List of usage examples for org.apache.commons.math.random RandomDataImpl RandomDataImpl
public RandomDataImpl()
From source file:benchmarks.dispatch.simulation.AbstractGenerator.java
public AbstractGenerator(long seed, Date now) { rdi = new RandomDataImpl(); rdi.reSeed(seed); this.now = now; }
From source file:guineu.modules.dataanalysis.zeroImputation.ZeroImputationTask.java
public ZeroImputationTask(Dataset dataset) { this.dataset = dataset; data = new RandomDataImpl(); }
From source file:com.l2jserver.service.network.keygen.SecureBlowfishKeygenService.java
@Override protected void doStart() throws ServiceStartException { random = new RandomDataImpl(); }
From source file:br.upe.ecomp.doss.algorithm.fss.Fish.java
public void performIndividualMovement(double[] stepInd, Problem problem) { RandomData random = new RandomDataImpl(); int dimensions = getDimensions(); double[] currentPosition = getCurrentPosition().clone(); double[] nextPosition = new double[getDimensions()]; for (int i = 0; i < dimensions; i++) { nextPosition[i] = currentPosition[i] + random.nextUniform(-1.0, 1.0) * stepInd[i]; if (nextPosition[i] > problem.getUpperBound(i) || nextPosition[i] < problem.getLowerBound(i)) { nextPosition[i] = currentPosition[i]; }//from ww w. java 2 s.c o m } deltaFitness = problem.getFitness(nextPosition) - getCurrentFitness(); if (problem.isFitnessBetterThan(getCurrentFitness(), problem.getFitness(nextPosition)) && deltaFitness < 0) { deltaFitness *= -1; } if (problem.isFitnessBetterThan(getCurrentFitness(), problem.getFitness(nextPosition))) { previousPosition = getCurrentPosition().clone(); updateCurrentPosition(nextPosition, problem.getFitness(nextPosition)); if (problem.isFitnessBetterThan(getBestFitness(), getCurrentFitness())) { updateBestPosition(getCurrentPosition(), getCurrentFitness()); } } else { deltaFitness = 0; } }
From source file:egat.replicatordynamics.SymmetricConstrainedAmoebaSearch.java
public SymmetricConstrainedAmoebaSearch(double tolerance, int maxIteration, PrintStream printStream) { this.tolerance = tolerance; this.maxIteration = maxIteration; this.printStream = printStream; this.randomData = new RandomDataImpl(); }
From source file:egat.replicatordynamics.SymmetricConstrainedFeasibleAmoebaSearch.java
public SymmetricConstrainedFeasibleAmoebaSearch(double tolerance, int maxIteration, PrintStream printStream, SymmetricRationalizableFinder rationalizableFinder) { this.tolerance = tolerance; this.maxIteration = maxIteration; this.printStream = printStream; this.randomData = new RandomDataImpl(); }
From source file:egat.replicatordynamics.SymmetricConstrainedTransformedAmoebaSearch.java
public SymmetricConstrainedTransformedAmoebaSearch(double tolerance, int maxIteration, PrintStream printStream, SymmetricRationalizableFinder rationalizableFinder) { this.tolerance = tolerance; this.maxIteration = maxIteration; this.printStream = printStream; this.rationalizableFinder = rationalizableFinder; this.randomData = new RandomDataImpl(); }
From source file:br.upe.ecomp.doss.problem.movingpeaks.MovingPeaks.java
/** * {@inheritDoc}//from w w w.j a v a 2 s. co m */ public void init() { random = new RandomDataImpl(); Peak peak; peaks = new ArrayList<Peak>(); for (int i = 0; i < 10; i++) { peak = new Peak(random); initPeak(peak); peaks.add(peak); } }
From source file:at.tuwien.ifs.somtoolbox.apps.helper.DataSetGenerator.java
@SuppressWarnings("unchecked") public DataSetGenerator() { rand = new RandomDataImpl(); classPoints = new Vector[CLASS_NAMES.length]; for (int i = 0; i < classPoints.length; i++) { classPoints[i] = new Vector<DataPoint>(); }//from ww w. j a v a2 s.c o m int i = 0; classPoints[i].addAll(generatePoints(CLASS_1 + "_1", 50, 5, 3, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_2", 50, 11, 3, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_3", 50, 5, 6, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_4", 50, 11, 6, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_5", 50, 5, 9, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_6", 50, 11, 9, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_7", 50, 5, 12, 1, 0.5)); classPoints[i].addAll(generatePoints(CLASS_1 + "_8", 50, 11, 12, 1, 0.5)); i++; classPoints[i].addAll(generatePoints(CLASS_2 + "_1", 50, 19, 7.5, 0.5, 2.75)); classPoints[i].addAll(generatePoints(CLASS_2 + "_2", 50, 23, 7.5, 0.5, 2.75)); classPoints[i].addAll(generatePoints(CLASS_2 + "_3", 50, 27, 7.5, 0.5, 2.75)); i++; classPoints[i].addAll(generatePoints(CLASS_3 + "_1_1", 50, 4, 18, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_2", 