| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You under the Apache License, Version 2.0 |
| * (the "License"); you may not use this file except in compliance with |
| * the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| package org.apache.commons.math.optimization.general; |
| |
| import org.apache.commons.math.FunctionEvaluationException; |
| |
| /** |
| * This interface represents a preconditioner for differentiable scalar |
| * objective function optimizers. |
| * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $ |
| * @since 2.0 |
| */ |
| public interface Preconditioner { |
| |
| /** |
| * Precondition a search direction. |
| * <p> |
| * The returned preconditioned search direction must be computed fast or |
| * the algorithm performances will drop drastically. A classical approach |
| * is to compute only the diagonal elements of the hessian and to divide |
| * the raw search direction by these elements if they are all positive. |
| * If at least one of them is negative, it is safer to return a clone of |
| * the raw search direction as if the hessian was the identity matrix. The |
| * rationale for this simplified choice is that a negative diagonal element |
| * means the current point is far from the optimum and preconditioning will |
| * not be efficient anyway in this case. |
| * </p> |
| * @param point current point at which the search direction was computed |
| * @param r raw search direction (i.e. opposite of the gradient) |
| * @return approximation of H<sup>-1</sup>r where H is the objective function hessian |
| * @exception FunctionEvaluationException if no cost can be computed for the parameters |
| * @exception IllegalArgumentException if point dimension is wrong |
| */ |
| double[] precondition(double[] point, double[] r) |
| throws FunctionEvaluationException, IllegalArgumentException; |
| |
| } |