------------------------------------------
  //  Constants declarations
  // -----------------------------------------------------------------------
  /** Sum. */
  public static final int SUM = 0;

  /** Minimum. */
  public static final int MIN = 1;

  /** Maximum. */
  public static final int MAX = 2;

  /** Mean. */
  public static final int MEAN = 3;

  /** Mode. */
  public static final int MODE = 4;

  /** Count. */
  public static final int COUNT = 5;

  /** Missing Count. */
  public static final int MISSING_COUNT = 6;

  /** Entropy. */
  public static final int ENTROPY = 7;

  /** Variance. */
  public static final int VARIANCE = 8;

  /** Standard deviation. */
  public static final int DEVIATION = 9;

  // -----------------------------------------------------------------------
  //  Variables declarations
  // -----------------------------------------------------------------------
  /** Aggregation attribute. */
  protected MiningAttribute attribute;

  // -----------------------------------------------------------------------
  //  Constructors
  // -----------------------------------------------------------------------
  /**
   * Empty constructor.
   */
  public AggregationMeasure() {

  }

  /**
   * Aggregation measure with given subtype and aggregation attribute.
   *
   * @param subtype measure subtype
   * @param attribute aggregation attribute
   */
  public AggregationMeasure(int subtype, MiningAttribute attribute) {

    this.subtype = subtype;
    this.attribute = attribute;
  }

  // -----------------------------------------------------------------------
  //  Getter and setter methods
  // -----------------------------------------------------------------------
  /**
   * Returns aggregation attribute.
   *
   * @return aggregation attribute
   */
  public MiningAttribute getAttribute() {
    return attribute;
  }

  /**
   * Sets new aggregation attribute.
   *
   * @param attribute new aggregation attribute
   */
  public void setAttribute(MiningAttribute attribute) {
    this.attribute = attribute;
  }

  // -----------------------------------------------------------------------
  //  Method of measure value calculation
  // -----------------------------------------------------------------------
  /**
   * Calculates aggregated measure value.
   *
   * @return measure value
   * @throws OLAPException unknwn subtype
   */
  public double measureValue() throws OLAPException {

    try {
      SimpleStats stats = measureDimension.getStats();

      if (subtype == SUM)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_SUM);
      else if (subtype == MIN)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_MIN);
      else if (subtype == MAX)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_MAX);
      else if (subtype == MEAN)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_MEAN);
      else if (subtype == MODE)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_MODE);
      else if (subtype == COUNT)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_COUNT);
      else if (subtype == MISSING_COUNT)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_MISSING_COUNT);
      else if (subtype == ENTROPY)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_ENTROPY);
      else if (subtype == VARIANCE)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_VARIANCE);
      else if (subtype == DEVIATION)
        return stats.getCalculatedValue(attribute, SimpleStats.STAT_DEVIATION);
      else
        throw new OLAPException("unknown subtype");
    }
    catch (MiningException ex) {
      throw new OLAPException( ex.toString() );
    }
  }
}