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:RealFunctionValidation.java

public static SummaryStatistics assessAccuracy(final Method method, final DataInputStream in,
        final DataOutputStream out)
        throws IOException, IllegalAccessException, IllegalArgumentException, InvocationTargetException {

    if (method.getReturnType() != Double.TYPE) {
        throw new IllegalArgumentException("method must return a double");
    }/*from   w w w .j  a va 2s.c o  m*/

    final Class<?>[] types = method.getParameterTypes();
    for (int i = 0; i < types.length; i++) {
        if (!types[i].isPrimitive()) {
            final StringBuilder builder = new StringBuilder();
            builder.append("argument #").append(i + 1).append(" of method ").append(method.getName())
                    .append("must be of primitive of type");
            throw new IllegalArgumentException(builder.toString());
        }
    }

    final SummaryStatistics stat = new SummaryStatistics();
    final Object[] parameters = new Object[types.length];
    while (true) {
        try {
            for (int i = 0; i < parameters.length; i++) {
                parameters[i] = readAndWritePrimitiveValue(in, out, types[i]);
            }
            final double expected = in.readDouble();
            if (FastMath.abs(expected) > 1E-16) {
                final Object value = method.invoke(null, parameters);
                final double actual = ((Double) value).doubleValue();
                final double err = FastMath.abs(actual - expected);
                final double ulps = err / FastMath.ulp(expected);
                out.writeDouble(expected);
                out.writeDouble(actual);
                out.writeDouble(ulps);
                stat.addValue(ulps);
            }
        } catch (EOFException e) {
            break;
        }
    }
    return stat;
}

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From source file:io.fabric8.example.variance.http.VarianceProcessor.java

@Override
public void process(Exchange exchange) throws Exception {
    String message = exchange.getIn().getBody(String.class);
    ObjectMapper objectMapper = new ObjectMapper();
    TypeFactory typeFactory = objectMapper.getTypeFactory();
    List<Double> values = objectMapper.readValue(message,
            typeFactory.constructCollectionType(List.class, Double.class));
    SummaryStatistics summaryStatistics = new SummaryStatistics();
    List<Double> list = new ObjectMapper().readValue(message, List.class);
    for (Double value : list) {
        summaryStatistics.addValue(value);
    }//from   w ww . j  av  a 2s  . co m
    String variance = Double.toString(summaryStatistics.getVariance());
    exchange.getOut().setBody(variance);
}

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From source file:io.fabric8.example.stddev.http.StdDevProcessor.java

@Override
public void process(Exchange exchange) throws Exception {
    String message = exchange.getIn().getBody(String.class);
    ObjectMapper objectMapper = new ObjectMapper();
    TypeFactory typeFactory = objectMapper.getTypeFactory();
    List<Double> values = objectMapper.readValue(message,
            typeFactory.constructCollectionType(List.class, Double.class));
    SummaryStatistics summaryStatistics = new SummaryStatistics();
    List<Double> list = new ObjectMapper().readValue(message, List.class);
    for (Double value : list) {
        summaryStatistics.addValue(value);
    }// w ww.j  a v a2 s  .  c  o m
    String stdDev = Double.toString(summaryStatistics.getStandardDeviation());
    exchange.getOut().setBody(stdDev);
}

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From source file:com.github.rinde.rinsim.util.StochasticSuppliersTest.java

/**
 * Tests whether the rescaling of the mean of a truncated normal distribution
 * is implemented correctly.//from   w ww  .  j  a  va 2s.  co m
 */
@Test
public void testNormalScaleMean() {
    final double[] means = new double[] { 1d, 2d, 3d, 10d, 100d };
    final double[] sds = new double[] { 1d, 1d, 3d, 5d, 100d };

    for (int i = 0; i < means.length; i++) {
        final StochasticSupplier<Double> ss = StochasticSuppliers.normal().mean(means[i]).std(sds[i])
                .lowerBound(0).scaleMean().redrawWhenOutOfBounds().buildDouble();

        final RandomGenerator rng = new MersenneTwister(123);
        final SummaryStatistics stats = new SummaryStatistics();
        for (int j = 0; j < 10000; j++) {
            stats.addValue(ss.get(rng.nextLong()));
        }
        // 1 % deviation from mean is acceptable
        final double allowedDeviation = 0.01 * means[i];
        assertEquals(means[i], stats.getMean(), allowedDeviation);
    }

