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Merged potentialEnergyError branch

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iasonmanolas 2022-01-26 15:19:28 +02:00
parent 872d3b1144 116e9a44f0
commit 941a766ec8
4 changed files with 2422 additions and 103 deletions
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148
src/main.cpp
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@ -22,19 +22,21 @@
#endif
int main(int argc, char *argv[])
{
// ReducedModelOptimization::Results optResults;
// optResults.load("/home/iason/Desktop/finding_submissionCode/"
// "build-ReducedModelOptimization-Clang-RelWithDebInfo/OptimizationResults/"
// "ConvergedJobs/12@single_reduced(100000_1.20)");
// ReducedModelEvaluator::evaluateReducedModel(optResults);
if (argc <= 5) {
#ifdef POLYSCOPE_DEFINED
// ReducedModelOptimization::Results optResults;
// optResults.load("/home/iason/Desktop/selectionOfPatterns_0.2To1.6/selectionOfPatterns/1.2/"
// "ConvergedJobs/12@single_reduced(100000_1.20)");
// ReducedModelEvaluator::evaluateReducedModel(optResults);
// return 0;
#endif
if (argc < 3) {
std::cerr << "Wrong number of input parameters. Expects at least 4 input parameters."
"Usage:\n"
"1)full pattern file path\n"
"2)reduced pattern file path\n"
"3)Optimization settings json file path\n"
"4)Optimization results directory path\n"
"5)[optional]Intermediate results directory path\n"
"3)Optimization results directory path\n"
"4)[optional]Intermediate results directory path\n"
"5)[optional]Optimization settings json file path\n"
"Exiting.."
<< std::endl;
std::cerr << "Input arguments are:" << std::endl;
@ -55,25 +57,35 @@ int main(int argc, char *argv[])
reducedPattern.scale(0.03, interfaceNodeIndex);
// Set the optization settings
const std::filesystem::path optimizationSettingsFilePath = argv[3];
if (!std::filesystem::exists(optimizationSettingsFilePath)) {
std::cerr << "Input optimization settings file does not exist:"
<< optimizationSettingsFilePath << std::endl;
}
ReducedModelOptimization::Settings settings_optimization;
if (argc > 5) {
const std::filesystem::path optimizationSettingsFilePath = argv[5];
if (!std::filesystem::exists(optimizationSettingsFilePath)) {
std::cerr << "Input optimization settings file does not exist:"
<< optimizationSettingsFilePath << std::endl;
}
#ifdef POLYSCOPE_DEFINED
// settings_optimization.save(optimizationSettingsFilePath.parent_path());
// std::cout << "Save settings to:" << optimizationSettingsFilePath << std::endl;
#else
settings_optimization.load(optimizationSettingsFilePath);
// settings_optimization.load(optimizationSettingsFilePath);
#endif
}
// settings_optimization.normalizationStrategy
// = ReducedModelOptimization::Settings::NormalizationStrategy::NonNormalized;
settings_optimization.optimizationStrategy = {{ReducedModelOptimization::A,
ReducedModelOptimization::I2,
ReducedModelOptimization::I3,
ReducedModelOptimization::J,
ReducedModelOptimization::R,
ReducedModelOptimization::Theta}};
// settings_optimization.setDefault();
// settings_optimization.rotationNormalizationEpsilon = 0;
// Optimize pairthere
const std::string optimizationName = std::to_string(fullPattern.EN()) + "#"
+ fullPattern.getLabel();
const std::string optimizationResultsDirectory = argv[4];
const std::string optimizationResultsDirectory = argv[3];
std::string resultsOutputDir;
bool optimizationResultFolderExists = false;
const std::filesystem::path crashedJobsDirPath(
@ -108,9 +120,9 @@ int main(int argc, char *argv[])
const std::vector<size_t> numberOfNodesPerSlot{1, 0, 0, 2, 1, 2, 1};
assert(interfaceNodeIndex == numberOfNodesPerSlot[0] + numberOfNodesPerSlot[3]);
ReducedModelOptimizer optimizer(numberOfNodesPerSlot);
const bool input_intermediateResultsDirectoryDefined = argc == 6;
