#ifndef REDUCEDMODELOPTIMIZER_STRUCTS_HPP
#define REDUCEDMODELOPTIMIZER_STRUCTS_HPP
#include <string>
#include "chronoseulersimulationmodel.hpp"
#include "csvfile.hpp"
#include "drmsimulationmodel.hpp"
#include "linearsimulationmodel.hpp"
#include "simulation_structs.hpp"
#include "simulationmodelfactory.hpp"
#include "trianglepatterngeometry.hpp"
#include "unordered_map"

namespace ReducedModelOptimization {

enum BaseSimulationScenario {
  Axial,
  Shear,
  Bending,
  Dome,
  Saddle,
  S,
  NumberOfBaseSimulationScenarios
};
inline static std::vector<std::string> baseSimulationScenarioNames{
    "Axial", "Shear", "Bending", "Dome", "Saddle", "S"};

struct Colors {
  using RGBColor = std::array<float, 3>;
  inline static RGBColor patternInitial{0.518, 0.518, 0.518};
  //    inline static RGBColor fullDeformed{0.583333, 0.890196,
  //    0.109804};
  inline static RGBColor patternDeformed{0.094, 0.094, 0.094};
  //    inline static RGBColor reducedInitial{0.890196, 0.109804,
  //    0.193138};
  inline static RGBColor reducedInitial{0.518, 0.518, 0.518};
  inline static RGBColor reducedDeformed{0.262, 0.627, 0.910};
};

struct xRange {
  std::string label{};
  double min{0};
  double max{0};

  inline bool operator<(const xRange& other) { return label < other.label; }
  std::string toString() const {
    return label + "=[" + std::to_string(min) + "," + std::to_string(max) + "]";
  }

  void fromString(const std::string& s) {
    const std::size_t equalPos = s.find("=");
    label = s.substr(0, equalPos);
    const std::size_t commaPos = s.find(",");
    const size_t minBeginPos = equalPos + 2;
    min = std::stod(s.substr(minBeginPos, commaPos - minBeginPos));
    const size_t maxBeginPos = commaPos + 1;
    const std::size_t closingBracketPos = s.find("]");
    max = std::stod(s.substr(maxBeginPos, closingBracketPos - maxBeginPos));
  }

  bool operator==(const xRange& xrange) const {
    return label == xrange.label && min == xrange.min && max == xrange.max;
  }

  std::tuple<std::string, double, double> toTuple() const {
    return std::make_tuple(label, min, max);
  }

  void set(const std::tuple<std::string, double, double>& inputTuple) {
    if (std::get<1>(inputTuple) > std::get<2>(inputTuple)) {
      std::cerr << "Invalid xRange tuple. Second argument(min) cant be smaller "
                   "than the third(max)"
                << std::endl;
      std::terminate();
      //            return;
    }
    std::tie(label, min, max) = inputTuple;
  }
};

enum OptimizationParameterIndex {
  E,
  A,
  I2,
  I3,
  J,
  R,
  Theta,
  NumberOfOptimizationVariables
};

inline int getParameterIndex(const std::string& s) {
  if ("E" == s) {
    return E;
  } else if ("A" == s) {
    return A;
  } else if ("I2" == s) {
    return I2;
  } else if ("I3" == s) {
    return I3;
  } else if ("J" == s) {
    return J;
  } else if ("R" == s || "HexSize" == s) {
    return R;
  } else if ("Theta" == s || "HexAngle" == s) {
    return Theta;
  } else {
    std::cerr
        << "Input is not recognized as a valid optimization variable index:"
        << s << std::endl;
    return -1;
  }
}

struct Settings {
  inline static std::string defaultFilename{"OptimizationSettings.json"};
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMaxMagnitudes{0.590241,
  //                                                                                  0.888372,
  //                                                                                  0.368304,
  //                                                                                  0.0127508,
  //                                                                                  1.18079,
  //                                                                                  0}; //final
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMaxMagnitudes{
  //        0.590241 / 6, 0.588372 / 6, 0.368304 / 2, 0.05, 1.18 / 4, 0};
  //        //final b,h= 0.001

  std::array<double, NumberOfBaseSimulationScenarios> baseScenarioMaxMagnitudes{
      0.590241 / 3, 0.588372 / 3, 0.368304,
      0.1,          1.18 / 2,     0};  // final b,h= 0.002
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMaxMagnitudes{0, 0, 0, 0.1, 0};

  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMaxMagnitudes{20.85302947095844,
  //                                  1.8073431893126763,
  //                                  0.2864731720436702,
  //                                  0.14982243562639147,
  //                                  0.18514829631059054};//median
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMaxMagnitudes{1.1725844893199244,
  //                                  0.3464275389927846,
  //                                  0.09527915004635197,
  //                                  0.06100757786262501,
  //                                  0.10631914784812076}; //5_1565 0.03axial
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMaxMagnitudes{/*15*/ 0 /*1.711973658196369*/,
  //                                  1.878077115238504,
  //                                  0.8,
  //                                  0.15851675178327318,
  //                                  0.8,
  //                                  /*1.711973658196369*/ 0}; //custom
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMaxMagnitudes{0,
  //                                  14.531854387244818,
  //                                  0.38321932238436796,
  //                                  0.21381267870193282,
  //                                  0.28901381608791094,
  //                                  1.711973658196369}; //9_14423
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMaxMagnitudes{1.1725844893199244,
  //                                  0.3464275389927846,
  //                                  0.09527915004635197,
  //                                  0.06100757786262501,
  //                                  0.10631914784812076}; //5_1565 0.03axial
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMagnitudes{9.82679, 0.138652, 0.247242, 0.739443,
  //        0.00675865}; //Hyperparam opt
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMaxMagnitudes{
  //        30, 8, 0.4421382884449713, 0.22758433903942452, 0.3247935583883217};

  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMagnitudes{10 * 6.310485381644259,
  //                               10 * 1.7100142258819078,
  //                               10 * 0.18857048204421728,
  //                               10 * 0.10813697502645818,
  //                               10 * 0.11982893539207524}; //6_338
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMagnitudes{7.72224,
  //                                                                               7.72224,
  //                                                                               0.89468,
  //                                                                               0.445912,
  //                                                                               0.625905};
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMagnitudes{0.407714,
  //                                                                               22.3524,
  //                                                                               0.703164,
  //                                                                               0.0226138,
  //                                                                               0.161316};
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMagnitudes{2, 1, 0.4, 0.2, 0.2}; //8_15444 magnitudes
  //        from randomBending0

  //        std::array<double, NumberOfBaseSimulationScenarios>
  //            baseScenarioMagnitudes{1.0600375226325425,
  //                                   0.6381040280710403,
  //                                   0.17201755995098306,
  //                                   0.0706601822149856,
  //                                   0.13578373479448072}; //8_15444
  //                                   magnitudes from displacements
  //    std::array<double, NumberOfBaseSimulationScenarios>
  //        baseScenarioMagnitudes{10 * 1.0600375226325425,
  //                               10 * 0.6381040280710403,
  //                               10 * 0.17201755995098306,
  //                               10 * 0.0706601822149856,
  //                               10 * 0.13578373479448072}; //8_15444
  //                               magnitudes from displacements

