Evidence.html

Evidence.java

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package blog;

import java.util.*;
import java.io.PrintStream;
import common.Util;

Stores the information extracted from evidence file. The evidence is of 2 kinds:

symbol evidence statements, which introduce the objects of the specified type that satisfy the stated condition;
value evidence statements, which specify the value of a term.

An Evidence object serves two purposes. First, it defines a set of Skolem constants, which are additional constant symbols that can be used in the evidence and query files. Second, it defines a set of evidence variables and an observed value for each of these variables. The evidence variables may be basic variables or other random variables created to represent the evidence. For example, if we have a value evidence statement:

height(mother(John)) = 13.7

then the evidence object creates a new random variable whose value is the value of the term height(mother(John)).

 
public class Evidence{

Creates a new Evidence object with no evidence.


    public Evidence( ){

    }


    public void addSymbolEvidence( SymbolEvidenceStatement sevid ){
	symbolEvidence.add( sevid );
	for (Iterator iter = sevid.getSkolemConstants().iterator(); 
	     iter.hasNext(); ) {
	    SkolemConstant c = (SkolemConstant) iter.next();
	    skolemConstants.add(c);
	    skolemConstantsByName.put(c.getName(), c);
	}
    }

Returns an unmodifiable Collection of SymbolEvidenceStatement objects.


    public Collection getSymbolEvidence( ){
	return Collections.unmodifiableCollection(symbolEvidence);
    }


    public void addValueEvidence( ValueEvidenceStatement evid ){
	valueEvidence.add( evid );
    }

Returns an unmodifiable Collection of ValueEvidenceStatement objects.


    public Collection getValueEvidence( ){
	return Collections.unmodifiableCollection(valueEvidence);
    }

Adds all symbol and value evidence statements from another evidence object.


    public void addAll(Evidence another) {
    	for (Iterator it = another.getSymbolEvidence().iterator(); 
	         it.hasNext(); ) {
	    addSymbolEvidence((SymbolEvidenceStatement)it.next());
	}
    	for (Iterator it = another.getValueEvidence().iterator(); 
	         it.hasNext(); ) {
	    addValueEvidence((ValueEvidenceStatement)it.next());
	}
    	compile();
    }

Returns the SkolemConstant object for the given symbol, or null if no such Skolem constant has been introduced.


    public SkolemConstant getSkolemConstant(String name) {
	return (SkolemConstant) skolemConstantsByName.get(name);
    }

Returns an unmodifiable List of the SkolemConstant objects introduced by this evidence, in the order they were introduced.


    public List getSkolemConstants() {
	return Collections.unmodifiableList(skolemConstants);
    }

Returns the set of evidence variables for which the user has observed values.

Returns: an unmodifiable Set of BayesNetVar objects


    public Set getEvidenceVars() {
	return Collections.unmodifiableSet(observedValues.keySet());
    }

    public Set getEvidenceVars(Timestep t) {
	Set evidenceAtTime = new HashSet();
	for(Iterator iter = observedValues.keySet().iterator(); 
	    iter.hasNext();) {
	    BayesNetVar var = 
		(BayesNetVar) iter.next();
	    if(var instanceof RandFuncAppVar) {
		RandFuncAppVar rfav = (RandFuncAppVar) var;
		Timestep t_prime = rfav.timestep();
		if (t_prime == null) {
		    if (t == null)
			evidenceAtTime.add(var);
		}
		else if (t_prime.equals(t))
		    evidenceAtTime.add(var);
	    }
	}
	return Collections.unmodifiableSet(evidenceAtTime);
    }

Returns the observed value of the given variable. for the given variable

Throws: IllegalArgumentException if no value has been observed


    public Object getObservedValue(BayesNetVar var) {
	if (!observedValues.containsKey(var)) {
	    throw new IllegalArgumentException("No observed value for " + var);
	}
	
	return observedValues.get(var);
    }

Returns true if the given partial world is complete enough to determine whether this evidence is true or false.


    public boolean isDetermined(PartialWorld w) {
	for (Iterator iter = symbolEvidence.iterator(); iter.hasNext(); ) {
	    SymbolEvidenceStatement stmt 
		= (SymbolEvidenceStatement) iter.next();
	    if (!stmt.isDetermined(w)) {
		return false;
	    }
	}

	for (Iterator iter = valueEvidence.iterator(); iter.hasNext(); ) {
	    ValueEvidenceStatement stmt
		= (ValueEvidenceStatement) iter.next();
	    if (!stmt.isDetermined(w)) {
		return false;
	    }
	}

	return true;
    }

Returns true if this evidence is true in the given world; otherwise false.


    public boolean isTrue(PartialWorld w) {
	for (Iterator iter = symbolEvidence.iterator(); iter.hasNext(); ) {
	    SymbolEvidenceStatement stmt 
		= (SymbolEvidenceStatement) iter.next();
	    if (!stmt.isTrue(w)) {
		return false;
	    }
	}

	for (Iterator iter = valueEvidence.iterator(); iter.hasNext(); ) {
	    ValueEvidenceStatement stmt
		= (ValueEvidenceStatement) iter.next();
	    if (!stmt.isTrue(w)) {
		return false;
	    }
	}

	return true;
    }

Prints the evidence to the given stream.