const bool input_intermediateResultsDirectoryDefined = argc == 5;
if (input_intermediateResultsDirectoryDefined) {
optimizer.setIntermediateResultsDirectoryPath(std::filesystem::path(argv[5]));
optimizer.setIntermediateResultsDirectoryPath(std::filesystem::path(argv[4]));
}
optimizer.initializePatterns(fullPattern,
reducedPattern,
@ -148,59 +160,59 @@ int main(int argc, char *argv[])
}
#ifdef POLYSCOPE_DEFINED
std::vector<std::string> scenarioLabels(
optimizationResults.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(optimizationResults.objectiveValue.perSimulationScenario_total.size());
for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
scenarioLabels[scenarioIndex]
= optimizationResults.reducedPatternSimulationJobs[scenarioIndex]->getLabel();
if (scenarioLabels[scenarioIndex].rfind("Axial", 0) == 0) {
colors[scenarioIndex] = colorAxial;
std::vector<std::string> scenarioLabels(
optimizationResults.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(
optimizationResults.objectiveValue.perSimulationScenario_total.size());
for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
scenarioLabels[scenarioIndex]
= optimizationResults.reducedPatternSimulationJobs[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("Shear", 0) == 0) {
colors[scenarioIndex] = colorShear;
} else if (scenarioLabels[scenarioIndex].rfind("Bending", 0) == 0) {
colors[scenarioIndex] = colorBending;
} 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(optimizationResults.objectiveValue.perSimulationScenario_total.size());
for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
y[scenarioIndex]
// = optimizationResults.objectiveValue.perSimulationScenario_rawTranslational[scenarioIndex]
// + optimizationResults.objectiveValue.perSimulationScenario_rawRotational[scenarioIndex];
= optimizationResults.objectiveValue.perSimulationScenario_total_unweighted[scenarioIndex];
}
std::vector<double> x = matplot::linspace(0, y.size() - 1, y.size());
std::vector<double> markerSizes(y.size(), 5);
SimulationResultsReporter::createPlot("scenario index",
"error",
x,
y,
markerSizes,
colors,
std::filesystem::path(resultsOutputDir)
.append("perScenarioObjectiveValues.png"));
// optimizationResults.saveMeshFiles();
std::cout << "Saved results to:" << resultsOutputDir << std::endl;
// optimizationResults.draw();
} 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(optimizationResults.objectiveValue.perSimulationScenario_total.size());
for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
y[scenarioIndex]
// = optimizationResults.objectiveValue.perSimulationScenario_rawTranslational[scenarioIndex]
// + optimizationResults.objectiveValue.perSimulationScenario_rawRotational[scenarioIndex];
= optimizationResults.objectiveValue
.perSimulationScenario_total_unweighted[scenarioIndex];
}
std::vector<double> x = matplot::linspace(0, y.size() - 1, y.size());
std::vector<double> markerSizes(y.size(), 5);
SimulationResultsReporter::createPlot("scenario index",
"error",
x,
y,
markerSizes,
colors,
std::filesystem::path(resultsOutputDir)
.append("perScenarioObjectiveValues.png"));
// optimizationResults.saveMeshFiles();
std::cout << "Saved results to:" << resultsOutputDir << std::endl;
// optimizationResults.draw();
// ReducedModelOptimization::Results optResults;
// optResults.load("/home/iason/Desktop/dlib_ensmallen_comparison/TestSets/"
// "singlePattern_dlib_firstSubmission/12@single_reduced(100000_1.20)");
ReducedModelEvaluator::evaluateReducedModel(optimizationResults);
const auto evaluationResults = ReducedModelEvaluator::evaluateReducedModel(optimizationResults);
ReducedModelEvaluator::printResults(evaluationResults, optimizationResults.label);
#endif
return 0;
return 0;
}

218
src/main.cpp.orig Normal file
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@ -0,0 +1,218 @@
