// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics // // Copyright (c) 2009-2017 Math.NET // // Permission is hereby granted, free of charge, to any person // obtaining a copy of this software and associated documentation // files (the "Software"), to deal in the Software without // restriction, including without limitation the rights to use, // copy, modify, merge, publish, distribute, sublicense, and/or sell // copies of the Software, and to permit persons to whom the // Software is furnished to do so, subject to the following // conditions: // // The above copyright notice and this permission notice shall be // included in all copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, // WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR // OTHER DEALINGS IN THE SOFTWARE. // using System; using IStation.Numerics.LinearAlgebra; using IStation.Numerics.LinearAlgebra.Double; namespace IStation.Numerics.Optimization { public abstract class MinimizerBase { public double GradientTolerance { get; set; } public double ParameterTolerance { get; set; } public double FunctionProgressTolerance { get; set; } public int MaximumIterations { get; set; } protected const double VerySmall = 1e-15; /// /// Creates a base class for minimization /// /// The gradient tolerance /// The parameter tolerance /// The function progress tolerance /// The maximum number of iterations protected MinimizerBase(double gradientTolerance, double parameterTolerance, double functionProgressTolerance, int maximumIterations) { GradientTolerance = gradientTolerance; ParameterTolerance = parameterTolerance; FunctionProgressTolerance = functionProgressTolerance; MaximumIterations = maximumIterations; } protected ExitCondition ExitCriteriaSatisfied(IObjectiveFunctionEvaluation candidatePoint, IObjectiveFunctionEvaluation lastPoint, int iterations) { Vector relGrad = new DenseVector(candidatePoint.Point.Count); double relativeGradient = 0.0; double normalizer = Math.Max(Math.Abs(candidatePoint.Value), 1.0); for (int ii = 0; ii < relGrad.Count; ++ii) { double projectedGradient = GetProjectedGradient(candidatePoint, ii); double tmp = projectedGradient * Math.Max(Math.Abs(candidatePoint.Point[ii]), 1.0) / normalizer; relativeGradient = Math.Max(relativeGradient, Math.Abs(tmp)); } if (relativeGradient < GradientTolerance) { return ExitCondition.RelativeGradient; } if (lastPoint != null) { double mostProgress = 0.0; for (int ii = 0; ii < candidatePoint.Point.Count; ++ii) { var tmp = Math.Abs(candidatePoint.Point[ii] - lastPoint.Point[ii]) / Math.Max(Math.Abs(lastPoint.Point[ii]), 1.0); mostProgress = Math.Max(mostProgress, tmp); } if (mostProgress < ParameterTolerance) { return ExitCondition.LackOfProgress; } double functionChange = candidatePoint.Value - lastPoint.Value; if (iterations > 500 && functionChange < 0 && Math.Abs(functionChange) < FunctionProgressTolerance) return ExitCondition.LackOfProgress; } return ExitCondition.None; } protected virtual double GetProjectedGradient(IObjectiveFunctionEvaluation candidatePoint, int ii) { return candidatePoint.Gradient[ii]; } protected void ValidateGradientAndObjective(IObjectiveFunctionEvaluation eval) { foreach (var x in eval.Gradient) { if (Double.IsNaN(x) || Double.IsInfinity(x)) throw new EvaluationException("Non-finite gradient returned.", eval); } if (Double.IsNaN(eval.Value) || Double.IsInfinity(eval.Value)) throw new EvaluationException("Non-finite objective function returned.", eval); } } }