  //    std::array<double, NumberOfBaseSimulationScenarios>
  //    baseScenarioMaxMagnitudes;

  std::string getOptimizationSettingsLabel() const {
    return simulationModelLabel_groundTruth + "_" +
           simulationModelLabel_reducedModel;
  }
  std::vector<std::vector<OptimizationParameterIndex>> optimizationStrategy = {
      //        {E,A, I2, I3, J, R, Theta}};
      {A, I2, I3, J, R, Theta}};
  //        {E}};
  //        {E, R, Theta}};
  //        {A, R, Theta}};
  std::optional<std::vector<double>>
      optimizationVariablesGroupsWeights;  // TODO:should be removed in the
                                           // future if not a splitting strategy
                                           // is used for the optimization
  enum NormalizationStrategy { NonNormalized, Epsilon };
  inline static std::vector<std::string> normalizationStrategyStrings{
      "NonNormalized", "Epsilon"};
  NormalizationStrategy normalizationStrategy{Epsilon};
  std::array<xRange, NumberOfOptimizationVariables> variablesRanges{
      xRange{"E", 1e-3, 1e3},  xRange{"A", 1e-3, 1e3}, xRange{"I2", 1e-3, 1e3},
      xRange{"I3", 1e-3, 1e3}, xRange{"J", 1e-3, 1e3}, xRange{"R", 0.05, 0.95},
      xRange{"Theta", -30, 30}};
  inline static std::string simulationModelLabel_groundTruth{
      //      ChronosEulerNonLinearSimulationModel::label};
      DRMSimulationModel::label};
  inline static std::string simulationModelLabel_reducedModel{
      LinearSimulationModel::label};
  //      ChronosEulerLinearSimulationModel::label};
  struct SettingsPSO {
    int numberOfParticles{200};
#ifdef USE_PSO
    inline static std::string optimizerName{"pso"};
#else
    inline static std::string optimizerName{"sa"};
#endif
  } pso;

  struct SettingsDlibGlobal {
    int numberOfFunctionCalls{100000};
  } dlib;

  double solverAccuracy{1e-2};
  double translationEpsilon{4e-3};
  //    double translationEpsilon{0};
  //    double angularDistanceEpsilon{vcg::math::ToRad(2.0)};
  double angularDistanceEpsilon{vcg::math::ToRad(0.0)};
  double targetBaseTriangleSize{0.03};
  CrossSectionType beamDimensions_pattern{0.002, 0.002};
  double youngsModulus_pattern{1e9};
  std::filesystem::path intermediateResultsDirectoryPath;
  struct ObjectiveWeights {
    double translational{1.2};
    double rotational{0.8};
    bool operator==(const ObjectiveWeights& other) const;
  };
  std::array<ObjectiveWeights, NumberOfBaseSimulationScenarios>
      perBaseScenarioObjectiveWeights;
  //    std::array<ObjectiveWeights, NumberOfBaseSimulationScenarios>
  //    perBaseScenarioObjectiveWeights{
  //        {{1.95, 0.05}, {0.87, 1.13}, {0.37, 1.63}, {0.01, 1.99},
  //        {0.94, 1.06}, {1.2, 0.8}}};
  std::array<std::pair<double, double>, NumberOfBaseSimulationScenarios>
  convertObjectiveWeightsToPairs() const {
    std::array<std::pair<double, double>, NumberOfBaseSimulationScenarios>
        objectiveWeightsPairs;
    for (int baseScenario = Axial;
         baseScenario != NumberOfBaseSimulationScenarios; baseScenario++) {
      objectiveWeightsPairs[baseScenario] = std::make_pair(
          perBaseScenarioObjectiveWeights[baseScenario].translational,
          perBaseScenarioObjectiveWeights[baseScenario].rotational);
    }
    return objectiveWeightsPairs;
  }

  struct JsonKeys {
    inline static std::string OptimizationStrategy{"OptimizationStrategy"};
    inline static std::string OptimizationStrategyGroupWeights{
        "OptimizationStrategyGroupWeights"};
    inline static std::string OptimizationVariables{"OptimizationVariables"};
    inline static std::string NumberOfFunctionCalls{"NumberOfFunctionCalls"};
    inline static std::string SolverAccuracy{"SolverAccuracy"};
    inline static std::string ObjectiveWeights{"ObjectiveWeight"};
  };

  nlohmann::json toJson() const {
    nlohmann::json json;
    json[GET_VARIABLE_NAME(optimizationStrategy)] = optimizationStrategy;
    if (optimizationVariablesGroupsWeights.has_value()) {
      json[GET_VARIABLE_NAME(ptimizationStrategyGroupWeights)] =
          optimizationVariablesGroupsWeights.value();
    }
    // write x ranges
    const std::array<std::tuple<std::string, double, double>,
                     NumberOfOptimizationVariables>
        xRangesAsTuples = [=]() {
          std::array<std::tuple<std::string, double, double>,
                     NumberOfOptimizationVariables>
              xRangesAsTuples;
          for (int optimizationParameterIndex = E;
               optimizationParameterIndex != NumberOfOptimizationVariables;
               optimizationParameterIndex++) {
            xRangesAsTuples[optimizationParameterIndex] =
                variablesRanges[optimizationParameterIndex].toTuple();
          }
          return xRangesAsTuples;
        }();
    json[JsonKeys::OptimizationVariables] = xRangesAsTuples;
    //        for (size_t xRangeIndex = 0; xRangeIndex < variablesRanges.size();
    //        xRangeIndex++) {
    //            const auto &xRange = variablesRanges[xRangeIndex];
    //            json[JsonKeys::OptimizationVariables + "_" +
    //            std::to_string(xRangeIndex)]
    //                = xRange.toString();
    //        }

    json[GET_VARIABLE_NAME(solverAccuracy)] = solverAccuracy;
    // Objective weights
    std::array<std::pair<double, double>, NumberOfBaseSimulationScenarios>
        objectiveWeightsPairs;
    std::transform(perBaseScenarioObjectiveWeights.begin(),
                   perBaseScenarioObjectiveWeights.end(),
                   objectiveWeightsPairs.begin(),
                   [](const ObjectiveWeights& objectiveWeights) {
                     return std::make_pair(objectiveWeights.translational,
                                           objectiveWeights.rotational);
                   });
    json[JsonKeys::ObjectiveWeights] = objectiveWeightsPairs;
    json[GET_VARIABLE_NAME(translationEpsilon)] = translationEpsilon;
    json[GET_VARIABLE_NAME(angularDistanceEpsilon)] =
        vcg::math::ToDeg(angularDistanceEpsilon);
    json[GET_VARIABLE_NAME(targetBaseTriangleSize)] = targetBaseTriangleSize;
    json[GET_VARIABLE_NAME(baseScenarioMaxMagnitudes)] =
        baseScenarioMaxMagnitudes;
    json[GET_VARIABLE_NAME(simulationModelLabel_groundTruth)] =
        simulationModelLabel_groundTruth;
    json[GET_VARIABLE_NAME(simulationModelLabel_reducedModel)] =
        simulationModelLabel_reducedModel;
    json[GET_VARIABLE_NAME(youngsModulus_pattern)] = youngsModulus_pattern;
    nlohmann::json json_dimensions;
    beamDimensions_pattern.to_json(json_dimensions, beamDimensions_pattern);
    json.update(json_dimensions);

