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

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

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Introduction

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

Prototype

public double getMean()

Source Link

Document

Returns the <a href="http://www.xycoon.com/arithmetic_mean.htm"> arithmetic mean </a> of the available values

Usage

From source file:org.wattdepot.server.http.api.DepositoryAverageValuesServer.java

/**
 * retrieve the depository measurement list for a sensor.
 * //from ww  w  .j a v a 2s .  com
 * @return measurement list.
 */
public InterpolatedValueList doRetrieve() {
    getLogger().log(Level.INFO,
            "GET /wattdepot/{" + orgId + "}/" + Labels.DEPOSITORY + "/{" + depositoryId + "}/" + Labels.VALUES
                    + "/" + Labels.AVERAGE + "/?" + Labels.SENSOR + "={" + sensorId + "}&" + Labels.START + "={"
                    + start + "}&" + Labels.END + "={" + end + "}&" + Labels.INTERVAL + "={" + interval + "}&"
                    + Labels.VALUE_TYPE + "={" + dataType + "}");
    if (isInRole(orgId)) {
        if (start != null && end != null && interval != null) {
            InterpolatedValueList ret = new InterpolatedValueList();
            try {
                Depository depository = depot.getDepository(depositoryId, orgId, true);
                XMLGregorianCalendar startRange = DateConvert.parseCalString(start);
                XMLGregorianCalendar endRange = DateConvert.parseCalString(end);
                int intervalMinutes = Integer.parseInt(interval);
                List<XMLGregorianCalendar> rangeList = Tstamp.getTimestampList(startRange, endRange,
                        intervalMinutes);
                if (rangeList != null) {
                    for (int i = 1; i < rangeList.size(); i++) {
                        Date valueDate = DateConvert.convertXMLCal(rangeList.get(i));
                        XMLGregorianCalendar startInterval = rangeList.get(i - 1);
                        XMLGregorianCalendar endInterval = rangeList.get(i);
                        List<XMLGregorianCalendar> intervalList = Tstamp.getNTimestampList(24, startInterval,
                                endInterval);
                        DescriptiveStatistics stats = new DescriptiveStatistics();
                        Date previous = null;
                        for (int j = 0; j < intervalList.size(); j++) {
                            Date timestamp = DateConvert.convertXMLCal(intervalList.get(j));
                            Double value = null;
                            if ("point".equals(dataType)) {
                                value = getValue(depositoryId, orgId, sensorId, timestamp);
                            } else {
                                if (previous != null) {
                                    value = getValue(depositoryId, orgId, sensorId, previous, timestamp);
                                }
                                previous = timestamp;
                            }
                            if (value != null) {
                                stats.addValue(value);
                            }
                        }

                        if (!Double.isNaN(stats.getMean())) {
                            ret.getInterpolatedValues().add(new InterpolatedValue(sensorId, stats.getMean(),
                                    depository.getMeasurementType(), valueDate));
                        }
                    }
                }
            } catch (IdNotFoundException e) {
                // TODO Auto-generated catch block
                e.printStackTrace();
            } catch (ParseException e) {
                // TODO Auto-generated catch block
                e.printStackTrace();
            } catch (DatatypeConfigurationException e) {
                // TODO Auto-generated catch block
                e.printStackTrace();
            }
            return ret;
        } else {
            setStatus(Status.CLIENT_ERROR_BAD_REQUEST, "Missing start and/or end times or interval.");
            return null;
        }
    } else {
        setStatus(Status.CLIENT_ERROR_BAD_REQUEST, "Bad credentials.");
        return null;
    }
}

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

public void onFinish(String id) {

    List<Object> record = new ArrayList<>();
    record.add(id);/* w ww. jav  a  2  s .  c  om*/
    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.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 www .  ja  va 2  s .  c o  m*/
 * @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
 *//*w  w  w.ja va  2s  .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:org.wso2.extension.siddhi.execution.var.backtest.Backtest.java

private void runStandardCoverageTest() {

    int numberOfExceptions = 0;

    for (int i = 0; i < VAR_PER_SAMPLE; i++) {
        if (actualVarList.get(i) <= calculatedVarList.get(i)) {
            numberOfExceptions++;//from   www.  ja  v a  2  s.c o  m
            meanViolations.add(actualVarList.get(i) - calculatedVarList.get(i));
        }
    }

    DescriptiveStatistics dsLoss = new DescriptiveStatistics(
            actualVarList.stream().mapToDouble(Double::doubleValue).toArray());
    DescriptiveStatistics dsVaR = new DescriptiveStatistics(
            calculatedVarList.stream().mapToDouble(Double::doubleValue).toArray());
    DescriptiveStatistics dsMV = new DescriptiveStatistics(
            meanViolations.stream().mapToDouble(Double::doubleValue).toArray());

    System.out.println("Loss mean : " + dsLoss.getMean());
    System.out.println("VaR mean  : " + dsVaR.getMean());
    System.out.println("No. of violations : " + numberOfExceptions);
    System.out.println("Violation mean  : " + dsMV.getMean());
    System.out.println("Violation Rate : " + (((double) numberOfExceptions) / (VAR_PER_SAMPLE)) * 100 + "%");
}

