public ArrayList<Double> getPosteriorDecodingScores(
SingleDPMatrix fMatrix, SingleDPMatrix bMatrix) {
ArrayList<Double> pdScores = new ArrayList<Double>();
State states[] = fMatrix.states();
double fScore = fMatrix.getScore();
double fMatrixScores[][] = fMatrix.scores;
double bMatrixScores[][] = bMatrix.scores;
int numberOfObservations = fMatrixScores.length;
int numberOfStates = states.length;
for (int i = 1; i < numberOfObservations - 1; i++) {
double sum = 0;
double g = Double.MIN_VALUE;
for (int s = 0; s < numberOfStates; s++) {
g = getWeight(states[s].getName());
/*
if( states[s].getName().equals("M")){
g=0;
}
else
{
g=1;
}
*/
double probOfOneState = Math.exp(fMatrixScores[i][s] + bMatrixScores[i][s] - fScore);
sum = sum + (probOfOneState * g);
}
pdScores.add(sum);
}
return pdScores;
} /*getPosteriorDecodingScores*/
public ArrayList<String> getPosteriorDecodingPath(
SingleDPMatrix fMatrix, SingleDPMatrix bMatrix) {
ArrayList<String> pdPath = new ArrayList<String>();
State states[] = fMatrix.states();
double fScore = fMatrix.getScore();
double fMatrixScores[][] = fMatrix.scores;
double bMatrixScores[][] = bMatrix.scores;
int numberOfObservations = fMatrixScores.length;
int numberOfStates = states.length;
for (int i = 1; i < numberOfObservations - 1; i++) {
ArrayList<Double> probOfStates = new ArrayList<Double>();
for (int s = 0; s < numberOfStates; s++) {
double probOfOneState = Math.exp(fMatrixScores[i][s] + bMatrixScores[i][s] - fScore);
probOfStates.add(probOfOneState);
}
Object max_obj = Collections.max(probOfStates);
int maxValueIndex = probOfStates.indexOf(max_obj);
State topScoredState = states[maxValueIndex];
pdPath.add(topScoredState.getName());
// System.out.print(topScoredState.getName());
}
// System.out.println();
// System.out.println("\n number of rows is " + numberOfObservations);
// System.out.println("\n length of posterior decoding path is " + pdPath.size());
return pdPath;
} /*getPosteriorDecodingPath*/
