Optimization: Try design with unifed objective function/evaluation concepts

src/Numerics/Numerics.csproj

@@ -122,8 +122,6 @@
     <Compile Include="Optimization\Implementation\NullEvaluation.cs" />
     <Compile Include="Optimization\Implementation\ObjectiveChecker.cs" />
     <Compile Include="Optimization\Implementation\WeakWolfeLineSearch.cs" />
-    <Compile Include="Optimization\IObjectiveFunction.cs" />
-    <Compile Include="Optimization\BaseObjectiveFunction.cs" />
     <Compile Include="Optimization\IUnconstrainedMinimizer.cs" />
     <Compile Include="Optimization\MinimizationOutput.cs" />
     <Compile Include="Optimization\MinimizationWithLineSearchOutput.cs" />

src/Numerics/Optimization/BaseEvaluation.cs

@@ -9,15 +9,34 @@ namespace MathNet.Numerics.Optimization
 {
     public abstract class BaseEvaluation : IEvaluation
     {
-        public EvaluationStatus Status { get; set; }
-        public Vector<double> Point { get; set; }
-        public double ValueRaw { get; set; }
-        public Vector<double> GradientRaw { get; set; }
-        public Matrix<double> HessianRaw { get; set; }
-                
-        protected BaseEvaluation()
+        public EvaluationStatus Status { get; protected set; }
+
+        protected Vector<double> PointRaw { get; set; }
+        protected double ValueRaw { get; set; }
+        protected Vector<double> GradientRaw { get; set; }
+        protected Matrix<double> HessianRaw { get; set; }
+
+        public bool GradientSupported { get; private set; }
+        public bool HessianSupported { get; private set; }
+
+        protected BaseEvaluation(bool gradient_supported, bool hessian_supported)
         {
             Status = EvaluationStatus.None;
+            this.GradientSupported = gradient_supported;
+            this.HessianSupported = hessian_supported;
+        }
+
+        public Vector<double> Point
+        {
+            get
+            {
+                return this.PointRaw;
+            }
+            set
+            {
+                this.PointRaw = value;
+                this.Status = EvaluationStatus.None;
+            }
         }
 
         public double Value
@@ -57,14 +76,9 @@ namespace MathNet.Numerics.Optimization
             }
         }
 
-        public void Reset(Vector<double> new_point)
-        {
-            this.Point = new_point;
-            this.Status = EvaluationStatus.None;
-        }
-
         protected abstract void setValue();
         protected abstract void setGradient();
         protected abstract void setHessian();
+        public abstract IEvaluation CreateNew();
     }
 }

src/Numerics/Optimization/BaseObjectiveFunction.cs

@@ -1,39 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-
-namespace MathNet.Numerics.Optimization
-{
-    public class BaseObjectiveFunction<T> : IObjectiveFunction where T : IEvaluation
-    {
-        public BaseObjectiveFunction(bool gradient_supported, bool hessian_supported)
-        {
-            _gradient_supported = gradient_supported;
-            _hessian_supported = hessian_supported;
-        }
-
-        private bool _gradient_supported;
-        private bool _hessian_supported;
-
-        public bool GradientSupported
-        {
-            get { return _gradient_supported; }
-        }
-
-        public bool HessianSupported
-        {
-            get { return _hessian_supported; }
-        }
-
-        public void Evaluate(LinearAlgebra.Vector<double> point, IEvaluation output)
-        {
-            output.Reset(point);
-        }
-
-        public virtual IEvaluation CreateEvaluationObject()
-        {
-            return default(T);
-        }
-    }
-}

src/Numerics/Optimization/IEvaluation.cs

@@ -12,17 +12,14 @@ namespace MathNet.Numerics.Optimization
     public interface IEvaluation
     {
         Vector<double> Point { get; set; }
-        EvaluationStatus Status { get; set; }
+        IEvaluation CreateNew();
 
