public void ApplyChange(DivisorChange change)
{
var divisor = divisors[change.Divisor];
divisor.ChangePosition(change.Direction);
lastChanges.AddLast(change);
}
public void UndoChange(DivisorChange change)
{
var divisor = divisors[change.Divisor];
divisor.ChangePosition(change.Direction == Direction.Left ? Direction.Right : Direction.Left);
}
protected override double[] DoIteration(List <IGWGraph <NodeData, EdgeData, GraphData> > TrainingGraphs, double[] weightCurrent, int globalIteration)
{
var weights = weightCurrent.ToArray();
var weightsSum = new double[weightCurrent.Length];
int iteration = 0;
double mcc = 0.0, mcc2 = 0.0;
var newPoint = new Point(weights, new int[weights.Length], 0.0);
{
double tp = 0.001, tn = CoreResiduesTraining, fp = 0.001, fn = 0.001;
MemoryPoints.Add(newPoint);
if (MemoryPoints.Count > memoryPoints)
{
MemoryPoints.RemoveAt(0);
}
ReferencePoint = new Point(weights, new int[weights.Length], 1.0);
for (int i = 0; i < TrainingGraphs.Count; i++)
{
var graph = TrainingGraphs[i];
//set scores according to weights
#region set weights
foreach (var node in graph.Nodes)
{
var scores = new double[Labels];
node.Data.Scores = scores;
for (int label = 0; label < Labels; label++)
{
for (int k = 0; k < weights.Length; k++)
{
scores[label] += weights[k] * BasisMerkmale[k].Score(node, label);
}
}
}
foreach (var edge in graph.Edges)
{
var scores = new double[Labels, Labels];
edge.Data.Scores = scores;
for (int label1 = 0; label1 < Labels; label1++)
{
for (int label2 = 0; label2 < Labels; label2++)
{
for (int k = 0; k < weights.Length; k++)
{
scores[label1, label2] += weights[k] * BasisMerkmale[k].Score(edge, label1, label2);
}
}
}
}
#endregion
//compute labeling with viterbi algorithm
var request = new SolveInference(graph as IGWGraph <ICRFNodeData, ICRFEdgeData, ICRFGraphData>, null, Labels, BufferSizeInference);
request.RequestInDefaultContext();
int[] labeling = request.Solution.Labeling;
//check nonequality
iteration++;
for (int k = 0; k < labeling.Length; k++)
{
if (graph.Data.ReferenceLabeling[k] > 0)
{
if (labeling[k] > 0)
{
tp += 1;
}
else
{
fn += 1;
}
}
else
{
if (labeling[k] > 0)
{
fp += 1;
}
else
{
tn += 1;
}
}
}
int[] countsPred = CountPred(graph, labeling);
int[] countsRef = CountPred(graph, graph.Data.ReferenceLabeling);
for (int k = 0; k < countsPred.Length; k++)
{
newPoint.Counts[k] += countsPred[k];
ReferencePoint.Counts[k] += countsRef[k];
}
//TrackResults(labeling, graph.Data.ReferenceLabeling);
}
//WriterResults();
var sensitivity = tp / (tp + fn);
var specificity = tn / (tn + fp);
mcc = (tp * tn - fp * fn) / Math.Sqrt((tp + fp) * (tp + fn) * (tn + fp) * (tn + fn));
newPoint.Score = mcc;
Log.Post("New MCC: " + Math.Round(mcc, 5) + " Sens: " + Math.Round(sensitivity, 5) + " Spec: " + Math.Round(specificity, 5));
}
//change Interval borders
{
var randomChanges = DivisorChange.RandomInstances(Intervals - 1);
foreach (var change in randomChanges)
{
var changesFor = random.Next(5);
if (changesFor == 0)
{
ValueMapRasa.ApplyChange(change);
}
else if (changesFor == 1)
{
ValueMapEMax01.ApplyChange(change);
}
else if (changesFor == 2)
{
ValueMapEMax11.ApplyChange(change);
}
else if (changesFor == 3)
{
ValueMapEDiff01.ApplyChange(change);
}
else if (changesFor == 4)
{
ValueMapEDiff11.ApplyChange(change);
}
}
