public static dMatrix getDeviation(List <dMatrix> list)
{
//check validity
int r1 = list[0].R, c1 = list[0].C;
foreach (dMatrix im in list)
{
if (r1 != im.R || c1 != im.C)
{
throw new Exception("error");
}
}
dMatrix m = new dMatrix(list[0]);
m.set(0);
for (int r = 0; r < m.R; r++)
{
for (int c = 0; c < m.C; c++)
{
List <double> dList = new List <double>();
foreach (dMatrix im in list)
{
dList.Add(im[r, c]);
}
m[r, c] = getDeviation(dList);
}
}
return(m);
}
//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);
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)
{
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 static void summarize(string fn = "f2")
{
StreamReader sr = new StreamReader(Global.outDir + Global.fResRaw);
string txt = sr.ReadToEnd();
sr.Close();
txt = txt.Replace("\r", "");
string[] regions = txt.Split(Global.triLineEndAry, StringSplitOptions.RemoveEmptyEntries);
StreamWriter sw = new StreamWriter(Global.outDir + Global.fResSum);
foreach (string region in regions)
{
string[] blocks = region.Split(Global.biLineEndAry, StringSplitOptions.RemoveEmptyEntries);
List <dMatrix> mList = new List <dMatrix>();
foreach (string im in blocks)
{
dMatrix m = new dMatrix(im);
mList.Add(m);
}
//get average
dMatrix avgM = new dMatrix(mList[0]);
avgM.set(0);
foreach (dMatrix m in mList)
{
avgM.add(m);
}
avgM.divide(mList.Count);
//get devi
dMatrix deviM = MathTool.getDeviation(mList);
sw.WriteLine("%averaged values:");
avgM.write(sw, fn);
sw.WriteLine();
sw.WriteLine("%deviations:");
deviM.write(sw, fn);
sw.WriteLine();
sw.WriteLine("%avg & devi:");
sMatrix sAvgM = new sMatrix(avgM, fn);
sAvgM.add("+-");
sMatrix sDeviM = new sMatrix(deviM, fn);
sAvgM.add(sDeviM);
sAvgM.write(sw);
sw.WriteLine("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n");
}
sw.Close();
}
override 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)
{
//non-rich edge
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];
}
}
}
//rich edge
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] * 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;
}
}
}
}