#include "csvfile.hpp"
#include "drmsimulationmodel.hpp"
#include "edgemesh.hpp"
#include "reducedmodelevaluator.hpp"
#include "reducedmodeloptimizer.hpp"
#include "simulationhistoryplotter.hpp"
#include "trianglepattterntopology.hpp"
#include <boost/algorithm/string.hpp>
#include <chrono>
#include <filesystem>
#include <iostream>
#include <iterator>
#include <stdexcept>
#include <string>
#include <string_view>
#include <vcg/complex/algorithms/update/position.h>
#ifdef POLYSCOPE_DEFINED
#include "polyscope/curve_network.h"
#include "polyscope/point_cloud.h"
#include "polyscope/polyscope.h"
#endif
int main(int argc, char *argv[])
{
<<<<<<< HEAD
// ReducedModelOptimization::Results optResults;
// optResults.load("/home/iason/Desktop/finding_submissionCode/"
// "build-ReducedModelOptimization-Clang-RelWithDebInfo/OptimizationResults/"
// "ConvergedJobs/12@single_reduced(100000_1.20)");
// ReducedModelEvaluator::evaluateReducedModel(optResults);
if (argc <= 5) {
=======
#ifdef POLYSCOPE_DEFINED
// ReducedModelOptimization::Results optResults;
// optResults.load("/home/iason/Desktop/selectionOfPatterns_0.2To1.6/selectionOfPatterns/1.2/"
// "ConvergedJobs/12@single_reduced(100000_1.20)");
// ReducedModelEvaluator::evaluateReducedModel(optResults);
// return 0;
#endif
if (argc < 3) {
>>>>>>> potentialEnergyError
std::cerr << "Wrong number of input parameters. Expects at least 4 input parameters."
"Usage:\n"
"1)full pattern file path\n"
"2)reduced pattern file path\n"
"3)Optimization results directory path\n"
"4)[optional]Intermediate results directory path\n"
"5)[optional]Optimization settings json file path\n"
"Exiting.."
<< std::endl;
std::cerr << "Input arguments are:" << std::endl;
std::copy(argv + 1, argv + argc, std::ostream_iterator<const char *>(std::cout, "\n"));
return 1;
}
// Populate the pattern pair to be optimized
const int interfaceNodeIndex = 3;
////Full pattern
const std::string filepath_fullPattern = argv[1];
PatternGeometry fullPattern(filepath_fullPattern);
// fullPattern.prependToLabel(std::to_string(fullPattern.EN()) + "#");
fullPattern.scale(0.03, interfaceNodeIndex);
////Reduced pattern
const std::string filepath_reducedPattern = argv[2];
PatternGeometry reducedPattern(filepath_reducedPattern);
reducedPattern.scale(0.03, interfaceNodeIndex);
// Set the optization settings
ReducedModelOptimization::Settings settings_optimization;
if (argc > 5) {
const std::filesystem::path optimizationSettingsFilePath = argv[5];
if (!std::filesystem::exists(optimizationSettingsFilePath)) {
std::cerr << "Input optimization settings file does not exist:"
<< optimizationSettingsFilePath << std::endl;
}
#ifdef POLYSCOPE_DEFINED
// settings_optimization.save(optimizationSettingsFilePath.parent_path());
// std::cout << "Save settings to:" << optimizationSettingsFilePath << std::endl;
#else
settings_optimization.load(optimizationSettingsFilePath);
#endif
}
// settings_optimization.setDefault();
// settings_optimization.rotationNormalizationEpsilon = 0;
// Optimize pairthere
const std::string optimizationName = std::to_string(fullPattern.EN()) + "#"
+ fullPattern.getLabel();
const std::string optimizationResultsDirectory = argv[3];
std::string resultsOutputDir;
bool optimizationResultFolderExists = false;
const std::filesystem::path crashedJobsDirPath(
std::filesystem::path(optimizationResultsDirectory)
.append("CrashedJobs")
.append(optimizationName));
if (std::filesystem::exists(crashedJobsDirPath)) {
resultsOutputDir = crashedJobsDirPath.string();
optimizationResultFolderExists = true;
}
const std::filesystem::path convergedJobsDirPath(
std::filesystem::path(optimizationResultsDirectory)
.append("ConvergedJobs")
.append(optimizationName));
if (std::filesystem::exists(convergedJobsDirPath)) {
