Examples of DescriptiveStatistics

org.apache.commons.math.stat.DescriptiveStatistics
DescriptiveStatistics implements the Univariate interface but maintains the set of values which contribute to the values being returned. This implementation of Univariate provides additional percentile functionality such as. This additional functionality comes with a price of increased storage costs. @version $Revision: 1.2 $ $Date: 2003/11/19 03:28:23 $
org.apache.commons.math.stat.descriptive.DescriptiveStatistics
Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data. The {@link #getWindowSize() windowSize}property sets a limit on the number of values that can be stored in the dataset. The default value, INFINITE_WINDOW, puts no limit on the size of the dataset. This value should be used with caution, as the backing store will grow without bound in this case. For very large datasets, {@link SummaryStatistics}, which does not store the dataset, should be used instead of this class. If windowSize is not INFINITE_WINDOW and more values are added than can be stored in the dataset, new values are added in a "rolling" manner, with new values replacing the "oldest" values in the dataset.
Note: this class is not threadsafe. Use {@link SynchronizedDescriptiveStatistics} if concurrent access from multiplethreads is required.
@version $Revision: 1054186 $ $Date: 2011-01-01 03:28:46 +0100 (sam. 01 janv. 2011) $
org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data. The {@link #getWindowSize() windowSize}property sets a limit on the number of values that can be stored in the dataset. The default value, INFINITE_WINDOW, puts no limit on the size of the dataset. This value should be used with caution, as the backing store will grow without bound in this case. For very large datasets, {@link SummaryStatistics}, which does not store the dataset, should be used instead of this class. If windowSize is not INFINITE_WINDOW and more values are added than can be stored in the dataset, new values are added in a "rolling" manner, with new values replacing the "oldest" values in the dataset.
Note: this class is not threadsafe. Use {@link SynchronizedDescriptiveStatistics} if concurrent access from multiplethreads is required.

Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

     * values and execute multi-pass algorithms
     */
    @Test
    public void testDescriptiveStatistics() throws Exception {


        DescriptiveStatistics u = new DescriptiveStatistics();


        loadStats("data/PiDigits.txt", u);
        Assert.assertEquals("PiDigits: std", std, u.getStandardDeviation(), 1E-14);
        Assert.assertEquals("PiDigits: mean", mean, u.getMean(), 1E-14);


        loadStats("data/Mavro.txt", u);
        Assert.assertEquals("Mavro: std", std, u.getStandardDeviation(), 1E-14);
        Assert.assertEquals("Mavro: mean", mean, u.getMean(), 1E-14);


        loadStats("data/Michelso.txt", u);
        Assert.assertEquals("Michelso: std", std, u.getStandardDeviation(), 1E-14);
        Assert.assertEquals("Michelso: mean", mean, u.getMean(), 1E-14);


        loadStats("data/NumAcc1.txt", u);
        Assert.assertEquals("NumAcc1: std", std, u.getStandardDeviation(), 1E-14);
        Assert.assertEquals("NumAcc1: mean", mean, u.getMean(), 1E-14);


        loadStats("data/NumAcc2.txt", u);
        Assert.assertEquals("NumAcc2: std", std, u.getStandardDeviation(), 1E-14);
        Assert.assertEquals("NumAcc2: mean", mean, u.getMean(), 1E-14);
    }

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

    /**
     * loads a DescriptiveStatistics off of a test file
     */
    private void loadStats(String resource, Object u) throws Exception {


        DescriptiveStatistics d = null;
        SummaryStatistics s = null;
        if (u instanceof DescriptiveStatistics) {
            d = (DescriptiveStatistics) u;
        } else {
            s = (SummaryStatistics) u;
        }
        u.getClass().getDeclaredMethod(
                "clear", new Class[]{}).invoke(u, new Object[]{});
        mean = Double.NaN;
        std = Double.NaN;


        InputStream resourceAsStream = CertifiedDataTest.class.getResourceAsStream(resource);
        Assert.assertNotNull("Could not find resource "+resource,resourceAsStream);
        BufferedReader in =
            new BufferedReader(
                    new InputStreamReader(
                            resourceAsStream));