         // Used by algorithm
+        bool GradientSupported { get; }
+        bool HessianSupported { get; }
+        EvaluationStatus Status { get; }
         double Value { get; }
         Vector<double> Gradient { get; }
         Matrix<double> Hessian { get; }
-
-        // Used by ObjectiveFunction
-        void Reset(Vector<double> new_point);
-        double ValueRaw { get; set; }
-        Vector<double> GradientRaw { get; set; }
-        Matrix<double> HessianRaw { get; set; }
     }
 }

src/Numerics/Optimization/IObjectiveFunction.cs

@@ -1,18 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-
-using MathNet.Numerics.LinearAlgebra;
-
-namespace MathNet.Numerics.Optimization
-{
-    public interface IObjectiveFunction
-    {
-        bool GradientSupported { get; }
-        bool HessianSupported { get; }
-
-        IEvaluation CreateEvaluationObject();
-        void Evaluate(Vector<double> point, IEvaluation output);   
-    }
-}

src/Numerics/Optimization/IUnconstrainedMinimizer.cs

@@ -8,7 +8,7 @@ namespace MathNet.Numerics.Optimization
 {
     public interface IUnconstrainedMinimizer
     {
-        MinimizationOutput FindMinimum(IObjectiveFunction objective, Vector<double> initial_guess);
+        MinimizationOutput FindMinimum(IEvaluation objective, Vector<double> initial_guess);
     }
 
 }

src/Numerics/Optimization/Implementation/NullEvaluation.cs

@@ -10,7 +10,7 @@ namespace MathNet.Numerics.Optimization.Implementation
     public class NullEvaluation : BaseEvaluation
     {
         public NullEvaluation(Vector<double> point) 
-            : base()
+            : base(false, false)
         {
             this.Point = point;
         }
@@ -28,5 +28,10 @@ namespace MathNet.Numerics.Optimization.Implementation
         {
             throw new NotImplementedException();
         }
+
+        public override IEvaluation CreateNew()
+        {
+            throw new NotImplementedException();
+        }
     }
 }

src/Numerics/Optimization/Implementation/ObjectiveChecker.cs

@@ -8,16 +8,21 @@ namespace MathNet.Numerics.Optimization.Implementation
 {
     public class CheckedEvaluation : IEvaluation
     {
-        private ObjectiveChecker Checker;
         public IEvaluation InnerEvaluation { get; private set; }
         private bool ValueChecked;
         private bool GradientChecked;
         private bool HessianChecked;
+        public Action<IEvaluation> ValueChecker { get; private set; }
+        public Action<IEvaluation> GradientChecker { get; private set; }
+        public Action<IEvaluation> HessianChecker { get; private set; }
 
-        public CheckedEvaluation(ObjectiveChecker checker, IEvaluation evaluation)
+
+        public CheckedEvaluation(IEvaluation objective, Action<IEvaluation> value_checker, Action<IEvaluation> gradient_checker, Action<IEvaluation> hessian_checker)
         {
-            this.Checker = checker;
-            this.InnerEvaluation = evaluation;
+            this.InnerEvaluation = objective;
+            this.ValueChecker = value_checker;
+            this.GradientChecker = gradient_checker;
+            this.HessianChecker = hessian_checker;
         }
 
         public Vector<double> Point
@@ -32,34 +37,6 @@ namespace MathNet.Numerics.Optimization.Implementation
             {
                 return this.InnerEvaluation.Status;
             }
-            set
-            {
-                this.InnerEvaluation.Status = value;
-            }
-        }
-
-        public double ValueRaw
-        {
-            get
-            {
-                return this.InnerEvaluation.Value;
-            }
-            set
-            {
-                this.InnerEvaluation.ValueRaw = value;
-            }
-        }
-
-        public Vector<double> GradientRaw
-        {
-            get { return this.InnerEvaluation.GradientRaw;  }
-            set { this.InnerEvaluation.GradientRaw = value; }
-        }
-
-        public Matrix<double> HessianRaw
-        {
-            get { return this.InnerEvaluation.HessianRaw; }
-            set { this.InnerEvaluation.HessianRaw = value; }
         }
 
         public double Value
@@ -78,7 +55,7 @@ namespace MathNet.Numerics.Optimization.Implementation
                     {
                         throw new EvaluationException("Objective function evaluation failed.", this.InnerEvaluation, e);
                     }
-                    this.Checker.ValueChecker(this.InnerEvaluation);
+                    this.ValueChecker(this.InnerEvaluation);
                     this.ValueChecked = true;
                 }
                 return this.InnerEvaluation.Value;
@@ -101,7 +78,7 @@ namespace MathNet.Numerics.Optimization.Implementation
                     {
                         throw new EvaluationException("Objective gradient evaluation failed.", this.InnerEvaluation, e);
                     }
-                    this.Checker.GradientChecker(this.InnerEvaluation);
+                    this.GradientChecker(this.InnerEvaluation);
                     this.GradientChecked = true;
                 }
                 return this.InnerEvaluation.Gradient;
@@ -124,60 +101,26 @@ namespace MathNet.Numerics.Optimization.Implementation
                     {
                         throw new EvaluationException("Objective hessian evaluation failed.", this.InnerEvaluation, e);
                     }
-                    this.Checker.HessianChecker(InnerEvaluation);
+                    this.HessianChecker(InnerEvaluation);
                     this.HessianChecked = true;
                 }
                 return this.InnerEvaluation.Hessian;
             }
         }
 
