content: /*
   *    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.
   */
  
  /*
   *    Puk.java
   *    Copyright (C) 2007 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.classifiers.functions.supportVector;
  
  import weka.core.Capabilities;
  import weka.core.Instance;
  import weka.core.Instances;
  import weka.core.Option;
  import weka.core.RevisionUtils;
  import weka.core.TechnicalInformation;
  import weka.core.TechnicalInformationHandler;
  import weka.core.Utils;
  import weka.core.Capabilities.Capability;
  import weka.core.TechnicalInformation.Field;
  import weka.core.TechnicalInformation.Type;
  
  import java.util.Enumeration;
  import java.util.Vector;
  
  /**
   <!-- globalinfo-start -->
   * The Pearson VII function-based universal kernel.<br/>
   * <br/>
   * For more information see:<br/>
   * <br/>
   * B. Uestuen, W.J. Melssen, L.M.C. Buydens (2006). Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel. Chemometrics and Intelligent Laboratory Systems. 81:29-40.
   * <p/>
   <!-- globalinfo-end -->
   * 
   <!-- options-start -->
   * Valid options are: <p/>
   * 
   * <pre> -D
   *  Enables debugging output (if available) to be printed.
   *  (default: off)</pre>
   * 
   * <pre> -no-checks
   *  Turns off all checks - use with caution!
   *  (default: checks on)</pre>
   * 
   * <pre> -C &lt;num&gt;
   *  The size of the cache (a prime number), 0 for full cache and 
   *  -1 to turn it off.
   *  (default: 250007)</pre>
   * 
   * <pre> -O &lt;num&gt;
   *  The Omega parameter.
   *  (default: 1.0)</pre>
   * 
   * <pre> -S &lt;num&gt;
   *  The Sigma parameter.
   *  (default: 1.0)</pre>
   * 
   <!-- options-end -->
   *
   * @author Bernhard Pfahringer (bernhard@cs.waikato.ac.nz)
   * @version $Revision: 5450 $
   */
  public class Puk 
    extends CachedKernel
    implements TechnicalInformationHandler {
    
    /** for serialization */
    private static final long serialVersionUID = 1682161522559978851L;
  
    /** The precalculated dotproducts of &lt;inst_i,inst_i&gt; */
    protected double m_kernelPrecalc[];
  
    /** Omega for the Puk kernel. */
    protected double m_omega = 1.0;
  
    /** Sigma for the Puk kernel. */
    protected double m_sigma = 1.0;
  
    /** Cached factor for the Puk kernel. */
    protected double m_factor = 1.0;
  
    /**
     * default constructor - does nothing.
     */
    public Puk() {
      super();
    }
    
    /**
     * Constructor. Initializes m_kernelPrecalc[].
     * 
     * @param data	the data to use
     * @param cacheSize	the size of the cache
     * @param omega	the exponent
     * @param sigma	the bandwidth
     * @throws Exception	if something goes wrong
     */
    public Puk(Instances data, int cacheSize, double omega, double sigma)
      throws Exception {
  
      super();
      
      setCacheSize(cacheSize);
      setOmega(omega);
      setSigma(sigma);
      
      buildKernel(data);
    }
    
    /**
     * Returns a string describing the kernel
     * 
     * @return a description suitable for displaying in the
     *         explorer/experimenter gui
     */
    public String globalInfo() {
      return 
          "The Pearson VII function-based universal kernel.\n\n"
        + "For more information see:\n\n"
        + getTechnicalInformation().toString();
    }
  
    /**
     * Returns an instance of a TechnicalInformation object, containing 
     * detailed information about the technical background of this class,
     * e.g., paper reference or book this class is based on.
     * 
     * @return the technical information about this class
     */
    public TechnicalInformation getTechnicalInformation() {
      TechnicalInformation 	result;
      
      result = new TechnicalInformation(Type.ARTICLE);
      result.setValue(Field.AUTHOR, "B. Uestuen and W.J. Melssen and L.M.C. Buydens");
      result.setValue(Field.YEAR, "2006");
      result.setValue(Field.TITLE, "Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel");
      result.setValue(Field.JOURNAL, "Chemometrics and Intelligent Laboratory Systems");
      result.setValue(Field.VOLUME, "81");
      result.setValue(Field.PAGES, "29-40");
      result.setValue(Field.PDF, "http://www.cac.science.ru.nl/research/publications/PDFs/ustun2006.pdf");
  
      return result;
    }
    
    /**
     * Returns an enumeration describing the available options.
     *
     * @return 		an enumeration of all the available options.
     */
    public Enumeration listOptions() {
      Vector		result;
      Enumeration		en;
      
      result = new Vector();
  
      en = super.listOptions();
      while (en.hasMoreElements())
        result.addElement(en.nextElement());
  
      result.addElement(new Option(
  	"\tThe Omega parameter.\n"
  	+ "\t(default: 1.0)",
  	"O", 1, "-O <num>"));
  
      result.addElement(new Option(
  	"\tThe Sigma parameter.\n"
  	+ "\t(default: 1.0)",
  	"S", 1, "-S <num>"));
  
      return result.elements();
    }
  
    /**
     * Parses a given list of options. <p/>
     * 
     <!-- options-start -->
     * Valid options are: <p/>
     * 
     * <pre> -D
     *  Enables debugging output (if available) to be printed.
     *  (default: off)</pre>
     * 
     * <pre> -no-checks
     *  Turns off all checks - use with caution!
     *  (default: checks on)</pre>
     * 
     * <pre> -C &lt;num&gt;
     *  The size of the cache (a prime number), 0 for full cache and 
     *  -1 to turn it off.
     *  (default: 250007)</pre>
     * 
     * <pre> -O &lt;num&gt;
     *  The Omega parameter.
     *  (default: 1.0)</pre>
     * 
     * <pre> -S &lt;num&gt;
     *  The Sigma parameter.
     *  (default: 1.0)</pre>
     * 
     <!-- options-end -->
     * 
     * @param options 	the list of options as an array of strings
     * @throws Exception 	if an option is not supported
     */
    public void setOptions(String[] options) throws Exception {
      String	tmpStr;
      