        String line = null;


        for (int j = 0; j < 60; j++) {
            line = in.readLine();
            if (j == 40) {
                mean =
                    Double.parseDouble(
                            line.substring(line.lastIndexOf(":") + 1).trim());
            }
            if (j == 41) {
                std =
                    Double.parseDouble(
                            line.substring(line.lastIndexOf(":") + 1).trim());
            }
        }


        line = in.readLine();


        while (line != null) {
            if (d != null) {
                d.addValue(Double.parseDouble(line.trim()));
            }  else {
                s.addValue(Double.parseDouble(line.trim()));
            }
            line = in.readLine();
        }

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

            sample[i] = FastMath.random();
        }
        // normalize this sample
        double standardizedSample[] = StatUtils.normalize(sample);


        DescriptiveStatistics stats = new DescriptiveStatistics();
        // Add the data from the array
        for (int i = 0; i < length; i++) {
            stats.addValue(standardizedSample[i]);
        }
        // the calculations do have a limited precision    
        double distance = 1E-10;
        // check the mean an standard deviation
        Assert.assertEquals(0.0, stats.getMean(), distance);
        Assert.assertEquals(1.0, stats.getStandardDeviation(), distance);


    }

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

     * @param sample Sample to normalize.
     * @return normalized (standardized) sample.
     * @since 2.2
     */
    public static double[] normalize(final double[] sample) {
        DescriptiveStatistics stats = new DescriptiveStatistics();


        // Add the data from the series to stats
        for (int i = 0; i < sample.length; i++) {
            stats.addValue(sample[i]);
        }


        // Compute mean and standard deviation
        double mean = stats.getMean();
        double standardDeviation = stats.getStandardDeviation();


        // initialize the standardizedSample, which has the same length as the sample
        double[] standardizedSample = new double[sample.length];


        for (int i = 0; i < sample.length; i++) {

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

        }


        @Override
        public Block evaluateFinal()
        {
            DescriptiveStatistics statistics = new DescriptiveStatistics();
            for (int i = 0; i < accumulators.size(); i++) {
                BlockCursor cursor = accumulators.get(i).evaluateFinal().cursor();
                checkArgument(cursor.advanceNextPosition(), "accumulator returned no results");
                statistics.addValue(getNumeric(cursor));
            }


            BlockBuilder builder = new BlockBuilder(SINGLE_VARBINARY);
            builder.append(formatApproximateOutput(statistics, confidence));
            return builder.build();

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

        }


        @Override
        public void evaluateFinal(int groupId, BlockBuilder output)
        {
            DescriptiveStatistics statistics = new DescriptiveStatistics();
            for (int i = 0; i < accumulators.size(); i++) {
                BlockBuilder builder = new BlockBuilder(accumulators.get(i).getFinalTupleInfo());
                accumulators.get(i).evaluateFinal(groupId, builder);
                BlockCursor cursor = builder.build().cursor();
                checkArgument(cursor.advanceNextPosition(), "accumulator returned no results");
                statistics.addValue(getNumeric(cursor));
            }


            output.append(formatApproximateOutput(statistics, confidence));
        }

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics


    @Test
    public void testMultiplePositions()
            throws Exception
    {
        DescriptiveStatistics stats = new DescriptiveStatistics();


        for (int i = 0; i < 500; ++i) {
            int uniques = ThreadLocalRandom.current().nextInt(20000) + 1;


            List<Object> values = createRandomSample(uniques, (int) (uniques * 1.5));


            long actual = estimateGroupByCount(values);
            double error = (actual - uniques) * 1.0 / uniques;


            stats.addValue(error);
        }


        assertLessThan(stats.getMean(), 1.0e-2);
        assertLessThan(Math.abs(stats.getStandardDeviation() - ApproximateCountDistinctAggregations.getStandardError()), 1.0e-2);
    }

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

                new int[]{10, 0, 0, 0},
                false);
        rp.reset(-3806751651286565680L);
        System.out.println("Random Seed = " + rp.getSeed());
        System.out.println("NM Seed = " + CC.getNameManager().getSeed());
        DescriptiveStatistics timeStats = new DescriptiveStatistics();
        DescriptiveStatistics trysStats = new DescriptiveStatistics();
        int count = 0;
        while (++count < 500) {
//            CC.resetTensorNames();
            Tensor t = rp.nextProduct(15);
            if (!(t instanceof Product))
                continue;


