| /* |
| * 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.math4.legacy.analysis.differentiation; |
| |
| import org.apache.commons.math4.legacy.TestUtils; |
| import org.apache.commons.math4.legacy.exception.DimensionMismatchException; |
| import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException; |
| import org.apache.commons.math4.legacy.core.jdkmath.AccurateMath; |
| 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 { |
| |
| @Override |
| public double value(double[] point) { |
| double d2 = 0; |
| for (double x : point) { |
| d2 += x * x; |
| } |
| return AccurateMath.sqrt(d2); |
| } |
| |
| @Override |
| 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; |
| } |
| |
| } |
| |
| } |