Java MersenneTwister類代碼示例

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Test if two clusters are significantly different in the metrics we look at for balancing.
 *
 * @param orig the utilization matrix from the original cluster
 * @param optimized the utilization matrix from the optimized cluster
 * @return The P value that the various derived resources come from the same probability distribution.  The probability
 * that the null hypothesis is correct.
 */
public static double[] testDifference(double[][] orig, double[][] optimized) {
  int nResources = RawAndDerivedResource.values().length;
  if (orig.length != nResources) {
    throw new IllegalArgumentException("orig must have number of rows equal to RawAndDerivedResource.");
  }
  if (optimized.length != nResources) {
    throw new IllegalArgumentException("optimized must have number of rows equal to RawAndDerivedResource.");
  }
  if (orig[0].length != optimized[0].length) {
    throw new IllegalArgumentException("The number of brokers must be the same.");
  }

  double[] pValues = new double[orig.length];

  //TODO:  For small N we want to do statistical bootstrapping (not the same as bootstrapping data).
  for (int resourceIndex = 0; resourceIndex < nResources; resourceIndex++) {
    RandomGenerator rng = new MersenneTwister(0x5d11121018463324L);
    KolmogorovSmirnovTest kolmogorovSmirnovTest = new KolmogorovSmirnovTest(rng);
    pValues[resourceIndex] =
        kolmogorovSmirnovTest.kolmogorovSmirnovTest(orig[resourceIndex], optimized[resourceIndex]);
  }

  return pValues;
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Randomly extracts sequences with limited total length.
 * @param sequenceLength0Upper
 * @param random
 * @param sequence
 * @return
 */
public static Pair<ArrayList<Sequence>, ArrayList<Sequence>> extract(int sequenceLength0Upper, MersenneTwister random, List<Sequence> sequence)
{
	ArrayList<Sequence> all=sequence.stream().collect(CollectionUtils.arrayListCollector());
	all=RandomUtils.permutation(all, random);
	int length=0;
	int num0=0;
	while(num0<all.size())
	{
		int len=all.get(num0).getLength();
		if(length+len>=sequenceLength0Upper) break;
		++num0;
		length+=len;
	}
	ArrayList<Sequence> sequence0=all.subList(0, num0).stream().collect(CollectionUtils.arrayListCollector());
	ArrayList<Sequence> sequence1=all.subList(num0, all.size()).stream().collect(CollectionUtils.arrayListCollector());
	return new Pair<>(sequence0, sequence1);
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Creates {@link BatchData} by loading wave files and converting them into spectrograms.  
 * 
 * @param numLowerLabel Number of sub-divisions in a single element.
 * @param silentLabelFunc A converter from the number of labels and sub-divisions to the index for the silent label.
 * @param finalInputHeight Input height of the spectrogram, seen from the final output layer.
 * @param waveFileDir Directory of wave files.
 * @param stftParam Parameters for short time Fourier transformation.
 * @param dpssParam Parameter for discrete prolate spheroidal sequences. 
 * @param freqOffset Beginning of the frequency band.
 * @param freqLength Length of the frequency band.
 * @param spectrogramMeanSd Mean and SD of the spectrograms in the training data. Used for input scaling.
 * @param inputHeightUpper Upper value of the combined input spectrogram.
 * @return
 * @throws IOException
 * @throws UnsupportedAudioFileException
 * @throws NotConvergedException
 */
public static BatchData create(List<Sequence> sequence, MersenneTwister random, int numLowerLabel, IntBinaryOperator silentLabelFunc, int finalInputHeight, Path waveFileDir, STFTParam stftParam, int dpssParam, int freqOffset, int freqLength, double[] spectrogramMeanSd, int inputHeightUpper) throws IOException, UnsupportedAudioFileException, NotConvergedException
{
	int marginBegin=finalInputHeight/2;
	int marginEnd=finalInputHeight/2-1;
	HashMap<Sequence, WavePosition> wavePosition=Sequence.wavePositionMap(sequence, waveFileDir);
	for(WavePosition wp: wavePosition.values())
	{
		int waveBegin=wp.getPosition()-marginBegin*stftParam.getShiftLength();
		int waveEnd=wp.getEnd()+marginEnd*stftParam.getShiftLength();
		wp.setPosition(waveBegin);
		wp.setLength(waveEnd-waveBegin);
	}
	HashMap<Sequence, float[]> spectrogram=SoundUtils.spectrogram(wavePosition, stftParam, dpssParam, freqOffset, freqLength);
	SoundUtils.whiteSpectrogram(spectrogram.values(), spectrogramMeanSd[0], spectrogramMeanSd[1]);
	
