Example usage for com.google.common.util.concurrent AtomicDouble AtomicDouble

Introduction

In this page you can find the example usage for com.google.common.util.concurrent AtomicDouble AtomicDouble.

Prototype

public AtomicDouble(double initialValue) 

Source Link

Document

Creates a new AtomicDouble with the given initial value.

Usage

From source file:com.netflix.spinnaker.kork.metrics.SpectatorMetricWriter.java

private AtomicDouble getGaugeStorage(Id id) {
    final AtomicDouble newGauge = new AtomicDouble(0);
    final AtomicDouble existingGauge = gauges.putIfAbsent(id, newGauge);
    if (existingGauge == null) {
        return newGauge;
    }//from ww w .ja  va 2 s  .  c  o  m

    return existingGauge;
}

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From source file:it.stilo.g.algo.PageRankPI.java

public static ArrayList<DoubleValues> compute(final WeightedGraph g, double beta, double sigma, int runner) {
    long time = System.currentTimeMillis();
    double[] ranks = new double[g.size];
    double[] oldRanks;
    int realSize = 0;
    for (int i = 0; i < g.size; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            realSize++;//from ww w .  j a  v a  2  s. co  m
        }
    }

    double iV = 1d / (double) realSize;

    for (int i = 0; i < g.size; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            ranks[i] = iV;
        }
    }

    double diff = 0;

    do {
        AtomicDouble S = new AtomicDouble(0.0);
        CountDownLatch first = new CountDownLatch(runner);
        CountDownLatch second = new CountDownLatch(runner);
        CountDownLatch third = new CountDownLatch(runner);

        oldRanks = Arrays.copyOf(ranks, ranks.length);

        Thread[] workers = new Thread[runner];
        for (int i = 0; i < runner; i++) {
            workers[i] = new Thread(
                    new PageRankPI(g, first, second, third, ranks, beta, realSize, S, i, runner));
            workers[i].setName("" + i);
            workers[i].start();
        }
        try {
            third.await();
        } catch (InterruptedException e) {
            logger.debug(e);
        }

    } while (ArraysUtil.L1(ArraysUtil.sub(oldRanks, ranks)) > sigma);

    ArrayList<DoubleValues> list = new ArrayList<DoubleValues>(realSize);
    for (int i = 0; i < ranks.length; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            list.add(new DoubleValues(i, ranks[i]));
        }
    }
    Collections.sort(list);

    logger.info(((System.currentTimeMillis() - time) / 1000d) + "s");
    return list;
}

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From source file:io.watchcat.node.monitoring.threshold.LoadAverageThresholds.java

@PostConstruct
public void postConstruct() {
    int numberOfCores = loadAverage.getNumberOfCpuCores();
    oneMinuteAverageCriticalThreshold = new AtomicDouble(numberOfCores + 3);
    oneMinuteAverageMajorThreshold = new AtomicDouble(numberOfCores + 2);
    oneMinuteAverageMinorThreshold = new AtomicDouble(numberOfCores + 1);

    fiveMinuteAverageCriticalThreshold = new AtomicDouble(numberOfCores + 2);
    fiveMinuteAverageMajorThreshold = new AtomicDouble(numberOfCores + 1);
    fiveMinuteAverageMinorThreshold = new AtomicDouble(numberOfCores);

    fifteenMinuteAverageCriticalThreshold = new AtomicDouble(numberOfCores + 0.25);
    fifteenMinuteAverageMajorThreshold = new AtomicDouble(numberOfCores);
    fifteenMinuteAverageMinorThreshold = new AtomicDouble(numberOfCores - 0.25);
}

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From source file:eu.amidst.core.learning.parametric.ParallelMaximumLikelihood.java

/**
 * {@inheritDoc}/*  ww  w .  j  a  va2s  .  c o m*/
 */
@Override
public void initLearning() {
    efBayesianNetwork = new EF_BayesianNetwork(dag);
    if (laplace) {
        sumSS = efBayesianNetwork.createInitSufficientStatistics();
        dataInstanceCount = new AtomicDouble(1.0); //Initial counts
    } else {
        sumSS = efBayesianNetwork.createZeroSufficientStatistics();
        dataInstanceCount = new AtomicDouble(0.0); //Initial counts
    }
}

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From source file:eu.amidst.dynamic.learning.parametric.ParallelMaximumLikelihood.java

/**
 * {@inheritDoc}/*from  w w  w  . ja va 2s  . c o m*/
 */
@Override
public void initLearning() {
    efBayesianNetwork = new EF_DynamicBayesianNetwork(dag);
    if (laplace) {
        sumSS = efBayesianNetwork.createInitSufficientStatistics();
        dataInstanceCount = new AtomicDouble(1.0); //Initial counts
    } else {
        sumSS = efBayesianNetwork.createZeroSufficientStatistics();
        dataInstanceCount = new AtomicDouble(0.0); //Initial counts
    }
}

---

From source file:eu.amidst.dynamic.learning.parametric.ParallelMLMissingData.java

/**
 * {@inheritDoc}//from  ww w.jav  a2 s.  c  o m
 */
@Override
public void initLearning() {
    efBayesianNetwork = new EF_DynamicBayesianNetwork(dag);
    if (laplace) {
        sumSS = DynamicPartialSufficientSatistics.createInitPartialSufficientStatistics(efBayesianNetwork);
        dataInstanceCount = new AtomicDouble(1.0); //Initial counts
    } else {
        sumSS = DynamicPartialSufficientSatistics.createZeroPartialSufficientStatistics(efBayesianNetwork);
        dataInstanceCount = new AtomicDouble(0.0); //Initial counts
    }
}

