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Java example source code file (GradientFunctionTest.java)

This example Java source code file (GradientFunctionTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

derivativestructure, dimensionmismatchexception, euclideandistance, gradientfunction, gradientfunctiontest, mathillegalargumentexception, multivariatedifferentiablefunction, test

The GradientFunctionTest.java Java example source code

/*
 * 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.math3.analysis.differentiation;

import org.apache.commons.math3.TestUtils;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.util.FastMath;
import org.junit.Test;


/**
 * Test for class {@link GradientFunction}.
 */
public class GradientFunctionTest {

    @Test
    public void test2DDistance() {
        EuclideanDistance f = new EuclideanDistance();
        GradientFunction g = new GradientFunction(f);
        for (double x = -10; x < 10; x += 0.5) {
            for (double y = -10; y < 10; y += 0.5) {
                double[] point = new double[] { x, y };
                TestUtils.assertEquals(f.gradient(point), g.value(point), 1.0e-15);
            }
        }
    }

    @Test
    public void test3DDistance() {
        EuclideanDistance f = new EuclideanDistance();
        GradientFunction g = new GradientFunction(f);
        for (double x = -10; x < 10; x += 0.5) {
            for (double y = -10; y < 10; y += 0.5) {
                for (double z = -10; z < 10; z += 0.5) {
                    double[] point = new double[] { x, y, z };
                    TestUtils.assertEquals(f.gradient(point), g.value(point), 1.0e-15);
                }
            }
        }
    }

    private static class EuclideanDistance implements MultivariateDifferentiableFunction {

        public double value(double[] point) {
            double d2 = 0;
            for (double x : point) {
                d2 += x * x;
            }
            return FastMath.sqrt(d2);
        }

        public DerivativeStructure value(DerivativeStructure[] point)
            throws DimensionMismatchException, MathIllegalArgumentException {
            DerivativeStructure d2 = point[0].getField().getZero();
            for (DerivativeStructure x : point) {
                d2 = d2.add(x.multiply(x));
            }
            return d2.sqrt();
        }

        public double[] gradient(double[] point) {
            double[] gradient = new double[point.length];
            double d = value(point);
            for (int i = 0; i < point.length; ++i) {
                gradient[i] = point[i] / d;
            }
            return gradient;
        }

    }

}

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