Very minimally tested ConjugateGradient minimizer is complete.

src/Numerics/Optimization/ConjugateGradientMinimizer.cs

@@ -34,25 +34,41 @@ namespace MathNet.Numerics.Optimization
             // First step
             var steepestDirection = -gradient;
             var searchDirection = steepestDirection;
-            var result = lineSearcher.FindConformingStep(objective, searchDirection, 1.0);
+            double initialStepSize = 100 * GradientTolerance / (gradient * gradient);
+            var result = lineSearcher.FindConformingStep(objective, searchDirection, initialStepSize);
             objective = result.FunctionInfoAtMinimum;
             ValidateGradient(objective.Gradient, objective.Point);
 
+            double stepSize = (objective.Point - initialGuess).Norm(2.0);
             // Subsequent steps
             int iterations = 1;
+            int totalLineSearchSteps = result.Iterations;
+            int noLineSearchIterations = result.Iterations > 0 ? 0 : 1;
+            int steepestDescentResets = 0;
             while (!ExitCriteriaSatisfied(objective.Point, objective.Gradient) && iterations < MaximumIterations)
             {
                 var previousSteepestDirection = steepestDirection;
                 steepestDirection = -objective.Gradient;
-                var searchDirectionAdjuster = steepestDirection * (steepestDirection - previousSteepestDirection) / (previousSteepestDirection * previousSteepestDirection);
-                searchDirection = steepestDirection + searchDirectionAdjuster * previousSteepestDirection;
-                result = lineSearcher.FindConformingStep(objective, searchDirection, 1.0);
+                var searchDirectionAdjuster = Math.Max(0, steepestDirection*(steepestDirection - previousSteepestDirection)/(previousSteepestDirection*previousSteepestDirection));
+                searchDirection = steepestDirection + searchDirectionAdjuster * searchDirection;
+                if (searchDirection * objective.Gradient >= 0)
+                {
+                    searchDirection = steepestDirection;
+                    steepestDescentResets += 1;
+                }
+
+
+                result = lineSearcher.FindConformingStep(objective, searchDirection, stepSize);
+
+                noLineSearchIterations += result.Iterations == 0 ? 1 : 0;
+                totalLineSearchSteps += result.Iterations;
+				stepSize = (result.FunctionInfoAtMinimum.Point - objective.Point).Norm(2.0);
 
                 objective = result.FunctionInfoAtMinimum;
                 iterations += 1;
             }
 
-            return new MinimizationResult(objective, iterations, MinimizationResult.ExitCondition.AbsoluteGradient);
+            return new MinimizationWithLineSearchResult(objective, iterations, MinimizationResult.ExitCondition.AbsoluteGradient, totalLineSearchSteps, noLineSearchIterations);
         }
 
         private bool ExitCriteriaSatisfied(Vector<double> candidatePoint, Vector<double> gradient)

src/UnitTests/OptimizationTests/TestConjugateGradientMinimizer.cs

@@ -1,11 +1,7 @@
 using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Text;
-
-using NUnit.Framework;
-
+using MathNet.Numerics.LinearAlgebra.Double;
 using MathNet.Numerics.Optimization;
+using NUnit.Framework;
 
 namespace MathNet.Numerics.UnitTests.OptimizationTests
 {
@@ -16,17 +12,23 @@ namespace MathNet.Numerics.UnitTests.OptimizationTests
         [Test]
         public void FindMinimum_Rosenbrock_Easy()
         {
-            var obj = new SimpleObjectiveFunction(RosenbrockFunction.Value, RosenbrockFunction.Gradient);
-            var solver = new ConjugateGradientMinimizer(1e-5, 100);
-            var result = solver.FindMinimum(obj, new MathNet.Numerics.LinearAlgebra.Double.DenseVector(new double[]{1.2,1.2}));
-            Assert.That(result.MinimizingPoint[0], Is.EqualTo(1.0));
-            Assert.That(result.MinimizingPoint[1], Is.EqualTo(1.0));
+            var obj = ObjectiveFunction.Gradient(RosenbrockFunction.Value, RosenbrockFunction.Gradient);
+            var solver = new ConjugateGradientMinimizer(1e-5, 1000);
+            var result = solver.FindMinimum(obj, new DenseVector(new[]{1.2,1.2}));
+
+            Assert.That(Math.Abs(result.MinimizingPoint[0]-1.0), Is.LessThan(1e-3));
+            Assert.That(Math.Abs(result.MinimizingPoint[1] - 1.0), Is.LessThan(1e-3));
         }
 
         [Test]
         public void FindMinimum_Rosenbrock_Hard()
         {
+            var obj = ObjectiveFunction.Gradient(RosenbrockFunction.Value, RosenbrockFunction.Gradient);
+            var solver = new ConjugateGradientMinimizer(1e-5, 1000);
+            var result = solver.FindMinimum(obj, new DenseVector(new[] { -1.2, 1.0 }));
 
+            Assert.That(Math.Abs(result.MinimizingPoint[0] - 1.0), Is.LessThan(1e-3));
+            Assert.That(Math.Abs(result.MinimizingPoint[1] - 1.0), Is.LessThan(1e-3));
         }
     }
 }

src/UnitTests/UnitTests.csproj

@@ -349,10 +349,6 @@
     <Compile Include="Random\SystemRandomSourceTests.cs" />
     <Compile Include="OptimizationTests\BfgsTest.cs" />
     <Compile Include="RootFindingTests\BisectionTest.cs" />
-    <Compile Include="MatrixHelpers.cs" />
-    <Compile Include="NumberTheoryTests\GcdRelatedTest.cs" />
-    <Compile Include="NumberTheoryTests\GcdRelatedTestBigInteger.cs" />
-    <Compile Include="NumberTheoryTests\IntegerTheoryTest.cs" />
     <Compile Include="OptimizationTests\RosenbrockFunction.cs" />
     <Compile Include="OptimizationTests\TestConjugateGradientMinimizer.cs" />
     <Compile Include="PermutationTest.cs" />