diff --git a/src/main/java/org/apache/commons/math3/analysis/differentiation/GradientFunction.java b/src/main/java/org/apache/commons/math3/analysis/differentiation/GradientFunction.java new file mode 100644 index 000000000..cc22c6958 --- /dev/null +++ b/src/main/java/org/apache/commons/math3/analysis/differentiation/GradientFunction.java @@ -0,0 +1,67 @@ +/* + * 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.analysis.MultivariateVectorFunction; + +/** Class representing the gradient of a multivariate function. + *
+ * The vectorial components of the function represent the derivatives + * with respect to each function parameters. + *
+ * @version $Id$ + * @since 3.1 + */ +public class GradientFunction implements MultivariateVectorFunction { + + /** Underlying real-valued function. */ + private final MultivariateDifferentiableFunction f; + + /** Simple constructor. + * @param f underlying real-valued function + */ + public GradientFunction(final MultivariateDifferentiableFunction f) { + this.f = f; + } + + /** {@inheritDoc} */ + public double[] value(double[] point) + throws IllegalArgumentException { + + // set up parameters + final DerivativeStructure[] dsX = new DerivativeStructure[point.length]; + for (int i = 0; i < point.length; ++i) { + dsX[i] = new DerivativeStructure(point.length, 1, i, point[i]); + } + + // compute the derivatives + final DerivativeStructure dsY = f.value(dsX); + + // extract the gradient + final double[] y = new double[point.length]; + final int[] orders = new int[point.length]; + for (int i = 0; i < point.length; ++i) { + orders[i] = 1; + y[i] = dsY.getPartialDerivative(orders); + orders[i] = 0; + } + + return y; + + } + +} diff --git a/src/test/java/org/apache/commons/math3/analysis/differentiation/GradientFunctionTest.java b/src/test/java/org/apache/commons/math3/analysis/differentiation/GradientFunctionTest.java new file mode 100644 index 000000000..7faf9b6c8 --- /dev/null +++ b/src/test/java/org/apache/commons/math3/analysis/differentiation/GradientFunctionTest.java @@ -0,0 +1,88 @@ +/* + * 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; + } + + } + +}