}

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From source file:io.fabric8.example.stddev.http.StdDevProcessorTest.java

@Test
public void testProcess() throws Exception {
    RandomGenerator rg = new JDKRandomGenerator();
    double[] array = new double[10];
    ObjectMapper objectMapper = new ObjectMapper();
    for (int i = 0; i < array.length; i++) {
        array[i] = rg.nextDouble();/*from   w w  w . j  a  va 2  s  .c o  m*/
    }
    String body = objectMapper.writeValueAsString(array);
    SummaryStatistics summaryStatistics = new SummaryStatistics();
    List<Double> list = new ObjectMapper().readValue(body, List.class);
    for (Double value : list) {
        summaryStatistics.addValue(value);
    }
    String stdDev = Double.toString(summaryStatistics.getStandardDeviation());

    resultEndpoint.expectedBodiesReceived(stdDev);

    template.sendBody(body);

    resultEndpoint.assertIsSatisfied();
}

---

From source file:io.fabric8.example.variance.http.VarianceProcessorTest.java

@Test
public void testProcess() throws Exception {
    RandomGenerator rg = new JDKRandomGenerator();
    double[] array = new double[10];
    ObjectMapper objectMapper = new ObjectMapper();
    for (int i = 0; i < array.length; i++) {
        array[i] = rg.nextDouble();/*  w w  w  .  j  av a  2 s  .  c o  m*/
    }
    String body = objectMapper.writeValueAsString(array);
    String expectedBody = "0.0";
    SummaryStatistics summaryStatistics = new SummaryStatistics();
    List<Double> list = new ObjectMapper().readValue(body, List.class);
    for (Double value : list) {
        summaryStatistics.addValue(value);
    }
    String variance = Double.toString(summaryStatistics.getVariance());

    resultEndpoint.expectedBodiesReceived(variance);

    template.sendBody(body);

    resultEndpoint.assertIsSatisfied();
}

---

From source file:io.fabric8.example.stddev.msg.StdDevProcessor.java

@Override
public void process(Exchange exchange) throws Exception {
    System.err.println("STD DEV GOT EXCHANGE " + exchange);
    String message = exchange.getIn().getBody(String.class);
    ObjectMapper objectMapper = new ObjectMapper();
    TypeFactory typeFactory = objectMapper.getTypeFactory();
    List<Double> values = objectMapper.readValue(message,
            typeFactory.constructCollectionType(List.class, Double.class));
    SummaryStatistics summaryStatistics = new SummaryStatistics();
    List<Double> list = new ObjectMapper().readValue(message, List.class);
    for (Double value : list) {
        summaryStatistics.addValue(value);
    }/*w  w w.j  a  v  a2 s  .  co m*/
    String stdDev = Double.toString(summaryStatistics.getStandardDeviation());

    ActiveMQDestination replyTo = exchange.getIn().getHeader("JMSReplyTo", ActiveMQDestination.class);
    final String messageId = exchange.getIn().getHeader("JMSMessageID", String.class);

    if (replyTo != null) {
        Exchange copy = new DefaultExchange(exchange);
        copy.setPattern(ExchangePattern.InOnly);
        copy.getIn().setHeader(Variables.CORRELATION_HEADER, messageId);
        copy.getIn().setBody(stdDev);
        producerTemplate.send("jms:queue:" + replyTo.getPhysicalName(), copy);
    }
}

---

From source file:io.fabric8.example.variance.msg.VarianceProcessor.java

@Override
public void process(Exchange exchange) throws Exception {
    System.err.println("VARIANCE GOT EXCHANGE " + exchange);
    String message = exchange.getIn().getBody(String.class);
    ObjectMapper objectMapper = new ObjectMapper();
    TypeFactory typeFactory = objectMapper.getTypeFactory();
    List<Double> values = objectMapper.readValue(message,
            typeFactory.constructCollectionType(List.class, Double.class));
    SummaryStatistics summaryStatistics = new SummaryStatistics();
    List<Double> list = new ObjectMapper().readValue(message, List.class);
    for (Double value : list) {
        summaryStatistics.addValue(value);
    }/*from   w w  w.j  a  v  a  2s  .co  m*/
    String variance = Double.toString(summaryStatistics.getVariance());
    ActiveMQDestination replyTo = exchange.getIn().getHeader("JMSReplyTo", ActiveMQDestination.class);
    final String messageId = exchange.getIn().getHeader("JMSMessageID", String.class);

