public Lattice(model m, inference inf, dataSeq x)
{
_w = x.Count;
_h = m.NTag;
_logBel = new belief(_w, _h);
List <dMatrix> YYlist = new List <dMatrix>();
List <List <double> > Ylist = new List <List <double> >();
inf.getYYandY(m, x, YYlist, Ylist);
for (int i = 0; i < _w; i++)
{
_logBel.belState[i] = new List <double>(Ylist[i]);
if (i > 0)
{
_logBel.belEdge[i] = new dMatrix(YYlist[i]);
}
}
_heuListList = new List <List <double> >();
for (int i = 0; i < _w; i++)
{
_heuListList.Add(new List <double>(new double[_h]));
}
Viterbi _bwdViterbi = new Viterbi(_w, _h);
for (int i = 0; i < _w; i++)
{
_bwdViterbi.setScores(i, Ylist[i], YYlist[i]);
}
List <int> tags = new List <int>();
_bwdViterbi.runViterbi(ref tags);
//update the viterbiHeuristicMap
for (int i = 0; i < _w; i++)
{
for (int j = 0; j < _h; j++)
{
double h = _bwdViterbi.getPathScore(i, j);
setHeuMap(i, j, h);
}
}
//get zGold
ZGold = 0;
for (int i = 0; i < x.Count; i++)
{
int s = x.getTags(i);
ZGold += Ylist[i][s];
if (i > 0)
{
int sPre = x.getTags(i - 1);
ZGold += YYlist[i][sPre, s];
}
}
}
//fast viterbi decode without probability
public void decodeViterbi_test(model m, dataSeq x, List <int> tags)
{
tags.Clear();
int nNode = x.Count;
int nState = m.NState;
dMatrix YY = new dMatrix(nState, nState);
double[] dAry = new double[nState];
List <double> Y = new List <double>(dAry);
Viterbi viter = new Viterbi(nNode, nState);
for (int i = 0; i < nNode; i++)
{
getLogYY(m, x, i, ref YY, ref Y, false, false);
viter.setScores(i, Y, YY);
}
List <int> states = new List <int>();
double numer = viter.runViterbi(ref states, false);
for (int i = 0; i < states.Count; i++)
{
int tag = m.hStateToTag(states[i]);
tags.Add(tag);
}
}
public double decodeViterbi(model m, dataSeq x, List <int> tags)
{
tags.Clear();
int nNode = x.Count;
int nTag = m.NTag;
dMatrix YY = new dMatrix(nTag, nTag);
double[] dAry = new double[nTag];
List <double> Y = new List <double>(dAry);
Viterbi viter = new Viterbi(nNode, nTag);
for (int i = 0; i < nNode; i++)
{
getLogYY(m, x, i, ref YY, ref Y, false, false);
viter.setScores(i, Y, YY);
}
List <int> states = new List <int>();
double numer = viter.runViterbi(ref states, false);
for (int i = 0; i < states.Count; i++)
{
int tag = states[i];
tags.Add(tag);
}
double Z = getZ(m, x, false);
return(Math.Exp(numer - Z));
}
//fast viterbi decode without probability
public void decodeViterbi_train(model m, dataSeq x, List <dMatrix> YYlist, List <List <double> > Ylist, List <int> tags)
{
int nNode = x.Count;
int nState = m.NState;
Viterbi viter = new Viterbi(nNode, nState);
for (int i = 0; i < nNode; i++)
{
viter.setScores(i, Ylist[i], YYlist[i]);
}
double numer = viter.runViterbi(ref tags, false);
}
//fast viterbi decode without probability
public void decodeViterbi_test(model m, dataSeq x, List <int> tags)
{
tags.Clear();
int nNode = x.Count;
int nTag = m.NTag;
dMatrix YY = new dMatrix(nTag, nTag);
double[] dAry = new double[nTag];
List <double> Y = new List <double>(dAry);
Viterbi viter = new Viterbi(nNode, nTag);
for (int i = 0; i < nNode; i++)
{
getLogYY(m, x, i, ref YY, ref Y, false, false);
viter.setScores(i, Y, YY);
}
viter.runViterbi(ref tags);
}
