Trust Region Methods: move to separate namespace

LICENSE.md

@@ -1,7 +1,7 @@
 Math.NET Numerics License (MIT/X11)
 ===================================
 
-Copyright (c) 2002-2018 Math.NET
+Copyright (c) 2002-2019 Math.NET
 
 Permission is hereby granted, free of charge, to any person
 obtaining a copy of this software and associated documentation

src/Numerics.Tests/OptimizationTests/NonLinearCurveFittingTests.cs

@@ -1,6 +1,7 @@
 using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Double;
 using MathNet.Numerics.Optimization;
+using MathNet.Numerics.Optimization.TrustRegion;
 using NUnit.Framework;
 using System;
 
@@ -441,7 +442,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         #region Thurber
 
         // model : Thurber (https://www.itl.nist.gov/div898/strd/nls/data/thurber.shtml)
-        //       f(x; b1 ... b7) = (b1 + b2*x + b3*x^2 + b4*x^3) / (1 + b5*x + b6*x^2 + b7*x^3) 
+        //       f(x; b1 ... b7) = (b1 + b2*x + b3*x^2 + b4*x^3) / (1 + b5*x + b6*x^2 + b7*x^3)
         // derivatives:
         //       df/db1 = 1/(b5*x + b6*x^2 + b7*x^3 + 1)
         //       df/db2 = x/(b5*x + b6*x^2 + b7*x^3 + 1)
@@ -548,7 +549,7 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
                 AssertHelpers.AlmostEqualRelative(ThurberPstd[i], result.StandardErrors[i], 6);
             }
         }
-        
+
         [Test]
         public void Thurber_TRDL_Dif()
         {

src/Numerics/Optimization/ITrustRegionSubProblem.cs → src/Numerics/Optimization/TrustRegion/ITrustRegionSubProblem.cs

@@ -1,6 +1,6 @@
 using MathNet.Numerics.LinearAlgebra;
 
-namespace MathNet.Numerics.Optimization
+namespace MathNet.Numerics.Optimization.TrustRegion
 {
     public interface ITrustRegionSubproblem
     {

src/Numerics/Optimization/Subproblems/DogLegSubproblem.cs → src/Numerics/Optimization/TrustRegion/Subproblems/DogLegSubproblem.cs

@@ -1,6 +1,6 @@
 using MathNet.Numerics.LinearAlgebra;
 
-namespace MathNet.Numerics.Optimization.Subproblems
+namespace MathNet.Numerics.Optimization.TrustRegion.Subproblems
 {
     internal class DogLegSubproblem : ITrustRegionSubproblem
     {

src/Numerics/Optimization/Subproblems/NewtonCGSubproblem.cs → src/Numerics/Optimization/TrustRegion/Subproblems/NewtonCGSubproblem.cs

@@ -1,7 +1,7 @@
-using MathNet.Numerics.LinearAlgebra;
+using System;
-using System;
+using MathNet.Numerics.LinearAlgebra;
 
-namespace MathNet.Numerics.Optimization.Subproblems
+namespace MathNet.Numerics.Optimization.TrustRegion.Subproblems
 {
     internal class NewtonCGSubproblem : ITrustRegionSubproblem
     {

src/Numerics/Optimization/Subproblems/Util.cs → src/Numerics/Optimization/TrustRegion/Subproblems/Util.cs

@@ -1,16 +1,16 @@
-using MathNet.Numerics.LinearAlgebra;
+using System;
-using System;
+using MathNet.Numerics.LinearAlgebra;
 
-namespace MathNet.Numerics.Optimization.Subproblems
+namespace MathNet.Numerics.Optimization.TrustRegion.Subproblems
 {
     internal static class Util
     {
         public static Tuple<double, double> FindBeta(double alpha, Vector<double> sd, Vector<double> gn, double delta)
         {
             // Pstep is intersection of the trust region boundary
-            // Pstep = α*Psd + β*(Pgn - α*Psd) 
+            // Pstep = α*Psd + β*(Pgn - α*Psd)
             // find r so that ||Pstep|| = Δ
-            // z = α*Psd, d = (Pgn - z) 
+            // z = α*Psd, d = (Pgn - z)
             // (d^2)β^2 + (2*z*d)β + (z^2 - Δ^2) = 0
             //
             // positive β is used for the quadratic formula

src/Numerics/Optimization/TrustRegionDogLegMinimizer.cs → src/Numerics/Optimization/TrustRegion/TrustRegionDogLegMinimizer.cs