	ArrayList<float[]> spectrogramList=sequence.stream().map(s->spectrogram.get(s)).collect(Collectors.toCollection(ArrayList::new));
	ArrayList<ArrayList<Integer>> packedSpectrogram=packedSpectrogramIndex(inputHeightUpper, spectrogramList, random, freqLength);
	
	int packedHeight=packedSpectrogram.stream()
			.mapToInt(spec->spec.stream().mapToInt(s->spectrogram.get(sequence.get(s)).length/freqLength).sum())
			.max().getAsInt();
	
	return new BatchData(spectrogramList, packedHeight, packedSpectrogram, sequence, numLowerLabel, silentLabelFunc, marginBegin, marginEnd, finalInputHeight, stftParam);
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
@Test
public void test1() {

	IFeatureCollection<IFeature> featColl = ShapefileReader
			.read(getClass().getClassLoader().getResource("parcelDecomposition/parcelle.shp").toString());

	IPolygon pol = (IPolygon) FromGeomToSurface.convertGeom(featColl.get(0).getGeom()).get(0);

	double maximalArea = 100;
	double maximalWidth = 20;
	RandomGenerator rng = new MersenneTwister(42);
	double epsilon = 0;
	double noise = 10;

	OBBBlockDecomposition obb = new OBBBlockDecomposition(pol, maximalArea, maximalWidth, rng, epsilon, noise);
	try {
		IFeatureCollection<IFeature> featCOut = obb.decompParcel();
		assertNotNull(featCOut);
		assertTrue(! featCOut.isEmpty());
	} catch (Exception e) {
		// TODO Auto-generated catch block
		e.printStackTrace();
		assertTrue(false);
	}

}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Returns the point closest to the exact center of the area spanned by the
 * graph.
 * @param graph The graph.
 * @return The point of the graph closest to the exact center of the area
 *         spanned by the graph.
 */
private Point getCenterMostPoint(Graph<?> graph) {
  final ImmutableList<Point> extremes = Graphs.getExtremes(graph);
  final Point exactCenter =
    Point.divide(Point.add(extremes.get(0), extremes.get(1)), 2d);
  Point center = graph.getRandomNode(new MersenneTwister());
  double distance = Point.distance(center, exactCenter);

  for (final Point p : graph.getNodes()) {
    final double pDistance = Point.distance(p, exactCenter);
    if (pDistance < distance) {
      center = p;
      distance = pDistance;
    }

    if (center.equals(exactCenter)) {
      return center;
    }
  }

  return center;
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
public static void main(String[] args) {
	if (args.length != 5) {
		System.err.println(usage());
		System.exit(1);
	}
	try {
		final Supplier<Agent> AGENT = createAgentFactoryByReflection(new File(args[0]), args[1]);
		final int REPEATS = Integer.parseInt(args[2]);
		final Duration ACTION_TIME_LIMIT = Duration.ofNanos((int) (Double.parseDouble(args[3]) * 1000 * 1000));
		final long RANDOM_SEED = Long.parseLong(args[4]);

		RandomDataGenerator random = new RandomDataGenerator(new MersenneTwister(RANDOM_SEED));
		MultipleGamesResult result = new Game(ACTION_TIME_LIMIT).playMultiple(AGENT, REPEATS, random);
		System.out.println(result.toCvsRow());

	} catch (Exception e) {
		System.err.println(e.toString());
		System.err.println();
		System.err.println(usage());
		System.exit(1);
	}
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * @param configFileName String with the address of the configuration file
 * @param outputFolder String with the address of the folder for storing results
 */
public Model(String configFileName, String outputFolder) {
    // TODO: Check that random numbers are working properly!
    config = new Config(configFileName);
    rand = new MersenneTwister(config.SEED);

    government = new Government();
    demographics = new Demographics();
    construction = new Construction();
    centralBank = new CentralBank();
    bank = new Bank();
    households = new ArrayList<>(config.TARGET_POPULATION*2);
    houseSaleMarket = new HouseSaleMarket();
    houseRentalMarket = new HouseRentalMarket();

