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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This is the stable version. Apart from bugfixes, this version does not receive any other updates.
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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 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.
 */

/*
 *    InstancesResultListener.java
 *    Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
 *
 */


package weka.experiment;

import weka.core.Attribute;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.RevisionUtils;

import java.io.BufferedOutputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.PrintWriter;
import java.util.Hashtable;

/**
 
 * Outputs the received results in arff format to a Writer. All results must be received before the instances can be written out.
 * 
 
 *
 
 * Valid options are: 

 * 
 * 
 -O <file name>
 *  The filename where output will be stored. Use - for stdout.
 *  (default temp file)
 * 
 
 * 
 * @author Len Trigg ([email protected])
 * @version $Revision: 1.11 $
 */
public class InstancesResultListener 
  extends CSVResultListener {
  
  /** for serialization */
  static final long serialVersionUID = -2203808461809311178L;

  /** Stores the instances created so far, before assigning to a header */
  protected transient FastVector m_Instances;
  
  /** Stores the attribute types for each column */
  protected transient int [] m_AttributeTypes;

  /** For lookup of indices given a string value for each nominal attribute */
  protected transient Hashtable [] m_NominalIndexes;

  /** Contains strings seen so far for each nominal attribute */ 
  protected transient FastVector [] m_NominalStrings;
 
  /** 
   * Sets temporary file.
   */
  public InstancesResultListener() {

    File resultsFile;
    try {
      resultsFile = File.createTempFile("weka_experiment", ".arff");
      resultsFile.deleteOnExit();
    } catch (Exception e) {
      System.err.println("Cannot create temp file, writing to standard out.");
      resultsFile = new File("-");
    }
    setOutputFile(resultsFile);
    setOutputFileName("");
  } 

  /**
   * Returns a string describing this result listener
   * @return a description of the result listener suitable for
   * displaying in the explorer/experimenter gui
   */
  public String globalInfo() {
    return
        "Outputs the received results in arff format to "
      + "a Writer. All results must be received before the instances can be "
      + "written out.";
  }

  /**
   * Prepare for the results to be received.
   *
   * @param rp the ResultProducer that will generate the results
   * @exception Exception if an error occurs during preprocessing.
   */
  public void preProcess(ResultProducer rp) throws Exception {

    m_RP = rp;
    if ((m_OutputFile == null) || (m_OutputFile.getName().equals("-"))) {
      m_Out = new PrintWriter(System.out, true);
    } else {
      m_Out = new PrintWriter(
	      new BufferedOutputStream(
	      new FileOutputStream(m_OutputFile)), true);
    }

    Object [] keyTypes = m_RP.getKeyTypes();
    Object [] resultTypes = m_RP.getResultTypes();

    m_AttributeTypes = new int [keyTypes.length + resultTypes.length];
    m_NominalIndexes = new Hashtable [m_AttributeTypes.length];
    m_NominalStrings = new FastVector [m_AttributeTypes.length];
    m_Instances = new FastVector();

    for (int i = 0; i < m_AttributeTypes.length; i++) {
      Object attribute = null;
      if (i < keyTypes.length) {
	attribute = keyTypes[i];
      } else {
	attribute = resultTypes[i - keyTypes.length];
      }
      if (attribute instanceof String) {
	m_AttributeTypes[i] = Attribute.NOMINAL;
	m_NominalIndexes[i] = new Hashtable();
	m_NominalStrings[i] = new FastVector();
      } else if (attribute instanceof Double) {
	m_AttributeTypes[i] = Attribute.NUMERIC;
      } else {
	throw new Exception("Unknown attribute type in column " + (i + 1));
      }
    }
  }
  
  /**
   * Perform any postprocessing. When this method is called, it indicates
   * that no more results will be sent that need to be grouped together
   * in any way.
   *
   * @param rp the ResultProducer that generated the results
   * @exception Exception if an error occurs
   */
  public void postProcess(ResultProducer rp) throws Exception {

    if (m_RP != rp) {
      throw new Error("Unrecognized ResultProducer sending results!!");
    }
    String [] keyNames = m_RP.getKeyNames();
    String [] resultNames = m_RP.getResultNames();
    FastVector attribInfo = new FastVector();
    for (int i = 0; i < m_AttributeTypes.length; i++) {
      String attribName = "Unknown";
      if (i < keyNames.length) {
	attribName = "Key_" + keyNames[i];
      } else {
	attribName = resultNames[i - keyNames.length];
      }
      
      switch (m_AttributeTypes[i]) {
      case Attribute.NOMINAL:
	if (m_NominalStrings[i].size() > 0) {
	  attribInfo.addElement(new Attribute(attribName,
					      m_NominalStrings[i]));
	} else {
	  attribInfo.addElement(new Attribute(attribName, (FastVector)null));
	}
	break;
      case Attribute.NUMERIC:
	attribInfo.addElement(new Attribute(attribName));
	break;
      case Attribute.STRING:
	attribInfo.addElement(new Attribute(attribName, (FastVector)null));
	break;
      default:
	throw new Exception("Unknown attribute type");
      }
    }

    Instances result = new Instances("InstanceResultListener", attribInfo, 
				     m_Instances.size());
    for (int i = 0; i < m_Instances.size(); i++) {
      result.add((Instance)m_Instances.elementAt(i));
    }

    m_Out.println(new Instances(result, 0));
    for (int i = 0; i < result.numInstances(); i++) {
      m_Out.println(result.instance(i));
    }
    
    if (!(m_OutputFile == null) && !(m_OutputFile.getName().equals("-"))) {
      m_Out.close();
    }
  }

  /**
   * Collects each instance and adjusts the header information.
   *
   * @param rp the ResultProducer that generated the result
   * @param key The key for the results.
   * @param result The actual results.
   * @exception Exception if the result could not be accepted.
   */
  public void acceptResult(ResultProducer rp, Object[] key, Object[] result) 
    throws Exception {

    if (m_RP != rp) {
      throw new Error("Unrecognized ResultProducer sending results!!");
    }
    
    Instance newInst = new Instance(m_AttributeTypes.length);
    for(int i = 0; i < m_AttributeTypes.length; i++) {
      Object val = null;
      if (i < key.length) {
	val = key[i];
      } else {
	val = result[i - key.length];
      }
      if (val == null) {
	newInst.setValue(i, Instance.missingValue());
      } else {
	switch (m_AttributeTypes[i]) {
	case Attribute.NOMINAL:
	  String str = (String) val;
	  Double index = (Double)m_NominalIndexes[i].get(str);
	  if (index == null) {
	    index = new Double(m_NominalStrings[i].size());
	    m_NominalIndexes[i].put(str, index);
	    m_NominalStrings[i].addElement(str);
	  }
	  newInst.setValue(i, index.doubleValue());
	  break;
	case Attribute.NUMERIC:
	  double dou = ((Double) val).doubleValue();
	  newInst.setValue(i, (double)dou);
	  break;
	default:
	  newInst.setValue(i, Instance.missingValue());
	}
      }
    }
    m_Instances.addElement(newInst);
  }
  
  /**
   * Returns the revision string.
   * 
   * @return		the revision
   */
  public String getRevision() {
    return RevisionUtils.extract("$Revision: 1.11 $");
  }
} // InstancesResultListener