#ifdef USE_ENSMALLEN
#ifdef USE_PSO
    json[GET_VARIABLE_NAME(pso.numberOfParticles)] = pso.numberOfParticles;
#endif
    json[GET_VARIABLE_NAME(pso.optimizerName)] = pso.optimizerName;
#else
    json[GET_VARIABLE_NAME(dlib.numberOfFunctionCalls)] =
        dlib.numberOfFunctionCalls;
#endif
    return json;
  }
  void save(const std::filesystem::path& saveToPath) {
    assert(std::filesystem::is_directory(saveToPath));
    nlohmann::json json = toJson();
    std::filesystem::path jsonFilePath(
        std::filesystem::path(saveToPath).append(defaultFilename));
    std::ofstream jsonFile(jsonFilePath.string());
    jsonFile << json;
    jsonFile.close();
  }

  bool load(const std::filesystem::path& jsonFilePath) {
    if (!std::filesystem::exists(jsonFilePath)) {
      std::cerr << "Optimization settings could not be loaded because input "
                   "filepath does "
                   "not exist:"
                << jsonFilePath << std::endl;
      assert(false);
      return false;
    }
    std::ifstream ifs(jsonFilePath);
    nlohmann::json json;
    ifs >> json;

    if (json.contains(GET_VARIABLE_NAME(optimizationStrategy))) {
      optimizationStrategy = std::vector<
          std::vector<ReducedModelOptimization::OptimizationParameterIndex>>(
          (json.at(GET_VARIABLE_NAME(optimizationStrategy))));
    }
    if (json.contains(GET_VARIABLE_NAME(optimizationStrategyGroupWeights))) {
      optimizationVariablesGroupsWeights = std::vector<double>(
          json[GET_VARIABLE_NAME(optimizationStrategyGroupWeights)]);
    }
    // read x ranges
    if (json.contains(JsonKeys::OptimizationVariables)) {
      const std::array<std::tuple<std::string, double, double>,
                       NumberOfOptimizationVariables>
          xRangesAsTuples = json.at(JsonKeys::OptimizationVariables);
      for (const auto& rangeTuple : xRangesAsTuples) {
        variablesRanges[getParameterIndex(std::get<0>(rangeTuple))].set(
            rangeTuple);
      }
    } else {  // NOTE:legacy compatibility
      size_t xRangeIndex = 0;
      while (true) {
        const std::string jsonXRangeKey = JsonKeys::OptimizationVariables +
                                          "_" + std::to_string(xRangeIndex++);
        if (!json.contains(jsonXRangeKey)) {
          break;
        }
        xRange x;
        x.fromString(json.at(jsonXRangeKey));
        variablesRanges[getParameterIndex(x.label)] = x;
      }
    }

    if (json.contains(GET_VARIABLE_NAME(dlib.numberOfFunctionCalls))) {
      dlib.numberOfFunctionCalls =
          json.at(GET_VARIABLE_NAME(dlib.numberOfFunctionCalls));
    }
    if (json.contains(GET_VARIABLE_NAME(solverAccuracy))) {
      solverAccuracy = json.at(GET_VARIABLE_NAME(solverAccuracy));
    }
    // Objective weights
    if (json.contains(JsonKeys::ObjectiveWeights)) {
      std::array<std::pair<double, double>, NumberOfBaseSimulationScenarios>
          objectiveWeightsPairs = json.at(JsonKeys::ObjectiveWeights);
      std::transform(objectiveWeightsPairs.begin(), objectiveWeightsPairs.end(),
                     perBaseScenarioObjectiveWeights.begin(),
                     [](const std::pair<double, double>& objectiveWeightsPair) {
                       return ObjectiveWeights{objectiveWeightsPair.first,
                                               objectiveWeightsPair.second};
                     });
    }
    if (json.contains(GET_VARIABLE_NAME(translationalNormalizationEpsilon))) {
      translationEpsilon =
          json[GET_VARIABLE_NAME(translationalNormalizationEpsilon)];
    }

    if (json.contains(GET_VARIABLE_NAME(angularDistanceEpsilon))) {
      angularDistanceEpsilon = vcg::math::ToRad(
          static_cast<double>(json[GET_VARIABLE_NAME(angularDistanceEpsilon)]));
    }

    if (json.contains(GET_VARIABLE_NAME(targetBaseTriangleSize))) {
      targetBaseTriangleSize =
          static_cast<double>(json[GET_VARIABLE_NAME(targetBaseTriangleSize)]);
    }

    if (json.contains(GET_VARIABLE_NAME(pso.numberOfParticles))) {
      pso.numberOfParticles =
          static_cast<int>(json[GET_VARIABLE_NAME(pso.numberOfParticles)]);
    }

    if (json.contains(GET_VARIABLE_NAME(simulationModelLabel_reducedModel))) {
      simulationModelLabel_reducedModel = static_cast<std::string>(
          json[GET_VARIABLE_NAME(simulationModelLabel_reducedModel)]);
    }

    beamDimensions_pattern.from_json(json, beamDimensions_pattern);

    if (json.contains(GET_VARIABLE_NAME(youngsModulus_pattern))) {
      youngsModulus_pattern =
          static_cast<double>(json[GET_VARIABLE_NAME(youngsModulus_pattern)]);
    }
    //        perBaseScenarioObjectiveWeights =
    //        json.at(JsonKeys::ObjectiveWeights);
    //        objectiveWeights.translational =
    //        json.at(JsonKeys::ObjectiveWeights); objectiveWeights.rotational =
    //        2 - objectiveWeights.translational;
    return true;
  }

  std::string toString() const { return toJson().dump(); }

  void writeHeaderTo(csvFile& os) const {
    if (!variablesRanges.empty()) {
      for (const xRange& range : variablesRanges) {
        os << range.label + " max";
        os << range.label + " min";
      }
    }
    os << "Function Calls";
    os << "Solution Accuracy";
    os << "Normalization trans epsilon";
    os << "Normalization rot epsilon(deg)";
    os << JsonKeys::ObjectiveWeights;
    os << "Optimization parameters";
    //        os << std::endl;
  }

  void writeSettingsTo(csvFile& os) const {
    if (!variablesRanges.empty()) {
      for (const xRange& range : variablesRanges) {
        os << range.max;
        os << range.min;
      }
    }
    os << dlib.numberOfFunctionCalls;
    os << solverAccuracy;
    os << std::to_string(translationEpsilon);
    os << std::to_string(vcg::math::ToDeg(angularDistanceEpsilon));
    std::string objectiveWeightsString;
    objectiveWeightsString += "{";
    for (int baseScenario = Axial;
         baseScenario != NumberOfBaseSimulationScenarios; baseScenario++) {
      objectiveWeightsString +=
          "{" +
          std::to_string(
              perBaseScenarioObjectiveWeights[baseScenario].translational) +
          "," +
          std::to_string(
              perBaseScenarioObjectiveWeights[baseScenario].rotational) +
          "}";
    }
    objectiveWeightsString += "}";
    os << objectiveWeightsString;

