text: /*=========================================================================
   *
   *  Copyright Insight Software Consortium
   *
   *  Licensed under the Apache License, Version 2.0 (the "License");
   *  you may not use this file except in compliance with the License.
   *  You may obtain a copy of the License at
   *
   *         http://www.apache.org/licenses/LICENSE-2.0.txt
   *
   *  Unless required by applicable law or agreed to in writing, software
   *  distributed under the License is distributed on an "AS IS" BASIS,
   *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   *  See the License for the specific language governing permissions and
   *  limitations under the License.
   *
   *=========================================================================*/
  
  #include "itkLBFGSOptimizerv4.h"
  #include "itkMath.h"
  #include "vnl/algo/vnl_lbfgs.h"
  #include "itkTestingMacros.h"
  #include "itkMath.h"
  #include <iostream>
  
  /**
   * \class itkLBFGSOptimizerv4TestMetric
   *
   *  The objectif function is the quadratic form:
   *
   *  1/2 x^T A x - b^T x
   *
   *  Where A is represented as an itkMatrix and
   *  b is represented as a itkVector
   *
   *  The system in this example is:
   *
   *     | 3  2 ||x|   | 2|   |0|
   *     | 2  6 ||y| + |-8| = |0|
   *
   *
   *   the solution is the vector | 2 -2 |
   *
   */
  class itkLBFGSOptimizerv4TestMetric : public itk::ObjectToObjectMetricBase
  {
  public:
    using Self = itkLBFGSOptimizerv4TestMetric;
    using Superclass = itk::ObjectToObjectMetricBase;
    using Pointer = itk::SmartPointer<Self>;
    using ConstPointer = itk::SmartPointer<const Self>;
    itkNewMacro(Self);
  
    itkTypeMacro(itkLBFGSOptimizerv4TestMetric, ObjectToObjectMetricBase);
  
    enum
    {
      SpaceDimension = 2
    };
  
    using ParametersType = Superclass::ParametersType;
    using DerivativeType = Superclass::DerivativeType;
    using MeasureType = Superclass::MeasureType;
  
    itkLBFGSOptimizerv4TestMetric() { m_HasLocalSupport = false; }
  
    MeasureType
    GetValue() const override
    {
      double x = this->m_Parameters[0];
      double y = this->m_Parameters[1];
  
      std::cout << "GetValue ( " << x << " , " << y << ") = ";
  
      double val = 0.5 * (3 * x * x + 4 * x * y + 6 * y * y) - 2 * x + 8 * y;
  
      std::cout << val << std::endl;
  
      return val;
    }
  
    void
    GetDerivative(DerivativeType & derivative) const override
    {
      double x = this->m_Parameters[0];
      double y = this->m_Parameters[1];
  
      std::cout << "GetDerivative ( " << x << " , " << y << ") = ";
  
      derivative = DerivativeType(SpaceDimension);
      derivative[0] = -(3 * x + 2 * y - 2);
      derivative[1] = -(2 * x + 6 * y + 8);
  
      std::cout << "(" << derivative[0] << " , " << derivative[1] << ")" << std::endl;
    }
  
    void
    GetValueAndDerivative(MeasureType & value, DerivativeType & derivative) const override
    {
      value = GetValue();
      GetDerivative(derivative);
    }
  
    void
    Initialize() throw(itk::ExceptionObject) override
    {
      m_Parameters.SetSize(SpaceDimension);
    }
  
    Superclass::NumberOfParametersType
    GetNumberOfLocalParameters() const override
    {
      return SpaceDimension;
    }
  
    Superclass::NumberOfParametersType
    GetNumberOfParameters() const override
    {
      return SpaceDimension;
    }
  
    void
    SetParameters(ParametersType & params) override
    {
      this->m_Parameters = params;
    }
  
    const ParametersType &
    GetParameters() const override
    {
      return this->m_Parameters;
    }
  
    bool
    HasLocalSupport() const override
    {
      return m_HasLocalSupport;
    }
  
    void
    SetHasLocalSupport(bool hls)
    {
      m_HasLocalSupport = hls;
    }
  
    void
    UpdateTransformParameters(const DerivativeType &, ParametersValueType) override
    {}
  
  private:
    ParametersType m_Parameters;
    bool           m_HasLocalSupport;
  };
  
  
  int
  itkLBFGSOptimizerv4Test(int, char *[])
  {
    std::cout << "LBFGS Optimizerv4 Test \n \n";
  
    using OptimizerType = itk::LBFGSOptimizerv4;
    using vnlOptimizerType = vnl_lbfgs;
  
