remoteexperiment.java

Java 编写的多种数据挖掘算法 包括聚类、分类、预处理等

/*
 *    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.
 */

/*
 *    RemoteExperiment.java
 *    Copyright (C) 2000 Mark Hall
 *
 */


package weka.experiment;

import weka.core.FastVector;
import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.Queue;
import weka.core.SerializedObject;
import weka.core.Utils;
import weka.core.xml.KOML;
import weka.core.xml.XMLOptions;
import weka.experiment.xml.XMLExperiment;

import java.io.BufferedInputStream;
import java.io.BufferedOutputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.rmi.Naming;
import java.util.Enumeration;

import javax.swing.DefaultListModel;

/**
 * Holds all the necessary configuration information for a distributed
 * experiment. This object is able to be serialized for storage on disk.<p>
 * 
 * This class is experimental at present. Has been tested using 
 * CSVResultListener (sending results to standard out) and 
 * DatabaseResultListener (InstantDB + RmiJdbc bridge). <p>
 *
 * Getting started:<p>
 *
 * Start InstantDB (with the RMI bridge) on some machine. If using java2
 * then specify -Djava.security.policy=db.policy to the
 * virtual machine. Where db.policy is as follows: <br>
 * <pre>
 * grant {
 *   permission java.security.AllPermission;
 * };
 * </pre><p>
 *
 * Start RemoteEngine servers on x machines as per the instructons in the
 * README_Experiment_Gui file. There must be a 
 * DatabaseUtils.props in either the HOME or current directory of each
 * machine, listing all necessary jdbc drivers.<p>
 *
 * The machine where a RemoteExperiment is started must also have a copy
 * of DatabaseUtils.props listing the URL to the machine where the 
 * database server is running (RmiJdbc + InstantDB). <p>
 *
 * Here is an example of starting a RemoteExperiment: <p>
 *
 * <pre>
 *
 * java -Djava.rmi.server.codebase=file:/path to weka classes/ \
 * weka.experiment.RemoteExperiment -L 1 -U 10 \
 * -T /home/ml/datasets/UCI/iris.arff \
 * -D "weka.experiment.DatabaseResultListener" \
 * -P "weka.experiment.RandomSplitResultProducer" \
 * -h rosebud.cs.waikato.ac.nz -h blackbird.cs.waikato.ac.nz -r -- \
 * -W weka.experiment.ClassifierSplitEvaluator -- \
 * -W weka.classifiers.bayes.NaiveBayes
 *
 * </pre> <p>
 * The "codebase" property tells rmi where to serve up weka classes from.
 * This can either be a file url (as long as a shared file system is being
 * used that is accessable by the remoteEngine servers), or http url (which
 * of course supposes that a web server is running and you have put your
 * weka classes somewhere that is web accessable). If using a file url the
 * trailing "/" is *most* important unless the weka classes are in a jar
 * file. <p>
 *
 <!-- options-start -->
 * Valid options are: <p/>
 * 
 * <pre> -L &lt;num&gt;
 *  The lower run number to start the experiment from.
 *  (default 1)</pre>
 * 
 * <pre> -U &lt;num&gt;
 *  The upper run number to end the experiment at (inclusive).
 *  (default 10)</pre>
 * 
 * <pre> -T &lt;arff file&gt;
 *  The dataset to run the experiment on.
 *  (required, may be specified multiple times)</pre>
 * 
 * <pre> -P &lt;class name&gt;
 *  The full class name of a ResultProducer (required).
 *  eg: weka.experiment.RandomSplitResultProducer</pre>
 * 
 * <pre> -D &lt;class name&gt;
 *  The full class name of a ResultListener (required).
 *  eg: weka.experiment.CSVResultListener</pre>
 * 
 * <pre> -N &lt;string&gt;
 *  A string containing any notes about the experiment.
 *  (default none)</pre>
 * 
 * <pre> 
 * Options specific to result producer weka.experiment.RandomSplitResultProducer:
 * </pre>
 * 
 * <pre> -P &lt;percent&gt;
 *  The percentage of instances to use for training.
 *  (default 66)</pre>
 * 
 * <pre> -D
 * Save raw split evaluator output.</pre>
 * 
 * <pre> -O &lt;file/directory name/path&gt;
 *  The filename where raw output will be stored.
 *  If a directory name is specified then then individual
 *  outputs will be gzipped, otherwise all output will be
 *  zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip)</pre>
 * 
 * <pre> -W &lt;class name&gt;
 *  The full class name of a SplitEvaluator.
 *  eg: weka.experiment.ClassifierSplitEvaluator</pre>
 * 
 * <pre> -R
 *  Set when data is not to be randomized and the data sets' size.
 *  Is not to be determined via probabilistic rounding.</pre>
 * 
 * <pre> 
 * Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator:
 * </pre>
 * 
 * <pre> -W &lt;class name&gt;
 *  The full class name of the classifier.
 *  eg: weka.classifiers.bayes.NaiveBayes</pre>
 * 
 * <pre> -C &lt;index&gt;
 *  The index of the class for which IR statistics
 *  are to be output. (default 1)</pre>
 * 
 * <pre> -I &lt;index&gt;
 *  The index of an attribute to output in the
 *  results. This attribute should identify an
 *  instance in order to know which instances are
 *  in the test set of a cross validation. if 0
 *  no output (default 0).</pre>
 * 
 * <pre> -P
 *  Add target and prediction columns to the result
 *  for each fold.</pre>
 * 
 * <pre> 
 * Options specific to classifier weka.classifiers.rules.ZeroR:
 * </pre>
 * 
 * <pre> -D
 *  If set, classifier is run in debug mode and
 *  may output additional info to the console</pre>
 * 
 <!-- options-end -->
 *
 * @author Mark Hall ([e-mail])
 * @version $Revision: 1.14 $
 */
public class RemoteExperiment 
  extends Experiment {
  
