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158 lines
6.8 KiB
158 lines
6.8 KiB
// <copyright file="BfgsTest.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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//
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// Copyright (c) 2009-2016 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using MathNet.Numerics.LinearAlgebra;
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using System;
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namespace MathNet.Numerics.Optimization.LineSearch
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{
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public abstract class WolfeLineSearch
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{
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protected double C1 { get; }
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protected double C2 { get; }
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protected double ParameterTolerance { get; }
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protected int MaximumIterations { get; }
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public WolfeLineSearch(double c1, double c2, double parameterTolerance, int maxIterations = 10)
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{
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if (c1 <= 0)
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throw new ArgumentException(string.Format("c1 {0} should be greater than 0", c1));
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if (c2 <= c1)
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throw new ArgumentException(string.Format("c1 {0} should be less than c2 {1}", c1, c2));
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if (c2 >= 1)
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throw new ArgumentException(string.Format("c2 {0} should be less than 1", c2));
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C1 = c1;
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C2 = c2;
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ParameterTolerance = parameterTolerance;
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MaximumIterations = maxIterations;
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}
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/// <summary>Implemented following http://www.math.washington.edu/~burke/crs/408/lectures/L9-weak-Wolfe.pdf</summary>
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/// <param name="startingPoint">The objective function being optimized, evaluated at the starting point of the search</param>
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/// <param name="searchDirection">Search direction</param>
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/// <param name="initialStep">Initial size of the step in the search direction</param>
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public LineSearchResult FindConformingStep(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep)
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{
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return FindConformingStep(startingPoint, searchDirection, initialStep, double.PositiveInfinity);
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}
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/// <summary></summary>
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/// <param name="startingPoint">The objective function being optimized, evaluated at the starting point of the search</param>
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/// <param name="searchDirection">Search direction</param>
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/// <param name="initialStep">Initial size of the step in the search direction</param>
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/// <param name="upperBound">The upper bound</param>
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public LineSearchResult FindConformingStep(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep, double upperBound)
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{
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ValidateInputArguments(startingPoint, searchDirection, initialStep, upperBound);
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double lowerBound = 0.0;
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double step = initialStep;
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double initialValue = startingPoint.Value;
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Vector<double> initialGradient = startingPoint.Gradient;
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double initialDd = searchDirection * initialGradient;
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IObjectiveFunction objective = startingPoint.CreateNew();
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int ii;
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MinimizationResult.ExitCondition reasonForExit = MinimizationResult.ExitCondition.None;
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for (ii = 0; ii < MaximumIterations; ++ii)
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{
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objective.EvaluateAt(startingPoint.Point + searchDirection * step);
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ValidateGradient(objective); // Differ! (added)
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ValidateValue(objective); // Differ! (added)
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double stepDd = searchDirection * objective.Gradient;
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if (objective.Value > initialValue + C1 * step * initialDd)
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{
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upperBound = step;
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step = 0.5 * (lowerBound + upperBound);
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}
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else if (WolfeCondition(stepDd,initialDd)) // Differ, weak Wolfe
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{
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lowerBound = step;
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step = double.IsPositiveInfinity(upperBound) ? 2 * lowerBound : 0.5 * (lowerBound + upperBound);
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}
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else
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{
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reasonForExit = WolfeExitCondition;
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break;
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}
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if (!double.IsInfinity(upperBound))
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{
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double maxRelChange = 0.0;
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for (int jj = 0; jj < objective.Point.Count; ++jj)
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{
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double tmp = Math.Abs(searchDirection[jj] * (upperBound - lowerBound)) / Math.Max(Math.Abs(objective.Point[jj]), 1.0);
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maxRelChange = Math.Max(maxRelChange, tmp);
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}
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if (maxRelChange < ParameterTolerance)
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{
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reasonForExit = MinimizationResult.ExitCondition.LackOfProgress;
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break;
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}
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}
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}
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if (ii == MaximumIterations && Double.IsPositiveInfinity(upperBound))
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{
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throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached. Function appears to be unbounded in search direction.", MaximumIterations));
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}
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if (ii == MaximumIterations)
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{
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throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached.", MaximumIterations));
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}
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return new LineSearchResult(objective, ii, step, reasonForExit);
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}
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protected abstract MinimizationResult.ExitCondition WolfeExitCondition { get; }
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protected abstract bool WolfeCondition(double stepDd, double initialDd);
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protected virtual void ValidateGradient(IObjectiveFunction objective)
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{
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}
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protected virtual void ValidateValue(IObjectiveFunction objective)
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{
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}
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protected virtual void ValidateInputArguments(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep, double upperBound)
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{
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}
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}
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}
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