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/*
* 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.
* <p>
* The vectorial components of the function represent the derivatives
* with respect to each function parameters.
* </p>
* @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) {
// 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;
}
}
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