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 * @since 2.0
024 * @deprecated as of 3.1 replaced by {@link org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableFunction}
025 */
026@Deprecated
027public interface DifferentiableMultivariateFunction extends MultivariateFunction {
028
029    /**
030     * Returns the partial derivative of the function with respect to a point coordinate.
031     * <p>
032     * The partial derivative is defined with respect to point coordinate
033     * x<sub>k</sub>. If the partial derivatives with respect to all coordinates are
034     * needed, it may be more efficient to use the {@link #gradient()} method which will
035     * compute them all at once.
036     * </p>
037     * @param k index of the coordinate with respect to which the partial
038     * derivative is computed
039     * @return the partial derivative function with respect to k<sup>th</sup> point coordinate
040     */
041    MultivariateFunction partialDerivative(int k);
042
043    /**
044     * Returns the gradient function.
045     * <p>If only one partial derivative with respect to a specific coordinate is
046     * needed, it may be more efficient to use the {@link #partialDerivative(int)} method
047     * which will compute only the specified component.</p>
048     * @return the gradient function
049     */
050    MultivariateVectorFunction gradient();
051
052}