/**
* Title: StanfordMaxEnt<p>
* Description: A Maximum Entropy Toolkit<p>
* Copyright: Copyright (c) Kristina Toutanova<p>
* Company: Stanford University<p>
* @author Kristina Toutanova
* @version 1.0
*/
package edu.stanford.nlp.maxent;
import edu.stanford.nlp.io.PrintFile;
import edu.stanford.nlp.util.Index;
import edu.stanford.nlp.util.IntPair;
/**
* This is a general class for Problem to be solved by the MaxEnt toolkit.
* There have to be experiments and features
*/
public class Problem {
public int exSize;
public int fSize;
/**
* This is the training data.
*/
public Experiments data;
/**
* These are the features.
*/
public Features functions;
public Problem(Experiments d, Features f) {
data = d;
functions = f;
exSize = d.size();
fSize = f.size();
}
public Problem() {
}
public void add(Feature f) {
functions.add(f);
fSize++;
}
public void removeLast() {
functions.removeLast();
fSize--;
}
public void print() {
System.out.println(" Problem printing ");
data.print();
System.out.println(" Function printing ");
for (int i = 0; i < fSize; i++) {
functions.get(i).print();
}
}
public void print(String filename) {
try {
PrintFile pf = new PrintFile(filename);
pf.println(" Problem printing ");
data.print(pf);
pf.println(" Function printing ");
for (int i = 0; i < fSize; i++) {
functions.get(i).print(pf);
}
} catch (Exception e) {
System.out.println("Exception in Problem.print()");
}
}
public static void main(String[] args) {
double[] f1 = {0, 1, 1, 0, 1, 1};
double[] f2 = {1, 0, 1, 1, 0, 1};
Experiments gophers = new Experiments();
for (int i = 0; i < 3; i++) {
gophers.add(new Experiments());
}
for (int i = 0; i < 3; i++) {
gophers.add(new Experiments());
}
gophers.ptilde();
Index<IntPair> instanceIndex = gophers.createIndex();
Features feats = new Features();
feats.add(new Feature(gophers, f1, instanceIndex));
feats.add(new Feature(gophers, f2, instanceIndex));
Problem p = new Problem(gophers, feats);
System.out.println(p.exSize);
System.out.println(p.functions.get(1).ftilde());
}
}