1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 18 package org.apache.commons.math.analysis; 19 20 /** 21 * Extension of {@link MultivariateRealFunction} representing a differentiable 22 * multivariate real function. 23 * @version $Revision: 811685 $ $Date: 2009-09-05 19:36:48 +0200 (sam. 05 sept. 2009) $ 24 * @since 2.0 25 */ 26 public interface DifferentiableMultivariateRealFunction extends MultivariateRealFunction { 27 28 /** 29 * Returns the partial derivative of the function with respect to a point coordinate. 30 * <p> 31 * The partial derivative is defined with respect to point coordinate 32 * x<sub>k</sub>. If the partial derivatives with respect to all coordinates are 33 * needed, it may be more efficient to use the {@link #gradient()} method which will 34 * compute them all at once. 35 * </p> 36 * @param k index of the coordinate with respect to which the partial 37 * derivative is computed 38 * @return the partial derivative function with respect to k<sup>th</sup> point coordinate 39 */ 40 MultivariateRealFunction partialDerivative(int k); 41 42 /** 43 * Returns the gradient function. 44 * <p>If only one partial derivative with respect to a specific coordinate is 45 * needed, it may be more efficient to use the {@link #partialDerivative(int)} method 46 * which will compute only the specified component.</p> 47 * @return the gradient function 48 */ 49 MultivariateVectorialFunction gradient(); 50 51 } 52
