Set<OWLProperty<?, ?>> currentProperties = new HashSet<OWLProperty<?, ?>>();
StepSizeStrategy currentStepSizeStrategy = StrategyFactory
.newStepSizeStrategy("EqualParts", currentPoint.size());
TrivialStrategy currentSelectionStrategy = new TrivialStrategy(
new HashSet<OWLClass>(currentPoint), currentProperties,
currentStepSizeStrategy, currentPoint, currentID + "");
/*new ExperimentManager().run(currentSelectionStrategy,
datasetsDirectory, ontology, resultsDirectory, tmpDirectory);
currentGainScore = new IntegralCalculator().getGainScore(
resultsDirectory, ontology, currentSelectionStrategy.getID());*/
double maxGainScore = currentGainScore;
ArrayList<OWLClass> maxPoint = new ArrayList<OWLClass>(currentPoint);
double maxID = currentID;
currentID++;
for (int i = 0; i < maxIterations; i++)
{
ArrayList<OWLClass> neighborPoint = getNeighborPoint(currentPoint);
for (int j = 0; j < 7; j++)
neighborPoint = getNeighborPoint(neighborPoint);
Set<OWLProperty<?, ?>> neighborProperties = new HashSet<OWLProperty<?, ?>>();
StepSizeStrategy neighborStepSizeStrategy = StrategyFactory
.newStepSizeStrategy("EqualParts", currentPoint.size());
TrivialStrategy neighborSelectionStrategy = new TrivialStrategy(
new HashSet<OWLClass>(neighborPoint), neighborProperties,
neighborStepSizeStrategy, neighborPoint, currentID + "");
/*new ExperimentManager()
.run(neighborSelectionStrategy, datasetsDirectory,
ontology, resultsDirectory, tmpDirectory);*/
double neighborGainScore = new IntegralCalculator().getGainScore(
resultsDirectory, ontology, neighborSelectionStrategy
.getID());
double probability = 1;
if (neighborGainScore < currentGainScore)