-        public void Reset(Vector<double> new_point)
+        public IEvaluation CreateNew()
         {
-            this.InnerEvaluation.Reset(new_point);
-        }
-    }
-
-    public class ObjectiveChecker : IObjectiveFunction
-    {
-        public IObjectiveFunction InnerObjective { get; private set; }
-        public Action<IEvaluation> ValueChecker { get; private set; }
-        public Action<IEvaluation> GradientChecker { get; private set; }
-        public Action<IEvaluation> HessianChecker { get; private set; }
-
-        public ObjectiveChecker(IObjectiveFunction objective, Action<IEvaluation> value_checker, Action<IEvaluation> gradient_checker, Action<IEvaluation> hessian_checker)
-        {
-            this.InnerObjective = objective;
-            this.ValueChecker = value_checker;
-            this.GradientChecker = gradient_checker;
-            this.HessianChecker = hessian_checker;
+            return new CheckedEvaluation(this.InnerEvaluation, this.ValueChecker, this.GradientChecker, this.HessianChecker);
         }
 
         public bool GradientSupported
         {
-            get { return this.InnerObjective.GradientSupported; }
+            get { return this.InnerEvaluation.GradientSupported; }
         }
 
         public bool HessianSupported
         {
-            get { return this.InnerObjective.HessianSupported; }
-        }
-
-        public void Evaluate(Vector<double> point, IEvaluation output)
-        {
-            try
-            {
-                this.InnerObjective.Evaluate(point, output);
-            }
-            catch (Exception e)
-            {
-                throw new EvaluationException("Objective evaluation failed.", new NullEvaluation(point), e);
-            }
-        }
-
-
-        public IEvaluation CreateEvaluationObject()
-        {
-            return this.InnerObjective.CreateEvaluationObject();
+            get { return this.InnerEvaluation.HessianSupported; }
         }
     }
 }

src/Numerics/Optimization/Implementation/WeakWolfeLineSearch.cs

@@ -23,11 +23,11 @@ namespace MathNet.Numerics.Optimization.Implementation
         }
 
         // Implemented following http://www.math.washington.edu/~burke/crs/408/lectures/L9-weak-Wolfe.pdf
-        public LineSearchOutput FindConformingStep(IObjectiveFunction objective, IEvaluation starting_point, Vector<double> search_direction, double initial_step)
+        public LineSearchOutput FindConformingStep(IEvaluation objective, IEvaluation starting_point, Vector<double> search_direction, double initial_step)
         {
 
-            if (!(objective is ObjectiveChecker))
-                objective = new ObjectiveChecker(objective, this.ValidateValue, this.ValidateGradient, null);
+            if (!(objective is CheckedEvaluation))
+                objective = new CheckedEvaluation(objective, this.ValidateValue, this.ValidateGradient, null);
 
             double lower_bound = 0.0;
             double upper_bound = Double.PositiveInfinity;
@@ -39,11 +39,11 @@ namespace MathNet.Numerics.Optimization.Implementation
             double initial_dd = search_direction * initial_gradient;
 
             int ii;
-            IEvaluation candidate_eval = objective.CreateEvaluationObject();
+            IEvaluation candidate_eval = objective.CreateNew();
             MinimizationOutput.ExitCondition reason_for_exit = MinimizationOutput.ExitCondition.None;
             for (ii = 0; ii < this.MaximumIterations; ++ii)
             {
-                objective.Evaluate(starting_point.Point + search_direction * step, candidate_eval);
+                candidate_eval.Point = starting_point.Point + search_direction * step;
 
                 double step_dd = search_direction * candidate_eval.Gradient;
 

src/Numerics/Optimization/NewtonMinimizer.cs

@@ -21,7 +21,7 @@ namespace MathNet.Numerics.Optimization
             this.UseLineSearch = use_line_search;
         }
 
-        public MinimizationOutput FindMinimum(IObjectiveFunction objective, Vector<double> initial_guess)
+        public MinimizationOutput FindMinimum(IEvaluation objective, Vector<double> initial_guess)
         {
             if (!objective.GradientSupported)
                 throw new IncompatibleObjectiveException("Gradient not supported in objective function, but required for Newton minimization.");
@@ -29,11 +29,11 @@ namespace MathNet.Numerics.Optimization
             if (!objective.HessianSupported)
                 throw new IncompatibleObjectiveException("Hessian not supported in objective function, but required for Newton minimization.");
 
