Package org.apache.commons.math3.stat.descriptive.moment

Examples of org.apache.commons.math3.stat.descriptive.moment.Variance.evaluate()


    @Test
    public void testAllTechniquesSingleton() {
        double[] singletonArray = new double[] { 1d };
        for (EstimationType e : EstimationType.values()) {
            UnivariateStatistic percentile = getTestMedian(e);
            Assert.assertEquals(1d, percentile.evaluate(singletonArray), 0);
            Assert.assertEquals(1d, percentile.evaluate(singletonArray, 0, 1),
                    0);
            Assert.assertEquals(1d,
                    new Median().evaluate(singletonArray, 0, 1, 5), 0);
            Assert.assertEquals(1d,
View Full Code Here


    public void testAllTechniquesSingleton() {
        double[] singletonArray = new double[] { 1d };
        for (EstimationType e : EstimationType.values()) {
            UnivariateStatistic percentile = getTestMedian(e);
            Assert.assertEquals(1d, percentile.evaluate(singletonArray), 0);
            Assert.assertEquals(1d, percentile.evaluate(singletonArray, 0, 1),
                    0);
            Assert.assertEquals(1d,
                    new Median().evaluate(singletonArray, 0, 1, 5), 0);
            Assert.assertEquals(1d,
                    new Median().evaluate(singletonArray, 0, 1, 100), 0);
View Full Code Here

                    0);
            Assert.assertEquals(1d,
                    new Median().evaluate(singletonArray, 0, 1, 5), 0);
            Assert.assertEquals(1d,
                    new Median().evaluate(singletonArray, 0, 1, 100), 0);
            Assert.assertTrue(Double.isNaN(percentile.evaluate(singletonArray,
                    0, 0)));
        }
    }
    @Test
    public void testAllTechniquesMedian() {
View Full Code Here

    @Test
    public void testAllTechniques5() {
        reset(5, Percentile.EstimationType.LEGACY);
        final UnivariateStatistic percentile = getUnivariateStatistic();
        Assert.assertEquals(this.percentile5, percentile.evaluate(testArray),
                getTolerance());
        testAssertMappedValues(testArray,
                new Object[][] { { Percentile.EstimationType.LEGACY, percentile5 }, { Percentile.EstimationType.R_1, 8.8000 },
                        { Percentile.EstimationType.R_2, 8.8000 }, { Percentile.EstimationType.R_3, 8.2000 }, { Percentile.EstimationType.R_4, 8.2600 },
                        { Percentile.EstimationType.R_5, 8.5600 }, { Percentile.EstimationType.R_6, 8.2900 },
View Full Code Here

        final double[] emptyArray = new double[] {};
        for (final Percentile.EstimationType e : Percentile.EstimationType.values()) {
            reset (50, e);
            final UnivariateStatistic percentile = getUnivariateStatistic();
            try {
                percentile.evaluate(nullArray);
                Assert.fail("Expecting MathIllegalArgumentException "
                        + "for null array");
            } catch (final MathIllegalArgumentException ex) {
                // expected
            }
View Full Code Here

                Assert.fail("Expecting MathIllegalArgumentException "
                        + "for null array");
            } catch (final MathIllegalArgumentException ex) {
                // expected
            }
            Assert.assertTrue(Double.isNaN(percentile.evaluate(emptyArray)));
        }

    }

    @Test
View Full Code Here

    public void testAllTechniquesSingleton() {
        final double[] singletonArray = new double[] { 1d };
        for (final Percentile.EstimationType e : Percentile.EstimationType.values()) {
            reset (50, e);
            final UnivariateStatistic percentile = getUnivariateStatistic();
            Assert.assertEquals(1d, percentile.evaluate(singletonArray), 0);
            Assert.assertEquals(1d, percentile.evaluate(singletonArray, 0, 1),
                    0);
            Assert.assertEquals(1d,
                    new Percentile().evaluate(singletonArray, 0, 1, 5), 0);
            Assert.assertEquals(1d,
View Full Code Here

        final double[] singletonArray = new double[] { 1d };
        for (final Percentile.EstimationType e : Percentile.EstimationType.values()) {
            reset (50, e);
            final UnivariateStatistic percentile = getUnivariateStatistic();
            Assert.assertEquals(1d, percentile.evaluate(singletonArray), 0);
            Assert.assertEquals(1d, percentile.evaluate(singletonArray, 0, 1),
                    0);
            Assert.assertEquals(1d,
                    new Percentile().evaluate(singletonArray, 0, 1, 5), 0);
            Assert.assertEquals(1d,
                    new Percentile().evaluate(singletonArray, 0, 1, 100), 0);
View Full Code Here

                    0);
            Assert.assertEquals(1d,
                    new Percentile().evaluate(singletonArray, 0, 1, 5), 0);
            Assert.assertEquals(1d,
                    new Percentile().evaluate(singletonArray, 0, 1, 100), 0);
            Assert.assertTrue(Double.isNaN(percentile.evaluate(singletonArray,
                    0, 0)));
        }
    }

    @Test
View Full Code Here

    public void testAllTechniquesEmpty() {
        final double[] singletonArray = new double[] { };
        for (final Percentile.EstimationType e : Percentile.EstimationType.values()) {
            reset (50, e);
            final UnivariateStatistic percentile = getUnivariateStatistic();
            Assert.assertEquals(Double.NaN, percentile.evaluate(singletonArray),
                    0);
            Assert.assertEquals(Double.NaN, percentile.evaluate(singletonArray,
                    0, 0),
                    0);
            Assert.assertEquals(Double.NaN,
View Full Code Here

TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.