Examples of org.apache.commons.math3.util.ContinuedFraction.evaluate()

Class org.apache.commons.math3.util.ContinuedFraction

Examples of org.apache.commons.math3.util.ContinuedFraction.evaluate()

org.apache.commons.math3.util.ContinuedFraction.evaluate()
Evaluates the continued fraction at the value x. @param x the evaluation point. @return the value of the continued fraction evaluated at x. @throws ConvergenceException if the algorithm fails to converge.

    @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,

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    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);

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                    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() {

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    @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 },

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        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
            }

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


    }


    @Test

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    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,

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        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);

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                    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

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    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,

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