    // export optimization parameters
    std::vector<std::vector<int>> vv;
    for (const std::vector<OptimizationParameterIndex>& v :
         optimizationStrategy) {
      std::vector<int> vi;
      vi.reserve(v.size());
      for (const OptimizationParameterIndex& parameter : v) {
        vi.emplace_back(parameter);
      }
      vv.push_back(vi);
    }
    os << Utilities::toString(vv);
  }
};

inline bool operator==(const Settings& settings1,
                       const Settings& settings2) noexcept {
  const bool haveTheSameObjectiveWeights =
      std::mismatch(settings1.perBaseScenarioObjectiveWeights.begin(),
                    settings1.perBaseScenarioObjectiveWeights.end(),
                    settings2.perBaseScenarioObjectiveWeights.begin())
          .first == settings1.perBaseScenarioObjectiveWeights.end();
  return settings1.dlib.numberOfFunctionCalls ==
             settings2.dlib.numberOfFunctionCalls &&
         settings1.variablesRanges == settings2.variablesRanges &&
         settings1.solverAccuracy == settings2.solverAccuracy &&
         haveTheSameObjectiveWeights &&
         settings1.translationEpsilon == settings2.translationEpsilon;
}

inline void updateMeshWithOptimalVariables(const std::vector<double>& x,
                                           SimulationEdgeMesh& m) {
  assert(CrossSectionType::name == RectangularBeamDimensions::name);
  const double E = x[0];
  const double A = x[1];
  const double beamWidth = std::sqrt(A);
  const double beamHeight = beamWidth;

  const double J = x[2];
  const double I2 = x[3];
  const double I3 = x[4];
  for (EdgeIndex ei = 0; ei < m.EN(); ei++) {
    Element& e = m.elements[ei];
    e.setDimensions(CrossSectionType(beamWidth, beamHeight));
    e.setMaterial(ElementMaterial(e.material.poissonsRatio, E));
    e.dimensions.inertia.J = J;
    e.dimensions.inertia.I2 = I2;
    e.dimensions.inertia.I3 = I3;
  }

  CoordType center_barycentric(1, 0, 0);
  CoordType interfaceEdgeMiddle_barycentric(0, 0.5, 0.5);
  CoordType movableVertex_barycentric(
      (center_barycentric + interfaceEdgeMiddle_barycentric) * x[x.size() - 2]);

  CoordType patternCoord0 = CoordType(0, 0, 0);
  double bottomEdgeHalfSize = 0.03 / std::tan(M_PI / 3);
  CoordType interfaceNodePosition(0, -0.03, 0);
  CoordType patternBottomRight =
      interfaceNodePosition + CoordType(bottomEdgeHalfSize, 0, 0);
  CoordType patternBottomLeft =
      interfaceNodePosition - CoordType(bottomEdgeHalfSize, 0, 0);
  vcg::Triangle3<double> baseTriangle(patternCoord0, patternBottomLeft,
                                      patternBottomRight);
  CoordType baseTriangleMovableVertexPosition =
      baseTriangle.cP(0) * movableVertex_barycentric[0] +
      baseTriangle.cP(1) * movableVertex_barycentric[1] +
      baseTriangle.cP(2) * movableVertex_barycentric[2];
  VectorType patternPlaneNormal(0, 0, 1);
  baseTriangleMovableVertexPosition =
      vcg::RotationMatrix(patternPlaneNormal,
                          vcg::math::ToRad(x[x.size() - 1])) *
      baseTriangleMovableVertexPosition;

  const int fanSize = 6;
  for (int rotationCounter = 0; rotationCounter < fanSize; rotationCounter++) {
    m.vert[2 * rotationCounter + 1].P() =
        vcg::RotationMatrix(patternPlaneNormal,
                            vcg::math::ToRad(60.0 * rotationCounter)) *
        baseTriangleMovableVertexPosition;
  }

  m.reset();
}

struct Results {
  std::string label{"EmptyLabel"};
  double time{-1};
  bool wasSuccessful{true};
  //      int numberOfSimulationCrashes{0};
  Settings settings;

  std::vector<std::pair<std::string, double>> optimalXNameValuePairs;
  std::vector<std::shared_ptr<SimulationJob>> pSimulationJobs_pattern;
  std::vector<std::shared_ptr<SimulationJob>> pSimulationJobs_reducedModel;

  // Full pattern
  PatternGeometry baseTrianglePattern;  // non-fanned,non-tiled full pattern
  vcg::Triangle3<double> baseTriangle;
  //      std::string notes;

  // Data gathered for csv exporting
  struct ObjectiveValues {
    double totalRaw;
    double total;
    std::vector<double> perSimulationScenario_rawTranslational;
    std::vector<double> perSimulationScenario_rawRotational;
    std::vector<double> perSimulationScenario_translational;
    std::vector<double> perSimulationScenario_rotational;
    std::vector<double> perSimulationScenario_total;
    std::vector<double> perSimulationScenario_total_unweighted;

  } objectiveValue;

  std::vector<double> perScenario_fullPatternPotentialEnergy;
  std::vector<double> objectiveValueHistory;
  std::vector<size_t> objectiveValueHistory_iteration;

  inline static std::string DefaultFileName{"OptimizationResults.json"};

  struct CSVExportingSettings {
    bool exportPE{false};
    bool exportIterationOfMinima{false};
    bool exportRawObjectiveValue{false};
    CSVExportingSettings() {}
  };

  const CSVExportingSettings exportSettings;
  struct JsonKeys {
    inline static std::string optimizationVariables{"OptimizationVariables"};
    inline static std::string baseTriangle{"BaseTriangle"};
    inline static std::string Label{"Label"};
    inline static std::string FullPatternLabel{"FullPatternLabel"};
    inline static std::string Settings{"OptimizationSettings"};
    inline static std::string FullPatternPotentialEnergies{"PE"};
    inline static std::string fullPatternYoungsModulus{"youngsModulus"};
  };

  void saveObjectiveValuePlot(
      const std::filesystem::path& outputImageDirPath) const {
    std::vector<std::string> scenarioLabels(
        objectiveValue.perSimulationScenario_total.size());
    const double colorAxial = 1;
    const double colorShear = 3;
    const double colorBending = 5;
    const double colorDome = 0.1;
    const double colorSaddle = 0;
    std::vector<double> colors(
        objectiveValue.perSimulationScenario_total.size());
    for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size();
         scenarioIndex++) {
      scenarioLabels[scenarioIndex] =
          pSimulationJobs_reducedModel[scenarioIndex]->getLabel();
      if (scenarioLabels[scenarioIndex].rfind("Axial", 0) == 0) {
        colors[scenarioIndex] = colorAxial;

      } else if (scenarioLabels[scenarioIndex].rfind("Shear", 0) == 0) {
        colors[scenarioIndex] = colorShear;

      } else if (scenarioLabels[scenarioIndex].rfind("Bending", 0) == 0) {
        colors[scenarioIndex] = colorBending;

