216 lines
10 KiB
C++
216 lines
10 KiB
C++
#include "csvfile.hpp"
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#include "drmsimulationmodel.hpp"
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#include "edgemesh.hpp"
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#include "reducedmodelevaluator.hpp"
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#include "reducedmodeloptimizer.hpp"
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#include "simulationhistoryplotter.hpp"
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#include "trianglepattterntopology.hpp"
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#include <boost/algorithm/string.hpp>
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#include <chrono>
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#include <filesystem>
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#include <iostream>
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#include <iterator>
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#include <stdexcept>
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#include <string>
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#include <string_view>
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#include <vcg/complex/algorithms/update/position.h>
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#ifdef POLYSCOPE_DEFINED
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#include "polyscope/curve_network.h"
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#include "polyscope/point_cloud.h"
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#include "polyscope/polyscope.h"
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#endif
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int main(int argc, char *argv[])
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{
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// ReducedModelOptimization::Results optResults;
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// optResults.load("/home/iason/Desktop/dlib_ensmallen_comparison/TestSets/"
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// "singlePattern_dlib_firstSubmission/12@single_reduced(100000_1.20)");
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// optResults.load("/home/iason/Coding/Projects/Approximating shapes with flat "
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// "patterns/ReducedModelOptimization/Results/OptimizationResults/"
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// "objectiveFunction/ConvergedJobs/testSet/7#12");
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// optResults.load("/home/iason/Desktop/dlib_ensmallen_comparison/TestSets/"
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// "singlePattern_dlib_23_12/12@single_reduced(100000_1.20)");
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// optResults.load("/home/iason/Desktop/dlib_ensmallen_comparison/TestSets/"
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// "singlePattern_ensmallen_AllVars_optParameters/7#12");
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// ReducedModelEvaluator::evaluateReducedModel(optResults);
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if (argc <= 5) {
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std::cerr << "Wrong number of input parameters. Expects at least 4 input parameters."
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"Usage:\n"
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"1)full pattern file path\n"
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"2)reduced pattern file path\n"
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"3)Optimization settings json file path\n"
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"4)Optimization results directory path\n"
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"5)[optional]Intermediate results directory path\n"
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"Exiting.."
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<< std::endl;
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std::cerr << "Input arguments are:" << std::endl;
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std::copy(argv + 1, argv + argc, std::ostream_iterator<const char *>(std::cout, "\n"));
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return 1;
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}
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// Populate the pattern pair to be optimized
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const int interfaceNodeIndex = 3;
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////Full pattern
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const std::string filepath_fullPattern = argv[1];
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PatternGeometry fullPattern(filepath_fullPattern);
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// fullPattern.prependToLabel(std::to_string(fullPattern.EN()) + "#");
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fullPattern.scale(0.03, interfaceNodeIndex);
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////Reduced pattern
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const std::string filepath_reducedPattern = argv[2];
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PatternGeometry reducedPattern(filepath_reducedPattern);
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reducedPattern.scale(0.03, interfaceNodeIndex);
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// Set the optization settings
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const std::filesystem::path optimizationSettingsFilePath = argv[3];
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if (!std::filesystem::exists(optimizationSettingsFilePath)) {
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std::cerr << "Input optimization settings file does not exist:"
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<< optimizationSettingsFilePath << std::endl;
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}
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ReducedModelOptimization::Settings settings_optimization;
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#ifdef POLYSCOPE_DEFINED
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// settings_optimization.save(optimizationSettingsFilePath.parent_path());
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// std::cout << "Save settings to:" << optimizationSettingsFilePath << std::endl;
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#else
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settings_optimization.load(optimizationSettingsFilePath);
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#endif
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// settings_optimization.setDefault();
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// settings_optimization.rotationNormalizationEpsilon = 0;
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// Optimize pairthere
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const std::string optimizationName = std::to_string(fullPattern.EN()) + "#"
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+ fullPattern.getLabel();
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const std::string optimizationResultsDirectory = argv[4];
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std::string resultsOutputDir;
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bool optimizationResultFolderExists = false;
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const std::filesystem::path crashedJobsDirPath(
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std::filesystem::path(optimizationResultsDirectory)
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.append("CrashedJobs")
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.append(optimizationName));
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if (std::filesystem::exists(crashedJobsDirPath)) {
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resultsOutputDir = crashedJobsDirPath.string();
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optimizationResultFolderExists = true;
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}
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const std::filesystem::path convergedJobsDirPath(
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std::filesystem::path(optimizationResultsDirectory)
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.append("ConvergedJobs")
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.append(optimizationName));
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if (std::filesystem::exists(convergedJobsDirPath)) {
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resultsOutputDir = convergedJobsDirPath.string();
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optimizationResultFolderExists = true;
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}
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ReducedModelOptimization::Results optimizationResults;
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constexpr bool shouldReoptimize = true;
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bool optimizationAlreadyComputed = false;
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if (!shouldReoptimize && optimizationResultFolderExists) {
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const bool resultsWereSuccessfullyLoaded = optimizationResults.load(resultsOutputDir);
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if (resultsWereSuccessfullyLoaded && optimizationResults.settings == settings_optimization) {
