init push
This commit is contained in:
toni
430
main.cpp
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430
main.cpp
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//#include "main.h"
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#include "Settings.h"
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#include "Plotty.h"
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// navMesh
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#include "navMesh/mesh.h"
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#include "navMesh/filter.h"
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#include "navMesh/meshPlotter.h"
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#include <memory>
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#include <thread>
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#include <experimental/filesystem>
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#include <Indoor/floorplan/v2/FloorplanReader.h>
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#include <Indoor/sensors/radio/model/WiFiModelLogDistCeiling.h>
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#include <Indoor/sensors/offline/FileReader.h>
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#include <Indoor/geo/Heading.h>
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#include <Indoor/geo/Point2.h>
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#include <Indoor/sensors/imu/TurnDetection.h>
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#include <Indoor/sensors/imu/StepDetection.h>
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#include <Indoor/sensors/imu/MotionDetection.h>
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#include <Indoor/sensors/imu/PoseDetection.h>
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#include <Indoor/sensors/pressure/RelativePressure.h>
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#include <Indoor/data/Timestamp.h>
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#include <Indoor/sensors/radio/model/WiFiModels.h>
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#include <Indoor/sensors/radio/setup/WiFiOptimizer.h>
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#include <Indoor/sensors/radio/setup/WiFiOptimizerLogDistCeiling.h>
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#include <Indoor/sensors/radio/setup/WiFiOptimizerPerFloor.h>
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#include <Indoor/math/stats/Statistics.h>
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#include <Indoor/smc/filtering/resampling/ParticleFilterResamplingSimpleImpoverishment.h>
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#include <Indoor/smc/filtering/resampling/ParticleFilterResamplingKDE.h>
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#include <Indoor/smc/filtering/resampling/ParticleFilterResamplingKDEPercent.h>
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#include <sys/stat.h>
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Stats::Statistics<float> run(Settings::DataSetup setup, unsigned long numFile, std::string folder) {
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// reading file
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Floorplan::IndoorMap* map = Floorplan::Reader::readFromFile(setup.map);
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Offline::FileReader fr(setup.training[numFile]);
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WiFiFingerprints fingerprints(setup.fingerprints);
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std::ifstream inp(setup.wifiModel, std::ifstream::binary);
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// ground truth
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std::vector<int> gtPath;
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for(int i = 0; i < setup.numGTPoints; ++i){gtPath.push_back(i);}
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Interpolator<uint64_t, Point3> gtInterpolator = fr.getGroundTruthPath(map, gtPath);
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Stats::Statistics<float> errorStats;
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//calculate distance of path
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std::vector<Interpolator<uint64_t, Point3>::InterpolatorEntry> gtEntries = gtInterpolator.getEntries();
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float distance = 0;
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for(unsigned long i = 1; i < gtEntries.size(); ++i){
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distance += gtEntries[i].value.getDistance(gtEntries[i-1].value);
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}
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std::cout << "Distance of Path: " << distance << std::endl;
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// error file
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const long int t = static_cast<long int>(time(nullptr));
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auto evalDir = std::experimental::filesystem::path(Settings::errorDir);
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evalDir.append(folder);
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if (!std::experimental::filesystem::exists(evalDir)) {
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std::experimental::filesystem::create_directory(evalDir);
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}
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std::ofstream errorFile;
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errorFile.open (evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t) + ".csv");
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std::ofstream activityFile;
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activityFile.open (evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t) + "_activity.csv");
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// wifi
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// WiFiModelLogDistCeiling WiFiModel(map);
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// WiFiModelPerFloor WiFiModelPerFloor(map);
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// WiFiModelPerBBox WiFiModelPerBBox(map);
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WiFiModel* wifiModel = nullptr;
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// with optimization
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if(Settings::WiFiModel::optimize){
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if (!inp.good() || (inp.peek()) || inp.eof()) {
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Assert::isFalse(fingerprints.getFingerprints().empty(), "no fingerprints available!");
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if (Settings::WiFiModel::useRegionalOpt) {
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// use a regional optimization scheme (one per floor)
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WiFiOptimizer::PerFloor opt(map, Settings::WiFiModel::vg_calib, WiFiOptimizer::Mode::QUALITY);
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WiFiOptimizer::LogDistCeiling ldc(map, Settings::WiFiModel::vg_calib, WiFiOptimizer::Mode::QUALITY);
