Example usage for java.lang Double compare

Introduction

In this page you can find the example usage for java.lang Double compare.

Prototype

public static int compare(double d1, double d2) 

Source Link

Document

Compares the two specified double values.

Usage

From source file:org.apache.pulsar.broker.loadbalance.impl.OverloadShedder.java

/**
 * Attempt to shed some bundles off every broker which is overloaded.
 *
 * @param loadData/* w  w w. j ava  2  s  . c o  m*/
 *            The load data to used to make the unloading decision.
 * @param conf
 *            The service configuration.
 * @return A map from bundles to unload to the brokers on which they are loaded.
 */
public Multimap<String, String> findBundlesForUnloading(final LoadData loadData,
        final ServiceConfiguration conf) {
    selectedBundlesCache.clear();
    final double overloadThreshold = conf.getLoadBalancerBrokerOverloadedThresholdPercentage() / 100.0;
    final Map<String, Long> recentlyUnloadedBundles = loadData.getRecentlyUnloadedBundles();

    // Check every broker and select
    loadData.getBrokerData().forEach((broker, brokerData) -> {

        final LocalBrokerData localData = brokerData.getLocalData();
        final double currentUsage = localData.getMaxResourceUsage();
        if (currentUsage < overloadThreshold) {
            if (log.isDebugEnabled()) {
                log.debug("[{}] Broker is not overloaded, ignoring at this point", broker);
            }
            return;
        }

        // We want to offload enough traffic such that this broker will go below the overload threshold
        // Also, add a small margin so that this broker won't be very close to the threshold edge.
        double percentOfTrafficToOffload = currentUsage - overloadThreshold
                + ADDITIONAL_THRESHOLD_PERCENT_MARGIN;
        double brokerCurrentThroughput = localData.getMsgThroughputIn() + localData.getMsgThroughputOut();

        double minimumThroughputToOffload = brokerCurrentThroughput * percentOfTrafficToOffload;

        log.info(
                "Attempting to shed load on {}, which has max resource usage above threshold {}% > {}% -- Offloading at least {} MByte/s of traffic",
                broker, currentUsage, overloadThreshold, minimumThroughputToOffload / 1024 / 1024);

        MutableDouble trafficMarkedToOffload = new MutableDouble(0);
        MutableBoolean atLeastOneBundleSelected = new MutableBoolean(false);

        if (localData.getBundles().size() > 1) {
            // Sort bundles by throughput, then pick the biggest N which combined make up for at least the minimum throughput to offload

            loadData.getBundleData().entrySet().stream().map((e) -> {
                // Map to throughput value
                // Consider short-term byte rate to address system resource burden
                String bundle = e.getKey();
                BundleData bundleData = e.getValue();
                TimeAverageMessageData shortTermData = bundleData.getShortTermData();
                double throughput = shortTermData.getMsgThroughputIn() + shortTermData.getMsgThroughputOut();
                return Pair.of(bundle, throughput);
            }).filter(e -> {
                // Only consider bundles that were not already unloaded recently
                return !recentlyUnloadedBundles.containsKey(e.getLeft());
            }).sorted((e1, e2) -> {
                // Sort by throughput in reverse order
                return Double.compare(e2.getRight(), e1.getRight());
            }).forEach(e -> {
                if (trafficMarkedToOffload.doubleValue() < minimumThroughputToOffload
                        || atLeastOneBundleSelected.isFalse()) {
                    selectedBundlesCache.put(broker, e.getLeft());
                    trafficMarkedToOffload.add(e.getRight());
                    atLeastOneBundleSelected.setTrue();
                }
            });
        } else if (localData.getBundles().size() == 1) {
            log.warn(
                    "HIGH USAGE WARNING : Sole namespace bundle {} is overloading broker {}. "
                            + "No Load Shedding will be done on this broker",
                    localData.getBundles().iterator().next(), broker);
        } else {
            log.warn("Broker {} is overloaded despite having no bundles", broker);
        }

