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Java源码示例：org.apache.commons.math3.stat.descriptive.UnivariateStatistic

示例1
@Test
public void testAllTechniquesNullEmpty() {

    final double[] nullArray = null;
    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
        }
        Assert.assertTrue(Double.isNaN(percentile.evaluate(emptyArray)));
    }

}
示例2
@Test
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,
                new Percentile().evaluate(singletonArray, 0, 1, 100), 0);
        Assert.assertTrue(Double.isNaN(percentile.evaluate(singletonArray,
                0, 0)));
    }
}
示例3
@Test
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,
                new Percentile().evaluate(singletonArray, 0, 0, 5), 0);
        Assert.assertEquals(Double.NaN,
                new Percentile().evaluate(singletonArray, 0, 0, 100), 0);
        Assert.assertTrue(Double.isNaN(percentile.evaluate(singletonArray,
                0, 0)));
    }
}
示例4
@Test
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,
                new Percentile().evaluate(singletonArray, 0, 1, 100), 0);
        Assert.assertTrue(Double.isNaN(percentile.evaluate(singletonArray,
                0, 0)));
    }
}
示例5
@Test
public void testAllTechniquesNullEmpty() {

    final double[] nullArray = null;
    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
        }
        Assert.assertTrue(Double.isNaN(percentile.evaluate(emptyArray)));
    }

}
示例6
/**
 * Apply the given statistic to this univariate collection.
 * @param stat the statistic to apply
 * @return the computed value of the statistic.
 */
@Override
public double apply(UnivariateStatistic stat) {
    double[] v = this.getValues();

    if (v != null) {
        return stat.evaluate(v, 0, v.length);
    }
    return Double.NaN;
}
示例7
/**
 * Apply the given statistic to this univariate collection.
 * @param stat the statistic to apply
 * @return the computed value of the statistic.
 */
@Override
public double apply(UnivariateStatistic stat) {
    double[] v = this.getValues();

    if (v != null) {
        return stat.evaluate(v, 0, v.length);
    }
    return Double.NaN;
}
示例8
/**
 * Apply the given statistic to this univariate collection.
 * @param stat the statistic to apply
 * @return the computed value of the statistic.
 */
@Override
public double apply(UnivariateStatistic stat) {
    double[] v = this.getValues();

    if (v != null) {
        return stat.evaluate(v, 0, v.length);
    }
    return Double.NaN;
}
示例9
/**
 * Apply the given statistic to this univariate collection.
 * @param stat the statistic to apply
 * @return the computed value of the statistic.
 */
@Override
public double apply(UnivariateStatistic stat) {
    double[] v = this.getValues();

    if (v != null) {
        return stat.evaluate(v, 0, v.length);
    }
    return Double.NaN;
}
示例10
/**
 * Apply the given statistic to this univariate collection.
 * @param stat the statistic to apply
 * @return the computed value of the statistic.
 */
@Override
public double apply(UnivariateStatistic stat) {
    double[] v = this.getValues();

    if (v != null) {
        return stat.evaluate(v, 0, v.length);
    }
    return Double.NaN;
}
示例11
protected AbstractStatistic(final UnivariateStatistic stat) {
    this.stat = stat;
}
示例12
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Variance();
}
示例13
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new GeometricMean();
}
示例14
/**
 * @see org.apache.commons.math3.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new FirstMoment();
}
示例15
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Sum();
}
示例16
@Override
public UnivariateStatistic copy() {
	return new MeanAboveMedian();
}
示例17
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Variance();
}
示例18
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Sum();
}
示例19
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Skewness();
}
示例20
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new GeometricMean();
}
示例21
/**
 * @see org.apache.commons.math3.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new ThirdMoment();
}
示例22
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Mean();
}
示例23
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Percentile(95.0);
}
示例24
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Max();
}
示例25
@Override
public UnivariateStatistic getUnivariateStatistic() {
    PSquarePercentile ptile = new PSquarePercentile(95);
    // Assert.assertNull(ptile.markers());
    return ptile;
}
示例26
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Median();
}
示例27
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new Kurtosis();
}
示例28
/**
 * {@inheritDoc}
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new SumOfLogs();
}
示例29
/**
 * @see org.apache.commons.math3.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
 */
@Override
public UnivariateStatistic getUnivariateStatistic() {
    return new ThirdMoment();
}
示例30
@Test
public void testAllTechniquesSpecialValues() {
    reset(50d, Percentile.EstimationType.LEGACY);
    final UnivariateStatistic percentile = getUnivariateStatistic();
    double[] specialValues =
            new double[] { 0d, 1d, 2d, 3d, 4d, Double.NaN };
    Assert.assertEquals(2.5d, percentile.evaluate(specialValues), 0);