    public void print(PrintStream s) {
	for (Iterator iter = symbolEvidence.iterator(); iter.hasNext(); ) {
	    SymbolEvidenceStatement stmt
		= (SymbolEvidenceStatement) iter.next();
	    System.out.println(stmt);
	}

	for (Iterator iter = valueEvidence.iterator(); iter.hasNext(); ) {
	    ValueEvidenceStatement stmt = (ValueEvidenceStatement) iter.next();
	    System.out.println(stmt);
	}
    }

    private void recordEvidence(BayesNetVar observedVar, Object observedValue, 
				Object source) {
	if (observedValues.containsKey(observedVar)) {
	    Object existingValue = observedValues.get(observedVar);
	    if (!existingValue.equals(observedValue)) {
		Util.fatalError("Evidence \"" + source + "\" contradicts "
				+ "earlier evidence.", false);
	    }
	} else {
	    observedValues.put(observedVar, observedValue);
	}
    }

    public double getEvidenceProb(PartialWorld curWorld) {
	return Math.exp(getEvidenceLogProb(curWorld));
    }

    public double getEvidenceProb(PartialWorld curWorld, Timestep t) {
	return Math.exp(getEvidenceLogProb(curWorld, t));
    }

    public double getEvidenceLogProb(PartialWorld curWorld) {
    	return getEvidenceLogProb(curWorld, getEvidenceVars());
    }

    public double getEvidenceLogProb(PartialWorld curWorld, Timestep t) {
    	return getEvidenceLogProb(curWorld, getEvidenceVars(t));
    }

    private double getEvidenceLogProb(PartialWorld curWorld, Set evidenceVars) {
	double evidenceLogSum = 0;
	
	for( Iterator iter = evidenceVars.iterator(); iter.hasNext(); ){
	    BayesNetVar var = (BayesNetVar) iter.next();
	    if (getObservedValue(var).equals(var.getValue(curWorld))) {
		evidenceLogSum += curWorld.getLogProbOfValue(var);
	    } else {
		// The value of this variable in curWorld is not the
		// observed value.
		evidenceLogSum += Double.NEGATIVE_INFINITY; 
		//implies that the actual probability is 0 
	    }
	}
	return evidenceLogSum;
    }

Returns true if the evidence satisfies type and scope constraints. If there are type or scope errors, prints messages to standard error and returns false.


    public boolean checkTypesAndScope(Model model) {
	boolean correct = true;
	
	for (Iterator iter = symbolEvidence.iterator(); iter.hasNext(); ) {
	    SymbolEvidenceStatement stmt 
		= (SymbolEvidenceStatement) iter.next();
	    if (!stmt.checkTypesAndScope(model)) {
		correct = false;
	    }
	}

	for (Iterator iter = valueEvidence.iterator(); iter.hasNext(); ) {
	    ValueEvidenceStatement stmt 
		= (ValueEvidenceStatement) iter.next();
	    if (!stmt.checkTypesAndScope(model)) {
		correct = false;
	    }
	}

	return correct;
    }

Does compilation steps that can only be done correctly once the model is complete. Prints messages to standard error if any errors are encountered. Returns the number of errors encountered.


    public int compile() {
	int errors = 0;
	LinkedHashSet callStack = new LinkedHashSet();

	for (Iterator iter = symbolEvidence.iterator(); iter.hasNext(); ) {
	    SymbolEvidenceStatement stmt 
		= (SymbolEvidenceStatement) iter.next();
	    int thisStmtErrors = stmt.compile(callStack);
	    if (thisStmtErrors == 0) {
		recordEvidence(stmt.getObservedVar(), stmt.getObservedValue(),
			       stmt);
	    }
	    errors += thisStmtErrors;
	}

	for (Iterator iter = valueEvidence.iterator(); iter.hasNext(); ) {
	    ValueEvidenceStatement stmt 
		= (ValueEvidenceStatement) iter.next();
	    int thisStmtErrors = stmt.compile(callStack);
	    if (thisStmtErrors == 0) {
		recordEvidence(stmt.getObservedVar(), stmt.getObservedValue(),
			       stmt);
	    }
	    errors += thisStmtErrors;
	}

	return errors;
    }

    public String toString() {
	List list = new LinkedList();
	list.addAll(getValueEvidence());
	list.addAll(getSymbolEvidence());
	return list.toString();
    }

    // List of SymbolEvidenceStatement
    private List symbolEvidence = new ArrayList();
 
    // List of ValueEvidenceStatement
    private List valueEvidence = new ArrayList();  
    
    // map from String to SkolemConstant
    private Map skolemConstantsByName = new HashMap(); 

    // List of SkolemConstant objects in the order they were introduced
    private List skolemConstants = new ArrayList();

    // map from BayesNetVar to Object
    private Map observedValues = new LinkedHashMap();
}

This file was generated on Tue Jun 08 17:53:36 PDT 2010 from file Evidence.java
by the ilog.language.tools.Hilite Java tool written by Hassan Aït-Kaci