      } else if (scenarioLabels[scenarioIndex].rfind("Dome", 0) == 0) {
        colors[scenarioIndex] = colorDome;
      } else if (scenarioLabels[scenarioIndex].rfind("Saddle", 0) == 0) {
        colors[scenarioIndex] = colorSaddle;
      } else {
        std::cerr << "Label could not be identified" << std::endl;
      }
    }
    std::vector<double> y(objectiveValue.perSimulationScenario_total.size());
    for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size();
         scenarioIndex++) {
      y[scenarioIndex]
          //          =
          //          optimizationResults.objectiveValue.perSimulationScenario_rawTranslational[scenarioIndex]
          //            +
          //            optimizationResults.objectiveValue.perSimulationScenario_rawRotational[scenarioIndex];
          = objectiveValue
                .perSimulationScenario_total_unweighted[scenarioIndex];
    }
    std::vector<double> x = matplot::linspace(0, y.size() - 1, y.size());
    std::vector<double> markerSizes(y.size(), 5);
    Utilities::createPlot("scenario index", "error", x, y, markerSizes, colors,
                          std::filesystem::path(outputImageDirPath)
                              .append("perScenarioObjectiveValues.svg"));
  }

  void save(const std::string& saveToPath,
            const bool shouldExportDebugFiles = false) {
    // clear directory
    if (std::filesystem::exists(saveToPath)) {
      for (const auto& entry :
           std::filesystem::directory_iterator(saveToPath)) {
        std::error_code ec;
        std::filesystem::remove_all(entry.path(), ec);
      }
    }
    std::filesystem::create_directories(saveToPath);

    // Save optimal X
    nlohmann::json json_optimizationResults;
    json_optimizationResults[JsonKeys::Label] = label;
    if (wasSuccessful) {
      std::string jsonValue_optimizationVariables;
      for (const auto& optimalXNameValuePair : optimalXNameValuePairs) {
        jsonValue_optimizationVariables.append(optimalXNameValuePair.first +
                                               ",");
      }
      jsonValue_optimizationVariables
          .pop_back();  // for deleting the last comma
      json_optimizationResults[JsonKeys::optimizationVariables] =
          jsonValue_optimizationVariables;

      for (const auto& optimalXNameValuePair : optimalXNameValuePairs) {
        json_optimizationResults[optimalXNameValuePair.first] =
            optimalXNameValuePair.second;
      }
    }
    // base triangle
    json_optimizationResults[JsonKeys::baseTriangle] = std::vector<double>{
        baseTriangle.cP0(0)[0], baseTriangle.cP0(0)[1], baseTriangle.cP0(0)[2],
        baseTriangle.cP1(0)[0], baseTriangle.cP1(0)[1], baseTriangle.cP1(0)[2],
        baseTriangle.cP2(0)[0], baseTriangle.cP2(0)[1], baseTriangle.cP2(0)[2]};
    baseTrianglePattern.save(std::filesystem::path(saveToPath).string());
    json_optimizationResults[JsonKeys::FullPatternLabel] =
        baseTrianglePattern.getLabel();

    // potential energies
    //          const int numberOfSimulationJobs =
    //          fullPatternSimulationJobs.size(); std::vector<double>
    //          fullPatternPE(numberOfSimulationJobs); for (int
    //          simulationScenarioIndex = 0; simulationScenarioIndex <
    //          numberOfSimulationJobs;
    //               simulationScenarioIndex++) {
    //              fullPatternPE[simulationScenarioIndex]
    //                  =
    //                  perScenario_fullPatternPotentialEnergy[simulationScenarioIndex];
    //          }
    //          json_optimizationResults[JsonKeys::FullPatternPotentialEnergies]
    //          = fullPatternPE;
    ////Save to json file
    std::filesystem::path jsonFilePath(
        std::filesystem::path(saveToPath).append(DefaultFileName));
    std::ofstream jsonFile_optimizationResults(jsonFilePath.string());
    jsonFile_optimizationResults << json_optimizationResults;

    /*TODO: Refactor since the meshes are saved for each simulation scenario
     * although they do not change*/
    // Save jobs and meshes for each simulation scenario

    if (shouldExportDebugFiles) {
      // Save the reduced and full patterns
      const std::filesystem::path simulationJobsPath(
          std::filesystem::path(saveToPath).append("SimulationJobs"));
      const int numberOfSimulationJobs = pSimulationJobs_pattern.size();
      for (int simulationScenarioIndex = 0;
           simulationScenarioIndex < numberOfSimulationJobs;
           simulationScenarioIndex++) {
        const std::shared_ptr<SimulationJob>& pFullPatternSimulationJob =
            pSimulationJobs_pattern[simulationScenarioIndex];
        std::filesystem::path simulationJobFolderPath(
            std::filesystem::path(simulationJobsPath)
                .append(std::to_string(simulationScenarioIndex) + "_" +
                        pFullPatternSimulationJob->label));
        std::filesystem::create_directories(simulationJobFolderPath);
        const auto fullPatternDirectoryPath =
            std::filesystem::path(simulationJobFolderPath).append("Full");
        std::filesystem::create_directory(fullPatternDirectoryPath);
        pFullPatternSimulationJob->save(fullPatternDirectoryPath.string());
        const std::shared_ptr<SimulationJob>& pReducedPatternSimulationJob =
            pSimulationJobs_reducedModel[simulationScenarioIndex];
        const auto reducedPatternDirectoryPath =
            std::filesystem::path(simulationJobFolderPath).append("Reduced");
        if (!std::filesystem::exists(reducedPatternDirectoryPath)) {
          std::filesystem::create_directory(reducedPatternDirectoryPath);
        }
        pReducedPatternSimulationJob->save(
            reducedPatternDirectoryPath.string());
      }

      //              constexpr bool shouldSaveObjectiveValuePlot =
      //              shouldExportDebugFiles; if (shouldSaveObjectiveValuePlot)
      //              {
      saveObjectiveValuePlot(saveToPath);
      //              }
    }
    csvFile csv_resultsLocalFile(
        std::filesystem::path(saveToPath).append("results.csv"), true);
    csv_resultsLocalFile << "Name";
    writeHeaderTo(csv_resultsLocalFile);
    settings.writeHeaderTo(csv_resultsLocalFile);
    csv_resultsLocalFile << endrow;
    csv_resultsLocalFile << baseTrianglePattern.getLabel();
    writeResultsTo(csv_resultsLocalFile);
    settings.writeSettingsTo(csv_resultsLocalFile);
    csv_resultsLocalFile << endrow;

    // save minima info
    //          std::filesystem::path csvFilepathMinimaInfo =
    //          std::filesystem::path(saveToPath)
    //                                                            .append("minimaInfo.csv");
    //          csvFile csv_minimaInfo(csvFilepathMinimaInfo, false);
    //          writeMinimaInfoTo(csv_minimaInfo);

    settings.save(saveToPath);

#ifdef POLYSCOPE_DEFINED
    std::cout << "Saved optimization results to:" << saveToPath << std::endl;
#endif
  }

  bool load(const std::filesystem::path& loadFromPath,
            const bool& shouldLoadDebugFiles = false) {
    assert(std::filesystem::is_directory(loadFromPath));
    std::filesystem::path jsonFilepath(
        std::filesystem::path(loadFromPath).append(DefaultFileName));
    if (!std::filesystem::exists(jsonFilepath)) {
      std::cerr << "Input path does not exist:" << loadFromPath << std::endl;
      return false;
    }
    // Load optimal X
    nlohmann::json json_optimizationResults;
    std::ifstream ifs(
        std::filesystem::path(loadFromPath).append(DefaultFileName));
    ifs >> json_optimizationResults;

