Example usage for org.apache.commons.math3.stat.descriptive SummaryStatistics addValue

Introduction

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

Prototype

public void addValue(double value)

Source Link

Document

Add a value to the data

Usage

From source file:edu.uiowa.icts.bluebutton.json.view.StatsFinder.java

private SummaryStatistics findStats() {
    SummaryStatistics stats = new SummaryStatistics();
    stats.setVarianceImpl(new Variance(false));
    for (IGetStats d : this.list) {
        if (d.getDoubleValue() != null) {
            stats.addValue(d.getDoubleValue());
        }//from  w  w  w.ja  va2  s  .c  o m
    }
    return stats;
}

From source file:net.sourceforge.jabm.report.SummaryStatisticsReportVariables.java

@Override
public void compute(SimEvent event) {
    super.compute(event);
    reportVariables.compute(event);//  ww w.j a  va 2s. c  om
    Map<Object, Number> bindings = reportVariables.getVariableBindings();
    for (Object variable : bindings.keySet()) {
        SummaryStatistics stats = summaryVariableBindings.get(variable);
        if (stats == null) {
            stats = new SummaryStatistics();
            summaryVariableBindings.put(variable, stats);
        }
        stats.addValue(bindings.get(variable).doubleValue());
    }
}

From source file:net.recommenders.rival.evaluation.statistics.ConfidenceInterval.java

/**
 * Method that takes only one metric as parameter. It is useful when
 * comparing more than two metrics (so that a confidence interval is
 * computed for each of them), as suggested in [Sakai, 2014]
 *
 * @param alpha probability of incorrectly rejecting the null hypothesis (1
 * - confidence_level)/*from  w ww.  j a  v a2  s .c  om*/
 * @param metricValuesPerDimension one value of the metric for each
 * dimension
 * @return array with the confidence interval: [mean - margin of error, mean
 * + margin of error]
 */
public double[] getConfidenceInterval(final double alpha, final Map<?, Double> metricValuesPerDimension) {
    SummaryStatistics differences = new SummaryStatistics();
    for (Double d : metricValuesPerDimension.values()) {
        differences.addValue(d);
    }
    return getConfidenceInterval(alpha, (int) differences.getN() - 1, (int) differences.getN(),
            differences.getStandardDeviation(), differences.getMean());
}

From source file:ijfx.core.stats.DefaultIjfxStatisticService.java

@Override
public SummaryStatistics getDatasetStatistics(Dataset dataset) {
    SummaryStatistics summary = new SummaryStatistics();
    Cursor<RealType<?>> cursor = dataset.cursor();
    cursor.reset();/*from   w w w .  j av  a 2s.  c om*/

    while (cursor.hasNext()) {
        cursor.fwd();
        double value = cursor.get().getRealDouble();
        summary.addValue(value);

    }
    return summary;
}

From source file:model.scenario.SimpleBuyerScenarioTest.java

@Test
public void rightPriceAndQuantityTestWithCascadeControllerFixed4Buyers() {
    for (int i = 0; i < 20; i++) {
        //to sell 4 you need to price them between 60 and 51 everytime
        final MacroII macroII = new MacroII(System.currentTimeMillis());
        SimpleBuyerScenario scenario = new SimpleBuyerScenario(macroII);
        scenario.setControllerType(CascadePIDController.class);
        scenario.setTargetInventory(20);
        scenario.setConsumptionRate(4);/*from  ww w.  j  a  v a  2  s .c o m*/
        scenario.setNumberOfBuyers(4);
        scenario.setNumberOfSuppliers(50);
        scenario.setSupplyIntercept(0);
        scenario.setSupplySlope(1);

        //4 buyers, buying 4 each, should be 16 units in total

        macroII.setScenario(scenario);
        macroII.start();
        for (PurchasesDepartment department : scenario.getDepartments())
            department.setTradePriority(Priority.BEFORE_STANDARD);

        while (macroII.schedule.getTime() < 3500) {
            System.out.println("--------------------------------");
            macroII.schedule.step(macroII);

            for (PurchasesDepartment department : scenario.getDepartments())
                System.out.println("inflow: " + department.getTodayInflow() + ", price: "
                        + department.getLastOfferedPrice() + ", averaged: "
                        + department.getAveragedClosingPrice());

