Example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getN

List of usage examples for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getN

  1. HOME
  2. Java
  3. org.apache.commons
  4. org.apache.commons.math3.stat.descriptive.*
  5. DescriptiveStatistics
  6. getN

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getN.

Prototype

public long getN()

Source Link

Document

Returns the number of available values

Usage

From source file:org.onosproject.store.cluster.impl.PhiAccrualFailureDetector.java

/**
 * Compute phi for the specified node id.
 * @param nodeId node id//from   ww w.j a va  2s  . c  om
 * @return phi value
 */
public double phi(NodeId nodeId) {
    checkNotNull(nodeId, "NodeId must not be null");
    if (!states.containsKey(nodeId)) {
        return BOOTSTRAP_PHI_VALUE;
    }
    History nodeState = states.get(nodeId);
    synchronized (nodeState) {
        long latestHeartbeat = nodeState.latestHeartbeatTime();
        DescriptiveStatistics samples = nodeState.samples();
        if (latestHeartbeat == -1 || samples.getN() < MIN_SAMPLES) {
            return 0.0;
        }
        return computePhi(samples, latestHeartbeat, System.currentTimeMillis());
    }
}

From source file:org.onosproject.store.cluster.impl.PhiAccrualFailureDetector.java

private double computePhi(DescriptiveStatistics samples, long tLast, long tNow) {
    long size = samples.getN();
    long t = tNow - tLast;
    return (size > 0) ? PHI_FACTOR * t / samples.getMean() : BOOTSTRAP_PHI_VALUE;
}

From source file:org.wildfly.swarm.proc.CSVCollector.java

public void onFinish(String id) {

    List<Object> record = new ArrayList<>();
    record.add(id);// w w w.  j a  v  a2 s  .c o m
    record.add(Paths.get(id).getFileName());
    for (Measure m : Measure.values()) {
        if (!results.containsKey(m)) {
            throw new RuntimeException("Measurement is missing " + m);
        }

        DescriptiveStatistics stats = results.get(m);
        record.add(stats.getN());
        record.add(stats.getMin());
        record.add(stats.getMax());
        record.add(stats.getMean());
        record.add(stats.getStandardDeviation());
        record.add(stats.getPercentile(50));
        record.add(stats.getPercentile(75));
    }

    try {
        csvOutput.printRecord(record);
        csvOutput.flush();
    } catch (IOException e) {
        throw new RuntimeException("Failed to write data", e);
    }
}

From source file:org.wildfly.swarm.proc.SystemOutCollector.java

public void onFinish(String id) {
    System.out.println("Results for " + id);
    for (Measure m : results.keySet()) {
        DescriptiveStatistics stats = results.get(m);
        System.out.println(m.name() + " Samples: " + stats.getN());
        System.out.println(m.name() + " min: " + stats.getMin());
        System.out.println(m.name() + " max: " + stats.getMax());
        System.out.println(m.name() + " 75p: " + stats.getPercentile(75));
    }//  ww w . j  a va 2 s  .  co m

}

From source file:org.wso2.carbon.ml.database.internal.MLDatabaseService.java

/**
 * Create the JSON string with summary statistics for a column.
 *
 * @param type Data-type of the column/*from  w w  w  .j  a  v  a 2 s.c  om*/
 * @param graphFrequencies Bin frequencies of the column
 * @param missing Number of missing values in the column
 * @param unique Number of unique values in the column
 * @param descriptiveStats DescriptiveStats object of the column
 * @return JSON representation of the summary statistics of the column
 */
private JSONArray createJson(String type, SortedMap<?, Integer> graphFrequencies, int missing, int unique,
        DescriptiveStatistics descriptiveStats) throws JSONException {

    JSONObject json = new JSONObject();
    JSONArray freqs = new JSONArray();
    Object[] categoryNames = graphFrequencies.keySet().toArray();
    // Create an array with intervals/categories and their frequencies.
    for (int i = 0; i < graphFrequencies.size(); i++) {
        JSONArray temp = new JSONArray();
        temp.put(categoryNames[i].toString());
        temp.put(graphFrequencies.get(categoryNames[i]));
        freqs.put(temp);
    }
    // Put the statistics to a json object
    json.put("unique", unique);
    json.put("missing", missing);

