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      */
partialDerivative(int k)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      */
gradient()49     MultivariateVectorialFunction gradient();
50 
51 }
52