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From source file:eu.amidst.core.learning.parametric.ParallelMLMissingData.java

/**
 * {@inheritDoc}//  w  w  w  .  jav  a 2  s .c  o m
 */
@Override
public void initLearning() {
    efBayesianNetwork = new EF_BayesianNetwork(dag);
    if (laplace) {
        sumSS = PartialSufficientSatistics.createInitPartialSufficientStatistics(efBayesianNetwork);
        dataInstanceCount = new AtomicDouble(1.0); //Initial counts
    } else {
        sumSS = PartialSufficientSatistics.createZeroPartialSufficientStatistics(efBayesianNetwork);
        dataInstanceCount = new AtomicDouble(0.0); //Initial counts
    }
}

---

From source file:it.stilo.g.algo.Leadership.java

public static ArrayList<DoubleValues> compute(final WeightedGraph g, double sigma, int runner) {
    long time = System.currentTimeMillis();
    double[] hub = new double[g.size];
    double[] auth = new double[g.size];
    double[] oldAuth;

    double iV = 1; //Hubness & Authority scores initialized by dafault to 1.

    for (int i = 0; i < g.size; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            auth[i] = iV;//from w w w.j  a  v  a2s. co m
            hub[i] = iV;
        }
    }

    //Shared accoumulator for normalization phase.
    AtomicDouble SAuth = new AtomicDouble(0.0);
    AtomicDouble SHub = new AtomicDouble(0.0);
    int count = 0;
    do {
        SAuth.set(0.0);
        SHub.set(0.0);
        CountDownLatch authority = new CountDownLatch(runner);
        CountDownLatch hubness = new CountDownLatch(runner);
        CountDownLatch normalizationStep = new CountDownLatch(runner);

        oldAuth = Arrays.copyOf(auth, auth.length);

        Thread[] workers = new Thread[runner];
        for (int i = 0; i < runner; i++) {
            workers[i] = new Thread(
                    new Leadership(g, authority, hubness, normalizationStep, hub, auth, SHub, SAuth, i, runner),
                    "" + i);
            workers[i].start();
        }

        try {
            normalizationStep.await();
        } catch (InterruptedException e) {
            logger.debug(e);
        }
        count++;
    } while (ArraysUtil.L1(ArraysUtil.sub(oldAuth, auth)) > sigma); //Repeat until reach the desiderd precision.

    ArrayList<DoubleValues> leader = new ArrayList<DoubleValues>();

    //Create ranking lists for Hubness & Authority
    for (int i = 0; i < auth.length; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            leader.add(new DoubleValues(i, (auth[i] + hub[i]) / 2.0d));
        }
    }

    Collections.sort(leader);

    logger.trace(((System.currentTimeMillis() - time) / 1000d) + "s\t" + count);
    return leader;
}

---

From source file:it.stilo.g.algo.HubnessAuthority.java

public static ArrayList<ArrayList<DoubleValues>> compute(final WeightedGraph g, double sigma, int runner) {
    long time = System.currentTimeMillis();
    double[] hub = new double[g.size];
    double[] auth = new double[g.size];
    double[] oldAuth;

    double iV = 1; //Hubness & Authority scores initialized by dafault to 1.

    for (int i = 0; i < g.size; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            auth[i] = iV;//  w w w .  j a  va2  s .co m
            hub[i] = iV;
        }
    }

    //Shared accoumulator for normalization phase.
    AtomicDouble SAuth = new AtomicDouble(0.0);
    AtomicDouble SHub = new AtomicDouble(0.0);
    int count = 0;
    do {
        SAuth.set(0.0);
        SHub.set(0.0);
        CountDownLatch authority = new CountDownLatch(runner);
        CountDownLatch hubness = new CountDownLatch(runner);
        CountDownLatch normalizationStep = new CountDownLatch(runner);

        oldAuth = Arrays.copyOf(auth, auth.length);

        Thread[] workers = new Thread[runner];
        for (int i = 0; i < runner; i++) {
            workers[i] = new Thread(new HubnessAuthority(g, authority, hubness, normalizationStep, hub, auth,
                    SHub, SAuth, i, runner), "" + i);
            workers[i].start();
        }

        try {
            normalizationStep.await();
        } catch (InterruptedException e) {
            logger.debug(e);
        }
        count++;
    } while (ArraysUtil.L1(ArraysUtil.sub(oldAuth, auth)) > sigma); //Repeat until reach the desiderd precision.

    ArrayList<DoubleValues> listAuth = new ArrayList<DoubleValues>();
    ArrayList<DoubleValues> listHub = new ArrayList<DoubleValues>();

    //Create ranking lists for Hubness & Authority
    for (int i = 0; i < auth.length; i++) {
        if (g.in[i] != null || g.out[i] != null) {
            listAuth.add(new DoubleValues(i, auth[i]));
            listHub.add(new DoubleValues(i, hub[i]));
        }
    }

    Collections.sort(listAuth);
    Collections.sort(listHub);

    ArrayList<ArrayList<DoubleValues>> list = new ArrayList<ArrayList<DoubleValues>>();
    list.add(new ArrayList(listAuth));
    list.add(new ArrayList(listHub));

    logger.trace(((System.currentTimeMillis() - time) / 1000d) + "s\t" + count);
    return list;
}

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From source file:it.geosolutions.jaiext.stats.HistogramMode.java

@Override
protected synchronized void clearStats() {
    // All the bins are set to 0
    for (int i = 0; i < numBins; i++) {
        bins[i] = new AtomicDouble(0);
    }//from  w  w  w. j  a v  a 2  s  . c o m
}

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