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From luc.maison...@free.fr
Subject Re: svn commit: r1230419 - in /commons/proper/math/trunk/src: main/java/org/apache/commons/math/distribution/TriangularDistribution.java test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
Date Thu, 12 Jan 2012 08:24:50 GMT
Hi S├ębastien,

----- Mail original -----
> Author: celestin
> Date: Thu Jan 12 07:01:43 2012
> New Revision: 1230419
> 
> URL: http://svn.apache.org/viewvc?rev=1230419&view=rev
> Log:
> Implementation of continuous triangular distributions (MATH-731).
> Patch contributed by Dennis Hendriks.
> 
> Added:
>     commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java
>       (with props)
>     commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
>       (with props)

You should probably also change the NOTICE file to include the licence text from the original
code.

Luc

> 
> Added:
> commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java
> URL:
> http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java?rev=1230419&view=auto
> ==============================================================================
> ---
> commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java
> (added)
> +++
> commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java
> Thu Jan 12 07:01:43 2012
> @@ -0,0 +1,260 @@
> +/*
> + * Licensed to the Apache Software Foundation (ASF) under one or
> more
> + * contributor license agreements.  See the NOTICE file distributed
> with
> + * this work for additional information regarding copyright
> ownership.
> + * The ASF licenses this file to You under the Apache License,
> Version 2.0
> + * (the "License"); you may not use this file except in compliance
> with
> + * the License.  You may obtain a copy of the License at
> + *
> + *      http://www.apache.org/licenses/LICENSE-2.0
> + *
> + * Unless required by applicable law or agreed to in writing,
> software
> + * distributed under the License is distributed on an "AS IS" BASIS,
> + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
> implied.
> + * See the License for the specific language governing permissions
> and
> + * limitations under the License.
> + */
> +
> +package org.apache.commons.math.distribution;
> +
> +import org.apache.commons.math.exception.NumberIsTooLargeException;
> +import org.apache.commons.math.exception.NumberIsTooSmallException;
> +import org.apache.commons.math.exception.OutOfRangeException;
> +import org.apache.commons.math.exception.util.LocalizedFormats;
> +import org.apache.commons.math.util.FastMath;
> +
> +/**
> + * Implementation of the triangular real distribution.
> + *
> + * @see <a
> href="http://en.wikipedia.org/wiki/Triangular_distribution">
> + * Triangular distribution (Wikipedia)</a>
> + *
> + * @version $Id$
> + * @since 3.0
> + */
> +public class TriangularDistribution extends AbstractRealDistribution
> {
> +    /** Serializable version identifier. */
> +    private static final long serialVersionUID = 20120112L;
> +
> +    /** Lower limit of this distribution (inclusive). */
> +    private final double a;
> +
> +    /** Upper limit of this distribution (inclusive). */
> +    private final double b;
> +
> +    /** Mode of this distribution. */
> +    private final double c;
> +
> +    /** Inverse cumulative probability accuracy. */
> +    private final double solverAbsoluteAccuracy;
> +
> +    /**
> +     * Create a triangular real distribution using the given lower
> limit,
> +     * upper limit, and mode.
> +     *
> +     * @param a Lower limit of this distribution (inclusive).
> +     * @param b Upper limit of this distribution (inclusive).
> +     * @param c Mode of this distribution.
> +     * @throws NumberIsTooLargeException if {@code a >= b} or if
> {@code c > b}
> +     * @throws NumberIsTooSmallException if {@code c < a}
> +     */
> +    public TriangularDistribution(double a, double c, double b)
> +        throws NumberIsTooLargeException, NumberIsTooSmallException
> {
> +        if (a >= b) {
> +            throw new NumberIsTooLargeException(
> +
>                            LocalizedFormats.LOWER_BOUND_NOT_BELOW_UPPER_BOUND,
> +                            a, b, false);
> +        }
> +        if (c < a) {
> +            throw new NumberIsTooSmallException(
> +                    LocalizedFormats.NUMBER_TOO_SMALL, c, a, true);
> +        }
> +        if (c > b) {
> +            throw new NumberIsTooLargeException(
> +                    LocalizedFormats.NUMBER_TOO_LARGE, c, b, true);
> +        }
> +
> +        this.a = a;
> +        this.c = c;
> +        this.b = b;
> +        solverAbsoluteAccuracy = FastMath.ulp(c);
> +    }
> +
> +    /**
> +     * Returns the mode {@code c} of this distribution.
