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/*
 *   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 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 General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see .
 */

/*
 * InterquartileRange.java
 * Copyright (C) 2006-2012 University of Waikato, Hamilton, New Zealand
 */

package weka.filters.unsupervised.attribute;

import java.util.ArrayList;
import java.util.Collections;
import java.util.Enumeration;
import java.util.Vector;

import weka.core.Attribute;
import weka.core.Capabilities;
import weka.core.Capabilities.Capability;
import weka.core.DenseInstance;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Option;
import weka.core.Range;
import weka.core.RevisionUtils;
import weka.core.Utils;
import weka.filters.SimpleBatchFilter;

/**
 *  A filter for detecting outliers and extreme values
 * based on interquartile ranges. The filter skips the class attribute.

 * 

 * Outliers:

 * Q3 + OF*IQR < x <= Q3 + EVF*IQR

 * or

 * Q1 - EVF*IQR <= x < Q1 - OF*IQR

 * 

 * Extreme values:

 * x > Q3 + EVF*IQR

 * or

 * x < Q1 - EVF*IQR

 * 

 * Key:

 * Q1 = 25% quartile

 * Q3 = 75% quartile

 * IQR = Interquartile Range, difference between Q1 and Q3

 * OF = Outlier Factor

 * EVF = Extreme Value Factor
 * 

 * 
 * 
 *  Valid options are:
 * 

 * 
 * 
 * -D
 *  Turns on output of debugging information.
 * 
 * 
 * 
 * -R <col1,col2-col4,...>
 *  Specifies list of columns to base outlier/extreme value detection
 *  on. If an instance is considered in at least one of those
 *  attributes an outlier/extreme value, it is tagged accordingly.
 *  'first' and 'last' are valid indexes.
 *  (default none)
 * 
 * 
 * 
 * -O <num>
 *  The factor for outlier detection.
 *  (default: 3)
 * 
 * 
 * 
 * -E <num>
 *  The factor for extreme values detection.
 *  (default: 2*Outlier Factor)
 * 
 * 
 * 
 * -E-as-O
 *  Tags extreme values also as outliers.
 *  (default: off)
 * 
 * 
 * 
 * -P
 *  Generates Outlier/ExtremeValue pair for each numeric attribute in
 *  the range, not just a single indicator pair for all the attributes.
 *  (default: off)
 * 
 * 
 * 
 * -M
 *  Generates an additional attribute 'Offset' per Outlier/ExtremeValue
 *  pair that contains the multiplier that the value is off the median.
 *     value = median + 'multiplier' * IQR
 * Note: implicitely sets '-P'. (default: off)
 * 
 * 
 * 
 * 
 * Thanks to Dale for a few brainstorming sessions.
 * 
 * @author Dale Fletcher (dale at cs dot waikato dot ac dot nz)
 * @author fracpete (fracpete at waikato dot ac dot nz)
 * @version $Revision: 12476 $
 */
public class InterquartileRange extends SimpleBatchFilter {

  /** for serialization */
  private static final long serialVersionUID = -227879653639723030L;

  /** indicator for non-numeric attributes */
  public final static int NON_NUMERIC = -1;

  /** enum for obtaining the various determined IQR values. */
  public enum ValueType {
    UPPER_EXTREME_VALUES, UPPER_OUTLIER_VALUES, LOWER_OUTLIER_VALUES, LOWER_EXTREME_VALUES, MEDIAN, IQR
  };

  /** the attribute range to work on */
  protected Range m_Attributes = new Range("first-last");

  /** the generated indices (only for performance reasons) */
  protected int[] m_AttributeIndices = null;

  /** the factor for detecting outliers */
  protected double m_OutlierFactor = 3;

  /** the factor for detecting extreme values, by default 2*m_OutlierFactor */
  protected double m_ExtremeValuesFactor = 2 * m_OutlierFactor;

  /** whether extreme values are also tagged as outliers */
  protected boolean m_ExtremeValuesAsOutliers = false;

  /** the upper extreme value threshold (= Q3 + EVF*IQR) */
  protected double[] m_UpperExtremeValue = null;

