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: 799857 $ $Date: 2009-08-01 09:07:12 -0400 (Sat, 01 Aug 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 }