AbstractScalarDifferentiableOptimizer.java

  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.  */

  18. package org.apache.commons.math3.optimization.general;

  20. import org.apache.commons.math3.analysis.DifferentiableMultivariateFunction;
  21. import org.apache.commons.math3.analysis.MultivariateVectorFunction;
  22. import org.apache.commons.math3.analysis.FunctionUtils;
  23. import org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableFunction;
  24. import org.apache.commons.math3.optimization.DifferentiableMultivariateOptimizer;
  25. import org.apache.commons.math3.optimization.GoalType;
  26. import org.apache.commons.math3.optimization.ConvergenceChecker;
  27. import org.apache.commons.math3.optimization.PointValuePair;
  28. import org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer;

  30. /**
  31.  * Base class for implementing optimizers for multivariate scalar
  32.  * differentiable functions.
  33.  * It contains boiler-plate code for dealing with gradient evaluation.
  34.  *
  35.  * @deprecated As of 3.1 (to be removed in 4.0).
  36.  * @since 2.0
  37.  */
  38. @Deprecated
  39. public abstract class AbstractScalarDifferentiableOptimizer
  40.     extends BaseAbstractMultivariateOptimizer<DifferentiableMultivariateFunction>
  41.     implements DifferentiableMultivariateOptimizer {
  42.     /**
  43.      * Objective function gradient.
  44.      */
  45.     private MultivariateVectorFunction gradient;

  47.     /**
  48.      * Simple constructor with default settings.
  49.      * The convergence check is set to a
  50.      * {@link org.apache.commons.math3.optimization.SimpleValueChecker
  51.      * SimpleValueChecker}.
  52.      * @deprecated See {@link org.apache.commons.math3.optimization.SimpleValueChecker#SimpleValueChecker()}
  53.      */
  54.     @Deprecated
  55.     protected AbstractScalarDifferentiableOptimizer() {}

  57.     /**
  58.      * @param checker Convergence checker.
  59.      */
  60.     protected AbstractScalarDifferentiableOptimizer(ConvergenceChecker<PointValuePair> checker) {
  61.         super(checker);
  62.     }

  64.     /**
  65.      * Compute the gradient vector.
  66.      *
  67.      * @param evaluationPoint Point at which the gradient must be evaluated.
  68.      * @return the gradient at the specified point.
  69.      * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
  70.      * if the allowed number of evaluations is exceeded.
  71.      */
  72.     protected double[] computeObjectiveGradient(final double[] evaluationPoint) {
  73.         return gradient.value(evaluationPoint);
  74.     }

  76.     /** {@inheritDoc} */
  77.     @Override
  78.     protected PointValuePair optimizeInternal(int maxEval,
  79.                                               final DifferentiableMultivariateFunction f,
  80.                                               final GoalType goalType,
  81.                                               final double[] startPoint) {
  82.         // Store optimization problem characteristics.
  83.         gradient = f.gradient();

  85.         return super.optimizeInternal(maxEval, f, goalType, startPoint);
  86.     }

  88.     /**
  89.      * Optimize an objective function.
  90.      *
  91.      * @param f Objective function.
  92.      * @param goalType Type of optimization goal: either
  93.      * {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
  94.      * @param startPoint Start point for optimization.
  95.      * @param maxEval Maximum number of function evaluations.
  96.      * @return the point/value pair giving the optimal value for objective
  97.      * function.
  98.      * @throws org.apache.commons.math3.exception.DimensionMismatchException
  99.      * if the start point dimension is wrong.
  100.      * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
  101.      * if the maximal number of evaluations is exceeded.
  102.      * @throws org.apache.commons.math3.exception.NullArgumentException if
  103.      * any argument is {@code null}.
  104.      */
  105.     public PointValuePair optimize(final int maxEval,
  106.                                    final MultivariateDifferentiableFunction f,
  107.                                    final GoalType goalType,
  108.                                    final double[] startPoint) {
  109.         return optimizeInternal(maxEval,
  110.                                 FunctionUtils.toDifferentiableMultivariateFunction(f),
  111.                                 goalType,
  112.                                 startPoint);
  113.     }
  114. }
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