    });

    return selectedBundlesCache;
}

---

From source file:gsn.http.rest.AndroidPushDelivery.java

@Override
public boolean equals(Object o) {
    if (this == o)
        return true;
    if (o == null || getClass() != o.getClass())
        return false;
    AndroidPushDelivery that = (AndroidPushDelivery) o;
    if (Double.compare(that.notificationId, notificationId) != 0)
        return false;
    if (httpPost != null ? !httpPost.getURI().equals(that.httpPost.getURI()) : that.httpPost != null)
        return false;
    return true;/*from   w ww .  j a v a  2s  . c o  m*/
}

---

From source file:com.yahoo.egads.utilities.SpectralMethods.java

public static RealMatrix mFilter(RealMatrix data, int windowSize, FilteringMethod method,
        double methodParameter) {

    int n = data.getRowDimension();
    int m = data.getColumnDimension();
    int k = n - windowSize + 1;
    int i = 0, ind = 0;
    double[] temp;
    double sum = 0;

    RealMatrix hankelMat = SpectralMethods.createHankelMatrix(data, windowSize);
    SingularValueDecomposition svd = new SingularValueDecomposition(hankelMat);

    double[] singularValues = svd.getSingularValues();

    switch (method) {
    case VARIANCE:
        temp = new double[singularValues.length - 1];

        for (i = 1; i < singularValues.length; ++i) {
            sum += (singularValues[i] * singularValues[i]);
        }/*  ww  w .j a  v  a 2  s  .c o m*/

        for (i = 0; i < temp.length; ++i) {
            temp[i] = (singularValues[i + 1] * singularValues[i + 1]) / sum;
        }

        sum = 0;
        for (i = temp.length - 1; i >= 0; --i) {
            sum += temp[i];
            if (sum >= 1 - methodParameter) {
                ind = i;
                break;
            }
        }

        break;

    case EXPLICIT:
        ind = (int) Math.max(Math.min(methodParameter - 1, singularValues.length - 1), 0);
        break;

    case K_GAP:
        final double[] eigenGaps = new double[singularValues.length - 1];
        Integer[] index = new Integer[singularValues.length - 1];
        for (i = 0; i < eigenGaps.length; ++i) {
            eigenGaps[i] = singularValues[i] - singularValues[i + 1];
            index[i] = i;
        }

        Arrays.sort(index, new Comparator<Integer>() {
            @Override
            public int compare(Integer o1, Integer o2) {
                return Double.compare(eigenGaps[o1], eigenGaps[o2]);
            }
        });

        int maxIndex = 0;
        for (i = index.length - (int) methodParameter; i < index.length; ++i) {
            if (index[i] > maxIndex) {
                maxIndex = index[i];
            }
        }

        ind = Math.min(maxIndex, singularValues.length / 3);
        break;

    case SMOOTHNESS:
        double[] variances = new double[singularValues.length];

        for (i = 1; i < singularValues.length; ++i) {
            variances[i] = (singularValues[i] * singularValues[i]);
        }
        variances[0] = variances[1];

        double smoothness = SpectralMethods
                .computeSmoothness(Arrays.copyOfRange(variances, 1, variances.length));

        if (methodParameter - smoothness < 0.01) {
            methodParameter += 0.01;
        }

        double invalidS = smoothness;
        int validIndex = 1, invalidIndex = singularValues.length;

        while (true) {
            if (invalidS >= methodParameter) {
                ind = invalidIndex - 1;
                break;
            } else if (invalidIndex - validIndex <= 1) {
                ind = validIndex - 1;
                break;
            }

            int ii = (validIndex + invalidIndex) / 2;

            double[] tempVariances = Arrays.copyOf(Arrays.copyOfRange(variances, 0, ii + 1),
                    singularValues.length);
            double s = SpectralMethods.computeSmoothness(tempVariances);

            if (s >= methodParameter) {
                validIndex = ii;
            } else {
                invalidIndex = ii;
                invalidS = s;
            }
        }

        break;

    case EIGEN_RATIO:
        int startIndex = 0, endIndex = singularValues.length - 1;

        if (singularValues[endIndex] / singularValues[0] >= methodParameter) {
            ind = endIndex;
        } else {
            while (true) {
                int midIndex = (startIndex + endIndex) / 2;
                if (singularValues[midIndex] / singularValues[0] >= methodParameter) {
                    if (singularValues[midIndex + 1] / singularValues[0] < methodParameter) {
                        ind = midIndex;
                        break;
                    } else {
                        startIndex = midIndex;
                    }
                } else {
                    endIndex = midIndex;
                }
            }
        }

