static public void RunNDDS(double threshold, IndependenceEstimation independentEstimation)
{
for (int groupIndex = 0; groupIndex < GroupVariable.AnnotatorGroups.Length; ++groupIndex)
{
Sij sij = Initialize(groupIndex, threshold, independentEstimation);
CoreFunction.Intgerate(Variable.LabelArray, groupIndex, ref sij);
DDSFunction.ObtainBinaryResult(sij, "NDDS", groupIndex);
Function.WriteBinaryResultFile("NDDS", groupIndex);
}
}
static public Sij Initialize(int groupIndex, double threshold, IndependenceEstimation independentEstimation)
{
#region 初始化
Sij sij = new Sij(1);
#endregion
Label[] labelArray = GroupFunction.DescendLabelsByNumber(groupIndex);
Graph BN = NDDSFunction.BuildBN(groupIndex, labelArray, independentEstimation, threshold);
#region 从BN中求每个情感（事件）的父节点（条件）
IDictionary <Label, IList <Label> > LabelsAndPas = new Dictionary <Label, IList <Label> >();
foreach (Label label in labelArray)
{
LabelsAndPas.Add(label, new List <Label>());
}
foreach (KeyValuePair <LabelPair, bool> hasRelationship in BN.AdjMatrix)
{
if (hasRelationship.Value)
{
LabelsAndPas[hasRelationship.Key.Second].Add(hasRelationship.Key.First);
}
}
#endregion
#region 求计算联合概率的参数
IDictionary <Sentence, IDictionary <LabelAndWitness, double> > Probability = new Dictionary <Sentence, IDictionary <LabelAndWitness, double> >();
foreach (Sentence sentence in Variable.Sentences)
{
Probability.Add(sentence, new Dictionary <LabelAndWitness, double>());
}
IDictionary <Smoothing, double[]> smoothingNumber = Function.SmoothingNumber(2);
foreach (KeyValuePair <Label, IList <Label> > labelAndPas in LabelsAndPas)
{
if (labelAndPas.Value.Count == 0)
{
foreach (Sentence sentence in Variable.Sentences)
{
double numberOfLabelTrue = 0;
double numberOfLabelFalse = 0;
foreach (Annotation annotation in sentence.AnnotaitonGroups[groupIndex].AnnotatorAnnotationDic.Values)
{
if (annotation.Labels[labelAndPas.Key])
{
++numberOfLabelTrue;
}
else
{
++numberOfLabelFalse;
}
}
if (NDDSVariable.SmoothBN != Smoothing.None)
{
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, false), new Labelset()), (numberOfLabelFalse + smoothingNumber[NDDSVariable.SmoothBN][0]) / (Variable.NumberOfAnnotationsPerSentenceAfterGrouping + smoothingNumber[NDDSVariable.SmoothBN][1]));
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, true), new Labelset()), (numberOfLabelTrue + (numberOfLabelTrue + smoothingNumber[NDDSVariable.SmoothBN][0]) / (Variable.NumberOfAnnotationsPerSentenceAfterGrouping + smoothingNumber[NDDSVariable.SmoothBN][1])));
}
else
{
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, false), new Labelset()), numberOfLabelFalse / Variable.NumberOfAnnotationsPerSentenceAfterGrouping);
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, true), new Labelset()), numberOfLabelTrue / Variable.NumberOfAnnotationsPerSentenceAfterGrouping);
}
}
}
else
{
for (int i = 0; i < Math.Pow(2, labelAndPas.Value.Count); ++i)
{
Labelset Labelset = new Labelset(labelAndPas.Value, i);
foreach (Sentence sentence in Variable.Sentences)
{