  /** for serialization */
  static final long serialVersionUID = -7357668825635314937L;

  /** The list of objects listening for remote experiment events */
  private FastVector m_listeners = new FastVector();

  /** Holds the names of machines with remoteEngine servers running */
  protected DefaultListModel m_remoteHosts = new DefaultListModel();
  
  /** The queue of available hosts */
  private Queue m_remoteHostsQueue = new Queue();

  /** The status of each of the remote hosts */
  private int [] m_remoteHostsStatus;

  /** The number of times tasks have failed on each remote host */
  private int [] m_remoteHostFailureCounts;

  /** status of the remote host: available */
  protected static final int AVAILABLE=0;
  /** status of the remote host: in use */
  protected static final int IN_USE=1;
  /** status of the remote host: connection failed */
  protected static final int CONNECTION_FAILED=2;
  /** status of the remote host: some other failure */
  protected static final int SOME_OTHER_FAILURE=3;

//    protected static final int TO_BE_RUN=0;
//    protected static final int PROCESSING=1;
//    protected static final int FAILED=2;
//    protected static final int FINISHED=3;

  /** allow at most 3 failures on a host before it is removed from the list
      of usable hosts */
  protected static final int MAX_FAILURES=3;

  /** Set to true if MAX_FAILURES exceeded on all hosts or connections fail 
      on all hosts or user aborts experiment (via gui) */
  private boolean m_experimentAborted = false;

  /** The number of hosts removed due to exceeding max failures */
  private int m_removedHosts;

  /** The count of failed sub-experiments */
  private int m_failedCount;

  /** The count of successfully completed sub-experiments */
  private int m_finishedCount;

  /** The base experiment to split up into sub experiments for remote
      execution */
  private Experiment m_baseExperiment = null;

  /** The sub experiments */
  protected Experiment [] m_subExperiments;

  /** The queue of sub experiments waiting to be processed */
  private Queue m_subExpQueue = new Queue();

  /** The status of each of the sub-experiments */
  protected int [] m_subExpComplete;

  /**
   * If true, then sub experiments are created on the basis of data sets
   * rather than run number.
   */
  protected boolean m_splitByDataSet = true;


  /**
   * Returns true if sub experiments are to be created on the basis of
   * data set..
   *
   * @return a <code>boolean</code> value indicating whether sub
   * experiments are to be created on the basis of data set (true) or
   * run number (false).
   */
  public boolean getSplitByDataSet() {
    return m_splitByDataSet;
  }

  /**
   * Set whether sub experiments are to be created on the basis of
   * data set.
   *
   * @param sd true if sub experiments are to be created on the basis
   * of data set. Otherwise sub experiments are created on the basis of
   * run number.
   */
  public void setSplitByDataSet(boolean sd) {
    m_splitByDataSet = sd;
  }
  
  /**
   * Construct a new RemoteExperiment using an empty Experiment as base 
   * Experiment
   * @throws Exception if the base experiment is null
   */
  public RemoteExperiment() throws Exception {
     this(new Experiment());
  }
  
  /**
   * Construct a new RemoteExperiment using a base Experiment
   * @param base the base experiment to use
   * @throws Exception if the base experiment is null
   */
  public RemoteExperiment(Experiment base) throws Exception {
    setBaseExperiment(base);
  }

  /**
   * Add an object to the list of those interested in recieving update
   * information from the RemoteExperiment
   * @param r a listener
   */
  public void addRemoteExperimentListener(RemoteExperimentListener r) {
    m_listeners.addElement(r);
  }

  /**
   * Get the base experiment used by this remote experiment
   * @return the base experiment
   */
  public Experiment getBaseExperiment() {
    return m_baseExperiment;
  }