        break;

    case GAP_RATIO:
        double[] gaps = new double[singularValues.length - 1];
        for (i = 0; i < gaps.length; ++i) {
            gaps[i] = singularValues[i] - singularValues[i + 1];
        }

        ind = 0;
        for (i = gaps.length - 1; i >= 0; --i) {
            if (gaps[i] / singularValues[0] >= methodParameter) {
                ind = i;
                break;
            }
        }

        break;

    default:
        ind = singularValues.length - 1;
        break;
    }

    ind = Math.max(0, Math.min(ind, singularValues.length - 1));
    RealMatrix truncatedHankelMatrix = MatrixUtils.createRealMatrix(k, m * windowSize);
    RealMatrix mU = svd.getU();
    RealMatrix mVT = svd.getVT();

    for (i = 0; i <= ind; ++i) {
        truncatedHankelMatrix = truncatedHankelMatrix
                .add(mU.getColumnMatrix(i).multiply(mVT.getRowMatrix(i)).scalarMultiply(singularValues[i]));
    }

    return SpectralMethods.averageHankelMatrix(truncatedHankelMatrix, windowSize);
}

---

From source file:com.perl5.lang.perl.internals.PerlVersion.java

@Override
public int compareTo(@NotNull PerlVersion o) {
    return Double.compare(getDoubleVersion(), o.getDoubleVersion());
}

---

From source file:edu.txstate.dmlab.clusteringwiki.cluster.KMeansClusterer.java

/**
 * Cluster a set of documentsToCluster provided as an array of indexes within the
 * term document matrix/*from  ww w.  j a  va 2 s .  c o m*/
 * @param docs
 * @return
 */
public List<ICluster> levelCluster(ICluster parent, int[] docs) {
    if (docs == null) { //cluster all docs
        return levelCluster(parent);
    }
    documentsToCluster = docs;

    setNumClusters();
    //choose initial cluster seeds
    String parentId = parent.getId();
    List<IClusterDocument> seeds = chooseSeeds(parentId);
    //create clusters and assign initial centroids/seeds
    List<ICluster> clusters = new ArrayList<ICluster>();
    for (int i = 0; i < numClusters; i++) {
        KMeansCluster cluster = new KMeansCluster(getNextClusterId(), context, parent);
        clusters.add(cluster);
    }
    //initial cluster assignments
    int numDocs = docs.length;
    int bestCluster;
    int currentCluster;
    double similarity;
    double maxSimilarity;
    // For every document d, find the cluster j whose centroid is 
    // most similar, assign d to cluster j.
    for (int i = 0; i < numDocs; i++) {
        bestCluster = 0;
        maxSimilarity = Double.MIN_VALUE;
        IClusterDocument d = allDocs.get(docs[i]);
        for (int j = 0; j < numClusters; j++) {
            similarity = seeds.get(j).computeSimilarity(d);
            if (Double.compare(similarity, maxSimilarity) > 0) {
                bestCluster = j;
                maxSimilarity = similarity;
            }
        }
        for (ICluster cluster : clusters)
            cluster.removeDocument(docs[i]);
        clusters.get(bestCluster).addDocument(docs[i]);
    }

    // Repeat until termination conditions are satisfied
    int iteration = 0;
    for (;;) {
        // For every cluster, re-compute the centroid based on the
        // current member documentsToCluster.
        for (int j = 0; j < numClusters; j++) {
            ((KMeansCluster) clusters.get(j)).computeCentroid();
        }
        // For every document d, find the cluster i whose centroid is 
        // most similar, assign d to cluster i. (If a document is 
        // equally similar from all centroids, then just dump it into 
        // cluster 0).
        int numChanged = 0;
        for (int i = 0; i < numDocs; i++) {
            bestCluster = 0;
            currentCluster = -1;
            maxSimilarity = Double.MIN_VALUE;
            IClusterDocument d = allDocs.get(docs[i]);
            for (int j = 0; j < numClusters; j++) {
                similarity = ((KMeansCluster) clusters.get(j)).getSimilarity(d);
                if (Double.compare(similarity, maxSimilarity) > 0) {
                    bestCluster = j;
                    maxSimilarity = similarity;
                }
                if (clusters.get(j).contains(docs[i]))
                    currentCluster = j;
            }
            //if another cluster is better
            if (bestCluster != currentCluster) {
                clusters.get(currentCluster).removeDocument(docs[i]);
                clusters.get(bestCluster).addDocument(docs[i]);
                numChanged++;
            }
        }
        iteration++;
        if (iteration > maxIterations || numChanged == 0)
            break;
    }

