/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  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
 *
 *         https://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 <algorithm>

#include "itkCommand.h"
#include "itkExhaustiveOptimizer.h"

#include "itkMath.h"
#include "itkTestingMacros.h"

/**
 *  The objectif function is the quadratic form:
 *
 *  1/2 x^T A x - b^T x
 *
 *  Where A is a matrix and b is a vector
 *  The system in this example is:
 *
 *     | 3  2 ||x|   | 2|   |0|
 *     | 2  6 ||y| + |-8| = |0|
 *
 *
 *   the solution is the vector | 2 -2 |
 *
 * \class RSGCostFunction
 */
class RSGCostFunction : public itk::SingleValuedCostFunction
{
public:
  using Self = RSGCostFunction;
  using Superclass = itk::SingleValuedCostFunction;
  using Pointer = itk::SmartPointer<Self>;
  using ConstPointer = itk::SmartPointer<const Self>;
  itkNewMacro(Self);

  enum
  {
    SpaceDimension = 2
  };

  using ParametersType = Superclass::ParametersType;
  using DerivativeType = Superclass::DerivativeType;
  using MeasureType = Superclass::MeasureType;

  RSGCostFunction() = default;


  MeasureType
  GetValue(const ParametersType & parameters) const override
  {

    double x = parameters[0];
    double y = parameters[1];

    std::cout << "GetValue( ";
    std::cout << x << ' ';
    std::cout << y << ") = ";

    MeasureType measure = 0.5 * (3 * x * x + 4 * x * y + 6 * y * y) - 2 * x + 8 * y;

    std::cout << measure << std::endl;

    return measure;
  }

  void
  GetDerivative(const ParametersType & parameters, DerivativeType & derivative) const override
  {

    double x = parameters[0];
    double y = parameters[1];

    std::cout << "GetDerivative( ";
    std::cout << x << ' ';
    std::cout << y << ") = ";

    derivative = DerivativeType(SpaceDimension);
    derivative[0] = 3 * x + 2 * y - 2;
    derivative[1] = 2 * x + 6 * y + 8;
  }


  unsigned int
  GetNumberOfParameters() const override
  {
    return SpaceDimension;
  }
};

class IndexObserver : public itk::Command
{
public:
  using Self = IndexObserver;
  using Superclass = itk::Command;
  using Pointer = itk::SmartPointer<Self>;

  itkNewMacro(IndexObserver);

  void
  Execute(const itk::Object * caller, const itk::EventObject &) override
  {
    using OptimizerType = itk::ExhaustiveOptimizer;
    const auto * optimizer = dynamic_cast<const OptimizerType *>(caller);

    if (nullptr != optimizer)
    {
      OptimizerType::ParametersType currentIndex = optimizer->GetCurrentIndex();

      if (currentIndex.GetSize() == 2)
      {
        std::cout << " @ index = " << currentIndex << std::endl;
        // Casting is safe here since the indices are always integer values (but there are stored in doubles):
        auto idx = static_cast<unsigned long>(currentIndex[0] + 21 * currentIndex[1]);
        m_VisitedIndices.push_back(idx);
      }
    }
  }

  void
  Execute(itk::Object * caller, const itk::EventObject & event) override
  {
    Execute(static_cast<const itk::Object *>(caller), event);
  }

  std::vector<unsigned long> m_VisitedIndices;
};

int
itkExhaustiveOptimizerTest(int, char *[])
{
  std::cout << "ExhaustiveOptimizer Test ";
  std::cout << std::endl << std::endl;

  using OptimizerType = itk::ExhaustiveOptimizer;

  using ScalesType = OptimizerType::ScalesType;


  // Declaration of an itkOptimizer
  auto itkOptimizer = OptimizerType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(itkOptimizer, ExhaustiveOptimizer, SingleValuedNonLinearOptimizer);


  // Index observer (enables us to check if all positions were indeed visisted):
  auto idxObserver = IndexObserver::New();
  itkOptimizer->AddObserver(itk::IterationEvent(), idxObserver);

  // Declaration of the CostFunction
  auto costFunction = RSGCostFunction::New();
  itkOptimizer->SetCostFunction(costFunction);


  using ParametersType = RSGCostFunction::ParametersType;


  const unsigned int spaceDimension = costFunction->GetNumberOfParameters();

