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];
}
}
}
//the scalar version
virtual public void getLogYY(double scalar, model m, dataSeq x, int i, ref dMatrix YY, ref List <double> Y, bool takeExp, bool mask)
{
YY.set(0);
listTool.listSet(ref Y, 0);
List <double> w = m.W;
List <featureTemp> fList = _fGene.getFeatureTemp(x, i);
int nTag = m.NTag;
for (int j = 0; j < fList.Count; j++)
{
featureTemp ptr = fList[j];
int id = ptr.id;
double v = ptr.val;
for (int s = 0; s < nTag; s++)
{
int f = _fGene.getNodeFeatID(id, s);
Y[s] += w[f] * scalar * v;
}
}
if (i > 0)
{
for (int s = 0; s < nTag; s++)
{
for (int sPre = 0; sPre < nTag; sPre++)
{
int f = _fGene.getEdgeFeatID(sPre, s);
YY[sPre, s] += w[f] * scalar;
}
}
}
double maskValue = double.MinValue;
if (takeExp)
{
listTool.listExp(ref Y);
YY.eltExp();
maskValue = 0;
}
if (mask)
{
List <int> tagList = x.getTags();
for (int s = 0; s < Y.Count; s++)
{
if (tagList[i] != s)
{
Y[s] = maskValue;
}
}
}
}
public void getYYandY(model m, dataSeq x, List <dMatrix> YYlist, List <List <double> > Ylist, List <dMatrix> maskYYlist, List <List <double> > maskYlist)
{
int nNodes = x.Count;
//int nTag = m.NTag;
int nState = m.NState;
double[] dAry = new double[nState];
bool mask = false;
try
{
//Global.rwlock.AcquireReaderLock(Global.readWaitTime);
for (int i = 0; i < nNodes; i++)
{
dMatrix YYi = new dMatrix(nState, nState);
List <double> Yi = new List <double>(dAry);
//compute the Mi matrix
getLogYY(m, x, i, ref YYi, ref Yi, false, mask);
YYlist.Add(YYi);
Ylist.Add(Yi);
maskYYlist.Add(new dMatrix(YYi));
maskYlist.Add(new List <double>(Yi));
}
//Global.rwlock.ReleaseReaderLock();
}
catch (ApplicationException)
{
Console.WriteLine("read out time!");
}
//get the masked YY and Y
double maskValue = double.MinValue;
dMatrix statesPerNodes = m.getStatesPerNode(x);
for (int i = 0; i < nNodes; i++)
{
List <double> Y = maskYlist[i];
List <int> tagList = x.getTags();
for (int s = 0; s < Y.Count; s++)
{
if (statesPerNodes[i, s] == 0)
{
Y[s] = maskValue;
}
}
}
}
virtual public void getLogYY(model m, dataSeq x, int i, ref dMatrix YY, ref List <double> Y, bool takeExp, bool mask)
{
YY.set(0);
listTool.listSet(ref Y, 0);
float[] w = m.W;
List <featureTemp> fList = _fGene.getFeatureTemp(x, i);
int nTag = m.NTag;
foreach (featureTemp ft in fList)
{
for (int s = 0; s < nTag; s++)
{
int f = _fGene.getNodeFeatID(ft.id, s);
Y[s] += w[f] * ft.val;
}
}
if (i > 0)
{
for (int s = 0; s < nTag; s++)
{
for (int sPre = 0; sPre < nTag; sPre++)
{
int f = _fGene.getEdgeFeatID(sPre, s);
YY[sPre, s] += w[f];
}
}
}
double maskValue = double.MinValue;
if (takeExp)
{
listTool.listExp(ref Y);
YY.eltExp();
maskValue = 0;
}
if (mask)
{
List <int> tagList = x.getTags();
for (int s = 0; s < Y.Count; s++)
{
if (tagList[i] != s)
{
Y[s] = maskValue;
}
}
}
}
public dMatrix getStatesPerNode(dataSeq x)
{
int n = x.Count;
dMatrix spn = x.GoldStatesPerNode;
if (spn == null || spn.R == 0)
{
List <int> tList = x.getTags();
spn = new dMatrix(tList.Count, _nTag);
for (int i = 0; i < tList.Count; i++)
{
int tag = tList[i];
spn[i, tag] = 1;
}
x.GoldStatesPerNode = spn;
}
return(spn);
}
public dMatrix getStatesPerNode(dataSeq x)
{
int n = x.Count;
dMatrix spn = x.GoldStatesPerNode;
if (spn == null || spn.R == 0)
{
List <int> tList = x.getTags();
spn = new dMatrix(tList.Count, _nHiddenState);
for (int i = 0; i < tList.Count; i++)
{
int tag = tList[i];
List <int> states = tagToHiddenStates(tag);
foreach (int s in states)
{
spn[i, s] = 1;
}
}
x.GoldStatesPerNode = spn;
}
return(spn);
}
//the scalar version
override public void getLogYY(double scalar, model m, dataSeq x, int i, ref dMatrix YY, ref List <double> Y, bool takeExp, bool mask)
{
YY.set(0);
listTool.listSet(ref Y, 0);
float[] w = m.W;
List <featureTemp> fList = _fGene.getFeatureTemp(x, i);
int nTag = m.NTag;
foreach (featureTemp ft in fList)
{
for (int s = 0; s < nTag; s++)
{
int f = _fGene.getNodeFeatID(ft.id, s);
Y[s] += w[f] * scalar * ft.val;
}
}
if (i > 0)
{
//non-rich
if (Global.useTraditionalEdge)
{
for (int s = 0; s < nTag; s++)
{
for (int sPre = 0; sPre < nTag; sPre++)
{
int f = _fGene.getEdgeFeatID(sPre, s);
YY[sPre, s] += w[f] * scalar;
}
}
}
//rich
foreach (featureTemp im in fList)
{
int id = im.id;
if (id < _fGene.getNRichFeatTemp())
{
for (int s = 0; s < nTag; s++)
{
for (int sPre = 0; sPre < nTag; sPre++)
{
int f = _fGene.getEdgeFeatID(id, sPre, s);
YY[sPre, s] += w[f] * scalar * im.val;
}
}
}
}
}
double maskValue = double.MinValue;
if (takeExp)
{
listTool.listExp(ref Y);
YY.eltExp();
maskValue = 0;
}
if (mask)
{
List <int> tagList = x.getTags();
for (int s = 0; s < Y.Count; s++)
{
if (tagList[i] != s)
{
Y[s] = maskValue;
}
}
}
}
