List of randomize() Examples

Examples of randomize()

com.heatonresearch.aifh.examples.ca.mergelife.physics.MergePhysics.randomize()
{@inheritDoc}
com.heatonresearch.aifh.examples.ca.mergelife.physics.Physics.randomize()
Randomize the physics to random values.
com.heatonresearch.aifh.examples.ca.mergelife.universe.Universe.randomize()
Randomize the universe. @param rnd A random number generator.
com.heatonresearch.aifh.examples.ca.mergelife.universe.UniverseRunner.randomize()
Randomize the universe grid. @param rnd Random number generator.
ise.mace.simulations.evolution.SimulationGenome.randomize()
org.encog.mathutil.randomize.ConsistentRandomizer.randomize()
Generate a random number based on the range specified in the constructor. @param d The range randomizer ignores this value. @return The random number.
org.encog.mathutil.randomize.ConstRandomizer.randomize()
Generate a random number based on the range specified in the constructor. @param d The range randomizer ignores this value. @return The random number.
org.encog.mathutil.randomize.Distort.randomize()
Distort the random number by the factor that was specified in the constructor. @param d The number to distort. @return The result.
org.encog.mathutil.randomize.GaussianRandomizer.randomize()
Generate a random number. @param d The input value, not used. @return The random number.
org.encog.mathutil.randomize.Randomizer.randomize()
Randomize the synapses and bias values in the basic network based on an array, modify the array. Previous values may be used, or they may be discarded, depending on the randomizer. @param network A network to randomize.
org.encog.ml.prg.extension.ProgramExtensionTemplate.randomize()
Randomize this actual tree node. @param rnd Random number generator. @param desiredType The desired type of the randomization, if allowed. @param actual The actual program node to randomize. @param minValue The minimum value to use for randomization. @param maxValue The maximum value to use for randomization.
org.encog.neural.flat.FlatNetwork.randomize()
Perform a simple randomization of the weights of the neural network between -1 and 1.
org.jwildfire.create.tina.random.AbstractRandomGenerator.randomize()
org.jwildfire.create.tina.random.MarsagliaRandomGenerator.randomize()
org.rsbot.script.wrappers.RSTile.randomize()
Randomizes this tile. @param maxXDeviation Max X distance from tile x. @param maxYDeviation Max Y distance from tile y. @return The randomized tile
org.spout.vanilla.world.generator.nether.object.GlowstonePatchObject.randomize()
org.spout.vanilla.world.generator.normal.object.BlockPatchObject.randomize()
org.spout.vanilla.world.generator.normal.object.CactusStackObject.randomize()
org.spout.vanilla.world.generator.normal.object.DungeonObject.randomize()
org.spout.vanilla.world.generator.normal.object.HugeMushroomObject.randomize()
org.spout.vanilla.world.generator.normal.object.SugarCaneStackObject.randomize()
org.spout.vanilla.world.generator.normal.object.tree.TreeObject.randomize()
org.spout.vanilla.world.generator.structure.StructurePiece.randomize()
org.spout.vanilla.world.generator.theend.object.SpireObject.randomize()
prolog.core.Cat.randomize()
weka.core.Instances.randomize()
Shuffles the instances in the set so that they are ordered randomly. @param random a random number generator

Examples of org.spout.vanilla.world.generator.structure.StructurePiece.randomize()

  @Override
  public List<StructurePiece> getNextPieces() {
    final StructurePiece piece = getNextPiece();
    piece.setPosition(position.add(rotate(0, -7, 10)));
    piece.setRotation(rotation);
    piece.randomize();
    return Lists.newArrayList(piece);
  }


  @Override
  public BoundingBox getBoundingBox() {

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Examples of org.spout.vanilla.world.generator.theend.object.SpireObject.randomize()

    if (y == -1) {
      return;
    }
    final SpireObject spire = new SpireObject();
    spire.setRandom(random);
    spire.randomize();
    if (spire.canPlaceObject(world, x, y, z)) {
      spire.placeObject(world, x, y, z);
    }
  }