  /** the upper outlier threshold (= Q3 + OF*IQR) */
  protected double[] m_UpperOutlier = null;

  /** the lower outlier threshold (= Q1 - OF*IQR) */
  protected double[] m_LowerOutlier = null;

  /** the interquartile range */
  protected double[] m_IQR = null;

  /** the median */
  protected double[] m_Median = null;

  /** the lower extreme value threshold (= Q1 - EVF*IQR) */
  protected double[] m_LowerExtremeValue = null;

  /**
   * whether to generate Outlier/ExtremeValue attributes for each attribute
   * instead of a general one
   */
  protected boolean m_DetectionPerAttribute = false;

  /** the position of the outlier attribute */
  protected int[] m_OutlierAttributePosition = null;

  /**
   * whether to add another attribute called "Offset", that lists the
   * 'multiplier' by which the outlier/extreme value is away from the median,
   * i.e., value = median + 'multiplier' * IQR 

   * automatically enables m_DetectionPerAttribute!
   */
  protected boolean m_OutputOffsetMultiplier = false;

  /**
   * Returns a string describing this filter
   * 
   * @return a description of the filter suitable for displaying in the
   *         explorer/experimenter gui
   */
  @Override
  public String globalInfo() {
    return "A filter for detecting outliers and extreme values based on "
      + "interquartile ranges. The filter skips the class attribute.\n\n"
      + "Outliers:\n" + "  Q3 + OF*IQR < x <= Q3 + EVF*IQR\n" + "  or\n"
      + "  Q1 - EVF*IQR <= x < Q1 - OF*IQR\n" + "\n" + "Extreme values:\n"
      + "  x > Q3 + EVF*IQR\n" + "  or\n" + "  x < Q1 - EVF*IQR\n" + "\n"
      + "Key:\n" + "  Q1  = 25% quartile\n" + "  Q3  = 75% quartile\n"
      + "  IQR = Interquartile Range, difference between Q1 and Q3\n"
      + "  OF  = Outlier Factor\n" + "  EVF = Extreme Value Factor";
  }

  /**
   * Returns an enumeration describing the available options.
   * 
   * @return an enumeration of all the available options.
   */
  @Override
  public Enumeration listOptions() {

    Vector result = new Vector();

    result.addElement(new Option(
      "\tSpecifies list of columns to base outlier/extreme value detection\n"
        + "\ton. If an instance is considered in at least one of those\n"
        + "\tattributes an outlier/extreme value, it is tagged accordingly.\n"
        + " 'first' and 'last' are valid indexes.\n" + "\t(default none)", "R",
      1, "-R "));

    result.addElement(new Option("\tThe factor for outlier detection.\n"
      + "\t(default: 3)", "O", 1, "-O "));

    result.addElement(new Option("\tThe factor for extreme values detection.\n"
      + "\t(default: 2*Outlier Factor)", "E", 1, "-E "));

    result.addElement(new Option("\tTags extreme values also as outliers.\n"
      + "\t(default: off)", "E-as-O", 0, "-E-as-O"));

    result
      .addElement(new Option(
        "\tGenerates Outlier/ExtremeValue pair for each numeric attribute in\n"
          + "\tthe range, not just a single indicator pair for all the attributes.\n"
          + "\t(default: off)", "P", 0, "-P"));

    result
      .addElement(new Option(
        "\tGenerates an additional attribute 'Offset' per Outlier/ExtremeValue\n"
          + "\tpair that contains the multiplier that the value is off the median.\n"
          + "\t   value = median + 'multiplier' * IQR\n"
          + "Note: implicitely sets '-P'." + "\t(default: off)", "M", 0, "-M"));

    result.addAll(Collections.list(super.listOptions()));