resultsOutputDir = convergedJobsDirPath.string();
optimizationResultFolderExists = true;
}
ReducedModelOptimization::Results optimizationResults;
constexpr bool shouldReoptimize = true;
bool optimizationAlreadyComputed = false;
if (!shouldReoptimize && optimizationResultFolderExists) {
const bool resultsWereSuccessfullyLoaded = optimizationResults.load(resultsOutputDir);
if (resultsWereSuccessfullyLoaded && optimizationResults.settings == settings_optimization) {
optimizationAlreadyComputed = true;
}
}
if (!optimizationAlreadyComputed) {
auto start = std::chrono::system_clock::now();
const std::vector<size_t> numberOfNodesPerSlot{1, 0, 0, 2, 1, 2, 1};
assert(interfaceNodeIndex == numberOfNodesPerSlot[0] + numberOfNodesPerSlot[3]);
ReducedModelOptimizer optimizer(numberOfNodesPerSlot);
const bool input_intermediateResultsDirectoryDefined = argc == 5;
if (input_intermediateResultsDirectoryDefined) {
optimizer.setIntermediateResultsDirectoryPath(std::filesystem::path(argv[4]));
}
optimizer.initializePatterns(fullPattern,
reducedPattern,
settings_optimization.variablesRanges);
optimizer.optimize(settings_optimization, optimizationResults);
optimizationResults.label = optimizationName;
optimizationResults.baseTriangleFullPattern.copy(fullPattern);
optimizationResults.settings = settings_optimization;
auto end = std::chrono::system_clock::now();
auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(end - start);
optimizationResults.time = elapsed.count() / 1000.0;
if (!optimizationResults.wasSuccessful) {
// resultsOutputDir = crashedJobsDirPath.string();
return 1;
}
resultsOutputDir = convergedJobsDirPath.string();
optimizationResults.save(resultsOutputDir, true);
csvFile csv_resultsLocalFile(std::filesystem::path(resultsOutputDir).append("results.csv"),
true);
csvFile csv_results({}, false);
std::vector<csvFile *> csvVector{&csv_resultsLocalFile, &csv_results};
csv_results << "Name";
csv_resultsLocalFile << "Name";
optimizationResults.writeHeaderTo(csvVector);
settings_optimization.writeHeaderTo(csv_results);
csv_results << endrow;
csv_resultsLocalFile << endrow;
csv_results << optimizationName;
csv_resultsLocalFile << optimizationName;
optimizationResults.writeResultsTo(csvVector);
settings_optimization.writeSettingsTo(csv_results);
csv_results << endrow;
csv_resultsLocalFile << endrow;
}
#ifdef POLYSCOPE_DEFINED
ReducedModelEvaluator::evaluateReducedModel(optimizationResults);
std::vector<std::string> scenarioLabels(
optimizationResults.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(
optimizationResults.objectiveValue.perSimulationScenario_total.size());
for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
scenarioLabels[scenarioIndex]
= optimizationResults.reducedPatternSimulationJobs[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(optimizationResults.objectiveValue.perSimulationScenario_total.size());
for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
y[scenarioIndex]
// = optimizationResults.objectiveValue.perSimulationScenario_rawTranslational[scenarioIndex]
// + optimizationResults.objectiveValue.perSimulationScenario_rawRotational[scenarioIndex];
= optimizationResults.objectiveValue
.perSimulationScenario_total_unweighted[scenarioIndex];
}
std::vector<double> x = matplot::linspace(0, y.size() - 1, y.size());
std::vector<double> markerSizes(y.size(), 5);
SimulationResultsReporter::createPlot("scenario index",
"error",
x,
y,
markerSizes,
colors,
std::filesystem::path(resultsOutputDir)
.append("perScenarioObjectiveValues.png"));
// optimizationResults.saveMeshFiles();
std::cout << "Saved results to:" << resultsOutputDir << std::endl;
optimizationResults.draw();
#endif
return 0;
}

82
src/reducedmodeloptimizer.cpp
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@ -140,27 +140,27 @@ double ReducedModelOptimizer::computeError(