    recorder = new collectors.Recorder(outputFolder);
    transactionRecorder = new collectors.MicroDataRecorder(outputFolder);
    creditSupply = new collectors.CreditSupply(outputFolder);
    coreIndicators = new collectors.CoreIndicators();
    householdStats = new collectors.HouseholdStats();
    housingMarketStats = new collectors.HousingMarketStats(houseSaleMarket);
    rentalMarketStats = new collectors.RentalMarketStats(housingMarketStats, houseRentalMarket);

    nSimulation = 0;
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Starts the demo.
 * @param args No args.
 */
public static void main(String[] args) {
  final String string = "AgentWise";
  final List<Point> points = measureString(string, 30, 30, 0);
  final RandomGenerator rng = new MersenneTwister(123);
  final Simulator sim = new Simulator(rng, Measure.valueOf(1000L,
      SI.MILLI(SI.SECOND)));
  sim.register(new PlaneRoadModel(new Point(0, 0), new Point(4500, 1200),
      SI.METER, Measure.valueOf(1000d, NonSI.KILOMETERS_PER_HOUR)));
  sim.configure();
  for (final Point p : points) {
    sim.register(new Vehicle(p, rng));
  }
  View.create(sim)
      .with(new PlaneRoadModelRenderer(), new VehicleRenderer(),
          new DemoPanel(string, rng)).show();
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
public BeaconTruck(VehicleDTO pDto, int seed,
                   double beaconRadius, double commRadius, double commReliability,
                   SchedulingStrategy pickupStrategy, SchedulingStrategy deliveryStrategy,
                   boolean doExchange) {
    super(pDto);

    this.beaconRadius = beaconRadius;
    this.commReliability = commReliability;
    this.commRadius = commRadius;
    this.doExchange = doExchange;

    this.messageStore = new MessageStore();
    this.pickupQueue = new ArrayList<BeaconParcel>();
    this.auctionActivity = new AuctionActivity(this, messageStore);
    this.fetchActivity = new FetchActivity(this, pickupStrategy);
    this.transportActivity = new TransportActivity(this, deliveryStrategy);
    this.exchangeActivity = new ExchangeActivity(this,messageStore);
    this.pickupActivity = new PickupActivity(this);
    this.deliverActivity = new DeliverActivity(this);
    this.discoverActivity = new DiscoverActivity(auctionActivity, this);
    this.exploreActivity = new ExploreActivity(this, new MersenneTwister(seed));

    this.setBeaconStatus(BeaconStatus.ACTIVE);
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
public static void drawMnist(DataSet mnist,INDArray reconstruct) throws InterruptedException {
	for(int j = 0; j < mnist.numExamples(); j++) {
		INDArray draw1 = mnist.get(j).getFeatureMatrix().mul(255);
		INDArray reconstructed2 = reconstruct.getRow(j);
		INDArray draw2 = Sampling.binomial(reconstructed2, 1, new MersenneTwister(123)).mul(255);

		DrawReconstruction d = new DrawReconstruction(draw1);
		d.title = "REAL";
		d.draw();
		DrawReconstruction d2 = new DrawReconstruction(draw2,1000,1000);
		d2.title = "TEST";
		
		d2.draw();
		Thread.sleep(1000);
		d.frame.dispose();
		d2.frame.dispose();

	}
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
@Override
protected void configure() {
    // Network API
    bind(Network.class).to(FastNetwork.class);

    bind(DynamicNetwork.class).to(DynamicFastNetwork.class);

    // NetworkModel API
    bind(Configuration.class).to(PropertiesConfiguration.class);

    bind(RandomGenerator.class).to(MersenneTwister.class);

    bind(BAModel.class).to(DefaultBAModel.class);
    bind(BAForestModel.class).to(DefaultBAForestModel.class);
    bind(KRegularModel.class).to(DefaultKRegularModel.class);
    bind(ERModel.class).to(EERModel.class);
    bind(GilbertModel.class).to(EGilberModel.class);
    bind(WSModel.class).to(DefaultWSModel.class);
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
@Test
public void testRandomNode() {
	RandomGenerator random = new MersenneTwister(0);
	HashMap<Integer, Integer> count = new HashMap<>();
	int numNodes = 10;
	int[] exclude = { 1, 2, 3, 4, 5};

	for (int i = 0; i < 100000; i++) {
		int randomN = NetworkModelUtils.getRandomNode(random, numNodes,
				exclude);
		if (count.containsKey(randomN)) {
			count.put(randomN, (count.get(randomN) + 1));
		} else {
			count.put(randomN, 1);
		}
		