    //          std::cout << json_optimizationResults.dump() << std::endl;

    label = json_optimizationResults.at(JsonKeys::Label);
    std::string optimizationVariablesString =
        *json_optimizationResults.find(JsonKeys::optimizationVariables);
    std::string optimizationVariablesDelimeter = ",";
    size_t pos = 0;
    std::vector<std::string> optimizationVariablesNames;
    while ((pos = optimizationVariablesString.find(
                optimizationVariablesDelimeter)) != std::string::npos) {
      const std::string variableName =
          optimizationVariablesString.substr(0, pos);
      optimizationVariablesNames.push_back(variableName);
      optimizationVariablesString.erase(
          0, pos + optimizationVariablesDelimeter.length());
    }
    optimizationVariablesNames.push_back(
        optimizationVariablesString);  // add last variable name

    optimalXNameValuePairs.resize(optimizationVariablesNames.size());
    for (int xVariable_index = 0;
         xVariable_index < optimizationVariablesNames.size();
         xVariable_index++) {
      const std::string xVariable_name =
          optimizationVariablesNames[xVariable_index];
      const double xVariable_value =
          *json_optimizationResults.find(xVariable_name);
      optimalXNameValuePairs[xVariable_index] =
          std::make_pair(xVariable_name, xVariable_value);
    }

    const std::string fullPatternLabel =
        json_optimizationResults.at(JsonKeys::FullPatternLabel);
    if (!baseTrianglePattern.load(std::filesystem::path(loadFromPath)
                                      .append(fullPatternLabel + ".ply")
                                      .string())) {
      if (!baseTrianglePattern.load(
              std::filesystem::path(loadFromPath)
                  .append(loadFromPath.stem().string() + ".ply")
                  .string())) {
        if (!baseTrianglePattern.load(std::filesystem::path(loadFromPath)
                                          .append(fullPatternLabel + ".obj")
                                          .string())) {
          baseTrianglePattern.load(
              std::filesystem::path(loadFromPath)
                  .append(loadFromPath.stem().string() + ".obj")
                  .string());
        }
      }
    }

    std::vector<double> baseTriangleVertices =
        json_optimizationResults.at(JsonKeys::baseTriangle);
    baseTriangle.P0(0) =
        CoordType(baseTriangleVertices[0], baseTriangleVertices[1],
                  baseTriangleVertices[2]);
    baseTriangle.P1(0) =
        CoordType(baseTriangleVertices[3], baseTriangleVertices[4],
                  baseTriangleVertices[5]);
    baseTriangle.P2(0) =
        CoordType(baseTriangleVertices[6], baseTriangleVertices[7],
                  baseTriangleVertices[8]);
    if (json_optimizationResults.contains(JsonKeys::fullPatternYoungsModulus)) {
      settings.youngsModulus_pattern =
          json_optimizationResults.at(JsonKeys::fullPatternYoungsModulus);
    } else {
      settings.youngsModulus_pattern = 1 * 1e9;
    }
    const std::filesystem::path folderPath_simulationJobs(
        std::filesystem::path(loadFromPath).append("SimulationJobs"));
    if (shouldLoadDebugFiles &&
        std::filesystem::exists(folderPath_simulationJobs)) {
      const std::vector<std::filesystem::path> scenariosSortedByName = [&]() {
        std::vector<std::filesystem::path> sortedByName;
        for (auto& entry :
             std::filesystem::directory_iterator(folderPath_simulationJobs))
          sortedByName.push_back(entry.path());

        std::sort(sortedByName.begin(), sortedByName.end(),
                  &Utilities::compareNat);
        return sortedByName;
      }();
      for (const auto& simulationScenarioPath : scenariosSortedByName) {
        if (!std::filesystem::is_directory(simulationScenarioPath)) {
          continue;
        }
        // Load full job
        const auto fullJobFilepath = Utilities::getFilepathWithExtension(
            std::filesystem::path(simulationScenarioPath).append("Full"),
            ".json");
        SimulationJob fullJob;
        fullJob.load(fullJobFilepath.string());
        fullJob.pMesh->setBeamMaterial(0.3, settings.youngsModulus_pattern);
        pSimulationJobs_pattern.push_back(
            std::make_shared<SimulationJob>(fullJob));
        // Load reduced job
        const auto reducedJobFilepath = Utilities::getFilepathWithExtension(
            std::filesystem::path(simulationScenarioPath).append("Reduced"),
            ".json");
        SimulationJob reducedJob;
        reducedJob.load(reducedJobFilepath.string());
        applyOptimizationResults_elements(*this, reducedJob.pMesh);
        pSimulationJobs_reducedModel.push_back(
            std::make_shared<SimulationJob>(reducedJob));
      }
    }
    settings.load(
        std::filesystem::path(loadFromPath).append(Settings::defaultFilename));

    return true;
  }

  template <typename MeshType>
  static void applyOptimizationResults_reducedModel_nonFanned(
      const ReducedModelOptimization::Results&
          reducedPattern_optimizationResults,
      const vcg::Triangle3<double>& patternBaseTriangle,
      MeshType& reducedModel) {
    std::unordered_map<std::string, double> optimalXVariables(
        reducedPattern_optimizationResults.optimalXNameValuePairs.begin(),
        reducedPattern_optimizationResults.optimalXNameValuePairs.end());
    assert((optimalXVariables.contains("R") &&
            optimalXVariables.contains("Theta")) ||
           (optimalXVariables.contains("HexSize") &&
            optimalXVariables.contains("HexAngle")));
    if (optimalXVariables.contains("HexSize")) {
      applyOptimizationResults_reducedModel_nonFanned(
          optimalXVariables.at("HexSize"), optimalXVariables.at("HexAngle"),
          patternBaseTriangle, reducedModel);
      return;
    }
    applyOptimizationResults_reducedModel_nonFanned(
        optimalXVariables.at("R"), optimalXVariables.at("Theta"),
        patternBaseTriangle, reducedModel);
  }

  template <typename MeshType>
  static void applyOptimizationResults_reducedModel_nonFanned(
      const double& hexSize,
      const double& hexAngle,
      const vcg::Triangle3<double>& patternBaseTriangle,
      MeshType& reducedModel) {
    // Set optimal geometrical params of the reduced pattern
    //          CoordType center_barycentric(1, 0, 0);
    //          CoordType interfaceEdgeMiddle_barycentric(0, 0.5, 0.5);
    //          CoordType movableVertex_barycentric(
    //              (center_barycentric * (1 - hexSize) +
    //              interfaceEdgeMiddle_barycentric));
    CoordType movableVertex_barycentric(1 - hexSize, hexSize / 2, hexSize / 2);