      tmpStr = Utils.getOption('O', options);
      if (tmpStr.length() != 0)
        setOmega(Double.parseDouble(tmpStr));
      else
        setOmega(1.0);
      
      tmpStr = Utils.getOption('S', options);
      if (tmpStr.length() != 0)
        setSigma(Double.parseDouble(tmpStr));
      else
        setSigma(1.0);
      
      super.setOptions(options);
    }
  
    /**
     * Gets the current settings of the Kernel.
     *
     * @return an array of strings suitable for passing to setOptions
     */
    public String[] getOptions() {
      int       i;
      Vector    result;
      String[]  options;
  
      result = new Vector();
      options = super.getOptions();
      for (i = 0; i < options.length; i++)
        result.add(options[i]);
  
      result.add("-O");
      result.add("" + getOmega());
  
      result.add("-S");
      result.add("" + getSigma());
  
      return (String[]) result.toArray(new String[result.size()]);	  
    }
  
    /**
     * returns the dot product
     * 
     * @param id1   	the index of instance 1
     * @param id2		the index of instance 2
     * @param inst1	the instance 1 object
     * @return 		the dot product
     * @throws Exception 	if something goes wrong
     */
    protected double evaluate(int id1, int id2, Instance inst1)
      throws Exception {
  
      if (id1 == id2) {
        return 1.0;
      } else {
        double precalc1;
        if (id1 == -1)
  	precalc1 = dotProd(inst1, inst1);
        else
  	precalc1 = m_kernelPrecalc[id1];
        Instance inst2 = m_data.instance(id2);
        double squaredDifference = -2.0 * dotProd(inst1, inst2) + precalc1 + m_kernelPrecalc[id2];
        double intermediate = m_factor * Math.sqrt(squaredDifference);
        double result = 1.0 / Math.pow(1.0 + intermediate * intermediate, getOmega());
        return result;
      }
    }
      
    /**
     * Sets the omega value.
     * 
     * @param value	the omega value
     */
    public void setOmega(double value) {
      m_omega  = value;
      m_factor = computeFactor(m_omega, m_sigma);
    }
    
    /**
     * Gets the omega value.
     * 
     * @return		the omega value
     */
    public double getOmega() {
      return m_omega;
    }
  
    /**
     * Returns the tip text for this property
     * 
     * @return 		tip text for this property suitable for
     * 			displaying in the explorer/experimenter gui
     */
    public String omegaTipText() {
      return "The Omega value.";
    }
  
    /**
     * Sets the sigma value.
     * 
     * @param value	the sigma value
     */
    public void setSigma(double value) {
      m_sigma  = value;
      m_factor = computeFactor(m_omega, m_sigma);
    }
    
    /**
     * Gets the sigma value.
     * 
     * @return		the sigma value
     */
    public double getSigma() {
      return m_sigma;
    }
  
    /**
     * Returns the tip text for this property
     * 
     * @return 		tip text for this property suitable for
     * 			displaying in the explorer/experimenter gui
     */
    public String sigmaTipText() {
      return "The Sigma value.";
    }
  
    /**
     * computes the factor for curve-fitting (see equation (13) in paper)
     * 
     * @param omega	the omega to use
     * @param sigma	the sigma to use
     * @return		the factor for curve-fitting
     */
    protected double computeFactor(double omega, double sigma) {
      double root = Math.sqrt(Math.pow(2.0, 1.0 / omega) - 1);
      return 2.0 * root / sigma;
    }
  
    /**
     * initializes variables etc.
     * 
     * @param data	the data to use
     */
    protected void initVars(Instances data) {
      super.initVars(data);
      
      m_factor        = computeFactor(m_omega, m_sigma);
      m_kernelPrecalc = new double[data.numInstances()];
    }
  
    /** 
     * Returns the Capabilities of this kernel.
     *
     * @return            the capabilities of this object
     * @see               Capabilities
     */
    public Capabilities getCapabilities() {
      Capabilities result = super.getCapabilities();
      result.disableAll();
      
      result.enable(Capability.NUMERIC_ATTRIBUTES);
      result.enableAllClasses();
      result.enable(Capability.MISSING_CLASS_VALUES);
      
      return result;
    }
    
    /**
     * builds the kernel with the given data. Initializes the kernel cache. 
     * The actual size of the cache in bytes is (64 * cacheSize).
     * 
     * @param data	the data to base the kernel on
     * @throws Exception	if something goes wrong
     */
    public void buildKernel(Instances data) throws Exception {
      // does kernel handle the data?
      if (!getChecksTurnedOff())
        getCapabilities().testWithFail(data);
      
      initVars(data);
  
      for (int i = 0; i < data.numInstances(); i++)
        m_kernelPrecalc[i] = dotProd(data.instance(i), data.instance(i));
    }
    
    /**
     * returns a string representation for the Kernel
     * 
     * @return 		a string representaiton of the kernel
     */
    public String toString() {
      return "Puk kernel";
    }
    
    /**
     * Returns the revision string.
     * 
     * @return		the revision
     */
    public String getRevision() {
      return RevisionUtils.extract("$Revision: 5450 $");
    }
  }
  