> +     *
> +     * @return the mode {@code c} of this distribution
> +     */
> +    public double getMode() {
> +        return c;
> +    }
> +
> +    /** {@inheritDoc} */
> +    @Override
> +    protected double getSolverAbsoluteAccuracy() {
> +        return solverAbsoluteAccuracy;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * For this distribution {@code P(X = x)} always evaluates to 0.
> +     *
> +     * @return 0
> +     */
> +    public double probability(double x) {
> +        return 0;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * For lower limit {@code a}, upper limit {@code b} and mode
> {@code c}, the
> +     * PDF is given by
> +     * <ul>
> +     * <li>{@code 2 * (x - a) / [(b - a) * (c - a)]} if {@code a <=
> x < c},</li>
> +     * <li>{@code 2 / (b - a)} if {@code x = c},</li>
> +     * <li>{@code 2 * (b - x) / [(b - a) * (b - c)]} if {@code c < x
> <= b},</li>
> +     * <li>{@code 0} otherwise.
> +     * </ul>
> +     */
> +    public double density(double x) {
> +        if (x < a) {
> +            return 0;
> +        }
> +        if (a <= x && x < c) {
> +            double divident = 2 * (x - a);
> +            double divisor = (b - a) * (c - a);
> +            return divident / divisor;
> +        }
> +        if (x == c) {
> +            return 2 / (b - a);
> +        }
> +        if (c < x && x <= b) {
> +            double divident = 2 * (b - x);
> +            double divisor = (b - a) * (b - c);
> +            return divident / divisor;
> +        }
> +        return 0;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * For lower limit {@code a}, upper limit {@code b} and mode
> {@code c}, the
> +     * CDF is given by
> +     * <ul>
> +     * <li>{@code 0} if {@code x < a},</li>
> +     * <li>{@code (x - a)^2 / [(b - a) * (c - a)]} if {@code a <= x
> < c},</li>
> +     * <li>{@code (c - a) / (b - a)} if {@code x = c},</li>
> +     * <li>{@code 1 - (b - x)^2 / [(b - a) * (b - c)]} if {@code c <
> x <= b},</li>
> +     * <li>{@code 1} if {@code x > b}.</li>
> +     * </ul>
> +     */
> +    public double cumulativeProbability(double x)  {
> +        if (x < a) {
> +            return 0;
> +        }
> +        if (a <= x && x < c) {
> +            double divident = (x - a) * (x - a);
> +            double divisor = (b - a) * (c - a);
> +            return divident / divisor;
> +        }
> +        if (x == c) {
> +            return (c - a) / (b - a);
> +        }
> +        if (c < x && x <= b) {
> +            double divident = (b - x) * (b - x);
> +            double divisor = (b - a) * (b - c);
> +            return 1 - (divident / divisor);
> +        }
> +        return 1;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * For lower limit {@code a}, upper limit {@code b}, and mode
> {@code c},
> +     * the mean is {@code (a + b + c) / 3}.
> +     */
> +    public double getNumericalMean() {
> +        return (a + b + c) / 3;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * For lower limit {@code a}, upper limit {@code b}, and mode
> {@code c},
> +     * the variance is {@code (a^2 + b^2 + c^2 - a * b - a * c - b *
> c) / 18}.
> +     */
> +    public double getNumericalVariance() {
> +        return (a * a + b * b + c * c - a * b - a * c - b * c) / 18;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * The lower bound of the support is equal to the lower limit
> parameter
> +     * {@code a} of the distribution.
> +     *
> +     * @return lower bound of the support
> +     */
> +    public double getSupportLowerBound() {
> +        return a;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * The upper bound of the support is equal to the upper limit
> parameter
> +     * {@code b} of the distribution.
> +     *
> +     * @return upper bound of the support
> +     */
> +    public double getSupportUpperBound() {
> +        return b;
> +    }
> +
> +    /** {@inheritDoc} */
> +    public boolean isSupportLowerBoundInclusive() {
> +        return true;
> +    }
> +
> +    /** {@inheritDoc} */
> +    public boolean isSupportUpperBoundInclusive() {
> +        return true;
> +    }
> +
> +    /**
> +     * {@inheritDoc}
> +     *
> +     * The support of this distribution is connected.