    DecimalFormat decimalFormat = new DecimalFormat("#.###");
    if (descriptiveStats.getN() != 0) {
        json.put("mean", decimalFormat.format(descriptiveStats.getMean()));
        json.put("min", decimalFormat.format(descriptiveStats.getMin()));
        json.put("max", decimalFormat.format(descriptiveStats.getMax()));
        json.put("median", decimalFormat.format(descriptiveStats.getPercentile(50)));
        json.put("std", decimalFormat.format(descriptiveStats.getStandardDeviation()));
        if (type.equalsIgnoreCase(FeatureType.NUMERICAL)) {
            json.put("skewness", decimalFormat.format(descriptiveStats.getSkewness()));
        }
    }
    json.put("values", freqs);
    json.put("bar", true);
    json.put("key", "Frequency");
    JSONArray summaryStatArray = new JSONArray();
    summaryStatArray.put(json);
    return summaryStatArray;
}

From source file:org.wso2.carbon.ml.dataset.internal.DatabaseHandler.java

/**
 * Create the JSON string with summary statistics for a column.
 *
 * @param type              Data-type of the column
 * @param graphFrequencies  Bin frequencies of the column
 * @param missing           Number of missing values in the column
 * @param unique            Number of unique values in the column
 * @param descriptiveStats  DescriptiveStats object of the column
 * @return                  JSON representation of the summary statistics of the column
 *//*from w  w  w  . j  av a  2  s . c om*/
private JSONArray createJson(String type, SortedMap<?, Integer> graphFrequencies, int missing, int unique,
        DescriptiveStatistics descriptiveStats) {
    JSONObject json = new JSONObject();
    JSONArray freqs = new JSONArray();
    Object[] categoryNames = graphFrequencies.keySet().toArray();
    // Create an array with intervals/categories and their frequencies.
    for (int i = 0; i < graphFrequencies.size(); i++) {
        JSONArray temp = new JSONArray();
        temp.put(categoryNames[i].toString());
        temp.put(graphFrequencies.get(categoryNames[i]));
        freqs.put(temp);
    }
    // Put the statistics to a json object
    json.put("unique", unique);
    json.put("missing", missing);

    DecimalFormat decimalFormat = new DecimalFormat("#.###");
    if (descriptiveStats.getN() != 0) {
        json.put("mean", decimalFormat.format(descriptiveStats.getMean()));
        json.put("median", decimalFormat.format(descriptiveStats.getPercentile(50)));
        json.put("std", decimalFormat.format(descriptiveStats.getStandardDeviation()));
        if (type.equalsIgnoreCase(FeatureType.NUMERICAL)) {
            json.put("skewness", decimalFormat.format(descriptiveStats.getSkewness()));
        }
    }
    json.put("values", freqs);
    json.put("bar", true);
    json.put("key", "Frequency");
    JSONArray summaryStatArray = new JSONArray();
    summaryStatArray.put(json);
    return summaryStatArray;
}

From source file:performancestatisticsasset.DistributionSet.java

public void setDistributionSet(String targetGroup, String targetTask, String targetMeasure,
        RecordList dataSet) {//from  w  ww .  j  a  v  a2 s .c  om
    //Determine the number of trials selected by group and by task
    int trials = 0;
    int len = dataSet.records.size();
    for (int i = 0; i < len; i++) {
        if (dataSet.records.get(i).getTrialNumber() > trials)
            trials = dataSet.records.get(i).getTrialNumber();
    }

    Distribution tempDist;
    DescriptiveStatistics tempStat;
    //For each trial of the set do
    for (int i = 0; i < trials; i++) {
        tempDist = new Distribution();
        tempStat = new DescriptiveStatistics();
        //Select data
        for (int j = 0; j < len; j++) {
            //If the current record is of the correct trial
            if ((dataSet.records.get(j).getTrialNumber() == i + 1)
                    && (targetGroup.equals(dataSet.records.get(j).getGroupID()))
                    && (targetTask.equals(dataSet.records.get(j).getTaskID()))) {
                //Fill distribution
                switch (targetMeasure) {
                case "time":
                    tempStat.addValue(dataSet.records.get(j).getTimeToComplete());
                    break;
                case "perf":
                    tempStat.addValue(dataSet.records.get(j).getPerformance());
                    break;
                }
            }
        }
        //Transfer the computed statistics to tempDist
        tempDist.max = tempStat.getMax();
        tempDist.min = tempStat.getMin();
        tempDist.sum = tempStat.getSum();
        tempDist.variance = tempStat.getVariance();
        tempDist.mean = tempStat.getMean();
        tempDist.stdDev = tempStat.getStandardDeviation();
        tempDist.skewness = tempStat.getSkewness();
        tempDist.kurtosis = tempStat.getKurtosis();
        tempDist.n = tempStat.getN();

