/*=========================================================================
 *
 *  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 <iostream>

#include "itkMaximumRatioDecisionRule.h"
#include "itkTestingMacros.h"


int
itkMaximumRatioDecisionRuleTest(int, char *[])
{

  using DecisionRuleType = itk::Statistics::MaximumRatioDecisionRule;
  auto decisionRule = DecisionRuleType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(decisionRule, MaximumRatioDecisionRule, DecisionRule);


  DecisionRuleType::MembershipVectorType discriminantScores;
  discriminantScores.resize(3);

  discriminantScores[0] = 0.3;
  discriminantScores[1] = 0.5;
  discriminantScores[2] = 0.2;

  DecisionRuleType::PriorProbabilityVectorType aPrioris;
  aPrioris.resize(3);

  aPrioris[0] = 0.2;
  aPrioris[1] = 0.1;
  aPrioris[2] = 0.6;

  decisionRule->SetPriorProbabilities(aPrioris);
  for (auto & value : aPrioris)
  {
    auto index = &value - &aPrioris.front();
    ITK_TEST_SET_GET_VALUE(value, decisionRule->GetPriorProbabilities()[index]);
  }

  if (decisionRule->Evaluate(discriminantScores) != 2)
  {
    std::cout << "[FAILED]" << std::endl;
    return EXIT_FAILURE;
  }

  // run with uniform prior
  aPrioris.clear();
  decisionRule->SetPriorProbabilities(aPrioris);
  for (auto & value : aPrioris)
  {
    auto index = &value - &aPrioris.front();
    ITK_TEST_SET_GET_VALUE(value, decisionRule->GetPriorProbabilities()[index]);
  }

  if (decisionRule->Evaluate(discriminantScores) != 1)
  {
    std::cout << "[FAILED]" << std::endl;
    return EXIT_FAILURE;
  }

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