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optimizationAlreadyComputed = true;
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}
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}
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if (!optimizationAlreadyComputed) {
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auto start = std::chrono::system_clock::now();
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const std::vector<size_t> numberOfNodesPerSlot{1, 0, 0, 2, 1, 2, 1};
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assert(interfaceNodeIndex == numberOfNodesPerSlot[0] + numberOfNodesPerSlot[3]);
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ReducedModelOptimizer optimizer(numberOfNodesPerSlot);
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const bool input_intermediateResultsDirectoryDefined = argc == 6;
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if (input_intermediateResultsDirectoryDefined) {
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optimizer.setIntermediateResultsDirectoryPath(std::filesystem::path(argv[5]));
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}
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optimizer.initializePatterns(fullPattern,
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reducedPattern,
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settings_optimization.variablesRanges);
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optimizer.optimize(settings_optimization, optimizationResults);
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optimizationResults.label = optimizationName;
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optimizationResults.baseTriangleFullPattern.copy(fullPattern);
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optimizationResults.settings = settings_optimization;
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auto end = std::chrono::system_clock::now();
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auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(end - start);
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optimizationResults.time = elapsed.count() / 1000.0;
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if (!optimizationResults.wasSuccessful) {
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// resultsOutputDir = crashedJobsDirPath.string();
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return 1;
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}
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resultsOutputDir = convergedJobsDirPath.string();
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optimizationResults.save(resultsOutputDir, true);
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csvFile csv_resultsLocalFile(std::filesystem::path(resultsOutputDir).append("results.csv"),
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true);
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csvFile csv_results({}, false);
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std::vector<csvFile *> csvVector{&csv_resultsLocalFile, &csv_results};
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csv_results << "Name";
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csv_resultsLocalFile << "Name";
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optimizationResults.writeHeaderTo(csvVector);
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settings_optimization.writeHeaderTo(csv_results);
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csv_results << endrow;
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csv_resultsLocalFile << endrow;
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csv_results << optimizationName;
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csv_resultsLocalFile << optimizationName;
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optimizationResults.writeResultsTo(csvVector);
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settings_optimization.writeSettingsTo(csv_results);
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csv_results << endrow;
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csv_resultsLocalFile << endrow;
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}
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ReducedModelEvaluator::evaluateReducedModel(optimizationResults);
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#ifdef POLYSCOPE_DEFINED
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std::vector<std::string> scenarioLabels(
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optimizationResults.objectiveValue.perSimulationScenario_total.size());
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const double colorAxial = 1;
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const double colorShear = 3;
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const double colorBending = 5;
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const double colorDome = 0.1;
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const double colorSaddle = 0;
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std::vector<double> colors(
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optimizationResults.objectiveValue.perSimulationScenario_total.size());
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for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
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scenarioLabels[scenarioIndex]
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= optimizationResults.reducedPatternSimulationJobs[scenarioIndex]->getLabel();
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if (scenarioLabels[scenarioIndex].rfind("Axial", 0) == 0) {
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colors[scenarioIndex] = colorAxial;
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} else if (scenarioLabels[scenarioIndex].rfind("Shear", 0) == 0) {
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colors[scenarioIndex] = colorShear;
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} else if (scenarioLabels[scenarioIndex].rfind("Bending", 0) == 0) {
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colors[scenarioIndex] = colorBending;
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} else if (scenarioLabels[scenarioIndex].rfind("Dome", 0) == 0) {
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colors[scenarioIndex] = colorDome;
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} else if (scenarioLabels[scenarioIndex].rfind("Saddle", 0) == 0) {
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colors[scenarioIndex] = colorSaddle;
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} else {
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std::cerr << "Label could not be identified" << std::endl;
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}
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}
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std::vector<double> y(optimizationResults.objectiveValue.perSimulationScenario_total.size());
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for (int scenarioIndex = 0; scenarioIndex < scenarioLabels.size(); scenarioIndex++) {
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y[scenarioIndex]
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// = optimizationResults.objectiveValue.perSimulationScenario_rawTranslational[scenarioIndex]
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// + optimizationResults.objectiveValue.perSimulationScenario_rawRotational[scenarioIndex];
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= optimizationResults.objectiveValue
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.perSimulationScenario_total_unweighted[scenarioIndex];
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}
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std::vector<double> x = matplot::linspace(0, y.size() - 1, y.size());
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std::vector<double> markerSizes(y.size(), 5);
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SimulationResultsReporter::createPlot("scenario index",
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"error",
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x,
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y,
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markerSizes,
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colors,
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std::filesystem::path(resultsOutputDir)
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.append("perScenarioObjectiveValues.png"));
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// optimizationResults.saveMeshFiles();
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std::cout << "Saved results to:" << resultsOutputDir << std::endl;
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// optimizationResults.draw();
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// ReducedModelOptimization::Results optResults;
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// optResults.load("/home/iason/Desktop/dlib_ensmallen_comparison/TestSets/"
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// "singlePattern_dlib_firstSubmission/12@single_reduced(100000_1.20)");
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#endif
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return 0;
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}
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