  /**
   * Set the base experiment. A sub experiment will be created for each
   * run in the base experiment.
   * @param base the base experiment to use.
   * @throws Exception if supplied base experiment is null
   */
  public void setBaseExperiment(Experiment base) throws Exception {
    if (base == null) {
      throw new Exception("Base experiment is null!");
    }
    m_baseExperiment = base;
    setRunLower(m_baseExperiment.getRunLower());
    setRunUpper(m_baseExperiment.getRunUpper());
    setResultListener(m_baseExperiment.getResultListener());
    setResultProducer(m_baseExperiment.getResultProducer());
    setDatasets(m_baseExperiment.getDatasets());
    setUsePropertyIterator(m_baseExperiment.getUsePropertyIterator());
    setPropertyPath(m_baseExperiment.getPropertyPath());
    setPropertyArray(m_baseExperiment.getPropertyArray());
    setNotes(m_baseExperiment.getNotes());
    m_ClassFirst = m_baseExperiment.m_ClassFirst;
    m_AdvanceDataSetFirst = m_baseExperiment.m_AdvanceDataSetFirst;
  }
  
  /**
   * Set the user notes.
   *
   * @param newNotes New user notes.
   */
  public void setNotes(String newNotes) {
    
    super.setNotes(newNotes);
    m_baseExperiment.setNotes(newNotes);
  }

  /**
   * Set the lower run number for the experiment.
   *
   * @param newRunLower the lower run number for the experiment.
   */
  public void setRunLower(int newRunLower) {
    
    super.setRunLower(newRunLower);
    m_baseExperiment.setRunLower(newRunLower);
  }

  /**
   * Set the upper run number for the experiment.
   *
   * @param newRunUpper the upper run number for the experiment.
   */
  public void setRunUpper(int newRunUpper) {
    
    super.setRunUpper(newRunUpper);
    m_baseExperiment.setRunUpper(newRunUpper);
  }

  /**
   * Sets the result listener where results will be sent.
   *
   * @param newResultListener the result listener where results will be sent.
   */
  public void setResultListener(ResultListener newResultListener) {
    
    super.setResultListener(newResultListener);
    m_baseExperiment.setResultListener(newResultListener);
  }

  /**
   * Set the result producer used for the current experiment.
   *
   * @param newResultProducer result producer to use for the current 
   * experiment.
   */
  public void setResultProducer(ResultProducer newResultProducer) {
    
    super.setResultProducer(newResultProducer);
    m_baseExperiment.setResultProducer(newResultProducer);
  }

  /**
   * Set the datasets to use in the experiment
   * @param ds the list of datasets to use
   */
  public void setDatasets(DefaultListModel ds) {
    super.setDatasets(ds);
    m_baseExperiment.setDatasets(ds);
  }

  /**
   * Sets whether the custom property iterator should be used.
   *
   * @param newUsePropertyIterator true if so
   */
  public void setUsePropertyIterator(boolean newUsePropertyIterator) {
    
    super.setUsePropertyIterator(newUsePropertyIterator);
    m_baseExperiment.setUsePropertyIterator(newUsePropertyIterator);
  }

  /**
   * Sets the path of properties taken to get to the custom property
   * to iterate over.
   *
   * @param newPropertyPath an array of PropertyNodes
   */
  public void setPropertyPath(PropertyNode [] newPropertyPath) {
    
    super.setPropertyPath(newPropertyPath);
    m_baseExperiment.setPropertyPath(newPropertyPath);
  }

  /**
   * Sets the array of values to set the custom property to.
   *
   * @param newPropArray a value of type Object which should be an
   * array of the appropriate values.
   */
  public void setPropertyArray(Object newPropArray) {
    super.setPropertyArray(newPropArray);
    m_baseExperiment.setPropertyArray(newPropArray);
  }

    
  /**
   * Prepares a remote experiment for running, creates sub experiments
   *
   * @throws Exception if an error occurs
   */
  public void initialize() throws Exception {
    if (m_baseExperiment == null) {
      throw new Exception("No base experiment specified!");
    }

    m_experimentAborted = false;
    m_finishedCount = 0;
    m_failedCount = 0;
    m_RunNumber = getRunLower();
    m_DatasetNumber = 0;
    m_PropertyNumber = 0;
    m_CurrentProperty = -1;
    m_CurrentInstances = null;
    m_Finished = false;

    if (m_remoteHosts.size() == 0) {
      throw new Exception("No hosts specified!");
    }
    // initialize all remote hosts to available
    m_remoteHostsStatus = new int [m_remoteHosts.size()];    
    m_remoteHostFailureCounts = new int [m_remoteHosts.size()];

    m_remoteHostsQueue = new Queue();
    // prime the hosts queue
    for (int i=0;i<m_remoteHosts.size();i++) {
      m_remoteHostsQueue.push(new Integer(i));
    }

    // set up sub experiments
    m_subExpQueue = new Queue();
    int numExps;
    if (getSplitByDataSet()) {
      numExps = m_baseExperiment.getDatasets().size();
    } else {
      numExps = getRunUpper() - getRunLower() + 1;
    }
    m_subExperiments = new Experiment[numExps];
    m_subExpComplete = new int[numExps];