    return result.elements();
  }

  /**
   * Parses a list of options for this object.
   * 

   * 
   *  Valid options are:
   * 

   * 
   * 
   * -D
   *  Turns on output of debugging information.
   * 
   * 
   * 
   * -R <col1,col2-col4,...>
   *  Specifies list of columns to base outlier/extreme value detection
   *  on. If an instance is considered in at least one of those
   *  attributes an outlier/extreme value, it is tagged accordingly.
   *  'first' and 'last' are valid indexes.
   *  (default none)
   * 
   * 
   * 
   * -O <num>
   *  The factor for outlier detection.
   *  (default: 3)
   * 
   * 
   * 
   * -E <num>
   *  The factor for extreme values detection.
   *  (default: 2*Outlier Factor)
   * 
   * 
   * 
   * -E-as-O
   *  Tags extreme values also as outliers.
   *  (default: off)
   * 
   * 
   * 
   * -P
   *  Generates Outlier/ExtremeValue pair for each numeric attribute in
   *  the range, not just a single indicator pair for all the attributes.
   *  (default: off)
   * 
   * 
   * 
   * -M
   *  Generates an additional attribute 'Offset' per Outlier/ExtremeValue
   *  pair that contains the multiplier that the value is off the median.
   *     value = median + 'multiplier' * IQR
   * Note: implicitely sets '-P'. (default: off)
   * 
   * 
   * 
   * 
   * @param options the list of options as an array of strings
   * @throws Exception if an option is not supported
   */
  @Override
  public void setOptions(String[] options) throws Exception {

    String tmpStr = Utils.getOption("R", options);
    if (tmpStr.length() != 0) {
      setAttributeIndices(tmpStr);
    } else {
      setAttributeIndices("first-last");
    }

    tmpStr = Utils.getOption("O", options);
    if (tmpStr.length() != 0) {
      setOutlierFactor(Double.parseDouble(tmpStr));
    } else {
      setOutlierFactor(3);
    }

    tmpStr = Utils.getOption("E", options);
    if (tmpStr.length() != 0) {
      setExtremeValuesFactor(Double.parseDouble(tmpStr));
    } else {
      setExtremeValuesFactor(2 * getOutlierFactor());
    }

    setExtremeValuesAsOutliers(Utils.getFlag("E-as-O", options));

    setDetectionPerAttribute(Utils.getFlag("P", options));

    setOutputOffsetMultiplier(Utils.getFlag("M", options));

    super.setOptions(options);

    Utils.checkForRemainingOptions(options);
  }

  /**
   * Gets the current settings of the filter.
   * 
   * @return an array of strings suitable for passing to setOptions
   */
  @Override
  public String[] getOptions() {

    Vector result = new Vector();

    result.add("-R");
    if (!getAttributeIndices().equals("")) {
      result.add(getAttributeIndices());
    } else {
      result.add("first-last");
    }

    result.add("-O");
    result.add("" + getOutlierFactor());

    result.add("-E");
    result.add("" + getExtremeValuesFactor());

    if (getExtremeValuesAsOutliers()) {
      result.add("-E-as-O");
    }

    if (getDetectionPerAttribute()) {
      result.add("-P");
    }

    if (getOutputOffsetMultiplier()) {
      result.add("-M");
    }

    Collections.addAll(result, super.getOptions());

    return result.toArray(new String[result.size()]);
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String attributeIndicesTipText() {
    return "Specify range of attributes to act on; "
      + " this is a comma separated list of attribute indices, with"
      + " \"first\" and \"last\" valid values; specify an inclusive"
      + " range with \"-\", eg: \"first-3,5,6-10,last\".";
  }

  /**
   * Gets the current range selection
   * 
   * @return a string containing a comma separated list of ranges
   */
  public String getAttributeIndices() {
    return m_Attributes.getRanges();
  }

  /**
   * Sets which attributes are to be used for interquartile calculations and
   * outlier/extreme value detection (only numeric attributes among the
   * selection will be used).
   * 
   * @param value a string representing the list of attributes. Since the string
   *          will typically come from a user, attributes are indexed from 1. 

