Switching computer

src/Numerics/Numerics.csproj

@@ -117,6 +117,7 @@
     <Compile Include="OdeSolvers\RungeKutta.cs" />
     <Compile Include="Optimization\BaseEvaluation.cs" />
     <Compile Include="Optimization\BaseObjectiveFunction.cs" />
+    <Compile Include="Optimization\LineSearch\WolfeLineSearch.cs" />
     <Compile Include="Optimization\NelderMeadSimplex.cs" />
     <Compile Include="Optimization\ObjectiveFunctions\LazyObjectiveFunctionBase.cs" />
     <Compile Include="Optimization\Exceptions.cs" />

src/Numerics/Optimization/BfgsBMinimizer.cs

@@ -6,6 +6,10 @@ using MathNet.Numerics.Optimization.LineSearch;
 
 namespace MathNet.Numerics.Optimization
 {
+    /// <summary>
+    /// Broyden–Fletcher–Goldfarb–Shanno Bounded (BFGS-B) algorithm is an iterative method for solving box-constrained nonlinear optimization problems
+    /// http://www.ece.northwestern.edu/~nocedal/PSfiles/limited.ps.gz
+    /// </summary>
     public class BfgsBMinimizer
     {
         public double GradientTolerance { get; set; }

src/Numerics/Optimization/BfgsMinimizer.cs

@@ -4,6 +4,9 @@ using MathNet.Numerics.Optimization.LineSearch;
 
 namespace MathNet.Numerics.Optimization
 {
+    /// <summary>
+    /// Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems
+    /// </summary>
     public class BfgsMinimizer
     {
         public double GradientTolerance { get; set; }

src/Numerics/Optimization/LineSearch/StrongWolfeLineSearch.cs

@@ -3,109 +3,19 @@ using MathNet.Numerics.LinearAlgebra;
 
 namespace MathNet.Numerics.Optimization.LineSearch
 {
-    public class StrongWolfeLineSearch
+    public class StrongWolfeLineSearch : WolfeLineSearch
     {
-        public double C1 { get; set; }
-        public double C2 { get; set; }
-        public double ParameterTolerance { get; set; }
-        public int MaximumIterations { get; set; }
-
         public StrongWolfeLineSearch(double c1, double c2, double parameterTolerance, int maxIterations = 10)
+            : base(c1, c2, parameterTolerance, maxIterations)
         {
-            C1 = c1;
-            C2 = c2;
-            ParameterTolerance = parameterTolerance;
-            MaximumIterations = maxIterations;
+            // Validation in base class
         }
 
-        // Implemented following http://www.math.washington.edu/~burke/crs/408/lectures/L9-weak-Wolfe.pdf
-        public LineSearchResult FindConformingStep(IObjectiveFunctionEvaluation objective, Vector<double> searchDirection, double initialStep, double upperBound = Double.PositiveInfinity)
-        {
-            double lowerBound = 0.0;
-            double step = initialStep;
-
-            double initialValue = objective.Value;
-            Vector<double> initialGradient = objective.Gradient;
-
-            double initialDd = searchDirection*initialGradient;
-
-            int ii;
-            IObjectiveFunction candidateEval = objective.CreateNew();
-            MinimizationResult.ExitCondition reasonForExit = MinimizationResult.ExitCondition.None;
-            for (ii = 0; ii < this.MaximumIterations; ++ii)
-            {
-                candidateEval.EvaluateAt(objective.Point + searchDirection*step);
-
-                double stepDd = searchDirection*candidateEval.Gradient;
-
-                if (candidateEval.Value > initialValue + C1*step*initialDd)
-                {
-                    upperBound = step;
-                    step = 0.5*(lowerBound + upperBound);
-                }
-                else if (Math.Abs(stepDd) > C2*Math.Abs(initialDd))
-                {
-                    lowerBound = step;
-                    step = Double.IsPositiveInfinity(upperBound) ? 2*lowerBound : 0.5*(lowerBound + upperBound);
-                }
-                else
-                {
-                    reasonForExit = MinimizationResult.ExitCondition.StrongWolfeCriteria;
-                    break;
-                }
-
-                if (!Double.IsInfinity(upperBound))
-                {
-                    double maxRelChange = 0.0;
-                    for (int jj = 0; jj < candidateEval.Point.Count; ++jj)
-                    {
-                        double tmp = Math.Abs(searchDirection[jj]*(upperBound - lowerBound))/Math.Max(Math.Abs(candidateEval.Point[jj]), 1.0);
-                        maxRelChange = Math.Max(maxRelChange, tmp);
-                    }
-                    if (maxRelChange < ParameterTolerance)
-                    {
-                        reasonForExit = MinimizationResult.ExitCondition.LackOfProgress;
-                        break;
-                    }
-                }
-            }
-
-            if (ii == MaximumIterations && Double.IsPositiveInfinity(upperBound))
-                throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached. Function appears to be unbounded in search direction.", MaximumIterations));
-            if (ii == MaximumIterations)
-                throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached.", MaximumIterations));
-
-            return new LineSearchResult(candidateEval, ii, step, reasonForExit);
-        }
-
-        bool Conforms(IObjectiveFunction startingPoint, Vector<double> searchDirection, double step, IObjectiveFunction endingPoint)
-        {
-            bool sufficientDecrease = endingPoint.Value <= startingPoint.Value + C1*step*(startingPoint.Gradient*searchDirection);
-            bool notTooSteep = endingPoint.Gradient*searchDirection >= C2*startingPoint.Gradient*searchDirection;
-
-            return step > 0 && sufficientDecrease && notTooSteep;
-        }
-
-        void ValidateValue(IObjectiveFunction eval)
-        {
-            if (!IsFinite(eval.Value))
-                throw new EvaluationException(String.Format("Non-finite value returned by objective function: {0}", eval.Value), eval);
-        }
-
-        void ValidateGradient(IObjectiveFunction eval)
-        {
-            foreach (double x in eval.Gradient)
-            {
-                if (!IsFinite(x))
-                {
-                    throw new EvaluationException(String.Format("Non-finite value returned by gradient: {0}", x), eval);
-                }
-            }
-        }
+        protected override MinimizationResult.ExitCondition WolfeExitCondition { get { return MinimizationResult.ExitCondition.StrongWolfeCriteria; } }
 