From source file:org.wso2.extension.siddhi.execution.var.backtest.BacktestIncremental.java

public void runTest() throws FileNotFoundException {

    Formatter formatter = new Formatter(new File("MonteCarloBacktestResults.csv"));
    formatter.format("%s%n", "date,varclose,varavg,varmax,corrloss,varmedian,varmode,lossclose,lossavg,lossmax,"
            + "corrvar,lossmedian,lossmode");
    String[] dates = { "jan-23", "jan-24", "jan-25", "jan-26", "jan-27", "jan-30", "jan-31", "feb-1", "feb-2",
            "feb-3" };
    String write = "%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s";
    //        VaRCalculator varCalculator = new HistoricalVaRCalculator(BATCH_SIZE, VAR_CI);
    VaRCalculator varCalculator = new ParametricVaRCalculator(BATCH_SIZE, VAR_CI);
    //        VaRCalculator varCalculator = new MonteCarloVarCalculator(BATCH_SIZE, VAR_CI, 2500, 100, 0.01);

    Map<String, Integer> assets = initPortfolio();
    Portfolio portfolio = varCalculator.createPortfolio("1", assets);
    varCalculator.addPortfolio("1", portfolio);

    for (int d = START_DATE; d <= END_DATE; d++) {
        System.out.println("\nDAY : " + dates[d - START_DATE] + "\n");
        ArrayList<Event> list = readBacktestData(d);
        HashMap<Integer, Double> varMap = new HashMap();
        HashMap<Integer, Double> lossMap = new HashMap();
        double var = 0;
        double loss = 0;
        String corrVar;/*from w  w  w .  j  a  v  a2 s  .co m*/
        String corrLoss;

        int counter = 0;
        for (int i = 0; i < list.size(); i++) {

            //System.out.print("Event " + (i + 1) + " : ");
            String jsonString = (String) varCalculator.calculateValueAtRisk(list.get(i));
            currentPortfolioValue = portfolio.getTotalPortfolioValue();

            if (jsonString != null) {

                JSONObject jsonObject = new JSONObject(jsonString);
                double tempVar = (Double) jsonObject.get(PORTFOLIO_KEY); // hardcoded for portfolio ID 1
                if (tempVar < 0) {
                    var = tempVar;
                    varMap.put(counter, var);
                    //System.out.printf("Var : %.4f", tempVar);
                }

                double tempLoss = currentPortfolioValue - previousPortfolioValue;
                if (tempLoss < 0) {
                    loss = tempLoss;
                    lossMap.put(counter, loss);
                    //System.out.printf(" Loss : %.4f", tempLoss);
                }
                counter++;
            }

            previousPortfolioValue = currentPortfolioValue;
            //System.out.println();
        }

        double[] vars = Stream.of(varMap.values().toArray(new Double[varMap.size()]))
                .mapToDouble(Double::doubleValue).toArray();
        DescriptiveStatistics statVar = new DescriptiveStatistics(vars);

        double[] losses = Stream.of(lossMap.values().toArray(new Double[lossMap.size()]))
                .mapToDouble(Double::doubleValue).toArray();
        DescriptiveStatistics statLoss = new DescriptiveStatistics(losses);

        System.out.println("Daily VaR CLOSE  : " + var);
        System.out.println("Daily VaR AVG    : " + statVar.getMean());

        Double min = statVar.getMin();
        System.out.println("Daily VaR MAX    : " + min);

        Integer minIndex = null;
        for (Map.Entry<Integer, Double> e : varMap.entrySet()) {
            if (e.getValue().equals(min)) {
                minIndex = e.getKey();
            }
        }

        if (lossMap.get(minIndex) == null) {
            corrLoss = "NO LOSS";
        } else {
            corrLoss = lossMap.get(minIndex).toString();
        }

        System.out.println("Crspng Loss      : " + corrLoss);
        System.out.println("Daily VaR MEDIAN : " + statVar.getPercentile(50));
        System.out.println("Daily VaR MODE   : " + mode(statVar.getValues()));

        System.out.println();

        System.out.println("Daily Loss CLOSE   : " + loss);
        System.out.println("Daily Loss AVG     : " + statLoss.getMean());

        min = statLoss.getMin();
        System.out.println("Daily Loss MAX     : " + min);

        for (Map.Entry<Integer, Double> e : lossMap.entrySet()) {
            if (e.getValue().equals(min)) {
                minIndex = e.getKey();
            }
        }

        if (varMap.get(minIndex) == null) {
            corrVar = "NO VAR";
        } else {
            corrVar = varMap.get(minIndex).toString();
        }

        System.out.println("Crspng VaR         : " + corrVar);
        System.out.println("Daily Loss MEDIAN  : " + statLoss.getPercentile(50));
        System.out.println("Daily Loss MODE    : " + mode(statLoss.getValues()));

        formatter.format("%s%n",
                String.format(write, dates[d - START_DATE], var, statVar.getMean(), statVar.getMin(), corrLoss,
                        statVar.getPercentile(50), mode(statVar.getValues()), loss, statLoss.getMean(),
                        statLoss.getMin(), corrVar, statLoss.getPercentile(50), mode(statLoss.getValues())));