   *          eg: first-3,5,6-last
   * @throws IllegalArgumentException if an invalid range list is supplied
   */
  public void setAttributeIndices(String value) {
    m_Attributes.setRanges(value);
  }

  /**
   * Sets which attributes are to be used for interquartile calculations and
   * outlier/extreme value detection (only numeric attributes among the
   * selection will be used).
   * 
   * @param value an array containing indexes of attributes to work on. Since
   *          the array will typically come from a program, attributes are
   *          indexed from 0.
   * @throws IllegalArgumentException if an invalid set of ranges is supplied
   */
  public void setAttributeIndicesArray(int[] value) {
    setAttributeIndices(Range.indicesToRangeList(value));
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String outlierFactorTipText() {
    return "The factor for determining the thresholds for outliers.";
  }

  /**
   * Sets the factor for determining the thresholds for outliers.
   * 
   * @param value the factor.
   */
  public void setOutlierFactor(double value) {
    if (value >= getExtremeValuesFactor()) {
      System.err
        .println("OutlierFactor must be smaller than ExtremeValueFactor");
    } else {
      m_OutlierFactor = value;
    }
  }

  /**
   * Gets the factor for determining the thresholds for outliers.
   * 
   * @return the factor.
   */
  public double getOutlierFactor() {
    return m_OutlierFactor;
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String extremeValuesFactorTipText() {
    return "The factor for determining the thresholds for extreme values.";
  }

  /**
   * Sets the factor for determining the thresholds for extreme values.
   * 
   * @param value the factor.
   */
  public void setExtremeValuesFactor(double value) {
    if (value <= getOutlierFactor()) {
      System.err
        .println("ExtremeValuesFactor must be greater than OutlierFactor!");
    } else {
      m_ExtremeValuesFactor = value;
    }
  }

  /**
   * Gets the factor for determining the thresholds for extreme values.
   * 
   * @return the factor.
   */
  public double getExtremeValuesFactor() {
    return m_ExtremeValuesFactor;
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String extremeValuesAsOutliersTipText() {
    return "Whether to tag extreme values also as outliers.";
  }

  /**
   * Set whether extreme values are also tagged as outliers.
   * 
   * @param value whether or not to tag extreme values also as outliers.
   */
  public void setExtremeValuesAsOutliers(boolean value) {
    m_ExtremeValuesAsOutliers = value;
  }

  /**
   * Get whether extreme values are also tagged as outliers.
   * 
   * @return true if extreme values are also tagged as outliers.
   */
  public boolean getExtremeValuesAsOutliers() {
    return m_ExtremeValuesAsOutliers;
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String detectionPerAttributeTipText() {
    return "Generates Outlier/ExtremeValue attribute pair for each numeric "
      + "attribute, not just a single pair for all numeric attributes together.";
  }

  /**
   * Set whether an Outlier/ExtremeValue attribute pair is generated for each
   * numeric attribute ("true") or just one pair for all numeric attributes
   * together ("false").
   * 
   * @param value whether or not to generate indicator attribute pairs for each
   *          numeric attribute.
   */
  public void setDetectionPerAttribute(boolean value) {
    m_DetectionPerAttribute = value;
    if (!m_DetectionPerAttribute) {
      m_OutputOffsetMultiplier = false;
    }
  }

  /**
   * Gets whether an Outlier/ExtremeValue attribute pair is generated for each
   * numeric attribute ("true") or just one pair for all numeric attributes
   * together ("false").
   * 
   * @return true if indicator attribute pairs are generated for each numeric
   *         attribute.
   */
  public boolean getDetectionPerAttribute() {
    return m_DetectionPerAttribute;
  }

  /**
   * Returns the tip text for this property
   * 
   * @return tip text for this property suitable for displaying in the
   *         explorer/experimenter gui
   */
  public String outputOffsetMultiplierTipText() {
    return "Generates an additional attribute 'Offset' that contains the "
      + "multiplier the value is off the median: "
      + "value = median + 'multiplier' * IQR";
  }

  /**
   * Set whether an additional attribute "Offset" is generated per
   * Outlier/ExtremeValue attribute pair that lists the multiplier the value is
   * off the median: value = median + 'multiplier' * IQR.
   * 
   * @param value whether or not to generate the additional attribute.
   */
  public void setOutputOffsetMultiplier(boolean value) {
    m_OutputOffsetMultiplier = value;
    if (m_OutputOffsetMultiplier) {
      m_DetectionPerAttribute = true;
    }
  }