-        bool IsFinite(double x)
+        protected override bool WolfeCondition(double stepDd, double initialDd)
         {
-            return !(Double.IsNaN(x) || Double.IsInfinity(x));
+            return Math.Abs(stepDd) > C2 * Math.Abs(initialDd);
         }
     }
 }

src/Numerics/Optimization/LineSearch/WeakWolfeLineSearch.cs

@@ -16,111 +16,22 @@ namespace MathNet.Numerics.Optimization.LineSearch
     /// http://en.wikipedia.org/wiki/Wolfe_conditions
     /// http://www.math.washington.edu/~burke/crs/408/lectures/L9-weak-Wolfe.pdf
     /// </summary>
-    public class WeakWolfeLineSearch
+    public class WeakWolfeLineSearch : WolfeLineSearch
     {
-        readonly double _c1;
-        readonly double _c2;
-        readonly double _parameterTolerance;
-        readonly int _maximumIterations;
-
         public WeakWolfeLineSearch(double c1, double c2, double parameterTolerance, int maxIterations = 10)
+            : base(c1,c2,parameterTolerance,maxIterations)
         {
-            if (c1 <= 0)
-                throw new ArgumentException(string.Format("c1 {0} should be greater than 0", c1));
-            if (c2 <= c1)
-                throw new ArgumentException(string.Format("c1 {0} should be less than c2 {1}", c1, c2));
-            if (c2 >= 1)
-                throw new ArgumentException(string.Format("c2 {0} should be less than 1", c2));
-
-            _c1 = c1;
-            _c2 = c2;
-            _parameterTolerance = parameterTolerance;
-            _maximumIterations = maxIterations;
+            // Validation in base class
         }
 