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Examples of prolog.core.Cat.randomize()

    return new Point3f(x*r,y*r,z*r);
  } 


  public static Cat randomCat(int seed,int v0,int v,int e0,int e) {
    Cat RG=new Cat();
    RG.randomize(seed,v0+ri(v),e0+ri(e));
    return RG;
  }
     
  public static Cat randomRanked(int seed,int v0,int v,int e0,int e,int giant,int m) {
    Cat RG=randomCat(seed,v0,v,e0,e);

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Examples of weka.core.Instances.randomize()

        // create new train/test sources
        if (splitPercentage > 0) {
          testSetPresent = true;
          Instances tmpInst = trainSource.getDataSet(actualClassIndex);
          if (!preserveOrder)
            tmpInst.randomize(new Random(seed));
          int trainSize = 
            (int) Math.round(tmpInst.numInstances() * splitPercentage / 100);
          int testSize  = tmpInst.numInstances() - trainSize;
          Instances trainInst = new Instances(tmpInst, 0, trainSize);
          Instances testInst  = new Instances(tmpInst, trainSize, testSize);

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Examples of weka.core.Instances.randomize()

        break;


        case 2: // Percent split
        m_Log.statusMessage("Randomizing instances...");
        inst.randomize(new Random(1));
        trainInst.randomize(new Random(1));
        int trainSize = trainInst.numInstances() * percent / 100;
        int testSize = trainInst.numInstances() - trainSize;
        Instances train = new Instances(trainInst, 0, trainSize);
        Instances test = new Instances(trainInst, trainSize, testSize);
        Instances testVis = new Instances(inst, trainSize, testSize);

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Examples of weka.core.Instances.randomize()

    filter.setInputFormat(instances);
    instances = Filter.useFilter(instances, filter);
    
    
    Random ran = new Random(System.currentTimeMillis());
    instances.randomize(ran);
    
    int max = 20;
    double[] acc = new double[max];
    while(max > 0) {

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Examples of weka.core.Instances.randomize()

    double[] acc = new double[max];
    while(max > 0) {
      
      //copy and randomize instances
      Instances full = new Instances(instances);
      full.randomize(ran);
      
      // using 5 fold CV to emulate the 80-20 random split of jkms
      Instances train = full.trainCV(5, 0);
      Instances test = full.testCV(5, 0);

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Examples of weka.core.Instances.randomize()

  }
  for (int k = 0; k < subsets[j].numInstances(); k++) {
    data.add(subsets[j].instance(k));
  }
  data.compactify();
  data.randomize(rand);
  m_classifiers[i][j].buildClassifier(data, i, j, 
              m_fitLogisticModels,
              m_numFolds, m_randomSeed);
      }
    }

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Examples of weka.core.Instances.randomize()

    if (m_splitThread == null) {
      final Instances dataSet = new Instances(e.getDataSet());
      m_splitThread = new Thread() {
    public void run() {
      try {
        dataSet.randomize(new Random(m_randomSeed));
        int trainSize = 
                (int)Math.round(dataSet.numInstances() * m_trainPercentage / 100);
        int testSize = dataSet.numInstances() - trainSize;
      
        Instances train = new Instances(dataSet, 0, trainSize);

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Examples of weka.core.Instances.randomize()

    }
    m_InitOptions = ((OptionHandler)m_Classifier).getOptions();
    m_BestPerformance = -99;
    m_NumAttributes = trainData.numAttributes();
    Random random = new Random(m_Seed);
    trainData.randomize(random);
    m_TrainFoldSize = trainData.trainCV(m_NumFolds, 0).numInstances();


    // Check whether there are any parameters to optimize
    if (m_CVParams.size() == 0) {
       m_Classifier.buildClassifier(trainData);

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