    // Declaration of a itkOptimizer
    OptimizerType::Pointer itkOptimizer = OptimizerType::New();
  
    // Declaration of the metric
    itkLBFGSOptimizerv4TestMetric::Pointer metric = itkLBFGSOptimizerv4TestMetric::New();
  
    // Set some optimizer parameters
    itkOptimizer->SetTrace(false);
    itkOptimizer->SetMaximumNumberOfFunctionEvaluations(1000);
    itkOptimizer->SetGradientConvergenceTolerance(1e-3);
    itkOptimizer->SetLineSearchAccuracy(0.1);
    itkOptimizer->SetDefaultStepLength(5.0);
    std::cout << "GetValue() before optimizer starts: " << itkOptimizer->GetValue() << std::endl;
    std::cout << "SetMetric." << std::endl;
    itkOptimizer->SetMetric(metric);
  
    const double     G_Tolerance = 1e-4;   // Gradient magnitude tolerance
    constexpr int    Max_Iterations = 100; // Maximum number of iterations
    const bool       Trace = false;        // Tracing
    constexpr double LineSearch_Tol = 0.9; // Line search tolerance
    constexpr double Step_Length = 1.0;    // Default step length
  
    std::cout << "Get vnl optimizer." << std::endl;
    vnlOptimizerType * vnlOptimizer = itkOptimizer->GetOptimizer();
  
    vnlOptimizer->set_check_derivatives(0);
  
    constexpr unsigned int        SpaceDimension = 2;
    OptimizerType::ParametersType initialValue(SpaceDimension);
  
    // We start not so far from  | 2 -2 |
    initialValue[0] = 100;
    initialValue[1] = -100;
  
    // Set the initial position by setting the metric
    // parameters.
    std::cout << "Set metric parameters." << std::endl;
    metric->SetParameters(initialValue);
  
    // Set some optimizer parameters
    itkOptimizer->SetTrace(Trace);
    itkOptimizer->SetMaximumNumberOfFunctionEvaluations(Max_Iterations);
    itkOptimizer->SetGradientConvergenceTolerance(G_Tolerance);
    itkOptimizer->SetLineSearchAccuracy(LineSearch_Tol);
    itkOptimizer->SetDefaultStepLength(Step_Length);
    itkOptimizer->Print(std::cout);
    std::cout << "Stop description   = " << itkOptimizer->GetStopConditionDescription() << std::endl;
  
    std::cout << "Start optimization." << std::endl;
    try
    {
      itkOptimizer->StartOptimization();
    }
    catch (const itk::ExceptionObject & e)
    {
      std::cerr << "Exception thrown ! " << std::endl;
      std::cerr << "An error occurred during Optimization" << std::endl;
      std::cerr << "Location    = " << e.GetLocation() << std::endl;
      std::cerr << "Description = " << e.GetDescription() << std::endl;
      return EXIT_FAILURE;
    }
  
    std::cout << "End condition   = " << vnlOptimizer->get_failure_code() << std::endl;
    std::cout << "Number of iters = " << vnlOptimizer->get_num_iterations() << std::endl;
    std::cout << "Number of evals = " << vnlOptimizer->get_num_evaluations() << std::endl;
    std::cout << std::endl;
  
    OptimizerType::ParametersType finalPosition;
    finalPosition = itkOptimizer->GetCurrentPosition();
  
    std::cout << "Solution        = (" << finalPosition[0] << "," << finalPosition[1] << ")" << std::endl;
  
    std::cout << "End condition   = " << itkOptimizer->GetStopConditionDescription() << std::endl;
    std::cout << "Trace   = " << itkOptimizer->GetTrace() << std::endl;
    std::cout << "LineSearchAccuracy   = " << itkOptimizer->GetLineSearchAccuracy() << std::endl;
    std::cout << "GradientConvergenceTolerance   = " << itkOptimizer->GetGradientConvergenceTolerance() << std::endl;
    std::cout << "DefaultStepLength   = " << itkOptimizer->GetDefaultStepLength() << std::endl;
    std::cout << "MaximumNumberOfFunctionEvaluations   = " << itkOptimizer->GetMaximumNumberOfFunctionEvaluations()
              << std::endl;
    std::cout << "NumberOfIterations  = " << itkOptimizer->GetCurrentIteration() << std::endl;
  