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// add all fingerprints to the optimizer (optimizer will add them to the correct floor/model)
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for (const WiFiFingerprint& fp : fingerprints.getFingerprints()) {
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opt.addFingerprint(fp);
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}
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wifiModel = dynamic_cast<WiFiModel*>(opt.optimizeAll(ldc.MIN_2_FPS));
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wifiModel->saveXML(setup.wifiModel);
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} else {
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/** NOTE: Funktioniert fürs Museum VIEL VIEL Besser */
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// use one model per AP for the whole map
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wifiModel = dynamic_cast<WiFiModel*>(new WiFiModelLogDistCeiling(map));
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WiFiOptimizer::LogDistCeiling opt(map, Settings::WiFiModel::vg_calib);
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for (const WiFiFingerprint& fp : fingerprints.getFingerprints()) {
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opt.addFingerprint(fp);
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}
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const WiFiOptimizer::LogDistCeiling::APParamsList res = opt.optimizeAll(opt.NONE);
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for (const WiFiOptimizer::LogDistCeiling::APParamsMAC& ap : res.get()) {
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const WiFiModelLogDistCeiling::APEntry entry(ap.params.getPos(), ap.params.txp, ap.params.exp, ap.params.waf);
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(dynamic_cast<WiFiModelLogDistCeiling*>(wifiModel))->addAP(ap.mac, entry);
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}
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wifiModel->saveXML(setup.wifiModel);
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}
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} else {
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// load WiFiModel from file. The factory will create the correct instance
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//WiFiModel->loadXML(setup.wifiModel);
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WiFiModelFactory fac(map);
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wifiModel = fac.loadXML(setup.wifiModel);
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}
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} else {
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// without optimization
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wifiModel = dynamic_cast<WiFiModel*>(new WiFiModelLogDistCeiling(map));
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(dynamic_cast<WiFiModelLogDistCeiling*>(wifiModel))->loadAPs(map, Settings::WiFiModel::TXP, Settings::WiFiModel::EXP, Settings::WiFiModel::WAF);
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Assert::isFalse(wifiModel->getAllAPs().empty(), "no AccessPoints stored within the map.xml");
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}
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// mesh
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NM::NavMeshSettings set;
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MyNavMesh mesh;
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MyNavMeshFactory fac(&mesh, set);
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fac.build(map);
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//add destination
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NM::NavMeshDijkstra::stamp(mesh, gtEntries.back().value);
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const Point3 srcPath0(26, 43, 7.5f);
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const Point3 srcPath1(62, 38, 1.7f);
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const Point3 srcPath2(62, 38, 1.8f);
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const Point3 srcPath3(62, 38, 1.8f);
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// add shortest-path to destination
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//const Point3 dst(51, 45, 1.7);
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//const Point3 dst(25, 45, 0);
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//NM::NavMeshDijkstra::stamp<MyNavMeshTriangle>(mesh, dst);
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// debug show
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//MeshPlotter dbg;
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//dbg.addFloors(map);
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//dbg.addOutline(map);
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//dbg.addMesh(mesh);
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//dbg.addDijkstra(mesh);
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//dbg.draw();
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Plotty plot(map);
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plot.buildFloorplan();
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plot.setGroundTruth(gtPath);
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// particle-filter
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const int numParticles = Settings::numParticles;
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//auto init = std::make_unique<MyPFInitFixed>(&mesh, srcPath0); // known position
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auto init = std::make_unique<MyPFInitUniform>(&mesh); // uniform distribution
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auto eval = std::make_unique<MyPFEval>(*wifiModel);
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auto trans = std::make_unique<MyPFTrans>(mesh, *wifiModel);
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auto resample = std::make_unique<SMC::ParticleFilterResamplingSimple<MyState>>();
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//auto resample = std::make_unique<SMC::ParticleFilterResamplingKDE<MyState, MyNavMeshTriangle>>(&mesh, Settings::KDE3D::gridSize, Settings::KDE3D::bandwidth);
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//auto resample = std::make_unique<SMC::ParticleFilterResamplingKDEPercent<MyState, MyNavMeshTriangle>>(&mesh, Settings::KDE3D::gridSize, Settings::KDE3D::bandwidth, 0.75);
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//auto resample = std::make_unique<SMC::ParticleFilterResamplingSimpleImpoverishment<MyState, MyNavMeshTriangle>>();
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//auto resample = std::make_unique<SMC::ParticleFilterResamplingKLD<MyState>>();
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//auto estimate = std::make_unique<SMC::ParticleFilterEstimationBoxKDE<MyState>>(map, 0.2, Point2(1,1));
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auto estimate = std::make_unique<SMC::ParticleFilterEstimationWeightedAverage<MyState>>();
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//auto estimate = std::make_unique<SMC::ParticleFilterEstimationMax<MyState>>();