double numberOfLabelTrue = 0;
double numberOfLabelFalse = 0;
foreach (Annotation annotation in sentence.AnnotaitonGroups[groupIndex].AnnotatorAnnotationDic.Values)
{
if (annotation.IsAccordingToLabelset(Labelset))
{
if (annotation.Labels[labelAndPas.Key])
{
++numberOfLabelTrue;
}
else
{
++numberOfLabelFalse;
}
}
}
if (NDDSVariable.SmoothBN != Smoothing.None)
{
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, false), Labelset), (numberOfLabelFalse + smoothingNumber[NDDSVariable.SmoothBN][0]) / (Variable.NumberOfAnnotationsPerSentenceAfterGrouping + smoothingNumber[NDDSVariable.SmoothBN][1]));
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, true), Labelset), (numberOfLabelTrue + smoothingNumber[NDDSVariable.SmoothBN][0]) / (Variable.NumberOfAnnotationsPerSentenceAfterGrouping + smoothingNumber[NDDSVariable.SmoothBN][1]));
}
else
{
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, false), Labelset), numberOfLabelFalse / Variable.NumberOfAnnotationsPerSentenceAfterGrouping);
Probability[sentence].Add(new LabelAndWitness(new Labelset(labelAndPas.Key, true), Labelset), numberOfLabelTrue / Variable.NumberOfAnnotationsPerSentenceAfterGrouping);
}
}
}
}
}
#endregion
#region 计算Sij
IDictionary <Sentence, double> denominator = new Dictionary <Sentence, double>();//归一化参数
foreach (Sentence sentence in Variable.Sentences)
{
sij.Value.Add(sentence, new Dictionary <Labelset, double>());
denominator.Add(sentence, 0);
for (int l = 0; l < Math.Pow(2, Variable.LabelArray.Length); ++l)
{
Labelset Labelset = new Labelset(Variable.LabelArray, l);
double value = 1;
foreach (Label label in labelArray)
{
Labelset singleLabelAnnotation = new Labelset(label, Labelset.Labels[label]);
Labelset subLabelset = new Labelset(LabelsAndPas[label], Labelset);
value *= Probability[sentence][new LabelAndWitness(singleLabelAnnotation, subLabelset)];
}
if (value != 0)
{
sij.Value[sentence].Add(Labelset, value);
denominator[sentence] += value;
}
}
}
#endregion
#region 归一化
foreach (Sentence sentence in Variable.Sentences.ToArray())
{
foreach (Labelset labelset in sij.Value[sentence].Keys.ToArray())
{
sij.Value[sentence][labelset] /= denominator[sentence];
}
}
#endregion
return(sij);
}
static private Graph BuildBN(int group, Label[] labelArray, IndependenceEstimation independentEstimation, double thresholdOfIndependentForNetwork)
{
#region Build-PMap-Skeleton
Graph H = new Graph();
int i = 0;
IDictionary <LabelPair, IList <Label> > labelPairAndWitness = new Dictionary <LabelPair, IList <Label> >();
while (i <= H.MaxDegree())
{
foreach (Label X in labelArray)
{
foreach (Label Y in labelArray)
{
LabelPair labelPair = new LabelPair(X, Y);
if (X != Y && H.AdjMatrix[labelPair] && H.AdjMatrix[labelPair.Reverse])//相接的点
{
foreach (List <Label> witness in H.GetLatentWitnesses(labelPair, i))
{
bool isAWitness = false;
switch (independentEstimation)
{
case IndependenceEstimation.Probability:
isAWitness = labelPair.IsAWitnessByProbability(witness, group, thresholdOfIndependentForNetwork);
break;