-            if (!(objective is ObjectiveChecker))
-                objective = new ObjectiveChecker(objective, this.ValidateObjective, this.ValidateGradient, this.ValidateHessian);
+            if (!(objective is CheckedEvaluation))
+                objective = new CheckedEvaluation(objective, this.ValidateObjective, this.ValidateGradient, this.ValidateHessian);
 
-            IEvaluation initial_eval = objective.CreateEvaluationObject();
-            objective.Evaluate(initial_guess, initial_eval);
+            IEvaluation initial_eval = objective.CreateNew();
+            initial_eval.Point = initial_guess;
 
             // Check that we're not already done
             if (this.ExitCriteriaSatisfied(initial_guess, initial_eval.Gradient))
@@ -81,7 +81,7 @@ namespace MathNet.Numerics.Optimization
                 }
                 else
                 {
-                    objective.Evaluate(candidate_point.Point + search_direction, candidate_point);
+                    candidate_point.Point = candidate_point.Point + search_direction;
                 }
 
                 tmp_line_search = false;

src/UnitTests/OptimizationTests/TestNewtonMinimizer.cs

@@ -11,9 +11,9 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
 {
     public class RosenbrockEvaluation : BaseEvaluation
     {
-        public const bool SupportsGradient = true;
-        public const bool SupportsHessian = true;
-                
+        public RosenbrockEvaluation()
+            : base(true, true) { }
+
         protected override void setValue()
         {
             this.ValueRaw = RosenbrockFunction.Value(this.Point);
@@ -28,6 +28,11 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         {
             this.HessianRaw = RosenbrockFunction.Hessian(this.Point);
         }
+
+        public override IEvaluation CreateNew()
+        {
+            return new RosenbrockEvaluation();
+        }
     }
 
     [TestFixture]
@@ -37,7 +42,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Rosenbrock_Easy()
         {
-            var obj = new BaseObjectiveFunction<RosenbrockEvaluation>(RosenbrockEvaluation.SupportsGradient, RosenbrockEvaluation.SupportsHessian);
+            var obj = new RosenbrockEvaluation();
 
             var solver = new NewtonMinimizer(1e-5, 1000);
             var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[] { 1.2, 1.2 }));
@@ -49,7 +54,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Rosenbrock_Hard()
         {
-            var obj = new BaseObjectiveFunction<RosenbrockEvaluation>(RosenbrockEvaluation.SupportsGradient, RosenbrockEvaluation.SupportsHessian);
+            var obj = new RosenbrockEvaluation();
             var solver = new NewtonMinimizer(1e-5, 1000);
             var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[] { -1.2, 1.0 }));
 
@@ -60,7 +65,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Rosenbrock_Overton()
         {
-            var obj = new BaseObjectiveFunction<RosenbrockEvaluation>(RosenbrockEvaluation.SupportsGradient, RosenbrockEvaluation.SupportsHessian);
+            var obj = new RosenbrockEvaluation();
             var solver = new NewtonMinimizer(1e-5, 1000);
             var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[] { -0.9, -0.5 }));
 
@@ -71,7 +76,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Linesearch_Rosenbrock_Easy()
         {
-            var obj = new BaseObjectiveFunction<RosenbrockEvaluation>(RosenbrockEvaluation.SupportsGradient, RosenbrockEvaluation.SupportsHessian);
+            var obj = new RosenbrockEvaluation();
             var solver = new NewtonMinimizer(1e-5, 1000, true);
             var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[] { 1.2, 1.2 }));
 
@@ -82,7 +87,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Linesearch_Rosenbrock_Hard()
         {
-            var obj = new BaseObjectiveFunction<RosenbrockEvaluation>(RosenbrockEvaluation.SupportsGradient, RosenbrockEvaluation.SupportsHessian);
+            var obj = new RosenbrockEvaluation();
             var solver = new NewtonMinimizer(1e-5, 1000, true);
             var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[] { -1.2, 1.0 }));
 
@@ -93,7 +98,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Linesearch_Rosenbrock_Overton()
         {
-            var obj = new BaseObjectiveFunction<RosenbrockEvaluation>(RosenbrockEvaluation.SupportsGradient, RosenbrockEvaluation.SupportsHessian);
+            var obj = new RosenbrockEvaluation();
             var solver = new NewtonMinimizer(1e-5, 1000, true);
             var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[] { -0.9, -0.5 }));