public double Calculate(int variable, Varset parents, Dictionary<ulong, int> paCounts)
{
parents.Set(variable, true);
double score = 0;
ContingencyTableNode ct = adTree.MakeContab(parents);
Calculate(ct, 1, 0, paCounts, variable, parents, -1, ref score);
foreach(KeyValuePair<ulong, int> pair in paCounts)
{
score -= ilogi[pair.Value];
}
parents.Set(variable, false);
return score;
}
public override double CalculateScore(int variable, Varset parents, DoubleMap cache)
{
Varset parentsCp = new Varset(parents);
// TODO check if this violates the constraints
//if(constraints != NULL && !constraints.SatisfiesConstraints(variable, parents))
//{
//}
// check for prunning
double tVal = T(variable, parentsCp);
for (int x = 0; x < network.Size(); x++)
{
if (parentsCp.Get(x))
{
parentsCp.Set(x, false);
// TODO check the constraints
//if (invalidParents.Count > 0 && invalidParents.Contains(parentsCp.ToULong()))
//{
// parentsCp.Set(x);
// continue;
//}
double tmp = cache.ContainsKey(parentsCp.ToULong()) ? cache[parentsCp.ToULong()] : 0;
if (tmp + tVal > 0)
{
return 0;
}
parentsCp.Set(x, true);
}
}
double score = llc.Calculate(variable, parentsCp);
// structure penalty
score -= tVal * baseComplexityPenalty;
//Console.WriteLine("score: " + score);
return score;
}
private ADNode MakeADTree(int i, BitArray recordNums, int depth, Varset variables)
{
// since this is index i, there are (variableCount - i) remaining variables.
// therefore, it will have that many children
int count = 0;
for(int idx = 0; idx < recordNums.Count; idx++)
{
if (recordNums[idx])
{
count += 1;
}
}
ADNode adn = new ADNode(network.Size() - i, count);
// check if we should just use a leaf list
if (adn.Count < rMin)
{
BitArray leafList = new BitArray(recordNums);
adn.LeafList = leafList;
return adn;
}
// for each of the remaining variables
for (int j = i; j < network.Size(); j++)
{
// create a vary node
variables.Set(j, true);
Varset newVariables = new Varset(variables);
VaryNode child = MakeVaryNode(j, recordNums, depth, newVariables);
adn.SetChild(j - i, child);
}
return adn;
}
private ContingencyTableNode MakeContabLeafList(Varset variables, BitArray records)
{
Varset variablesCp = new Varset(variables);
if (variablesCp.Equals(zero))
{
int count = 0;
for (int i = 0; i < records.Count; i++)
{
if (records[i])
{
count += 1;
}
}
return new ContingencyTableNode(count, 0, 1);
}
int firstIndex = variables.FindFirst();
int cardinality = network.GetCardinality(firstIndex);
ContingencyTableNode ct = new ContingencyTableNode(0, cardinality, 0);
variablesCp.Set(firstIndex, false);
Varset remainingVariables = new Varset(variablesCp);
for (int k = 0; k < cardinality; k++)
{
BitArray r = new BitArray(recordCount);
r = r.Or(records);
r = r.And(consistentRecords[firstIndex][k]);
int count = 0;
for (int i = 0; i < r.Count; i++)
{
if (r[i])
{
count += 1;
}
}
if (count > 0)
{
ContingencyTableNode child = MakeContabLeafList(remainingVariables, r);
ct.SetChild(k, child);
ct.LeafCount += child.LeafCount;
}
}
return ct;
}
public Varset Divide(Varset varset)
{
int length = this.item.Count;
Varset n = new Varset(this);
Varset d = new Varset(varset);
//Console.Write("n: ");
//n.Print();
//Console.Write("d: ");
//d.Print();
Varset m = new Varset(n.item.Length);
m.Set(0, true);
Varset q = new Varset(n.item.Count);
Varset zero = new Varset(n.item.Count);
if (n.Equals(zero))
{
return zero;
}
else if (d.Equals(zero))
{
throw new ArgumentException("Zero Division.");
}
while (d.LessThan(n) || d.Equals(n))
{
d = d.LeftShift(1);
m = m.LeftShift(1);
}
Varset one = new Varset(n.item.Length);
one.Set(0, true);
while (one.LessThan(m))
{
d = d.RightShift(1);
m = m.RightShift(1);
if (d.LessThan(n) || d.Equals(n))