  /**
   * Gets whether an additional attribute "Offset" is generated per
   * Outlier/ExtremeValue attribute pair that lists the multiplier the value is
   * off the median: value = median + 'multiplier' * IQR.
   * 
   * @return true if the additional attribute is generated.
   */
  public boolean getOutputOffsetMultiplier() {
    return m_OutputOffsetMultiplier;
  }

  /**
   * Returns the Capabilities of this filter.
   * 
   * @return the capabilities of this object
   * @see Capabilities
   */
  @Override
  public Capabilities getCapabilities() {
    Capabilities result = super.getCapabilities();
    result.disableAll();

    // attributes
    result.enableAllAttributes();

    // class
    result.enableAllClasses();
    result.enable(Capability.MISSING_CLASS_VALUES);
    result.enable(Capability.NO_CLASS);

    return result;
  }

  /**
   * Determines the output format based on the input format and returns this. In
   * case the output format cannot be returned immediately, i.e.,
   * hasImmediateOutputFormat() returns false, then this method will called from
   * batchFinished() after the call of preprocess(Instances), in which, e.g.,
   * statistics for the actual processing step can be gathered.
   * 
   * @param inputFormat the input format to base the output format on
   * @return the output format
   * @throws Exception in case the determination goes wrong
   * @see #hasImmediateOutputFormat()
   * @see #batchFinished()
   */
  @Override
  protected Instances determineOutputFormat(Instances inputFormat)
    throws Exception {
    ArrayList atts;
    ArrayList values;
    Instances result;
    int i;

    // attributes must be numeric
    m_Attributes.setUpper(inputFormat.numAttributes() - 1);
    m_AttributeIndices = m_Attributes.getSelection();
    for (i = 0; i < m_AttributeIndices.length; i++) {
      // ignore class
      if (m_AttributeIndices[i] == inputFormat.classIndex()) {
        m_AttributeIndices[i] = NON_NUMERIC;
        continue;
      }
      // not numeric -> ignore it
      if (!inputFormat.attribute(m_AttributeIndices[i]).isNumeric()) {
        m_AttributeIndices[i] = NON_NUMERIC;
      }
    }

    // get old attributes
    atts = new ArrayList();
    for (i = 0; i < inputFormat.numAttributes(); i++) {
      atts.add(inputFormat.attribute(i));
    }

    if (!getDetectionPerAttribute()) {
      m_OutlierAttributePosition = new int[1];
      m_OutlierAttributePosition[0] = atts.size();

      // add 2 new attributes
      values = new ArrayList();
      values.add("no");
      values.add("yes");
      atts.add(new Attribute("Outlier", values));

      values = new ArrayList();
      values.add("no");
      values.add("yes");
      atts.add(new Attribute("ExtremeValue", values));
    } else {
      m_OutlierAttributePosition = new int[m_AttributeIndices.length];

      for (i = 0; i < m_AttributeIndices.length; i++) {
        if (m_AttributeIndices[i] == NON_NUMERIC) {
          continue;
        }

        m_OutlierAttributePosition[i] = atts.size();

        // add new attributes
        values = new ArrayList();
        values.add("no");
        values.add("yes");
        atts.add(new Attribute(inputFormat.attribute(m_AttributeIndices[i])
          .name() + "_Outlier", values));

        values = new ArrayList();
        values.add("no");
        values.add("yes");
        atts.add(new Attribute(inputFormat.attribute(m_AttributeIndices[i])
          .name() + "_ExtremeValue", values));

        if (getOutputOffsetMultiplier()) {
          atts.add(new Attribute(inputFormat.attribute(m_AttributeIndices[i])
            .name() + "_Offset"));
        }
      }
    }