const double &scenarioWeight,
const Settings::ObjectiveWeights &objectiveWeights)
{
// const double translationalError
// = computeDisplacementError(simulationResults_fullPattern.displacements,
// simulationResults_reducedPattern.displacements,
// reducedToFullInterfaceViMap,
// normalizationFactor_translationalDisplacement);
const double translationalError
= computeRawTranslationalError(simulationResults_fullPattern.displacements,
simulationResults_reducedPattern.displacements,
reducedToFullInterfaceViMap);
= computeDisplacementError(simulationResults_fullPattern.displacements,
simulationResults_reducedPattern.displacements,
reducedToFullInterfaceViMap,
normalizationFactor_translationalDisplacement);
// const double translationalError
// = computeRawTranslationalError(simulationResults_fullPattern.displacements,
// simulationResults_reducedPattern.displacements,
// reducedToFullInterfaceViMap);
// std::cout << "normalization factor:" << normalizationFactor_rotationalDisplacement << std::endl;
// std::cout << "trans error:" << translationalError << std::endl;
// const double rotationalError
// = computeRotationalError(simulationResults_fullPattern.rotationalDisplacementQuaternion,
// simulationResults_reducedPattern.rotationalDisplacementQuaternion,
// reducedToFullInterfaceViMap,
// normalizationFactor_rotationalDisplacement);
const double rotationalError
= computeRawRotationalError(simulationResults_fullPattern.rotationalDisplacementQuaternion,
simulationResults_reducedPattern.rotationalDisplacementQuaternion,
reducedToFullInterfaceViMap);
= computeRotationalError(simulationResults_fullPattern.rotationalDisplacementQuaternion,
simulationResults_reducedPattern.rotationalDisplacementQuaternion,
reducedToFullInterfaceViMap,
normalizationFactor_rotationalDisplacement);
// const double rotationalError
// = computeRawRotationalError(simulationResults_fullPattern.rotationalDisplacementQuaternion,
// simulationResults_reducedPattern.rotationalDisplacementQuaternion,
// reducedToFullInterfaceViMap);
// std::cout << "rot error:" << rotationalError<< std::endl;
const double simulationError = objectiveWeights.translational * translationalError
+ objectiveWeights.rotational * rotationalError;
@ -267,15 +267,11 @@ double ReducedModelOptimizer::objective(const std::vector<double> &x)
std::cout << "Failed simulation" << std::endl;
#endif
} else {
// double simulationScenarioError = 0;
// constexpr bool usePotentialEnergy = false;
// if (usePotentialEnergy) {
// simulationScenarioError += std::abs(
// reducedModelResults.internalPotentialEnergy
// - global.fullPatternResults[simulationScenarioIndex].internalPotentialEnergy
// / global.fullPatternResults[simulationScenarioIndex]
// .internalPotentialEnergy);
// } else {
// const double simulationScenarioError_PE = std::abs(
// (reducedModelResults.internalPotentialEnergy
// - global.fullPatternResults[simulationScenarioIndex].internalPotentialEnergy)
// / global.fullPatternResults[simulationScenarioIndex].internalPotentialEnergy);
// else {
#ifdef POLYSCOPE_DEFINED
#ifdef USE_SCENARIO_WEIGHTS
const double scenarioWeight = global.scenarioWeights[simulationScenarioIndex];
@ -285,7 +281,7 @@ double ReducedModelOptimizer::objective(const std::vector<double> &x)
#else
const double scenarioWeight = 1;
#endif
const double simulationScenarioError = computeError(
const double simulationScenarioError_displacements = computeError(
global.fullPatternResults[simulationScenarioIndex],
reducedModelResults,
global.reducedToFullInterfaceViMap,
@ -294,7 +290,8 @@ double ReducedModelOptimizer::objective(const std::vector<double> &x)
scenarioWeight,
global.objectiveWeights[simulationScenarioIndex]);
simulationErrorsPerScenario[simulationScenarioIndex] = simulationScenarioError;