double tp = 0.001, tn = CoreResiduesTraining, fp = 0.001, fn = 0.001;
//var newPoint = new Point(weights, new int[weights.Length], 0.0);
//MemoryPoints.Add(newPoint);
//if (MemoryPoints.Count > memoryPoints)
// MemoryPoints.RemoveAt(0);
//ReferencePoint = new Point(weights, new int[weights.Length], 1.0);
for (int i = 0; i < TrainingGraphs.Count; i++)
{
var graph = TrainingGraphs[i];
SetWeightsCRF(weights, graph);
//compute labeling with viterbi algorithm
var request = new SolveInference(graph as IGWGraph <ICRFNodeData, ICRFEdgeData, ICRFGraphData>, null, Labels, BufferSizeInference);
request.RequestInDefaultContext();
int[] labeling = request.Solution.Labeling;
//check nonequality
for (int k = 0; k < labeling.Length; k++)
{
if (graph.Data.ReferenceLabeling[k] > 0)
{
if (labeling[k] > 0)
{
tp += 1;
}
else
{
fn += 1;
}
}
else
{
if (labeling[k] > 0)
{
fp += 1;
}
else
{
tn += 1;
}
}
}
int[] countsPred = CountPred(graph, labeling);
int[] countsRef = CountPred(graph, graph.Data.ReferenceLabeling);
//for (int k = 0; k < countsPred.Length; k++)
//{
// newPoint.Counts[k] += countsPred[k];
// //ReferencePoint.Counts[k] += countsRef[k];
//}
//TrackResults(labeling, graph.Data.ReferenceLabeling);
}
//WriterResults();
var sensitivity = tp / (tp + fn);
var specificity = tn / (tn + fp);
mcc2 = (tp * tn - fp * fn) / Math.Sqrt((tp + fp) * (tp + fn) * (tn + fp) * (tn + fn));
//newPoint.Score = mcc2;
Log.Post("New MCC(IChanged): " + Math.Round(mcc, 5) + " Sens: " + Math.Round(sensitivity, 5) + " Spec: " + Math.Round(specificity, 5));
}
if (mcc2 > mcc)
{
ValueMapRasa.lastChanges.Clear();
ValueMapEMax01.lastChanges.Clear();
ValueMapEMax11.lastChanges.Clear();
ValueMapEDiff01.lastChanges.Clear();
ValueMapEDiff11.lastChanges.Clear();
Log.Post("Intervals changed");
MemoryPoints.RemoveAt(MemoryPoints.Count - 1);
}
else
{
ValueMapRasa.UndoLastChanges();
ValueMapEMax01.UndoLastChanges();
ValueMapEMax11.UndoLastChanges();
ValueMapEDiff01.UndoLastChanges();
ValueMapEDiff11.UndoLastChanges();
if (MemoryPoints.Count == 1)
{
MemoryPoints.Add(ReferencePoint);
}
var deltaomega = new double[weights.Length];
for (int k = 0; k < MemoryPoints.Count - 1; k++)
{
var pointOne = MemoryPoints[k];
for (int l = k + 1; l < MemoryPoints.Count; l++)
{
var pointTwo = MemoryPoints[l];
int[] countsRefMinusPred = new int[weights.Length];
for (int m = 0; m < weights.Length; m++)
{
countsRefMinusPred[m] = (pointOne.Counts[m] - pointTwo.Counts[m]);
}
var weightedScore = 0.0;
for (int m = 0; m < weights.Length; m++)
{
weightedScore += weights[m] * (countsRefMinusPred[m]);
}
double l2normsq = (countsRefMinusPred.Sum(entry => entry * entry));
var loss = 100 * (pointOne.Score - pointTwo.Score);
var deltaomegaFactor = (loss - weightedScore) / (l2normsq);
for (int m = 0; m < weights.Length; m++)
{
if (l2normsq > 0)
{
deltaomega[m] += deltaomegaFactor * countsRefMinusPred[m];
}
}
}
}
//if (MemoryPoints.Count >= memoryPoints)
{
//normalize
var normFactor = MemoryPoints.Count * (MemoryPoints.Count - 1) / 2;
for (int m = 0; m < weights.Length; m++)
{
deltaomega[m] /= normFactor;
}
for (int k = 0; k < weights.Length; k++)
{
weights[k] += deltaomega[k];
}
}
//else
//{
// for (int k = 0; k < weights.Length; k++)
// {
// weights[k] = 0.02 * random.NextDouble() - 0.01;
// }
//}
//if (iteration == 1)
//MemoryPoints.Remove(ReferencePoint);
}
return(weights);
}