    //set cluster labels
    for (int j = 0; j < numClusters; j++) {
        ICluster c = clusters.get(j);
        c.deduceLabel();
        if (c.getLabel().equals("") && c.getDocuments() == null) {
            //if empty cluster, trim
            clusters.remove(j);
            j--;
            numClusters--;
        }
    }

    return clusters;

}

---

From source file:org.noise_planet.noisecapture.MeasurementService.java

/**
 * @param dBGain Gain in dB//from w w w  .ja  v a  2s.  com
 */
public void setdBGain(double dBGain) {
    this.dBGain = dBGain;
    if (audioProcess != null && Double.compare(0, dBGain) != 0) {
        audioProcess.setGain((float) Math.pow(10, dBGain / 20));
    }
}

---

From source file:com.opengamma.analytics.financial.equity.option.EquityOption.java

@Override
public boolean equals(final Object obj) {
    if (this == obj) {
        return true;
    }/*from   ww  w.  j a  va2  s.c  o m*/
    if (!(obj instanceof EquityOption)) {
        return false;
    }
    final EquityOption other = (EquityOption) obj;
    if (Double.compare(_strike, other._strike) != 0) {
        return false;
    }
    if (Double.compare(_timeToExpiry, other._timeToExpiry) != 0) {
        return false;
    }
    if (_isCall != other._isCall) {
        return false;
    }
    if (_exerciseType != other._exerciseType) {
        return false;
    }
    if (_settlementType != other._settlementType) {
        return false;
    }
    if (Double.compare(_timeToSettlement, other._timeToSettlement) != 0) {
        return false;
    }
    if (Double.compare(_unitAmount, other._unitAmount) != 0) {
        return false;
    }
    if (!ObjectUtils.equals(_currency, other._currency)) {
        return false;
    }
    return true;
}

---

From source file:com.mesosphere.dcos.cassandra.common.config.ClusterTaskConfig.java

@Override
public boolean equals(Object o) {
    if (this == o)
        return true;
    if (o == null || getClass() != o.getClass())
        return false;

    ClusterTaskConfig that = (ClusterTaskConfig) o;

    if (Double.compare(that.cpus, cpus) != 0)
        return false;
    if (memoryMb != that.memoryMb)
        return false;
    return diskMb == that.diskMb;

}

---

From source file:com.opengamma.analytics.financial.equity.option.EquityIndexOption.java

@Override
public boolean equals(final Object obj) {
    if (this == obj) {
        return true;
    }/*www  .java 2  s  .c  o m*/
    if (!(obj instanceof EquityIndexOption)) {
        return false;
    }
    final EquityIndexOption other = (EquityIndexOption) obj;
    if (Double.compare(_strike, other._strike) != 0) {
        return false;
    }
    if (Double.compare(_timeToExpiry, other._timeToExpiry) != 0) {
        return false;
    }
    if (_isCall != other._isCall) {
        return false;
    }
    if (_exerciseType != other._exerciseType) {
        return false;
    }
    if (_settlementType != other._settlementType) {
        return false;
    }
    if (Double.compare(_timeToSettlement, other._timeToSettlement) != 0) {
        return false;
    }
    if (Double.compare(_unitAmount, other._unitAmount) != 0) {
        return false;
    }
    if (!ObjectUtils.equals(_currency, other._currency)) {
        return false;
    }
    return true;
}

---

From source file:r.lang.DoubleVector.java

@Override
public int compare(int index1, int index2) {
    return Double.compare(values[index1], values[index2]);
}

---

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