/* Copyright (C) 2010 Univ. of Massachusetts Amherst, Computer Science Dept.
This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit).
http://www.cs.umass.edu/~mccallum/mallet
This software is provided under the terms of the Common Public License,
version 1.0, as published by http://www.opensource.org. For further
information, see the file `LICENSE' included with this distribution. */
package cc.mallet.fst.semi_supervised.constraints;
import cc.mallet.fst.SumLattice;
import cc.mallet.fst.semi_supervised.StateLabelMap;
import cc.mallet.types.FeatureVector;
import cc.mallet.types.InstanceList;
import java.util.ArrayList;
import java.util.BitSet;
/**
* Interface for GE constraint that considers
* either one or two states.
*
* @author Gregory Druck
*/
public interface GEConstraint {
/**
* Computes the composite constraint feature value
* (over all constraint features) for FeatureVector fv
* and a transition from state li1 to li2.
*
* @param input FeatureVector on transition
* @param inputPosition Position of input in sequence
* @param srcIndex Source state index for transition
* @param destIndex Destination state index for transition
* @return Constraint feature value
*/
double getCompositeConstraintFeatureValue(FeatureVector input, int inputPosition, int srcIndex, int destIndex);
/**
* Returns the total constraint value.
*
* @return Constraint value
*/
double getValue();
/**
* Compute expectations using cached lattices.
*
* @param lattices Cached SumLattices
* @param data Unlabeled data
*/
void computeExpectations(ArrayList<SumLattice> lattices);
/**
* Zero expectation values. Called before re-computing gradient.
*/
void zeroExpectations();
/**
* Sets that map between the state indices and label indices.
*
* @param map StateLabelMap
*/
void setStateLabelMap(StateLabelMap map);
/**
* This is used in multi-threading.
*
* @return A copy of the GEConstraint.
*/
GEConstraint copy();
/**
* @return true if constraint feature only considers one state
*/
boolean isOneStateConstraint();
/**
* @param data Unlabeled data
* @return Returns a bitset of the size of the data, with the bit set if a constraint feature fires in that instance.
*/
BitSet preProcess(InstanceList data);
/**
* Gives the constraint the option to do some caching
* using only the FeatureVector. For example, the
* constrained input features could be cached.
*
* @param input FeatureVector input
*/
void preProcess(FeatureVector input);
}