> +     *
> +     * @return {@code true}
> +     */
> +    public boolean isSupportConnected() {
> +        return true;
> +    }
> +
> +    @Override
> +    public double inverseCumulativeProbability(double p)
> +        throws OutOfRangeException {
> +        if (p < 0.0 || p > 1.0) {
> +            throw new OutOfRangeException(p, 0, 1);
> +        }
> +        if (p == 0.0) {
> +            return a;
> +        }
> +        if (p == 1.0) {
> +            return b;
> +        }
> +        final double pc = (c - a) / (b - a);
> +        if (p == pc) {
> +            return c;
> +        }
> +        if (p < pc) {
> +            return a + FastMath.sqrt(p * (b - a) * (c - a));
> +        }
> +        return b - FastMath.sqrt((1 - p) * (b - a) * (b - c));
> +    }
> +}
> 
> Propchange:
> commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java
> ------------------------------------------------------------------------------
>     svn:eol-style = native
> 
> Propchange:
> commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/TriangularDistribution.java
> ------------------------------------------------------------------------------
>     svn:keywords = Author Date Id Revision
> 
> Added:
> commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
> URL:
> http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java?rev=1230419&view=auto
> ==============================================================================
> ---
> commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
> (added)
> +++
> commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
> Thu Jan 12 07:01:43 2012
> @@ -0,0 +1,189 @@
> +/*
> + * Licensed to the Apache Software Foundation (ASF) under one or
> more
> + * contributor license agreements.  See the NOTICE file distributed
> with
> + * this work for additional information regarding copyright
> ownership.
> + * The ASF licenses this file to You under the Apache License,
> Version 2.0
> + * (the "License"); you may not use this file except in compliance
> with
> + * the License.  You may obtain a copy of the License at
> + *
> + *      http://www.apache.org/licenses/LICENSE-2.0
> + *
> + * Unless required by applicable law or agreed to in writing,
> software
> + * distributed under the License is distributed on an "AS IS" BASIS,
> + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
> implied.
> + * See the License for the specific language governing permissions
> and
> + * limitations under the License.
> + */
> +
> +package org.apache.commons.math.distribution;
> +
> +import java.util.Arrays;
> +
> +import org.apache.commons.math.exception.NumberIsTooLargeException;
> +import org.apache.commons.math.exception.NumberIsTooSmallException;
> +import org.junit.Assert;
> +import org.junit.Test;
> +
> +/**
> + * Test cases for {@link TriangularDistribution}. See class javadoc
> for
> + * {@link RealDistributionAbstractTest} for further details.
> + */
> +public class TriangularDistributionTest extends
> RealDistributionAbstractTest {
> +
> +    // --- Override tolerance
> -------------------------------------------------
> +
> +    @Override
> +    public void setUp() throws Exception {
> +        super.setUp();
> +        setTolerance(1e-4);
> +    }
> +
> +    //--- Implementations for abstract methods
> --------------------------------
> +
> +    /**
> +     * Creates the default triangular distribution instance to use
> in tests.
> +     */
> +    @Override
> +    public TriangularDistribution makeDistribution() {
> +        // Left side 5 wide, right side 10 wide.
> +        return new TriangularDistribution(-3, 2, 12);
> +    }
> +
> +    /**
> +     * Creates the default cumulative probability distribution test
> input
> +     * values.
> +     */
> +    @Override
> +    public double[] makeCumulativeTestPoints() {
> +        return new double[] { -3.0001,                 // below
> lower limit
> +                              -3.0,                    // at lower
> limit
> +                              -2.0, -1.0, 0.0, 1.0,    // on lower
> side
> +                              2.0,                     // at mode
> +                              3.0, 4.0, 10.0, 11.0,    // on upper
> side
> +                              12.0,                    // at upper
> limit
> +                              12.0001                  // above
> upper limit
> +                            };
> +    }
> +
> +    /**
> +     * Creates the default cumulative probability density test
> expected values.
> +     */
> +    @Override
> +    public double[] makeCumulativeTestValues() {
> +        // Top at 2 / (b - a) = 2 / (12 - -3) = 2 / 15 = 7.5
> +        // Area left  = 7.5 * 5  * 0.5 = 18.75 (1/3 of the total
> area)
> +        // Area right = 7.5 * 10 * 0.5 = 37.5  (2/3 of the total
> area)
> +        // Area total = 18.75 + 37.5 = 56.25
> +        // Derivative left side = 7.5 / 5 = 1.5
> +        // Derivative right side = -7.5 / 10 = -0.75
> +        double third = 1 / 3.0;
> +        double left = 18.75;
> +        double area = 56.25;
> +        return new double[] { 0.0,
> +                              0.0,
> +                              0.75 / area, 3 / area, 6.75 / area, 12
> / area,
> +                              third,
> +                              (left + 7.125) / area, (left + 13.5) /
> area,
> +                              (left + 36) / area, (left + 37.125) /
> area,
> +                              1.0,
> +                              1.0
> +                            };
> +    }
> +
> +    /**
> +     * Creates the default inverse cumulative probability
> distribution test
> +     * input values.