        //Add tempDist to distributionSet
        distributionSet.add(tempDist);
    }
}

From source file:performancestatisticsasset.DistributionSet.java

public void setDistributionSet(String targetTask, String targetMeasure, RecordList dataSet) {
    //Determine the number of trials selected by task
    int trials = 0;
    int len = dataSet.records.size();
    for (int i = 0; i < len; i++) {
        if (dataSet.records.get(i).getTrialNumber() > trials)
            trials = dataSet.records.get(i).getTrialNumber();
    }//  ww  w  .  j a  v a 2  s . co  m

    Distribution tempDist;
    DescriptiveStatistics tempStat;
    //For each trial of the set do
    for (int i = 0; i < trials; i++) {
        tempDist = new Distribution();
        tempStat = new DescriptiveStatistics();
        //Select data
        for (int j = 0; j < len; j++) {
            //If the current record is of the correct trial
            if ((dataSet.records.get(j).getTrialNumber() == i + 1)
                    && (targetTask.equals(dataSet.records.get(j).getTaskID()))) {
                //Fill distribution
                switch (targetMeasure) {
                case "time":
                    tempStat.addValue(dataSet.records.get(j).getTimeToComplete());
                    break;
                case "perf":
                    tempStat.addValue(dataSet.records.get(j).getPerformance());
                    break;
                }
            }
        }
        //Transfer the computed statistics to tempDist
        tempDist.max = tempStat.getMax();
        tempDist.min = tempStat.getMin();
        tempDist.sum = tempStat.getSum();
        tempDist.variance = tempStat.getVariance();
        tempDist.mean = tempStat.getMean();
        tempDist.stdDev = tempStat.getStandardDeviation();
        tempDist.skewness = tempStat.getSkewness();
        tempDist.kurtosis = tempStat.getKurtosis();
        tempDist.n = tempStat.getN();

        //Add tempDist to distributionSet
        distributionSet.add(tempDist);
    }
}

From source file:sandbox.sfwatergit.peerinfluence.io.TXTWriter.java

public static void writeStatistics(TDoubleObjectHashMap<DescriptiveStatistics> statsMap, String xLab,
        String file) throws IOException {
    double[] keys = statsMap.keys();
    Arrays.sort(keys);/* w w  w.j a v  a 2 s .c  o m*/

    BufferedWriter writer = new BufferedWriter(new FileWriter(file));

    writer.write(xLab);
    writer.write(TAB);
    writer.write("mean");
    writer.write(TAB);
    writer.write("median");
    writer.write(TAB);
    writer.write("min");
    writer.write(TAB);
    writer.write("max");
    writer.write(TAB);
    writer.write("n");
    writer.newLine();

    for (double key : keys) {
        DescriptiveStatistics stats = statsMap.get(key);

        writer.write(String.valueOf(key));
        writer.write(TAB);
        writer.write(String.valueOf(stats.getMean()));
        writer.write(TAB);
        writer.write(String.valueOf(stats.getPercentile(50)));
        writer.write(TAB);
        writer.write(String.valueOf(stats.getMin()));
        writer.write(TAB);
        writer.write(String.valueOf(stats.getMax()));
        writer.write(TAB);
        writer.write(String.valueOf(stats.getN()));
        writer.newLine();
    }

    writer.close();
}

From source file:tools.descartes.bungee.viewer.RunResultView.java

private void update() {
    if (runResult != null) {
        sanityCheckValue.setSelection(runResult.passedSanityCheck());
        scheduleCheckValue.setSelection(runResult.passedScheduleCheck());
        completedCheckValue.setSelection(runResult.isRunCompleted());
        successCheckValue.setSelection(runResult.isRunSuccessful());

        DescriptiveStatistics timingStats = runResult.getTimingStats();
        if (timingStats.getN() > 0) {
            timingMeanValue.setText(String.format("%.3f", timingStats.getMean()));
            timingStdValue.setText(String.format("%.3f", timingStats.getStandardDeviation()));
        } else {/*from w  ww . j  a  v  a  2  s  .  co m*/
            timingMeanValue.setText("-");
            timingStdValue.setText("-");
        }

        DescriptiveStatistics responseStats = runResult.getResponseTimeStats();
        if (responseStats.getN() > 0) {
            responseTimeMeanValue.setText(String.format("%.3f", responseStats.getMean()));
            responseTimeStdValue.setText(String.format("%.3f", responseStats.getStandardDeviation()));
        } else {
            responseTimeMeanValue.setText("-");
            responseTimeStdValue.setText("-");
        }
    }
}