    reducedModel.vert[0].P() =
        patternBaseTriangle.cP(0) * movableVertex_barycentric[0] +
        patternBaseTriangle.cP(1) * movableVertex_barycentric[1] +
        patternBaseTriangle.cP(2) * movableVertex_barycentric[2];
    if (hexAngle != 0) {
      reducedModel.vert[0].P() =
          vcg::RotationMatrix(CoordType{0, 0, 1}, vcg::math::ToRad(hexAngle)) *
          reducedModel.vert[0].cP();
    }
    //    for (int rotationCounter = 0;
    //         rotationCounter < ReducedModelOptimizer::fanSize;
    //         rotationCounter++) {
    //        pReducedPatternSimulationEdgeMesh->vert[2 * rotationCounter].P()
    //            =
    //            vcg::RotationMatrix(ReducedModelOptimizer::patternPlaneNormal,
    //                                  vcg::math::ToRad(60.0 *
    //                                  rotationCounter))
    //              * baseTriangleMovableVertexPosition;
    //    }
    //          reducedPattern.registerForDrawing();
    //          polyscope::show();
    //          CoordType p0 = reducedPattern.vert[0].P();
    //          CoordType p1 = reducedPattern.vert[1].P();
    //          int i = 0;
    //          i++;
  }

  static void applyOptimizationResults_elements(
      const ReducedModelOptimization::Results&
          reducedPattern_optimizationResults,
      const std::shared_ptr<SimulationEdgeMesh>&
          pReducedModel_SimulationEdgeMesh) {
    assert(CrossSectionType::name == RectangularBeamDimensions::name);
    // Set reduced parameters fron the optimization results
    std::unordered_map<std::string, double> optimalXVariables(
        reducedPattern_optimizationResults.optimalXNameValuePairs.begin(),
        reducedPattern_optimizationResults.optimalXNameValuePairs.end());

    const std::string ALabel = "A";
    if (optimalXVariables.contains(ALabel)) {
      const double A = optimalXVariables.at(ALabel);
      const double beamWidth = std::sqrt(A);
      const double beamHeight = beamWidth;
      CrossSectionType elementDimensions(beamWidth, beamHeight);
      for (int ei = 0; ei < pReducedModel_SimulationEdgeMesh->EN(); ei++) {
        Element& e = pReducedModel_SimulationEdgeMesh->elements[ei];
        e.setDimensions(elementDimensions);
      }
    }

    const double poissonsRatio = 0.3;
    const std::string ymLabel = "E";
    if (optimalXVariables.contains(ymLabel)) {
      const double E = optimalXVariables.at(ymLabel);
      const ElementMaterial elementMaterial(poissonsRatio, E);
      for (int ei = 0; ei < pReducedModel_SimulationEdgeMesh->EN(); ei++) {
        Element& e = pReducedModel_SimulationEdgeMesh->elements[ei];
        e.setMaterial(elementMaterial);
      }
    }

    const std::string JLabel = "J";
    if (optimalXVariables.contains(JLabel)) {
      const double J = optimalXVariables.at(JLabel);
      for (int ei = 0; ei < pReducedModel_SimulationEdgeMesh->EN(); ei++) {
        Element& e = pReducedModel_SimulationEdgeMesh->elements[ei];
        e.dimensions.inertia.J = J;
      }
    }

    const std::string I2Label = "I2";
    if (optimalXVariables.contains(I2Label)) {
      const double I2 = optimalXVariables.at(I2Label);
      for (int ei = 0; ei < pReducedModel_SimulationEdgeMesh->EN(); ei++) {
        Element& e = pReducedModel_SimulationEdgeMesh->elements[ei];
        e.dimensions.inertia.I2 = I2;
      }
    }

    const std::string I3Label = "I3";
    if (optimalXVariables.contains(I3Label)) {
      const double I3 = optimalXVariables.at(I3Label);
      for (int ei = 0; ei < pReducedModel_SimulationEdgeMesh->EN(); ei++) {
        Element& e = pReducedModel_SimulationEdgeMesh->elements[ei];
        e.dimensions.inertia.I3 = I3;
      }
    }
    pReducedModel_SimulationEdgeMesh->reset();
  }

#if POLYSCOPE_DEFINED
  void draw(const std::vector<int>& desiredSimulationScenariosIndices =
                std::vector<int>()) const {
    PolyscopeInterface::init();
    assert(pSimulationJobs_pattern.size() ==
           pSimulationJobs_reducedModel.size());
    pSimulationJobs_pattern[0]->pMesh->registerForDrawing(
        Colors::patternInitial);
    pSimulationJobs_reducedModel[0]->pMesh->registerForDrawing(
        Colors::reducedInitial, false);

    const int numberOfSimulationJobs = pSimulationJobs_pattern.size();
    const std::vector<int> scenariosToDraw = [&]() {
      if (desiredSimulationScenariosIndices.empty()) {
        std::vector<int> v(numberOfSimulationJobs);
        std::iota(v.begin(), v.end(), 0);  // draw all
        return v;
      } else {
        return desiredSimulationScenariosIndices;
      }
    }();

    for (const int& simulationJobIndex : scenariosToDraw) {
      // Drawing of full pattern results
      const std::shared_ptr<SimulationJob>& pSimulationJob_pattern =
          pSimulationJobs_pattern[simulationJobIndex];
      pSimulationJob_pattern->registerForDrawing(
          pSimulationJobs_pattern[0]->pMesh->getLabel());

      std::unique_ptr<SimulationModel> pPatternSimulator =
          SimulationModelFactory::create(
              settings.simulationModelLabel_groundTruth);
      pPatternSimulator->setStructure(pSimulationJob_pattern->pMesh);
      SimulationResults simulationResults_pattern =
          pPatternSimulator->executeSimulation(pSimulationJob_pattern);
      //      ChronosEulerSimulationModel simulator_pattern;
      //      simulator_pattern.settings.analysisType =
      //          ChronosEulerSimulationModel::Settings::AnalysisType::NonLinear;
      //      SimulationResults simulationResults_pattern =
      //          simulator_pattern.executeSimulation(pSimulationJob_pattern);
      simulationResults_pattern.registerForDrawing(Colors::patternDeformed,
                                                   true);
      //        SimulationResults fullModelLinearResults =
      //            linearSimulator.executeSimulation(pFullPatternSimulationJob);
      //        fullModelLinearResults.setLabelPrefix("linear");
      //        fullModelLinearResults.registerForDrawing(Colors::fullDeformed,false);
      // Drawing of reduced pattern results
      const std::shared_ptr<SimulationJob>& pSimulationJob_reducedModel =
          pSimulationJobs_reducedModel[simulationJobIndex];
      //            pReducedPatternSimulationJob->pMesh->registerForDrawing();
      //            polyscope::show();
      //                    SimulationResults reducedModelResults =
      //                    drmSimulator.executeSimulation(
      //                        pReducedPatternSimulationJob);
      //        reducedModelResults.registerForDrawing(Colors::reducedDeformed,
      //        false);
      //            SimulationResults reducedModelResults
      //                =
      //                drmSimulator.executeSimulation(pReducedPatternSimulationJob,
      //                                                 DRMSimulationModel::Settings());
      std::unique_ptr<SimulationModel> pSimulator_reducedModel =
          SimulationModelFactory::create(
              settings.simulationModelLabel_reducedModel);
      pSimulator_reducedModel->setStructure(pSimulationJob_reducedModel->pMesh);
      //      ChronosEulerSimulationModel simulator_reducedModel;
      //      simulator_reducedModel.settings.analysisType =
      //          ChronosEulerSimulationModel::Settings::AnalysisType::Linear;
      SimulationResults simulationResults_reducedModel =
          pSimulator_reducedModel->executeSimulation(
              pSimulationJob_reducedModel);
      simulationResults_reducedModel.registerForDrawing(Colors::reducedDeformed,
                                                        true);
      polyscope::options::programName =
          pSimulationJobs_pattern[0]->pMesh->getLabel();
      //            polyscope::view::resetCameraToHomeView();
      polyscope::show();
      // Save a screensh
      const std::string screenshotFilename =
          "/home/iason/Coding/Projects/Approximating shapes with flat "
          "patterns/RodModelOptimizationForPatterns/Results/Images/" +
          pSimulationJobs_pattern[0]->pMesh->getLabel() + "_" +
          pSimulationJob_pattern->getLabel();
      polyscope::screenshot(screenshotFilename, false);
      pSimulationJob_pattern->unregister(
          pSimulationJobs_pattern[0]->pMesh->getLabel());
      simulationResults_reducedModel.unregister();
      simulationResults_pattern.unregister();
      //            double error =
      //            computeError(reducedModelLinearResults.displacements,
      //                                        fullModelResults.displacements);
      //            std::cout << "Error of simulation scenario "
      //                      <<
      //                      simulationScenarioStrings[simulationScenarioIndex]
      //                      << " is " << error
      //                      << std::endl;
    }
  }
#endif  // POLYSCOPE_DEFINED
  void saveMeshFiles() const {
    const int numberOfSimulationJobs = pSimulationJobs_pattern.size();
    assert(numberOfSimulationJobs != 0 &&
           pSimulationJobs_pattern.size() ==
               pSimulationJobs_reducedModel.size());