> +     */
> +    @Override
> +    public double[] makeInverseCumulativeTestPoints() {
> +        // Exclude the points outside the limits, as they have
> cumulative
> +        // probability of zero and one, meaning the inverse returns
> the
> +        // limits and not the points outside the limits.
> +        double[] points = makeCumulativeTestValues();
> +        return Arrays.copyOfRange(points, 1, points.length - 1);
> +    }
> +
> +    /**
> +     * Creates the default inverse cumulative probability density
> test expected
> +     * values.
> +     */
> +    @Override
> +    public double[] makeInverseCumulativeTestValues() {
> +        // Exclude the points outside the limits, as they have
> cumulative
> +        // probability of zero and one, meaning the inverse returns
> the
> +        // limits and not the points outside the limits.
> +        double[] points = makeCumulativeTestPoints();
> +        return Arrays.copyOfRange(points, 1, points.length - 1);
> +    }
> +
> +    /** Creates the default probability density test expected
> values. */
> +    @Override
> +    public double[] makeDensityTestValues() {
> +        return new double[] { 0,
> +                              0,
> +                              2 / 75.0, 4 / 75.0, 6 / 75.0, 8 /
> 75.0,
> +                              10 / 75.0,
> +                              9 / 75.0, 8 / 75.0, 2 / 75.0, 1 /
> 75.0,
> +                              0,
> +                              0
> +                            };
> +    }
> +
> +    //--- Additional test cases
> -----------------------------------------------
> +
> +    /** Test lower bound getter. */
> +    @Test
> +    public void testGetLowerBound() {
> +        TriangularDistribution distribution = makeDistribution();
> +        Assert.assertEquals(-3.0,
> distribution.getSupportLowerBound(), 0);
> +    }
> +
> +    /** Test upper bound getter. */
> +    @Test
> +    public void testGetUpperBound() {
> +        TriangularDistribution distribution = makeDistribution();
> +        Assert.assertEquals(12.0,
> distribution.getSupportUpperBound(), 0);
> +    }
> +
> +    /** Test pre-condition for equal lower/upper limit. */
> +    @Test(expected=NumberIsTooLargeException.class)
> +    public void testPreconditions1() {
> +        new TriangularDistribution(0, 0, 0);
> +    }
> +
> +    /** Test pre-condition for lower limit larger than upper limit.
> */
> +    @Test(expected=NumberIsTooLargeException.class)
> +    public void testPreconditions2() {
> +        new TriangularDistribution(1, 1, 0);
> +    }
> +
> +    /** Test pre-condition for mode larger than upper limit. */
> +    @Test(expected=NumberIsTooLargeException.class)
> +    public void testPreconditions3() {
> +        new TriangularDistribution(0, 2, 1);
> +    }
> +
> +    /** Test pre-condition for mode smaller than lower limit. */
> +    @Test(expected=NumberIsTooSmallException.class)
> +    public void testPreconditions4() {
> +        new TriangularDistribution(2, 1, 3);
> +    }
> +
> +    /** Test mean/variance. */
> +    @Test
> +    public void testMeanVariance() {
> +        TriangularDistribution dist;
> +
> +        dist = new TriangularDistribution(0, 0.5, 1.0);
> +        Assert.assertEquals(dist.getNumericalMean(), 0.5, 0);
> +        Assert.assertEquals(dist.getNumericalVariance(), 1 / 24.0,
> 0);
> +
> +        dist = new TriangularDistribution(0, 1, 1);
> +        Assert.assertEquals(dist.getNumericalMean(), 2 / 3.0, 0);
> +        Assert.assertEquals(dist.getNumericalVariance(), 1 / 18.0,
> 0);
> +
> +        dist = new TriangularDistribution(-3, 2, 12);
> +        Assert.assertEquals(dist.getNumericalMean(), 3 + (2 / 3.0),
> 0);
> +        Assert.assertEquals(dist.getNumericalVariance(), 175 / 18.0,
> 0);
> +    }
> +}
> 
> Propchange:
> commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
> ------------------------------------------------------------------------------
>     svn:eol-style = native
> 
> Propchange:
> commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/TriangularDistributionTest.java
> ------------------------------------------------------------------------------
>     svn:keywords = Author Date Id Revision
> 
> 
> 

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