    // generate header
    result = new Instances(inputFormat.relationName(), atts, 0);
    result.setClassIndex(inputFormat.classIndex());

    return result;
  }

  /**
   * computes the thresholds for outliers and extreme values
   * 
   * @param instances the data to work on
   */
  protected void computeThresholds(Instances instances) {
    int i;
    double[] values;
    int[] sortedIndices;
    int half;
    int quarter;
    double q1;
    double q2;
    double q3;

    m_UpperExtremeValue = new double[m_AttributeIndices.length];
    m_UpperOutlier = new double[m_AttributeIndices.length];
    m_LowerOutlier = new double[m_AttributeIndices.length];
    m_LowerExtremeValue = new double[m_AttributeIndices.length];
    m_Median = new double[m_AttributeIndices.length];
    m_IQR = new double[m_AttributeIndices.length];

    for (i = 0; i < m_AttributeIndices.length; i++) {
      // non-numeric attribute?
      if (m_AttributeIndices[i] == NON_NUMERIC) {
        continue;
      }

      // sort attribute data
      values = instances.attributeToDoubleArray(m_AttributeIndices[i]);
      sortedIndices = Utils.sort(values);

      // determine indices
      half = sortedIndices.length / 2;
      quarter = half / 2;

      if (sortedIndices.length % 2 == 1) {
        q2 = values[sortedIndices[half]];
      } else {
        q2 = (values[sortedIndices[half]] + values[sortedIndices[half + 1]]) / 2;
      }

      if (half % 2 == 1) {
        q1 = values[sortedIndices[quarter]];
        q3 = values[sortedIndices[sortedIndices.length - quarter - 1]];
      } else {
        q1 = (values[sortedIndices[quarter]] + values[sortedIndices[quarter + 1]]) / 2;
        q3 = (values[sortedIndices[sortedIndices.length - quarter - 1]] + values[sortedIndices[sortedIndices.length
          - quarter]]) / 2;
      }

      // determine thresholds and other values
      m_Median[i] = q2;
      m_IQR[i] = q3 - q1;
      m_UpperExtremeValue[i] = q3 + getExtremeValuesFactor() * m_IQR[i];
      m_UpperOutlier[i] = q3 + getOutlierFactor() * m_IQR[i];
      m_LowerOutlier[i] = q1 - getOutlierFactor() * m_IQR[i];
      m_LowerExtremeValue[i] = q1 - getExtremeValuesFactor() * m_IQR[i];
    }
  }

  /**
   * Returns the values for the specified type.
   * 
   * @param type the type of values to return
   * @return the values
   */
  public double[] getValues(ValueType type) {
    switch (type) {
    case UPPER_EXTREME_VALUES:
      return m_UpperExtremeValue;
    case UPPER_OUTLIER_VALUES:
      return m_UpperOutlier;
    case LOWER_OUTLIER_VALUES:
      return m_LowerOutlier;
    case LOWER_EXTREME_VALUES:
      return m_LowerExtremeValue;
    case MEDIAN:
      return m_Median;
    case IQR:
      return m_IQR;
    default:
      throw new IllegalArgumentException("Unhandled value type: " + type);
    }
  }

  /**
   * returns whether the instance has an outlier in the specified attribute or
   * not
   * 
   * @param inst the instance to test
   * @param index the attribute index
   * @return true if the instance is an outlier
   */
  protected boolean isOutlier(Instance inst, int index) {
    boolean result;
    double value;

    value = inst.value(m_AttributeIndices[index]);
    result = ((m_UpperOutlier[index] < value) && (value <= m_UpperExtremeValue[index]))
      || ((m_LowerExtremeValue[index] <= value) && (value < m_LowerOutlier[index]));

    return result;
  }

  /**
   * returns whether the instance is an outlier or not
   * 
   * @param inst the instance to test
   * @return true if the instance is an outlier
   */
  protected boolean isOutlier(Instance inst) {
    boolean result;
    int i;

    result = false;

    for (i = 0; i < m_AttributeIndices.length; i++) {
      // non-numeric attribute?
      if (m_AttributeIndices[i] == NON_NUMERIC) {
        continue;
      }

      result = isOutlier(inst, i);

      if (result) {
        break;
      }
    }

    return result;
  }

  /**
   * returns whether the instance has an extreme value in the specified
   * attribute or not
   * 
   * @param inst the instance to test
   * @param index the attribute index
   * @return true if the instance is an extreme value
   */
  protected boolean isExtremeValue(Instance inst, int index) {
    boolean result;
    double value;

    value = inst.value(m_AttributeIndices[index]);
    result = (value > m_UpperExtremeValue[index])
      || (value < m_LowerExtremeValue[index]);