    if (replyTo != null) {
        Exchange copy = new DefaultExchange(exchange);
        copy.setPattern(ExchangePattern.InOnly);
        copy.getIn().setHeader(Variables.CORRELATION_HEADER, messageId);
        copy.getIn().setBody(variance);
        producerTemplate.send("jms:queue:" + replyTo.getPhysicalName(), copy);
        System.err.println("REPLIED TO " + "jms:queue:" + replyTo.getPhysicalName());
    } else {
        System.err.println("REPLOY NOT SET for exchange: " + exchange.getIn().getHeaders());
    }
}

---

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

/**
 * Implements equation (8.13) from "Elementary Statistics: A Problem Solving
 * Approach 4th Edition", Andrew L. Comrey, Howard B. Lee
 *
 * @return the standard error as the ratio of the standard deviation divided
 * by the sqrt(number of users) of the distribution of difference scores.
 *//*  w  ww .  j a va 2  s.co  m*/
public double getStandardError() {
    Set<V> overlap = new HashSet<V>(baselineMetricPerDimension.keySet());
    overlap.retainAll(testMetricPerDimension.keySet());

    // paired or matched samples --> analyse distribution of difference scores
    SummaryStatistics differences = new SummaryStatistics();
    for (V key : overlap) {
        double diff = baselineMetricPerDimension.get(key) - testMetricPerDimension.get(key);
        differences.addValue(diff);
    }

    double e = differences.getStandardDeviation() / Math.sqrt(differences.getN());
    return e;
}

---

From source file:eu.crydee.alignment.aligner.ae.MetricsSummaryAE.java

@Override
public void collectionProcessComplete() throws AnalysisEngineProcessException {
    try {//from   w w  w  .j  ava2s  .com
        String template = IOUtils.toString(getClass()
                .getResourceAsStream("/eu/crydee/alignment/aligner/ae/" + "metrics-summarizer-template.html"));
        String titledTemplate = template.replace("@@TITLE@@",
                "Metrics summarizer" + LocalDateTime.now().format(DateTimeFormatter.ISO_DATE_TIME));
        StringBuilder sb = new StringBuilder();
        sb.append("<table class=\"table table-striped ").append("table-condensed\">\n")
                .append("            <thead>\n").append("                <tr>\n")
                .append("                    <th>City\\Metric</th>\n");
        for (String key : keys) {
            sb.append("                    <th>").append(methodsMetadata.get(key).getRight()).append("</th>\n");
        }
        sb.append("                <tr>\n").append("            </thead>\n").append("            <tbody>\n");
        for (String ele : results.rowKeySet()) {
            sb.append("                <tr>\n").append("                    <td>").append(ele)
                    .append("</td>\n");
            Map<String, Samples> metricResults = results.row(ele);
            for (String key : keys) {
                Samples samples = metricResults.get(key);
                SummaryStatistics ss = new SummaryStatistics();
                samples.samples.forEach(d -> ss.addValue(d));
                double mean = ss.getMean();
                boolean significant = TestUtils.tTest(samples.mu,
                        ArrayUtils.toPrimitive(samples.samples.toArray(new Double[0])), 0.05),
                        above = samples.mu > mean;
                String summary = String.format("%.3f", samples.mu) + " <small class=\"text-muted\">"
                        + String.format("%.3f", ss.getMean()) + ""
                        + String.format("%.3f", ss.getStandardDeviation()) + "</small>";
                logger.info(ele + "\t" + key + "\t" + summary + "\t" + significant);
                sb.append("                    <td class=\"")
                        .append(significant ? (above ? "success" : "danger") : "warning").append("\">")
                        .append(summary).append("</td>\n");
            }
            sb.append("                </tr>\n");
        }
        sb.append("            </tbody>\n").append("        </table>");
        FileUtils.write(new File(htmlFilepath), titledTemplate.replace("@@TABLE@@", sb.toString()),
                StandardCharsets.UTF_8);
    } catch (IOException ex) {
        logger.error("IO problem with the HTML output.");
        throw new AnalysisEngineProcessException(ex);
    }
}

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