onepassdataindexer.java

最大熵分类器

///////////////////////////////////////////////////////////////////////////////
// Copyright (C) 2001 Jason Baldridge and Gann Bierner
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
//
// This library 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 Lesser General Public
// License along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
//////////////////////////////////////////////////////////////////////////////   
package opennlp.maxent;

import gnu.trove.TIntArrayList;
import gnu.trove.TLinkedList;
import gnu.trove.TObjectIntHashMap;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Set;

/**
 * An indexer for maxent model data which handles cutoffs for uncommon
 * contextual predicates and provides a unique integer index for each of the
 * predicates. 
 *
 * @author      Jason Baldridge
 * @version $Revision: 1.5 $, $Date: 2007/03/15 04:51:26 $
 */
public class OnePassDataIndexer extends AbstractDataIndexer  {

    /**
     * One argument constructor for DataIndexer which calls the two argument
     * constructor assuming no cutoff.
     *
     * @param eventStream An Event[] which contains the a list of all the Events
     *               seen in the training data.
     */     
    public OnePassDataIndexer(EventStream eventStream) {
        this(eventStream, 0);
    }

    /**
     * Two argument constructor for DataIndexer.
     *
     * @param eventStream An Event[] which contains the a list of all the Events
     *               seen in the training data.
     * @param cutoff The minimum number of times a predicate must have been
     *               observed in order to be included in the model.
     */
    public OnePassDataIndexer(EventStream eventStream, int cutoff) {
        TObjectIntHashMap predicateIndex;
        TLinkedList events;
        List eventsToCompare;

        predicateIndex = new TObjectIntHashMap();
        System.out.println("Indexing events using cutoff of " + cutoff + "\n");

        System.out.print("\tComputing event counts...  ");
        events = computeEventCounts(eventStream,predicateIndex,cutoff);
        System.out.println("done. "+events.size()+" events");

        System.out.print("\tIndexing...  ");
        eventsToCompare = index(events,predicateIndex);
        // done with event list
        events = null;
        // done with predicates
        predicateIndex = null;

        System.out.println("done.");

        System.out.print("Sorting and merging events... ");
        sortAndMerge(eventsToCompare);
        System.out.println("Done indexing.");
    }


    
    /**
     * Reads events from <tt>eventStream</tt> into a linked list.  The
     * predicates associated with each event are counted and any which
     * occur at least <tt>cutoff</tt> times are added to the
     * <tt>predicatesInOut</tt> map along with a unique integer index.
     *
     * @param eventStream an <code>EventStream</code> value
     * @param predicatesInOut a <code>TObjectIntHashMap</code> value
     * @param cutoff an <code>int</code> value
     * @return a <code>TLinkedList</code> value
     */
    private TLinkedList computeEventCounts(EventStream eventStream,
        TObjectIntHashMap predicatesInOut,
        int cutoff) {
      Set predicateSet = new HashSet();
      TObjectIntHashMap counter = new TObjectIntHashMap();
      TLinkedList events = new TLinkedList();
      while (eventStream.hasNext()) {
        Event ev = eventStream.nextEvent();
        events.addLast(ev);
        update(ev.getContext(),predicateSet,counter,cutoff);
      }
      predCounts = new int[predicateSet.size()];
      int index = 0;
      for (Iterator pi=predicateSet.iterator();pi.hasNext();index++) {
        String predicate = (String) pi.next();
        predCounts[index] = counter.get(predicate);
        predicatesInOut.put(predicate,index);
      }
      return events;
    }

    protected List index(TLinkedList events,
                       TObjectIntHashMap predicateIndex) {
        TObjectIntHashMap omap = new TObjectIntHashMap();

        int numEvents = events.size();
        int outcomeCount = 0;
        List eventsToCompare = new ArrayList(numEvents);
        TIntArrayList indexedContext = new TIntArrayList();

        for (int eventIndex=0; eventIndex<numEvents; eventIndex++) {
            Event ev = (Event)events.removeFirst();
            String[] econtext = ev.getContext();
            ComparableEvent ce;
	    
            int ocID;
            String oc = ev.getOutcome();
	    
            if (omap.containsKey(oc)) {
                ocID = omap.get(oc);
            } else {
                ocID = outcomeCount++;
                omap.put(oc, ocID);
            }

            for (int i=0; i<econtext.length; i++) {
                String pred = econtext[i];
                if (predicateIndex.containsKey(pred)) {
                    indexedContext.add(predicateIndex.get(pred));
                }
            }

            // drop events with no active features
            if (indexedContext.size() > 0) {
                ce = new ComparableEvent(ocID, indexedContext.toNativeArray());
                eventsToCompare.add(ce);
            }
            else {
              System.err.println("Dropped event "+ev.getOutcome()+":"+Arrays.asList(ev.getContext()));
            }
            // recycle the TIntArrayList
            indexedContext.resetQuick();
        }
        outcomeLabels = toIndexedStringArray(omap);
        predLabels = toIndexedStringArray(predicateIndex);
        return eventsToCompare;
    }
    
}