		for (int e : exclude) {
			assertNotSame(e, randomN);
		}
	}
	for(int k: count.keySet()){
		System.out.println("node: "+k+" c: "+count.get(k));
	}
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
private static ArrayList<ArrayList<Integer>> packedSpectrogramIndex(int heightUpper, List<float[]> spectrogram, MersenneTwister random, int inputWidth)
{
	int[] shuffleSpectrogram;
	if(random!=null) shuffleSpectrogram=RandomUtils.permutation(spectrogram.size(), random);
	else shuffleSpectrogram=ArrayUtils.createSequence(0, spectrogram.size());
	ArrayList<int[]> dataHeight=new ArrayList<int[]>();
	HashMap<Integer, LinkedList<Integer>> inputSpec=new HashMap<>();
	for(int s: shuffleSpectrogram)
	{
		float[] spec=spectrogram.get(s);
		int specHeight=spec.length/inputWidth;
		int[] minHeight=null;
		if(dataHeight.size()>0) minHeight=Collections.min(dataHeight, (o1, o2)->o1[1]-o2[1]);

		if(dataHeight.size()>0 && heightUpper-minHeight[1]>=specHeight)
		{
			minHeight[1]+=specHeight;
			inputSpec.putIfAbsent(minHeight[0], new LinkedList<>());
			inputSpec.get(minHeight[0]).add(s);
		}
		else
		{
			inputSpec.putIfAbsent(dataHeight.size(), new LinkedList<>());
			inputSpec.get(dataHeight.size()).add(s);
			dataHeight.add(new int[]{dataHeight.size(), specHeight});
		}
	}
	ArrayList<ArrayList<Integer>> packedIndex=new ArrayList<>(inputSpec.size());
	for(int packed=0; packed<inputSpec.size(); ++packed) packedIndex.add(new ArrayList<Integer>(inputSpec.get(packed)));
	return packedIndex;
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Makes batch inputs.
 * This method must be called before training or recognition with a DNN.
 * @param maxBatchSize
 * @param randomShuffle
 * @param inputWidth
 * @throws IOException
 */
public void batch(int maxBatchSize, MersenneTwister randomShuffle, int inputWidth) throws IOException
{
	this.maxBatchSize=maxBatchSize;
	numBatch=MathUtils.ceil(inputData.size(), maxBatchSize);
	batchData=new ArrayList<>(numBatch);
	batchLabel=new ArrayList<>(numBatch); 
	int[] shuffleInput;
	if(randomShuffle!=null) shuffleInput=RandomUtils.permutation(inputData.size(), randomShuffle);
	else shuffleInput=ArrayUtils.createSequence(0, inputData.size());
	packBatchIndex=new ArrayList<int[]>();
	for(int p=0; p<inputData.size(); ++p) packBatchIndex.add(null);
	for(int b=0; b<numBatch; ++b)
	{
		batchData.add(new ArrayList<float[]>(maxBatchSize));
		batchLabel.add(new byte[labelHeight*maxBatchSize]);
		for(int i=0; i<maxBatchSize; ++i)
		{
			int in=i*numBatch+b;
			if(in<inputData.size())
			{
				int si=shuffleInput[in];
				batchData.get(b).add(inputData.get(si));
				System.arraycopy(inputLabel.get(si), 0, batchLabel.get(b), i*labelHeight, labelHeight);
				packBatchIndex.set(si, new int[]{b, i});
			}
			else
			{
				for(int i1=i; i1<maxBatchSize; ++i1) batchData.get(b).add(new float[packedHeight*inputWidth]);
				Arrays.fill(batchLabel.get(b), i*packedHeight, batchLabel.get(b).length, (byte)-1);
				break;
			}
		}
	}
}
 

import org.apache.commons.math3.random.MersenneTwister; //導入依賴的package包/類
/**
 * Initializes network parameters according to http://arxiv.org/abs/1502.01852.
 * @see http://arxiv.org/abs/1502.01852
 * @param layer
 * @param random
 */
public static void initParam(List<Layer> layer, MersenneTwister random)
{
	for(Layer la: layer) if(la instanceof ParamLayer)
	{
		int size=0;
		ConvLayer cl=(ConvLayer)la;
		size=cl.getLower().getNumChannel()*cl.getFilterHeight()*cl.getFilterHeight();
		double scale=Math.sqrt(2.0/size);
		for(int i=0; i<cl.getWeightF().length; ++i) cl.getWeightF()[i]=(float)(random.nextGaussian()*scale);
		for(int i=0; i<cl.getBiasF().length; ++i) cl.getBiasF()[i]=0;
	}
}