    return result;
  }

  /**
   * returns whether the instance is an extreme value or not
   * 
   * @param inst the instance to test
   * @return true if the instance is an extreme value
   */
  protected boolean isExtremeValue(Instance inst) {
    boolean result;
    int i;

    result = false;

    for (i = 0; i < m_AttributeIndices.length; i++) {
      // non-numeric attribute?
      if (m_AttributeIndices[i] == NON_NUMERIC) {
        continue;
      }

      result = isExtremeValue(inst, i);

      if (result) {
        break;
      }
    }

    return result;
  }

  /**
   * returns the mulitplier of the IQR the instance is off the median for this
   * particular attribute.
   * 
   * @param inst the instance to test
   * @param index the attribute index
   * @return the multiplier
   */
  protected double calculateMultiplier(Instance inst, int index) {
    double result;
    double value;

    value = inst.value(m_AttributeIndices[index]);
    result = (value - m_Median[index]) / m_IQR[index];

    return result;
  }

  /**
   * Processes the given data (may change the provided dataset) and returns the
   * modified version. This method is called in batchFinished(). This
   * implementation only calls process(Instance) for each instance in the given
   * dataset.
   * 
   * @param instances the data to process
   * @return the modified data
   * @throws Exception in case the processing goes wrong
   * @see #batchFinished()
   */
  @Override
  protected Instances process(Instances instances) throws Exception {
    Instances result;
    Instance instOld;
    Instance instNew;
    int i;
    int n;
    double[] values;
    int numAttNew;
    int numAttOld;

    if (!isFirstBatchDone()) {
      computeThresholds(instances);
    }

    result = getOutputFormat();
    numAttOld = instances.numAttributes();
    numAttNew = result.numAttributes();

    for (n = 0; n < instances.numInstances(); n++) {
      instOld = instances.instance(n);
      values = new double[numAttNew];
      System.arraycopy(instOld.toDoubleArray(), 0, values, 0, numAttOld);

      // per attribute?
      if (!getDetectionPerAttribute()) {
        // outlier?
        if (isOutlier(instOld)) {
          values[m_OutlierAttributePosition[0]] = 1;
        }
        // extreme value?
        if (isExtremeValue(instOld)) {
          values[m_OutlierAttributePosition[0] + 1] = 1;
          // tag extreme values also as outliers?
          if (getExtremeValuesAsOutliers()) {
            values[m_OutlierAttributePosition[0]] = 1;
          }
        }
      } else {
        for (i = 0; i < m_AttributeIndices.length; i++) {
          // non-numeric attribute?
          if (m_AttributeIndices[i] == NON_NUMERIC) {
            continue;
          }

          // outlier?
          if (isOutlier(instOld, m_AttributeIndices[i])) {
            values[m_OutlierAttributePosition[i]] = 1;
          }
          // extreme value?
          if (isExtremeValue(instOld, m_AttributeIndices[i])) {
            values[m_OutlierAttributePosition[i] + 1] = 1;
            // tag extreme values also as outliers?
            if (getExtremeValuesAsOutliers()) {
              values[m_OutlierAttributePosition[i]] = 1;
            }
          }
          // add multiplier?
          if (getOutputOffsetMultiplier()) {
            values[m_OutlierAttributePosition[i] + 2] =
              calculateMultiplier(instOld, m_AttributeIndices[i]);
          }
        }
      }

      // generate new instance
      instNew = new DenseInstance(1.0, values);
      instNew.setDataset(result);

      // copy possible strings, relational values...
      copyValues(instNew, false, instOld.dataset(), outputFormatPeek());

      // add to output
      result.add(instNew);
    }

    return result;
  }

  /**
   * Returns the revision string.
   * 
   * @return the revision
   */
  @Override
  public String getRevision() {
    return RevisionUtils.extract("$Revision: 12476 $");
  }

  /**
   * Main method for testing this class.
   * 
   * @param args should contain arguments to the filter: use -h for help
   */
  public static void main(String[] args) {
    runFilter(new InterquartileRange(), args);
  }
}