    testAssertMappedValues(specialValues, new Object[][] {
            { Percentile.EstimationType.LEGACY, 2.5d }, { Percentile.EstimationType.R_1, 2.0 }, { Percentile.EstimationType.R_2, 2.0 }, { Percentile.EstimationType.R_3, 1.0 },
            { Percentile.EstimationType.R_4, 1.5 }, { Percentile.EstimationType.R_5, 2.0 }, { Percentile.EstimationType.R_6, 2.0 },
            { Percentile.EstimationType.R_7, 2.0 }, { Percentile.EstimationType.R_8, 2.0 }, { Percentile.EstimationType.R_9, 2.0 }}, 50d, 0d);

    specialValues =
            new double[] { Double.NEGATIVE_INFINITY, 1d, 2d, 3d,
                    Double.NaN, Double.POSITIVE_INFINITY };
    Assert.assertEquals(2.5d, percentile.evaluate(specialValues), 0);

    testAssertMappedValues(specialValues, new Object[][] {
            { Percentile.EstimationType.LEGACY, 2.5d }, { Percentile.EstimationType.R_1, 2.0 }, { Percentile.EstimationType.R_2, 2.0 }, { Percentile.EstimationType.R_3, 1.0 },
            { Percentile.EstimationType.R_4, 1.5 }, { Percentile.EstimationType.R_5, 2.0 }, { Percentile.EstimationType.R_7, 2.0 }, { Percentile.EstimationType.R_7, 2.0 },
            { Percentile.EstimationType.R_8, 2.0 }, { Percentile.EstimationType.R_9, 2.0 } }, 50d, 0d);

    specialValues =
            new double[] { 1d, 1d, Double.POSITIVE_INFINITY,
                    Double.POSITIVE_INFINITY };
    Assert.assertTrue(Double.isInfinite(percentile.evaluate(specialValues)));

    testAssertMappedValues(specialValues, new Object[][] {
            // This is one test not matching with R results.
            { Percentile.EstimationType.LEGACY, Double.POSITIVE_INFINITY },
            { Percentile.EstimationType.R_1,/* 1.0 */Double.NaN },
            { Percentile.EstimationType.R_2, /* Double.POSITIVE_INFINITY */Double.NaN },
            { Percentile.EstimationType.R_3, /* 1.0 */Double.NaN }, { Percentile.EstimationType.R_4, /* 1.0 */Double.NaN },
            { Percentile.EstimationType.R_5, Double.POSITIVE_INFINITY },
            { Percentile.EstimationType.R_6, Double.POSITIVE_INFINITY },
            { Percentile.EstimationType.R_7, Double.POSITIVE_INFINITY },
            { Percentile.EstimationType.R_8, Double.POSITIVE_INFINITY },
            { Percentile.EstimationType.R_9, Double.POSITIVE_INFINITY }, }, 50d, 0d);

    specialValues = new double[] { 1d, 1d, Double.NaN, Double.NaN };
    Assert.assertTrue(Double.isNaN(percentile.evaluate(specialValues)));
    testAssertMappedValues(specialValues, new Object[][] {
            { Percentile.EstimationType.LEGACY, Double.NaN }, { Percentile.EstimationType.R_1, 1.0 }, { Percentile.EstimationType.R_2, 1.0 }, { Percentile.EstimationType.R_3, 1.0 },
            { Percentile.EstimationType.R_4, 1.0 }, { Percentile.EstimationType.R_5, 1.0 },{ Percentile.EstimationType.R_6, 1.0 },{ Percentile.EstimationType.R_7, 1.0 },
            { Percentile.EstimationType.R_8, 1.0 }, { Percentile.EstimationType.R_9, 1.0 },}, 50d, 0d);

    specialValues =
            new double[] { 1d, 1d, Double.NEGATIVE_INFINITY,
                    Double.NEGATIVE_INFINITY };

    testAssertMappedValues(specialValues, new Object[][] {
            { Percentile.EstimationType.LEGACY, Double.NaN }, { Percentile.EstimationType.R_1, Double.NaN },
            { Percentile.EstimationType.R_2, Double.NaN }, { Percentile.EstimationType.R_3, Double.NaN }, { Percentile.EstimationType.R_4, Double.NaN },
            { Percentile.EstimationType.R_5, Double.NaN }, { Percentile.EstimationType.R_6, Double.NaN },
            { Percentile.EstimationType.R_7, Double.NaN }, { Percentile.EstimationType.R_8, Double.NaN }, { Percentile.EstimationType.R_9, Double.NaN }
            }, 50d, 0d);

}