50, 5.5, 18, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_3", 50, 7, 18, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_4", 50, 8.5, 18, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_5", 50, 10, 18, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_6", 50, 11.5, 18, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_7", 50, 4, 19.5, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_8", 50, 5.5, 19.5, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_9", 50, 7, 19.5, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_10", 50, 8.5, 19.5, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_11", 50, 10, 19.5, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_12", 50, 11.5, 19.5, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_13", 50, 4, 21, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_14", 50, 5.5, 21, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_15", 50, 7, 21, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_16", 50, 8.5, 21, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_17", 50, 10, 21, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_1_18", 50, 11.5, 21, 0.25, 0.25)); classPoints[i].addAll(generatePoints(CLASS_3 + "_2", 50, 8, 24.5, 2.5, 1.25)); i++; classPoints[i].addAll(generatePoints(CLASS_4 + "_1_1", 50, 19, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_2", 50, 20, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_3", 50, 21, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_4", 50, 22, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_5", 50, 23, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_6", 50, 24, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_7", 50, 25, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_8", 50, 26, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_9", 50, 27, 18, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_10", 50, 19, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_11", 50, 20, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_12", 50, 21, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_13", 50, 22, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_14", 50, 23, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_15", 50, 24, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_16", 50, 25, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_17", 50, 26, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_1_18", 50, 27, 19, 0.125, 0.125)); classPoints[i].addAll(generatePoints(CLASS_4 + "_2", 50, 20, 22.5, 1, 0.75)); classPoints[i].addAll(generatePoints(CLASS_4 + "_3", 50, 26, 22.5, 1, 0.75)); classPoints[i].addAll(generatePoints(CLASS_4 + "_4", 50, 23, 26.5, 2.5, 0.75)); i++; classPoints[i].addAll(generatePoints(CLASS_5 + "_1", 50, 8, 33, 2.5, 0.5)); classPoints[i].addAll(generatePoints(CLASS_5 + "_2", 50, 8, 36, 2.5, 0.5)); classPoints[i].addAll(generatePoints(CLASS_5 + "_3", 50, 8, 39, 2.5, 0.5)); classPoints[i].addAll(generatePoints(CLASS_5 + "_4", 50, 8, 42, 2.5, 0.5)); i++; classPoints[i].addAll(generatePoints(CLASS_6 + "_1", 50, 20, 33.5, 1, 0.75)); classPoints[i].addAll(generatePoints(CLASS_6 + "_2", 50, 26, 33.5, 1, 0.75)); classPoints[i].addAll(generatePoints(CLASS_6 + "_3_1", 50, 19, 37.5, 0.25, 0.5)); classPoints[i].addAll(generatePoints(CLASS_6 + "_3_2", 50, 20.5, 37.5, 0.25, 0.5)); classPoints[i].addAll(generatePoints(CLASS_6 + "_3_3", 50, 22, 37.5, 0.25, 0.5)); classPoints[i].addAll(generatePoints(CLASS_6 + "_3_4", 50, 23.5, 37.5, 0.25, 0.5)); classPoints[i].addAll(generatePoints(CLASS_6 + "_3_5", 50, 25, 37.5, 0.25, 0.5)); classPoints[i].addAll(generatePoints(CLASS_6 + "_3_6", 50, 26.5, 37.5, 0.25, 0.5)); classPoints[i].addAll(generatePoints(CLASS_6 + "_4", 50, 20, 41.5, 1, 0.75)); classPoints[i].addAll(generatePoints(CLASS_6 + "_5", 50, 26, 41.5, 1, 0.75)); for (Vector<DataPoint> classPoint : classPoints) { allPoints.addAll(classPoints[i]); } // wenn alle generiert +minval damit alle positiv sind makeNonNegative(allPoints); }
From source file:br.upe.ecomp.doss.algorithm.chargedpso.ChargedPSO.java
private void chargeParticles(ChargedPSOParticle[] particles, double chargedParticlesLenght) { RandomData random = new RandomDataImpl(); List<Integer> indexes = new ArrayList<Integer>(); for (int i = 0; i < particles.length; i++) { indexes.add(i);// w w w .j ava 2 s . c o m } int index; int randomNumber; for (int i = 0; i < chargedParticlesLenght; i++) { randomNumber = random.nextInt(0, indexes.size() - 1); index = indexes.remove(randomNumber); particles[index].setCharge(particleCharge); } }