    }

    formatter.close();
}

From source file:org.wso2.extension.siddhi.execution.var.backtest.BacktestIncrementalTest.java

private void runViolationTest() {
    Formatter formatter = null;//from   w ww.  j a v a  2  s .  c  o  m
    try {
        formatter = new Formatter(new File(METHOD + "-" + DATA_SET + "-" + VAR_CI + ".csv"));
        formatter.format("%s,%s%n", "VaR", "Loss");
    } catch (FileNotFoundException e) {
        e.printStackTrace();
    }
    DescriptiveStatistics lossStat = new DescriptiveStatistics(
            lossList.stream().mapToDouble(Double::doubleValue).toArray());
    DescriptiveStatistics varStat = new DescriptiveStatistics(
            varList.stream().mapToDouble(Double::doubleValue).toArray());
    DescriptiveStatistics violationStat = new DescriptiveStatistics();
    int failCount = 0;
    int numberOfData = varList.size();
    for (int i = 0; i < numberOfData - 1; i++) {
        formatter.format("%.3f,%.3f%n", varList.get(i), lossList.get(i + 1));
        if (lossList.get(i + 1) < varList.get(i)) {
            violationStat.addValue(varList.get(i));
            failCount++;
        }
    }
    formatter.close();
    System.out.println("Number of data : " + numberOfData);
    System.out.printf("Loss Mean : %.2f\n", lossStat.getMean());
    System.out.printf("Var Mean : %.2f\n", varStat.getMean());
    System.out.printf("Number of violations : %d\n", failCount);
    System.out.printf("Mean Violation : %.2f\n", violationStat.getMean());
    System.out.printf("Violation Rate : %.2f%%\n", ((double) failCount) / (numberOfData - 1) * 100);
}

From source file:performancestatisticsasset.DistributionSet.java

public void setDistributionSet(String targetGroup, String targetTask, String targetMeasure,
        RecordList dataSet) {/*from  www. j a v a 2s.c o  m*/
    //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();
    }//from  w ww . j a  va 2  s . c  o 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:Pooling.collectStatsTime.java

public static void main(String[] args) throws IOException {
    /*         int maxN = 1000;
             double[] prob = {0.25,0.5,0.75,1.00};
             int[] maxPoolSize = {35};//from ww  w  .ja  va  2  s.co  m
             int nTests = 50;
                     
             String folder = "randGraphsSimRes";
             for (int t = 0; t < maxPoolSize.length; t++)
             {
     FileWriter fw = new FileWriter(folder + File.separator + "statsDesignTime" + maxPoolSize[t] + ".txt");
     for (int n = 10; n <= maxN; n+=10)
     {
         DescriptiveStatistics stats = new DescriptiveStatistics();
         for (int i = 1; i <= nTests; i++)
         {
             String resfile = "testResults_" + n + "_" + maxPoolSize[t] + "_" + i + ".txt";
             BufferedReader br = new BufferedReader(new FileReader(folder + File.separator + resfile));
             System.out.println(resfile);
             String s = br.readLine();
             StringTokenizer st = new StringTokenizer(s," ");
             st.nextToken();
             int k = Integer.parseInt(st.nextToken());
             stats.addValue(((double)k)/1000);
         }
         fw.write(n + " " + stats.getMean() + " " + (stats.getStandardDeviation()/Math.sqrt(nTests)) +  "\n");
     }
     fw.close();
             } */

    int[] ns = { 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150 };
    int[] maxPoolSizes = { 15, 25, 35 };
    int nTests = 10;
    for (int sz = 0; sz < maxPoolSizes.length; sz++) {
        FileWriter fw = new FileWriter("statisticsTime_" + maxPoolSizes[sz] + ".txt");
        for (int in = 0; in < ns.length; in++) {
            DescriptiveStatistics stats = new DescriptiveStatistics();
            for (int it = 0; it < nTests; it++) {
                String outdir = "Test_" + maxPoolSizes[sz] + "_" + ns[in] + "_" + it;
                String repFile = outdir + File.separator + "report.txt";
                System.out.println(outdir);
                BufferedReader br = new BufferedReader(new FileReader(repFile));
                String s = "";
                for (int i = 0; i < 6; i++)
                    s = br.readLine();
                StringTokenizer st = new StringTokenizer(s, ":");
                st.nextToken();
                double tm = Double.parseDouble(st.nextToken());
                stats.addValue(tm);
            }
            double maxtime = stats.getMax();
            DescriptiveStatistics stats1 = new DescriptiveStatistics();
            for (int i = 0; i < nTests; i++)
                if (stats.getElement(i) != maxtime)
                    stats1.addValue(stats.getElement(i));
            fw.write(ns[in] + " " + stats1.getMean() + " "
                    + (stats1.getStandardDeviation() / Math.sqrt((nTests - 1))) + "\n");
        }
        fw.close();
    }
}