  // We start not so far from  | 2 -2 |
  ParametersType initialPosition(spaceDimension);
  initialPosition[0] = 0.0;
  initialPosition[1] = -4.0;

  itkOptimizer->SetInitialPosition(initialPosition);


  ScalesType parametersScale(spaceDimension);
  parametersScale[0] = 1.0;
  parametersScale[1] = 1.0;

  itkOptimizer->SetScales(parametersScale);


  auto stepLength = 1.0;
  itkOptimizer->SetStepLength(stepLength);
  ITK_TEST_SET_GET_VALUE(stepLength, itkOptimizer->GetStepLength());


  using StepsType = OptimizerType::StepsType;
  StepsType steps(2);
  steps[0] = 10;
  steps[1] = 10;

  itkOptimizer->SetNumberOfSteps(steps);
  ITK_TEST_SET_GET_VALUE(steps, itkOptimizer->GetNumberOfSteps());


  std::cout << "MaximumNumberOfIterations: " << itkOptimizer->GetMaximumNumberOfIterations() << std::endl;

  try
  {
    itkOptimizer->StartOptimization();
  }
  catch (const itk::ExceptionObject & e)
  {
    std::cout << "Exception thrown ! " << std::endl;
    std::cout << "An error occurred during Optimization" << std::endl;
    std::cout << "Location    = " << e.GetLocation() << std::endl;
    std::cout << "Description = " << e.GetDescription() << std::endl;
    return EXIT_FAILURE;
  }


  bool minimumValuePass = itk::Math::abs(itkOptimizer->GetMinimumMetricValue() - -10) < 1E-3;

  std::cout << "MinimumMetricValue = " << itkOptimizer->GetMinimumMetricValue() << std::endl;
  std::cout << "Minimum Position = " << itkOptimizer->GetMinimumMetricValuePosition() << std::endl;

  bool maximumValuePass = itk::Math::abs(itkOptimizer->GetMaximumMetricValue() - 926) < 1E-3;
  std::cout << "MaximumMetricValue = " << itkOptimizer->GetMaximumMetricValue() << std::endl;
  std::cout << "Maximum Position = " << itkOptimizer->GetMaximumMetricValuePosition() << std::endl;

  ParametersType finalPosition = itkOptimizer->GetMinimumMetricValuePosition();
  std::cout << "Solution        = (";
  std::cout << finalPosition[0] << ',';
  std::cout << finalPosition[1] << ')' << std::endl;

  bool                       visitedIndicesPass = true;
  std::vector<unsigned long> visitedIndices = idxObserver->m_VisitedIndices;

  size_t requiredNumberOfSteps = (2 * steps[0] + 1) * (2 * steps[1] + 1);
  if (visitedIndices.size() != requiredNumberOfSteps)
  {
    visitedIndicesPass = false;
  }

  std::sort(visitedIndices.begin(), visitedIndices.end());

  for (size_t i = 0; i < visitedIndices.size(); ++i)
  {
    if (visitedIndices[i] != i)
    {
      visitedIndicesPass = false;
      std::cout << "Mismatch in visited index " << visitedIndices[i] << " @ " << i << std::endl;
      break;
    }
  }

  //
  // check results to see if it is within range
  //
  bool   trueParamsPass = true;
  double trueParameters[2] = { 2, -2 };
  for (unsigned int j = 0; j < 2; ++j)
  {
    if (itk::Math::abs(finalPosition[j] - trueParameters[j]) > 0.01)
    {
      trueParamsPass = false;
    }
  }

  if (!minimumValuePass || !maximumValuePass || !trueParamsPass || !visitedIndicesPass)
  {
    std::cout << "minimumValuePass   = " << minimumValuePass << std::endl;
    std::cout << "maximumValuePass   = " << maximumValuePass << std::endl;
    std::cout << "trueParamsPass     = " << trueParamsPass << std::endl;
    std::cout << "visitedIndicesPass = " << visitedIndicesPass << std::endl;
    std::cout << "Test failed." << std::endl;
    return EXIT_FAILURE;
  }


  std::cout << "Test passed." << std::endl;
  return EXIT_SUCCESS;
}