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simplify and add smoother_update_times

release/4.3a0
Varun Agrawal 2025-01-28 16:10:20 -05:00 committed by Frank Dellaert
parent 761d19ab4f
commit 5e99b0e34d
1 changed files with 20 additions and 8 deletions
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28
examples/Hybrid_City10000.cpp
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@ -90,16 +90,12 @@ HybridNonlinearFactor HybridLoopClosureFactor(size_t loop_counter, size_t key_s,
size_t key_t, size_t key_t,
const Pose2& measurement) { const Pose2& measurement) {
DiscreteKey l(L(loop_counter), 2); DiscreteKey l(L(loop_counter), 2);
noiseModel::Diagonal::shared_ptr loop_noise_model =
noiseModel::Diagonal::Sigmas(
Vector3(1.0 / 30.0, 1.0 / 30.0, 1.0 / 100.0));
noiseModel::Diagonal::shared_ptr loose_noise_model =
noiseModel::Diagonal::Sigmas(Vector3::Ones() * 100);
auto f0 = std::make_shared<BetweenFactor<Pose2>>( auto f0 = std::make_shared<BetweenFactor<Pose2>>(
X(key_s), X(key_t), measurement, loose_noise_model); X(key_s), X(key_t), measurement,
noiseModel::Diagonal::Sigmas(Vector3::Ones() * 100));
auto f1 = std::make_shared<BetweenFactor<Pose2>>( auto f1 = std::make_shared<BetweenFactor<Pose2>>(
X(key_s), X(key_t), measurement, loop_noise_model); X(key_s), X(key_t), measurement, pose_noise_model);
std::vector<NonlinearFactorValuePair> factors{{f0, 0.0}, {f1, 0.0}}; std::vector<NonlinearFactorValuePair> factors{{f0, 0.0}, {f1, 0.0}};
HybridNonlinearFactor mixtureFactor(l, {f0, f1}); HybridNonlinearFactor mixtureFactor(l, {f0, f1});
return mixtureFactor; return mixtureFactor;
@ -145,7 +141,7 @@ int main(int argc, char* argv[]) {
std::list<double> time_list; std::list<double> time_list;
HybridSmoother smoother(0.99); HybridSmoother smoother;
HybridNonlinearFactorGraph graph; HybridNonlinearFactorGraph graph;
@ -163,7 +159,12 @@ int main(int argc, char* argv[]) {
graph.push_back(PriorFactor<Pose2>(X(0), prior_pose, prior_noise_model)); graph.push_back(PriorFactor<Pose2>(X(0), prior_pose, prior_noise_model));
std::vector<std::pair<size_t, double>> smoother_update_times;
clock_t before_update = clock();
SmootherUpdate(smoother, graph, initial, maxNrHypotheses, &result); SmootherUpdate(smoother, graph, initial, maxNrHypotheses, &result);
clock_t after_update = clock();
smoother_update_times.push_back({index, after_update - before_update});
size_t key_s, key_t{0}; size_t key_s, key_t{0};
@ -223,7 +224,10 @@ int main(int argc, char* argv[]) {
if (smoother_update) { if (smoother_update) {
gttic_(SmootherUpdate); gttic_(SmootherUpdate);
before_update = clock();
SmootherUpdate(smoother, graph, initial, maxNrHypotheses, &result); SmootherUpdate(smoother, graph, initial, maxNrHypotheses, &result);
after_update = clock();
smoother_update_times.push_back({index, after_update - before_update});
gttoc_(SmootherUpdate); gttoc_(SmootherUpdate);
} }
@ -246,7 +250,10 @@ int main(int argc, char* argv[]) {
index += 1; index += 1;
} }
before_update = clock();
SmootherUpdate(smoother, graph, initial, maxNrHypotheses, &result); SmootherUpdate(smoother, graph, initial, maxNrHypotheses, &result);
after_update = clock();
smoother_update_times.push_back({index, after_update - before_update});
gttic_(HybridSmootherOptimize); gttic_(HybridSmootherOptimize);
HybridValues delta = smoother.hybridBayesNet().optimize(); HybridValues delta = smoother.hybridBayesNet().optimize();
@ -262,6 +269,11 @@ int main(int argc, char* argv[]) {
/// Write result to file /// Write result to file
write_result(result, (key_t + 1), "Hybrid_City10000.txt"); write_result(result, (key_t + 1), "Hybrid_City10000.txt");
//TODO Write to file
// for (size_t i = 0; i < smoother_update_times.size(); i++) {
// auto p = smoother_update_times.at(i);
// std::cout << p.first << ", " << p.second / CLOCKS_PER_SEC << std::endl;
// }
ofstream outfile_time; ofstream outfile_time;
std::string time_file_name = "Hybrid_City10000_time.txt"; std::string time_file_name = "Hybrid_City10000_time.txt";
outfile_time.open(time_file_name); outfile_time.open(time_file_name);