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
018package org.apache.commons.math3.optimization.general;
019
020/**
021 * This interface represents a preconditioner for differentiable scalar
022 * objective function optimizers.
023 * @deprecated As of 3.1 (to be removed in 4.0).
024 * @since 2.0
025 */
026@Deprecated
027public interface Preconditioner {
028    /**
029     * Precondition a search direction.
030     * <p>
031     * The returned preconditioned search direction must be computed fast or
032     * the algorithm performances will drop drastically. A classical approach
033     * is to compute only the diagonal elements of the hessian and to divide
034     * the raw search direction by these elements if they are all positive.
035     * If at least one of them is negative, it is safer to return a clone of
036     * the raw search direction as if the hessian was the identity matrix. The
037     * rationale for this simplified choice is that a negative diagonal element
038     * means the current point is far from the optimum and preconditioning will
039     * not be efficient anyway in this case.
040     * </p>
041     * @param point current point at which the search direction was computed
042     * @param r raw search direction (i.e. opposite of the gradient)
043     * @return approximation of H<sup>-1</sup>r where H is the objective function hessian
044     */
045    double[] precondition(double[] point, double[] r);
046}