@@ -1,4 +1,4 @@
-namespace MathNet.Numerics.Optimization
+namespace MathNet.Numerics.Optimization.TrustRegion
 {
     public sealed class TrustRegionDogLegMinimizer : TrustRegionMinimizerBase
     {

src/Numerics/Optimization/TrustRegionMinimizerBase.cs → src/Numerics/Optimization/TrustRegion/TrustRegionMinimizerBase.cs

@@ -1,14 +1,14 @@
-using MathNet.Numerics.LinearAlgebra;
+using System;
-using System;
 using System.Collections.Generic;
 using System.Linq;
+using MathNet.Numerics.LinearAlgebra;
 
-namespace MathNet.Numerics.Optimization
+namespace MathNet.Numerics.Optimization.TrustRegion
 {
     public abstract class TrustRegionMinimizerBase : NonlinearMinimizerBase
     {
         /// <summary>
-        /// The trust region subproblem. 
+        /// The trust region subproblem.
         /// </summary>
         public static ITrustRegionSubproblem Subproblem;
 
@@ -51,7 +51,7 @@ namespace MathNet.Numerics.Optimization
         /// Non-linear least square fitting by the trust-region algorithm.
         /// </summary>
         /// <param name="objective">The objective model, including function, jacobian, observations, and parameter bounds.</param>
-        /// <param name="subproblem">The subproblem</param> 
+        /// <param name="subproblem">The subproblem</param>
         /// <param name="initialGuess">The initial guess values.</param>
         /// <param name="functionTolerance">The stopping threshold for L2 norm of the residuals.</param>
         /// <param name="gradientTolerance">The stopping threshold for infinity norm of the gradient vector.</param>
@@ -112,7 +112,7 @@ namespace MathNet.Numerics.Optimization
 
             // First, calculate function values and setup variables
             var P = ProjectToInternalParameters(initialGuess); // current internal parameters
-            var Pstep = Vector<double>.Build.Dense(P.Count); // the change of parameters    
+            var Pstep = Vector<double>.Build.Dense(P.Count); // the change of parameters
             var RSS = EvaluateFunction(objective, initialGuess); // Residual Sum of Squares
 
             if (maximumIterations < 0)
@@ -127,7 +127,7 @@ namespace MathNet.Numerics.Optimization
                 return new NonlinearMinimizationResult(objective, -1, exitCondition);
             }
 
-            // When only function evaluation is needed, set maximumIterations to zero, 
+            // When only function evaluation is needed, set maximumIterations to zero,
             if (maximumIterations == 0)
             {
                 exitCondition = ExitCondition.ManuallyStopped;
@@ -142,7 +142,7 @@ namespace MathNet.Numerics.Optimization
             // evaluate projected gradient and Hessian
             var jac = EvaluateJacobian(objective, P);
             var Gradient = jac.Item1; // objective.Gradient;
-            var Hessian = jac.Item2; // objective.Hessian;            
+            var Hessian = jac.Item2; // objective.Hessian;
 
             // if ||g||_oo <= gtol, found and stop
             if (Gradient.InfinityNorm() <= gradientTolerance)
@@ -182,7 +182,7 @@ namespace MathNet.Numerics.Optimization
                 var Pnew = P + Pstep; // parameters to test
                 // evaluate function at Pnew
                 var RSSnew = EvaluateFunction(objective, Pnew);
-                
+
                 // if RSS == NaN, stop
                 if (double.IsNaN(RSSnew))
                 {
@@ -204,7 +204,7 @@ namespace MathNet.Numerics.Optimization
                     delta = delta * 0.25;
                     if (delta <= radiusTolerance * (radiusTolerance + P.DotProduct(P)))
                     {
-                        exitCondition = ExitCondition.LackOfProgress; 
+                        exitCondition = ExitCondition.LackOfProgress;
                         break;
                     }
                 }

src/Numerics/Optimization/TrustRegionNewtonCGMinimizer.cs → src/Numerics/Optimization/TrustRegion/TrustRegionNewtonCGMinimizer.cs

@@ -1,4 +1,4 @@
-namespace MathNet.Numerics.Optimization
+namespace MathNet.Numerics.Optimization.TrustRegion
 {
     public sealed class TrustRegionNewtonCGMinimizer : TrustRegionMinimizerBase
     {
@@ -10,4 +10,3 @@
         { }
     }
 }
-

src/Numerics/Optimization/TrustRegionSubProblem.cs → src/Numerics/Optimization/TrustRegion/TrustRegionSubProblem.cs

@@ -1,6 +1,6 @@
-using MathNet.Numerics.Optimization.Subproblems;
+using MathNet.Numerics.Optimization.TrustRegion.Subproblems;
 
-namespace MathNet.Numerics.Optimization
+namespace MathNet.Numerics.Optimization.TrustRegion
 {
     public static class TrustRegionSubproblem
     {