{
n = n.Subtract(d);
q = q.Or(m);
}
}
q = q.SubVarset(length);
n = n.SubVarset(length);
//Console.Write("q: ");
//q.Print();
//Console.Write("n: ");
//n.Print();
return q;
}
public static Varset ClearCopy(Varset varset, int index)
{
Varset cp = new Varset(varset);
cp.Set(index, false);
return cp;
}
public Varset Subtract(Varset varset)
{
Varset cp = new Varset(varset);
if (cp.item.Length < item.Length)
{
AlignLength(cp);
}
Varset one = new Varset(1);
one.Set(0, true);
cp = cp.Not();
cp = cp.StaticAdd(one);
cp = cp.StaticAdd(this);
return cp;
}
public Varset NextPermutation()
{
Varset vs = new Varset(this);
Varset one = new Varset(0);
one.Set(0, true);
Varset tmp = vs.Or(vs.Subtract(one)).StaticAdd(one);
Varset nextVariables = tmp.Or(tmp.And(tmp.Not().StaticAdd(one)).Divide(vs.And(vs.Not().StaticAdd(one))).RightShift(1).Subtract(one));
return nextVariables;
}
private void CalculateScoresInternal(int variable, DoubleMap cache)
{
// calculate initial score
Varset empty = new Varset(variableCount + 1); // 注意: c++だと0
double score = scoringFunction.CalculateScore(variable, empty, cache);
if (score < 1)
{
cache[empty.ToULong()] = score;
}
int prunedCount = 0;
for (int layer = 1; layer <= maxParents && !outOfTime; layer++)
{
// DEBUG
Console.WriteLine("layer: " + layer + ", prunedCount: " + prunedCount);
Varset variables = new Varset(variableCount + 1); // 注意: c++だと0
for (int i = 0; i < layer; i++)
{
variables.Set(i, true);
}
Varset max = new Varset(variableCount);
max.Set(variableCount, true);
while (variables.LessThan(max) && !outOfTime)
{
if (!variables.Get(variable))
{
score = scoringFunction.CalculateScore(variable, variables, cache);
if (score < 0)
{
cache[variables.ToULong()] = score;
}
else
{
prunedCount++;
}
}
variables = variables.NextPermutation();
}
if (!outOfTime)
{
highestCompletedLayer = layer;
}
}
}
public override double CalculateScore(int variable, Varset parents, DoubleMap cache)
{
Scratch s = scratchSpace[variable];
// TODO check if this violates the constraints
//if (constraints != NULL && !constraints->satisfiesConstraints(variable, parents))
//{
// s->invalidParents.insert(parents);
// return 1;
//}
for (int x = 0; x < network.Size(); x++)
{
if (parents.Get(x))
{
parents.Set(x, false);
// TODO check the constraints
//if (invalidParents.Count > 0 && invalidParents.Contains(parents.ToULong()))
//{
// // we cannot say anything if we skipped this because of constraints
// parents.Set(x, true);
// continue;
//}
parents.Set(x, true);
}
}
Lg(parents, ref s);
Varset variables = new Varset(parents);
variables.Set(variable, true);
s.Score = 0;
ContingencyTableNode ct = adTree.MakeContab(variables);
Dictionary<ulong, int> paCounts = new Dictionary<ulong, int>();
Calculate(ct, 1, 0, paCounts, variables, -1, ref s);
// check constraints (Theorem 9 from de Campos and Ji '11)
// only bother if the alpha bound is okay
// check if can prune
if (s.Aij <= 0.8349)
{
double bound = -1.0 * ct.LeafCount * s.Lri;
// check each subset
for (int x = 0; x < network.Size(); x++)
{
if (parents.Get(x))
{
parents.Set(x, false);
// check the constraints
//if (s->invalidParents.find(parents) != s->invalidParents.end())
//{
// // we cannot say anything if we skipped this because of constraints
// VARSET_SET(parents, x);
// continue;
//}
double tmp = cache.ContainsKey(parents.ToULong()) ? cache[parents.ToULong()] : 0;
// if the score is larger (better) than the bound, then we can prune
if (tmp > bound)
{
return 0;
}
parents.Set(x, true);
}
}
}
foreach (KeyValuePair<ulong, int> kvp in paCounts)
{
s.Score += s.Lgij;
s.Score -= ScoreCalculator.GammaLn(s.Aij + kvp.Value);
}
//parents.Print();
//Console.WriteLine(variable);
return s.Score;
}