    pSimulationJobs_pattern[0]->pMesh->save(
        "undeformed " + pSimulationJobs_pattern[0]->pMesh->getLabel() + ".ply");
    pSimulationJobs_reducedModel[0]->pMesh->save(
        "undeformed " + pSimulationJobs_reducedModel[0]->pMesh->getLabel() +
        ".ply");
    DRMSimulationModel simulator_drm;
    LinearSimulationModel simulator_linear;
    for (int simulationJobIndex = 0;
         simulationJobIndex < numberOfSimulationJobs; simulationJobIndex++) {
      // Drawing of full pattern results
      const std::shared_ptr<SimulationJob>& pFullPatternSimulationJob =
          pSimulationJobs_pattern[simulationJobIndex];
      DRMSimulationModel::Settings drmSettings;
      SimulationResults fullModelResults = simulator_drm.executeSimulation(
          pFullPatternSimulationJob, drmSettings);
      fullModelResults.saveDeformedModel();

      // Drawing of reduced pattern results
      const std::shared_ptr<SimulationJob>& pReducedPatternSimulationJob =
          pSimulationJobs_reducedModel[simulationJobIndex];
      SimulationResults reducedModelResults =
          simulator_linear.executeSimulation(pReducedPatternSimulationJob);
      reducedModelResults.saveDeformedModel();
    }
  }

  void writeHeaderTo(csvFile& os) const {
    if (exportSettings.exportRawObjectiveValue) {
      os << "Total raw Obj value";
    }
    os << "Total Obj value";
    if (exportSettings.exportIterationOfMinima) {
      os << "Iteration of minima";
    }
    for (int simulationScenarioIndex = 0;
         simulationScenarioIndex < pSimulationJobs_pattern.size();
         simulationScenarioIndex++) {
      const std::string simulationScenarioName =
          pSimulationJobs_pattern[simulationScenarioIndex]->getLabel();
      os << "Obj value Trans " + simulationScenarioName;
      os << "Obj value Rot " + simulationScenarioName;
      os << "Obj value Total " + simulationScenarioName;
    }

    if (exportSettings.exportPE) {
      for (int simulationScenarioIndex = 0;
           simulationScenarioIndex < pSimulationJobs_pattern.size();
           simulationScenarioIndex++) {
        const std::string simulationScenarioName =
            pSimulationJobs_pattern[simulationScenarioIndex]->getLabel();
        os << "PE " + simulationScenarioName;
      }
    }
    for (const auto& nameValuePair : optimalXNameValuePairs) {
      os << nameValuePair.first;
    }
    os << "Time(s)";
    //        os << "#Crashes";
    //        os << "notes";
  }

  void writeHeaderTo(
      std::vector<csvFile*>& vectorOfPointersToOutputStreams) const {
    for (csvFile* outputStream : vectorOfPointersToOutputStreams) {
      writeHeaderTo(*outputStream);
    }
  }

  void writeResultsTo(csvFile& os) const {
    if (exportSettings.exportRawObjectiveValue) {
      os << objectiveValue.totalRaw;
    }
    os << objectiveValue.total;
    if (exportSettings.exportIterationOfMinima &&
        !objectiveValueHistory_iteration.empty()) {
      os << objectiveValueHistory_iteration.back();
    }
    for (int simulationScenarioIndex = 0;
         simulationScenarioIndex < pSimulationJobs_pattern.size();
         simulationScenarioIndex++) {
      os << objectiveValue
                .perSimulationScenario_translational[simulationScenarioIndex];
      os << objectiveValue
                .perSimulationScenario_rotational[simulationScenarioIndex];
      os << objectiveValue.perSimulationScenario_total[simulationScenarioIndex];
    }
    if (exportSettings.exportPE) {
      for (int simulationScenarioIndex = 0;
           simulationScenarioIndex < pSimulationJobs_pattern.size();
           simulationScenarioIndex++) {
        os << perScenario_fullPatternPotentialEnergy[simulationScenarioIndex];
      }
    }
    for (const auto& optimalXNameValuePair : optimalXNameValuePairs) {
      os << optimalXNameValuePair.second;
    }

    os << time;
    //        if (numberOfSimulationCrashes == 0) {
    //            os << "-";
    //        } else {
    //            os << numberOfSimulationCrashes;
    //        }
    //        os << notes;
  }

  void writeResultsTo(
      std::vector<csvFile*>& vectorOfPointersToOutputStreams) const {
    for (csvFile*& outputStream : vectorOfPointersToOutputStreams) {
      writeResultsTo(*outputStream);
    }
  }

  void writeMinimaInfoTo(csvFile& outputCsv) {
    outputCsv << "Iteration";
    outputCsv << "Objective value";
    for (int objectiveValueIndex = 0;
         objectiveValueIndex < objectiveValueHistory.size();
         objectiveValueIndex++) {
      outputCsv.endrow();
      outputCsv << objectiveValueHistory_iteration[objectiveValueIndex];
      outputCsv << objectiveValueHistory[objectiveValueIndex];
    }
  }
};
enum SimulationModelTag { DRM, Linear };

inline bool Settings::ObjectiveWeights::operator==(
    const ObjectiveWeights& other) const {
  return this->translational == other.translational &&
         this->rotational == other.rotational;
}
}  // namespace ReducedModelOptimization
#endif  // REDUCEDMODELOPTIMIZER_STRUCTS_HPP