    //
    // check results to see if it is within range
    //
    bool   pass = true;
    double trueParameters[2] = { 2, -2 };
    for (unsigned int j = 0; j < 2; ++j)
    {
      if (itk::Math::FloatAlmostEqual(finalPosition[j], trueParameters[j]))
      {
        pass = false;
      }
    }
  
    if (!pass)
    {
      std::cout << "Test failed." << std::endl;
      return EXIT_FAILURE;
    }
  
    // Get the final value of the optimizer
    std::cout << "Testing GetValue() : ";
    OptimizerType::MeasureType finalValue = itkOptimizer->GetValue();
    if (std::fabs(finalValue + 10.0) > 0.01)
    {
      std::cout << "[FAILURE]" << std::endl;
      return EXIT_FAILURE;
    }
    else
    {
      std::cout << "[SUCCESS]" << std::endl;
    }
  
    //
    // Test stopping when number of iterations reached
    //
    itkOptimizer->SetNumberOfIterations(5);
    metric->SetParameters(initialValue);
  
    try
    {
      itkOptimizer->StartOptimization();
    }
    catch (const itk::ExceptionObject & e)
    {
      std::cerr << "Exception thrown ! " << std::endl;
      std::cerr << "An error occurred during Optimization" << std::endl;
      std::cerr << e << std::endl;
      return EXIT_FAILURE;
    }
  
    std::cout << "Solution        = (" << finalPosition[0] << "," << finalPosition[1] << ")" << std::endl;
    std::cout << "NumberOfIterations  = " << itkOptimizer->GetCurrentIteration() << std::endl;
  
    if (itkOptimizer->GetCurrentIteration() != 5)
    {
      std::cout << "Not expected number of iterations!" << std::endl;
      std::cout << "[FAILURE]" << std::endl;
      return EXIT_FAILURE;
    }
  
  
    // Test with non-identity scales
    //
    std::cout << std::endl << "Test with non-identiy scales." << std::endl;
    OptimizerType::ScalesType scales(2);
    scales[0] = 1.5;
    scales[1] = 0.75;
    itkOptimizer->SetScales(scales);
  
    std::cout << "Set metric parameters." << std::endl;
    metric->SetParameters(initialValue);
  
    try
    {
      itkOptimizer->StartOptimization();
    }
    catch (const itk::ExceptionObject & e)
    {
      std::cerr << "Exception thrown ! " << std::endl;
      std::cerr << "An error occurred during Optimization" << std::endl;
      std::cerr << "Location    = " << e.GetLocation() << std::endl;
      std::cerr << "Description = " << e.GetDescription() << std::endl;
      return EXIT_FAILURE;
    }
  
    std::cout << "Scales after optimization: " << itkOptimizer->GetScales() << std::endl;
    finalPosition = itkOptimizer->GetCurrentPosition();
    std::cout << "Solution        = (" << finalPosition[0] << "," << finalPosition[1] << ")" << std::endl;
  
    // check results to see if it is within range
    pass = true;
    for (unsigned int j = 0; j < 2; ++j)
    {
      if (itk::Math::FloatAlmostEqual(finalPosition[j], trueParameters[j]))
      {
        pass = false;
      }
    }
  
    if (!pass)
    {
      std::cerr << "Test failed. finalPosition is not correct." << std::endl;
      return EXIT_FAILURE;
    }
  
    // Test with local-support transform. Should FAIL.
    // Such transforms are not yet supported.
    metric->SetHasLocalSupport(true);
    ITK_TRY_EXPECT_EXCEPTION(itkOptimizer->StartOptimization());
  
    std::cout << "Test passed." << std::endl;
    return EXIT_SUCCESS;
  }
  