simulationErrorsPerScenario[simulationScenarioIndex]
= simulationScenarioError_displacements /*+ simulationScenarioError_PE*/;
// }
// #ifdef POLYSCOPE_DEFINED
// reducedJob->pMesh->registerForDrawing(Colors::reducedInitial);
@ -979,7 +976,12 @@ ReducedModelOptimizer::getFullPatternMaxSimulationForces(
.append(m_pFullPatternSimulationMesh->getLabel() + ".json"));
const bool fullPatternScenarioMagnitudesExist = std::filesystem::exists(
patternMaxForceMagnitudesFilePath);
if (fullPatternScenarioMagnitudesExist && !recomputeForceMagnitudes) {
#ifdef POLYSCOPE_DEFINED
constexpr bool recomputeMagnitudes = true;
#else
constexpr bool recomputeMagnitudes = true;
#endif
if (fullPatternScenarioMagnitudesExist && !recomputeMagnitudes) {
nlohmann::json json;
std::ifstream ifs(patternMaxForceMagnitudesFilePath.string());
ifs >> json;
@ -987,6 +989,7 @@ ReducedModelOptimizer::getFullPatternMaxSimulationForces(
= static_cast<std::array<double, NumberOfBaseSimulationScenarios>>(json.at("maxMagn"));
return fullPatternSimulationScenarioMaxMagnitudes;
}
//#endif
fullPatternSimulationScenarioMaxMagnitudes = computeFullPatternMaxSimulationForces(
desiredBaseSimulationScenarioIndices);
@ -999,6 +1002,11 @@ ReducedModelOptimizer::getFullPatternMaxSimulationForces(
std::ofstream jsonFile(patternMaxForceMagnitudesFilePath.string());
jsonFile << json;
#ifdef POLYSCOPE_DEFINED
std::cout << "Saved base scenario max magnitudes to:" << patternMaxForceMagnitudesFilePath
<< std::endl;
#endif
//#endif
assert(fullPatternSimulationScenarioMaxMagnitudes.size()
== desiredBaseSimulationScenarioIndices.size());
@ -1405,7 +1413,6 @@ double fullPatternMaxSimulationForceRotationalObjective(const double &forceMagni
settings);
const double &desiredRotationAngle = global.desiredMaxRotationAngle;
double error;
#ifdef POLYSCOPE_DEFINED
// job.pMesh->setLabel("initial");
// job.pMesh->registerForDrawing();
// results.registerForDrawing();
@ -1444,6 +1451,7 @@ double fullPatternMaxSimulationForceRotationalObjective(const double &forceMagni
// job.save(outputPath);
// settings.save(outputPath);
#ifdef POLYSCOPE_DEFINED
std::cout << "Force:" << forceMagnitude << " Error is:" << vcg::math::ToDeg(error) << std::endl;
#endif
return error;
@ -1560,7 +1568,7 @@ double ReducedModelOptimizer::computeFullPatternMaxSimulationForce(
switch (scenario) {
case Axial:
global.desiredMaxDisplacementValue = 0.03 * baseTriangleHeight;
global.desiredMaxDisplacementValue = 0.04 * baseTriangleHeight;
break;
case Shear:
global.desiredMaxDisplacementValue = 0.04 * baseTriangleHeight;
@ -1922,7 +1930,11 @@ void ReducedModelOptimizer::optimize(
.append(m_pFullPatternSimulationMesh->getLabel())
.append(pFullPatternSimulationJob->getLabel()));
// .append(pFullPatternSimulationJob->getLabel() + ".json")
constexpr bool recomputeFullPatternResults = false;
#ifdef POLYSCOPE_DEFINED
constexpr bool recomputeFullPatternResults = true;
#else
constexpr bool recomputeFullPatternResults = true;
#endif
SimulationResults fullPatternResults;
if (!recomputeFullPatternResults && std::filesystem::exists(jobResultsDirectoryPath)) {
fullPatternResults.load(std::filesystem::path(jobResultsDirectoryPath).append("Results"),
@ -2034,10 +2046,10 @@ void ReducedModelOptimizer::optimize(
global.fullPatternSimulationJobs[0]->pMesh->unregister();
}
#endif
if (global.optimizationSettings.normalizationStrategy
== Settings::NormalizationStrategy::Epsilon) {
computeObjectiveValueNormalizationFactors();
}
// if (global.optimizationSettings.normalizationStrategy
// == Settings::NormalizationStrategy::Epsilon) {
computeObjectiveValueNormalizationFactors();
// }
#ifdef POLYSCOPE_DEFINED
std::cout << "Running reduced model optimization" << std::endl;
#endif

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