001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017 018package org.apache.commons.math3.analysis; 019 020/** 021 * Extension of {@link MultivariateFunction} representing a differentiable 022 * multivariate real function. 023 * @version $Id: DifferentiableMultivariateFunction.java 1415149 2012-11-29 13:12:55Z erans $ 024 * @since 2.0 025 * @deprecated as of 3.1 replaced by {@link org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableFunction} 026 */ 027@Deprecated 028public interface DifferentiableMultivariateFunction extends MultivariateFunction { 029 030 /** 031 * Returns the partial derivative of the function with respect to a point coordinate. 032 * <p> 033 * The partial derivative is defined with respect to point coordinate 034 * x<sub>k</sub>. If the partial derivatives with respect to all coordinates are 035 * needed, it may be more efficient to use the {@link #gradient()} method which will 036 * compute them all at once. 037 * </p> 038 * @param k index of the coordinate with respect to which the partial 039 * derivative is computed 040 * @return the partial derivative function with respect to k<sup>th</sup> point coordinate 041 */ 042 MultivariateFunction partialDerivative(int k); 043 044 /** 045 * Returns the gradient function. 046 * <p>If only one partial derivative with respect to a specific coordinate is 047 * needed, it may be more efficient to use the {@link #partialDerivative(int)} method 048 * which will compute only the specified component.</p> 049 * @return the gradient function 050 */ 051 MultivariateVectorFunction gradient(); 052 053}