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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  }