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ReducedModelOptimization
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Makes multiple copies of the reduced model such that they can be used in the openmp paralllel loop.

This commit is contained in:
Iason 2021-02-04 16:05:48 +02:00
parent 858282c859
commit 265680ea05
1 changed files with 31 additions and 37 deletions
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68
src/main.cpp
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@ -24,25 +24,28 @@ int main(int argc, char *argv[]) {
std::vector<vcg::Point2i> singleBarReducedModelEdges{vcg::Point2i(0, 3)};
FlatPattern singleBarReducedModel(numberOfNodesPerSlot,
singleBarReducedModelEdges);
singleBarReducedModel.setLabel("Single bar reduced model");
singleBarReducedModel.setLabel("SingleBar_reduced");
singleBarReducedModel.scale(0.03);
singleBarReducedModel.savePly(singleBarReducedModel.getLabel() + ".ply");
std::vector<vcg::Point2i> CWreducedModelEdges{vcg::Point2i(1, 5),
vcg::Point2i(3, 1)};
FlatPattern CWReducedModel(numberOfNodesPerSlot, CWreducedModelEdges);
CWReducedModel.setLabel("CW reduced model");
CWReducedModel.setLabel("CW_reduced");
CWReducedModel.scale(0.03);
std::vector<vcg::Point2i> CCWreducedModelEdges{vcg::Point2i(1, 5),
vcg::Point2i(3, 5)};
FlatPattern CCWReducedModel(numberOfNodesPerSlot, CCWreducedModelEdges);
CCWReducedModel.setLabel("CCW reduced model");
CCWReducedModel.setLabel("CCW_reduced");
CCWReducedModel.scale(0.03);
std::vector<FlatPattern *> reducedModels{&singleBarReducedModel,
&CWReducedModel, &CCWReducedModel};
// Define the ranges that the optimizer will use
ReducedModelOptimizer::xRange beamWidth{"B", 0.5, 1.5};
ReducedModelOptimizer::xRange beamDimensionsRatio{"bOverh", 0.7, 1.3};
ReducedModelOptimizer::xRange beamE{"E", 0.1, 1.9};
// Test set of full patterns
std::string fullPatternsTestSetDirectory = "../TestSet";
// "/home/iason/Documents/PhD/Research/Approximating shapes with flat "
@ -71,19 +74,16 @@ int main(int argc, char *argv[]) {
// for (double rangeOffset = 0.15; rangeOffset <= 0.95; rangeOffset += 0.05)
// {
ReducedModelOptimizer::Settings settings;
for (settings.maxSimulations = 2600; settings.maxSimulations < 5000;
settings.maxSimulations += 200) {
ReducedModelOptimizer::xRange beamWidth{"B", 0.5, 1.5};
ReducedModelOptimizer::xRange beamDimensionsRatio{"bOverh", 0.7, 1.3};
ReducedModelOptimizer::xRange beamE{"E", 0.1, 1.9};
for (settings.maxSimulations = 100; settings.maxSimulations < 3500;
settings.maxSimulations += 100) {
std::string xRangesString = beamWidth.toString() + " " +
beamDimensionsRatio.toString() + " " +
beamE.toString();
std::cout << xRangesString << std::endl;
settings.xRanges = {beamWidth, beamDimensionsRatio, beamE};
std::filesystem::path thisOptimizationDirectory(
std::filesystem::path("../OptimizationResults").append(xRangesString));
std::filesystem::create_directories(thisOptimizationDirectory);
// std::filesystem::path thisOptimizationDirectory(
// std::filesystem::path("../OptimizationResults").append(xRangesString));
// std::filesystem::create_directories(thisOptimizationDirectory);
// csvfile thisOptimizationStatistics(
// std::filesystem::path(thisOptimizationDirectory)
// .append("statistics.csv")
@ -96,10 +96,9 @@ int main(int argc, char *argv[]) {
resultsPerPattern(patternPairs.size());
auto start = std::chrono::high_resolution_clock::now();
#pragma omp parallel for // schedule(static) num_threads(8)
//#pragma omp parallel for
for (int patternPairIndex = 0; patternPairIndex < patternPairs.size();
patternPairIndex++) {
FlatPattern *pPattern = patternPairs[patternPairIndex].first;
// const auto filepathString = filepath.string();
// Use only the base triangle version
// std::cout << "Full pattern:" << filepathString << std::endl;
@ -120,27 +119,13 @@ int main(int argc, char *argv[]) {
// cp.copy(*reducedModels[0]);
const std::vector<size_t> numberOfNodesPerSlot{1, 0, 0, 2, 1, 2, 1};
ReducedModelOptimizer optimizer(numberOfNodesPerSlot);
optimizer.initializePatterns(*pPattern,
optimizer.initializePatterns(*patternPairs[patternPairIndex].first,
*patternPairs[patternPairIndex].second,
optimizationSpaceSamplingDisplacements,
optimizationExcludedEi);
// optimizer.optimize({ReducedModelOptimizer::Axial});
ReducedModelOptimizer::Results optimizationResults =
optimizer.optimize(settings);
// errors.push_back(optimizationResults.objectiveValue);
// SimulationResultsReporter::createPlot(
// "", "Objective value", errors,
// std::filesystem::path(thisOptimizationDirectory)
// .append("ObjectiveValues.png")
// .string());
// thisOptimizationStatistics << filepath.stem().string()
// << optimizationResults.objectiveValue;
// if (optimizationResults.numberOfSimulationCrashes == 0) {
// thisOptimizationStatistics << "No crashes";
// } else {
// thisOptimizationStatistics
// << optimizationResults.numberOfSimulationCrashes;
// }
// thisOptimizationStatistics << endrow;
totalError += optimizationResults.objectiveValue;
resultsPerPattern[patternPairIndex] =
@ -159,6 +144,16 @@ int main(int argc, char *argv[]) {
auto runtime_ms =
std::chrono::duration_cast<std::chrono::milliseconds>(end - start);
// for (int patternPairIndex = 0; patternPairIndex < patternPairs.size();
// patternPairIndex++) {
// std::filesystem::path
// saveToPath(std::filesystem::path("../OptimizationResults")
// .append(resultsPerPattern[patternPairIndex].first));
// std::filesystem::create_directory(std::filesystem::path(saveToPath));
// resultsPerPattern[patternPairIndex].second.save(saveToPath);
// }
csvfile statistics(std::filesystem::path("../OptimizationResults")
.append("statistics.csv")
.string(),
@ -176,19 +171,18 @@ int main(int argc, char *argv[]) {
statistics << totalError;
for (const auto &patternObjectiveValue : resultsPerPattern) {
statistics << patternObjectiveValue.second.objectiveValue;
}
statistics << runtime_ms.count() / 1000.0;
for (const auto &patternObjectiveValue : resultsPerPattern) {
for (const double &optimalX : patternObjectiveValue.second.x) {
statistics << optimalX;
}
}
statistics << runtime_ms.count() / 1000.0;
statistics << endrow;
}
for(auto patternPair:patternPairs){
delete patternPair.first;
delete patternPair.second;
}
for (auto patternPair : patternPairs) {
delete patternPair.first;
delete patternPair.second;
}
return 0;
}