-        /// <param name="startingPoint">The objective function being optimized, evaluated at the starting point of the search</param>
-        /// <param name="searchDirection">Search direction</param>
-        /// <param name="initialStep">Initial size of the step in the search direction</param>
-        public LineSearchResult FindConformingStep(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep)
-        {
-            if (!startingPoint.IsGradientSupported)
-                throw new ArgumentException("objective function does not support gradient");
-
-            double lowerBound = 0.0;
-            double upperBound = Double.PositiveInfinity;
-            double step = initialStep;
-
-            Vector<double> initialPoint = startingPoint.Point;
-            double initialValue = startingPoint.Value;
-            Vector<double> initialGradient = startingPoint.Gradient;
-
-            double initialDd = searchDirection * initialGradient;
-
-            var objective = startingPoint.CreateNew();
-            int ii;
-            MinimizationResult.ExitCondition reasonForExit = MinimizationResult.ExitCondition.None;
-            for (ii = 0; ii < _maximumIterations; ++ii)
-            {
-                objective.EvaluateAt(initialPoint + searchDirection * step);
-                ValidateGradient(objective);
-                ValidateValue(objective);
-
-                double stepDd = searchDirection * objective.Gradient;
-
-                if (objective.Value > initialValue + _c1 * step * initialDd)
-                {
-                    upperBound = step;
-                    step = 0.5 * (lowerBound + upperBound);
-                }
-                else if (stepDd < _c2 * initialDd)
-                {
-                    lowerBound = step;
-                    step = Double.IsPositiveInfinity(upperBound) ? 2 * lowerBound : 0.5 * (lowerBound + upperBound);
-                }
-                else
-                {
-                    reasonForExit = MinimizationResult.ExitCondition.WeakWolfeCriteria;
-                    break;
-                }
-
-                if (!Double.IsInfinity(upperBound))
-                {
-                    double maxRelChange = 0.0;
-                    for (int jj = 0; jj < objective.Point.Count; ++jj)
-                    {
-                        double tmp = Math.Abs(searchDirection[jj] * (upperBound - lowerBound)) / Math.Max(Math.Abs(objective.Point[jj]), 1.0);
-                        maxRelChange = Math.Max(maxRelChange, tmp);
-                    }
-                    if (maxRelChange < _parameterTolerance)
-                    {
-                        reasonForExit = MinimizationResult.ExitCondition.LackOfProgress;
-                        break;
-                    }
-                }
-            }
-
-            if (ii == _maximumIterations && Double.IsPositiveInfinity(upperBound))
-            {
-                throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached. Function appears to be unbounded in search direction.", _maximumIterations));
-            }
-
-            if (ii == _maximumIterations)
-            {
-                throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached.", _maximumIterations));
-            }
-
-            return new LineSearchResult(objective, ii, step, reasonForExit);
-        }
+        protected override MinimizationResult.ExitCondition WolfeExitCondition { get { return MinimizationResult.ExitCondition.WeakWolfeCriteria; } }
 
-        bool Conforms(IObjectiveFunction startingPoint, Vector<double> searchDirection, double step, IObjectiveFunction endingPoint)
+        protected override bool WolfeCondition(double stepDd, double initialDd)
         {
-            bool sufficientDecrease = endingPoint.Value <= startingPoint.Value + _c1 * step * (startingPoint.Gradient * searchDirection);
-            bool notTooSteep = endingPoint.Gradient * searchDirection >= _c2 * startingPoint.Gradient * searchDirection;
-
-            return step > 0 && sufficientDecrease && notTooSteep;
+            return stepDd < C2 * initialDd;
         }
 
-        static void ValidateValue(IObjectiveFunction eval)
+        protected override void ValidateValue(IObjectiveFunction eval)
         {
             if (!IsFinite(eval.Value))
             {
@@ -128,20 +39,26 @@ namespace MathNet.Numerics.Optimization.LineSearch
             }
         }
 
-        static void ValidateGradient(IObjectiveFunction eval)
+        protected override void ValidateInputArguments(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep, double upperBound)
+        {
+            if (!startingPoint.IsGradientSupported)
+                throw new ArgumentException("objective function does not support gradient");
+        }
+
+        protected override void ValidateGradient(IObjectiveFunction eval)
         {
             foreach (double x in eval.Gradient)
             {
                 if (!IsFinite(x))
                 {
-                    throw new EvaluationException(String.Format("Non-finite value returned by gradient: {0}", x), eval);
+                    throw new EvaluationException(string.Format("Non-finite value returned by gradient: {0}", x), eval);
                 }
             }
         }
 
         static bool IsFinite(double x)
         {
-            return !(Double.IsNaN(x) || Double.IsInfinity(x));
+            return !(double.IsNaN(x) || double.IsInfinity(x));
         }
     }
 }