        }

        SummaryStatistics averagePrice = new SummaryStatistics();
        for (int j = 0; j < 1000; j++) {
            macroII.schedule.step(macroII);
            averagePrice.addValue(macroII.getMarket(UndifferentiatedGoodType.GENERIC).getLastPrice());
        }
        //price should be any between 60 and 51
        assertEquals(16, averagePrice.getMean(), .5d);
        assertEquals(macroII.getMarket(UndifferentiatedGoodType.GENERIC).getYesterdayVolume(), 16, 1d); //every day 4 goods should have been traded

    }

}

From source file:com.isentropy.accumulo.iterators.RowStatsTransformingIterator.java

@Override
protected void transformRange(SortedKeyValueIterator<Key, Value> input, KVBuffer output) throws IOException {
    SummaryStatistics stats = new SummaryStatistics();
    Key k = null;//  www . j  a  va  2  s .  c o  m
    while (input.hasTop()) {
        k = input.getTopKey();
        Value v = input.getTopValue();
        Object vo = value_input_serde.deserialize(v.get());
        if (vo instanceof Number) {
            stats.addValue(((Number) vo).doubleValue());
        }
        input.next();
    }
    output.append(k, new Value(value_output_serde.serialize(stats)));
}

From source file:net.sourceforge.jabm.report.BatchMetaReport.java

private void onSimulationFinished() {
    logger.debug("reports = " + reports);
    for (Report report : reports) {
        Map<Object, Number> singleSimulationVars = report.getVariableBindings();
        Iterator<Object> i = singleSimulationVars.keySet().iterator();
        while (i.hasNext()) {
            Object variable = i.next();
            Object value = singleSimulationVars.get(variable);
            if (value instanceof Number) {
                double dValue = singleSimulationVars.get(variable).doubleValue();
                SummaryStatistics stats = variables.get(variable);
                if (stats == null) {
                    stats = new SummaryStatistics();
                    variables.put(variable, stats);
                }//from   w  w  w. j  a  va  2s. c o m
                stats.addValue(dValue);
            }
        }
    }
}

From source file:net.sourceforge.jabm.report.PayoffMap.java

public void updatePayoff(Strategy strategy, double fitness) {
    SummaryStatistics stats = (SummaryStatistics) payoffs.get(strategy);
    if (stats == null) {
        stats = (SummaryStatistics) createStatisticalSummary(strategy);
        payoffs.put(strategy, stats);/*from  w w w  .  j  a v  a  2  s.  c om*/
        strategyIndex.add(strategy);
    }
    stats.addValue(fitness);
}

From source file:cl.usach.managedbeans.CreditosManagedBean.java

public double buscarPromedioSrpintGrupo(SprintGrupos springG) {
    List<Equipo> eqs = buscarEquipos(springG);
    SummaryStatistics stats = new SummaryStatistics();
    int s;/*from  w  ww  .  j  a va 2 s  .c  o m*/
    for (Equipo equipo : eqs) {
        s = buscarTiempoTareas(equipo);
        stats.addValue(s);
    }
    double mean = stats.getMean();
    mean = (double) Math.round(mean * 10) / 10;
    return mean;
}

From source file:cl.usach.managedbeans.CreditosManagedBean.java

public double buscarDesviacionStandarSrpintGrupo(SprintGrupos sprintG) {
    List<Equipo> eqs = buscarEquipos(sprintG);
    SummaryStatistics stats = new SummaryStatistics();
    int s;//from  w  w  w . j av a2  s.  c om
    for (Equipo equipo : eqs) {
        s = buscarTiempoTareas(equipo);
        stats.addValue(s);
    }
    double dv = stats.getStandardDeviation();
    dv = (double) Math.round(dv * 10) / 10;
    return dv;
}