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
018 package org.apache.commons.math.analysis;
019
020 /**
021 * Extension of {@link MultivariateRealFunction} representing a differentiable
022 * multivariate real function.
023 * @version $Revision: 811685 $ $Date: 2009-09-05 13:36:48 -0400 (Sat, 05 Sep 2009) $
024 * @since 2.0
025 */
026 public interface DifferentiableMultivariateRealFunction extends MultivariateRealFunction {
027
028 /**
029 * Returns the partial derivative of the function with respect to a point coordinate.
030 * <p>
031 * The partial derivative is defined with respect to point coordinate
032 * x<sub>k</sub>. If the partial derivatives with respect to all coordinates are
033 * needed, it may be more efficient to use the {@link #gradient()} method which will
034 * compute them all at once.
035 * </p>
036 * @param k index of the coordinate with respect to which the partial
037 * derivative is computed
038 * @return the partial derivative function with respect to k<sup>th</sup> point coordinate
039 */
040 MultivariateRealFunction partialDerivative(int k);
041
042 /**
043 * Returns the gradient function.
044 * <p>If only one partial derivative with respect to a specific coordinate is
045 * needed, it may be more efficient to use the {@link #partialDerivative(int)} method
046 * which will compute only the specified component.</p>
047 * @return the gradient function
048 */
049 MultivariateVectorialFunction gradient();
050
051 }