            Product from = (Product) t, target = from;


            long start = System.nanoTime();
            ProductsBijectionsPort port = new ProductsBijectionsPort(from.getContent(), target.getContent());


            int[] bijection;
            boolean good = false;
            int trys = 0;
            OUTER:
            while (trys++ < 5000 && (bijection = port.take()) != null) {
                for (int i = 0; i < bijection.length; ++i)
                    if (bijection[i] != i)
                        continue OUTER;
                good = true;
                break;
            }


            double millis = 1E-6 * (System.nanoTime() - start);
            timeStats.addValue(millis);
            trysStats.addValue(trys);


            if (!good)
                throw new RuntimeException();
        }
        System.out.println(timeStats);

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

                new int[]{10, 0, 0, 0},
                false);
        rp.reset(-3806751651286565680L);
        System.out.println("Random Seed = " + rp.getSeed());
        System.out.println("NM Seed = " + CC.getNameManager().getSeed());
        DescriptiveStatistics timeStats = new DescriptiveStatistics();
        DescriptiveStatistics trysStats = new DescriptiveStatistics();
        int count = 0;
        while (++count < 500) {
//            CC.resetTensorNames();
            Tensor t = rp.nextProduct(15);
            if (!(t instanceof Product))
                continue;


            Product from = (Product) t;


            long start = System.nanoTime();
            ProductsBijectionsPort port = new ProductsBijectionsPort(from.getContent(), from.getContent());


            int[] bijection;
            boolean good = false;
            int trys = 0;
            OUTER:
            while (trys++ < 5000 && (bijection = port.take()) != null) {
                for (int i = 0; i < bijection.length; ++i)
                    if (bijection[i] != i)
                        continue OUTER;
                good = true;
                break;
            }


            double millis = 1E-6 * (System.nanoTime() - start);
            timeStats.addValue(millis);
            trysStats.addValue(trys);


            if (!good)
                throw new RuntimeException();
        }
        System.out.println(timeStats);

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Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

            BufferedWriter timSigOut = new BufferedWriter(new FileWriter("/home/stas/Projects/stableSort/timSig.dat"));
            BufferedWriter insertionSigOut = new BufferedWriter(new FileWriter("/home/stas/Projects/stableSort/insertionSig.dat"));






            DescriptiveStatistics timSort;
            DescriptiveStatistics insertionSort;


            int tryies = 200;
            int arrayLength = 0;
            for (; arrayLength < 1000; ++arrayLength) {


                int[] coSort = nextArray(arrayLength, bitsStreamGenerator);


                timSort = new DescriptiveStatistics();
                insertionSort = new DescriptiveStatistics();
                for (int i = 0; i < tryies; ++i) {
                    int[] t1 = nextArray(arrayLength, bitsStreamGenerator);
                    int[] t2 = t1.clone();


                    long start = System.currentTimeMillis();
                    ArraysUtils.timSort(t1, coSort);
                    long stop = System.currentTimeMillis();
                    timSort.addValue(stop - start);


                    start = System.currentTimeMillis();
                    ArraysUtils.insertionSort(t2, coSort);
                    stop = System.currentTimeMillis();
                    insertionSort.addValue(stop - start);
                }
                timMeanOut.write(arrayLength + "\t" + timSort.getMean() + "\n");
                insertionMeanOut.write(arrayLength + "\t" + insertionSort.getMean() + "\n");


                timMaxOut.write(arrayLength + "\t" + timSort.getMax() + "\n");
                insertionMaxOut.write(arrayLength + "\t" + insertionSort.getMax() + "\n");


                timSigOut.write(arrayLength + "\t" + timSort.getStandardDeviation() + "\n");
                insertionSigOut.write(arrayLength + "\t" + insertionSort.getStandardDeviation() + "\n");
            }
            timMeanOut.close();
            insertionMeanOut.close();
            timMaxOut.close();
            insertionMaxOut.close();

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