src/Numerics/Optimization/LineSearch/WolfeLineSearch.cs

@@ -0,0 +1,131 @@
+using MathNet.Numerics.LinearAlgebra;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+
+namespace MathNet.Numerics.Optimization.LineSearch
+{
+    public abstract class WolfeLineSearch
+    {
+        protected double C1 { get; }
+        protected double C2 { get; }
+        protected double ParameterTolerance { get; }
+        protected int MaximumIterations { get; }
+
+        public WolfeLineSearch(double c1, double c2, double parameterTolerance, int maxIterations = 10)
+        {
+            if (c1 <= 0)
+                throw new ArgumentException(string.Format("c1 {0} should be greater than 0", c1));
+            if (c2 <= c1)
+                throw new ArgumentException(string.Format("c1 {0} should be less than c2 {1}", c1, c2));
+            if (c2 >= 1)
+                throw new ArgumentException(string.Format("c2 {0} should be less than 1", c2));
+
+            C1 = c1;
+            C2 = c2;
+            ParameterTolerance = parameterTolerance;
+            MaximumIterations = maxIterations;
+        }
+
+        /// <summary>Implemented following http://www.math.washington.edu/~burke/crs/408/lectures/L9-weak-Wolfe.pdf</summary>
+        /// <param name="startingPoint">The objective function being optimized, evaluated at the starting point of the search</param>
+        /// <param name="searchDirection">Search direction</param>
+        /// <param name="initialStep">Initial size of the step in the search direction</param>
+        public LineSearchResult FindConformingStep(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep)
+        {
+            return FindConformingStep(startingPoint, searchDirection, initialStep, double.PositiveInfinity);
+        }
+
+        /// <summary></summary>
+        /// <param name="startingPoint">The objective function being optimized, evaluated at the starting point of the search</param>
+        /// <param name="searchDirection">Search direction</param>
+        /// <param name="initialStep">Initial size of the step in the search direction</param>
+        /// <param name="upperBound">The upper bound</param>
+        public LineSearchResult FindConformingStep(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep, double upperBound)
+        {
+            ValidateInputArguments(startingPoint, searchDirection, initialStep, upperBound);
+
+            double lowerBound = 0.0;
+            double step = initialStep;
+
+            double initialValue = startingPoint.Value;
+            Vector<double> initialGradient = startingPoint.Gradient;
+
+            double initialDd = searchDirection * initialGradient;
+
+            IObjectiveFunction objective = startingPoint.CreateNew();
+            int ii;
+            MinimizationResult.ExitCondition reasonForExit = MinimizationResult.ExitCondition.None;
+            for (ii = 0; ii < MaximumIterations; ++ii)
+            {
+                objective.EvaluateAt(startingPoint.Point + searchDirection * step);
+                ValidateGradient(objective);    // Differ! (added)
+                ValidateValue(objective);       // Differ! (added)
+
+                double stepDd = searchDirection * objective.Gradient;
+
+                if (objective.Value > initialValue + C1 * step * initialDd)
+                {
+                    upperBound = step;
+                    step = 0.5 * (lowerBound + upperBound);
+                }
+                else if (WolfeCondition(stepDd,initialDd))   // Differ, weak Wolfe
+                {
+                    lowerBound = step;
+                    step = double.IsPositiveInfinity(upperBound) ? 2 * lowerBound : 0.5 * (lowerBound + upperBound);
+                }
+                else
+                {
+                    reasonForExit = WolfeExitCondition; 
+                    break;
+                }
+
+                if (!double.IsInfinity(upperBound))
+                {
+                    double maxRelChange = 0.0;
+                    for (int jj = 0; jj < objective.Point.Count; ++jj)
+                    {
+                        double tmp = Math.Abs(searchDirection[jj] * (upperBound - lowerBound)) / Math.Max(Math.Abs(objective.Point[jj]), 1.0);
+                        maxRelChange = Math.Max(maxRelChange, tmp);
+                    }
+                    if (maxRelChange < ParameterTolerance)
+                    {
+                        reasonForExit = MinimizationResult.ExitCondition.LackOfProgress;
+                        break;
+                    }
+                }
+            }
+
+            if (ii == MaximumIterations && Double.IsPositiveInfinity(upperBound))
+            {
+                throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached. Function appears to be unbounded in search direction.", MaximumIterations));
+            }
+
+            if (ii == MaximumIterations)
+            {
+                throw new MaximumIterationsException(String.Format("Maximum iterations ({0}) reached.", MaximumIterations));
+            }
+
+            return new LineSearchResult(objective, ii, step, reasonForExit);
+        }
+        protected abstract MinimizationResult.ExitCondition WolfeExitCondition { get; }
+
+        protected abstract bool WolfeCondition(double stepDd, double initialDd);
+
+        protected virtual void ValidateGradient(IObjectiveFunction objective)
+        {
+        }
+        protected virtual void ValidateValue(IObjectiveFunction objective)
+        {
+        }
+
+        protected virtual void ValidateInputArguments(IObjectiveFunctionEvaluation startingPoint, Vector<double> searchDirection, double initialStep, double upperBound)
+        {
+
+        }
+    }
+
+        
+    
+}

src/UnitTests/OptimizationTests/NelderMeadSimplexTests.cs

@@ -52,10 +52,10 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
             var nms = new NelderMeadSimplex(1e-6, 1000);
             double a = 5;
             double b = 10;
+            System.Random r = new System.Random(2);
             IObjectiveFunction objFun = ObjectiveFunction.Value((constants)=>
             {
                 double ssq = 0;
-                System.Random r = new System.Random();
                 for (double x = -10; x < 10; x += .1)
                 {
                     double yTrue = a * x * x + b * x + r.NextDouble();