case IndependenceEstimation.MutualInformation:
isAWitness = labelPair.IsAWitnessByMI(witness, group, thresholdOfIndependentForNetwork);
break;
}
if (isAWitness)
{
labelPairAndWitness.Add(labelPair, witness);
H.AdjMatrix[labelPair] = false;
H.AdjMatrix[labelPair.Reverse] = false;
break;
}
}
}
}
}
++i;
}
#endregion
#region Mark-Immoralities
bool isChanged = true;
while (isChanged)
{
isChanged = false;
foreach (Label Xi in labelArray)
{
foreach (Label Xj in labelArray)
{
foreach (Label Xk in labelArray)
{
if (Xi != Xj && Xj != Xk && Xi != Xk)//三个情感两两不等
{
if (H.AdjMatrix[new LabelPair(Xi, Xj)] && H.AdjMatrix[new LabelPair(Xj, Xi)] &&
H.AdjMatrix[new LabelPair(Xj, Xk)] && H.AdjMatrix[new LabelPair(Xk, Xj)] &&
!H.AdjMatrix[new LabelPair(Xi, Xk)] && !H.AdjMatrix[new LabelPair(Xk, Xi)])
{
if ((labelPairAndWitness.ContainsKey(new LabelPair(Xi, Xk)) && !labelPairAndWitness[new LabelPair(Xi, Xk)].Contains(Xj)))
{
H.AdjMatrix[new LabelPair(Xj, Xi)] = false;
H.AdjMatrix[new LabelPair(Xj, Xk)] = false;
isChanged = true;
}
}
}
}
}
}
}
#endregion
#region Build-PDAG
bool isConverged = false;
while (!isConverged)
{
//R1
bool foundR1 = false;
foreach (Label X in labelArray)
{
foreach (Label Y in labelArray)
{
foreach (Label Z in labelArray)
{
if (X != Y && X != Z && Y != Z)
{
if (H.AdjMatrix[new LabelPair(X, Y)] && !H.AdjMatrix[new LabelPair(Y, X)] &&
H.AdjMatrix[new LabelPair(Y, Z)] && H.AdjMatrix[new LabelPair(Z, Y)] &&
!H.AdjMatrix[new LabelPair(X, Z)] && !H.AdjMatrix[new LabelPair(Z, X)])
{
H.AdjMatrix[new LabelPair(Z, Y)] = false;
foundR1 = true;
}
}
}
}
}
//R2
bool foundR2 = false;
foreach (Label X in labelArray)
{
foreach (Label Y in labelArray)
{
foreach (Label Z in labelArray)
{
if (X != Y && X != Z && Y != Z)
{
if (H.AdjMatrix[new LabelPair(X, Y)] && !H.AdjMatrix[new LabelPair(Y, X)] &&
H.AdjMatrix[new LabelPair(Y, Z)] && !H.AdjMatrix[new LabelPair(Z, Y)] &&
H.AdjMatrix[new LabelPair(X, Z)] && H.AdjMatrix[new LabelPair(Z, X)])
{
H.AdjMatrix[new LabelPair(Z, X)] = false;
foundR2 = true;
}
}
}
}
}
//R3
bool foundR3 = false;
foreach (Label X in labelArray)
{
foreach (Label Y1 in labelArray)
{
foreach (Label Y2 in labelArray)
{
foreach (Label Z in labelArray)
{
if (X != Y1 && X != Y2 && X != Z && Y1 != Y2 && Y1 != Z && Y2 != Z)
{
if (H.AdjMatrix[new LabelPair(X, Y1)] && H.AdjMatrix[new LabelPair(Y1, X)] &&
H.AdjMatrix[new LabelPair(X, Y2)] && H.AdjMatrix[new LabelPair(Y2, X)] &&
H.AdjMatrix[new LabelPair(X, Z)] && H.AdjMatrix[new LabelPair(Z, X)] &&
H.AdjMatrix[new LabelPair(Y1, Z)] && !H.AdjMatrix[new LabelPair(Z, Y1)] &&
H.AdjMatrix[new LabelPair(Y2, Z)] && !H.AdjMatrix[new LabelPair(Z, Y2)])
{
H.AdjMatrix[new LabelPair(Z, X)] = false;
foundR3 = true;
}
}
}
}
}
}
//是否Converged
if (!foundR1 && !foundR2 && !foundR3)
{
isConverged = true;
}
}
#endregion
#region Complete-BN
foreach (Label X in labelArray)
{
foreach (Label Y in labelArray)
{
if (X != Y)
{
if (H.AdjMatrix[new LabelPair(X, Y)] && H.AdjMatrix[new LabelPair(Y, X)])
{
H.AdjMatrix[new LabelPair(Y, X)] = false;
}
}
}
}
#endregion
return(H);
}