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// setup
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MyFilter pf(numParticles, std::move(init));
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pf.setEvaluation(std::move(eval));
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pf.setTransition(std::move(trans));
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pf.setResampling(std::move(resample));
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pf.setEstimation(std::move(estimate));
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pf.setNEffThreshold(0.5);
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// sensors
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MyControl ctrl;
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MyObservation obs;
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StepDetection sd;
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PoseDetection pd;
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TurnDetection td(dynamic_cast<PoseProvider*>(&pd));
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RelativePressure relBaro;
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ActivityDetector act;
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relBaro.setCalibrationTimeframe( Timestamp::fromMS(5000) );
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Timestamp lastTimestamp = Timestamp::fromMS(0);
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int gtActivity = 0;
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// parse each sensor-value within the offline data
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for (const Offline::Entry& e : fr.getEntries()) {
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const Timestamp ts = Timestamp::fromMS(static_cast<long>(e.ts));
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if (e.type == Offline::Sensor::WIFI) {
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obs.wifi = fr.getWiFiGroupedByTime()[static_cast<unsigned long>(e.idx)].data;
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ctrl.wifi = fr.getWiFiGroupedByTime()[static_cast<unsigned long>(e.idx)].data;
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} else if (e.type == Offline::Sensor::ACC) {
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if (sd.add(ts, fr.getAccelerometer()[static_cast<unsigned long>(e.idx)].data)) {
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++ctrl.numStepsSinceLastEval;
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}
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const Offline::TS<AccelerometerData>& _acc = fr.getAccelerometer()[static_cast<unsigned long>(e.idx)];
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pd.addAccelerometer(ts, _acc.data);
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//simpleActivity walking / standing
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act.add(ts, fr.getAccelerometer()[static_cast<unsigned long>(e.idx)].data);
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} else if (e.type == Offline::Sensor::GYRO) {
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const Offline::TS<GyroscopeData>& _gyr = fr.getGyroscope()[static_cast<unsigned long>(e.idx)];
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const float delta_gyro = td.addGyroscope(ts, _gyr.data);
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ctrl.headingChangeSinceLastEval += delta_gyro;
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} else if (e.type == Offline::Sensor::BARO) {
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relBaro.add(ts, fr.getBarometer()[static_cast<unsigned long>(e.idx)].data);
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obs.relativePressure = relBaro.getPressureRealtiveToStart();
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obs.sigmaPressure = relBaro.getSigma();
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//simpleActivity stairs up / down
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act.add(ts, fr.getBarometer()[static_cast<unsigned long>(e.idx)].data);
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activityFile << ts.ms() << " " << gtActivity << " " << static_cast<int>(act.get()) << "\n";
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} else if (e.type == Offline::Sensor::ACTIVITY) {
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//get the activity recorded by the user by pressing a button
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gtActivity = fr.getActivity()[static_cast<unsigned long>(e.idx)].data;
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}
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if (ctrl.numStepsSinceLastEval > 0) {
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obs.currentTime = ts;
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ctrl.currentTime = ts;
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// if(ctrl.numStepsSinceLastEval > 0){
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// pf.updateTransitionOnly(&ctrl);
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// }
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MyState est = pf.update(&ctrl, obs); //pf.updateEvaluationOnly(obs);
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ctrl.afterEval();
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Point3 gtPos = gtInterpolator.get(static_cast<uint64_t>(ts.ms())) + Point3(0,0,0.1f);
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lastTimestamp = ts;
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ctrl.lastEstimate = est.pos.pos;
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//plot
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//dbg.showParticles(pf.getParticles());
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//dbg.setCurPos(est.pos.pos);
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//dbg.setGT(gtPos);
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//dbg.addEstimationNode(est.pos.pos);
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//dbg.addGroundTruthNode(gtPos);
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//dbg.setTimeInMinute(static_cast<int>(ts.sec()) / 60, static_cast<int>(static_cast<int>(ts.sec())%60));
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//dbg.draw();
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//get shortest path to destination and plot
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est.pos = mesh.getLocationNearestTo(est.pos.pos);
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std::vector<NM::NavMeshLocation<MyNavMeshTriangle>> path = est.pos.tria->getPathToDestination<MyNavMeshTriangle>(est.pos.pos);
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plot.setPathToDestination(path);
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plot.showParticles(pf.getParticles());
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plot.setCurEst(est.pos.pos);
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plot.setGroundTruth(gtPos);
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plot.addEstimationNode(est.pos.pos);
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plot.setActivity(static_cast<int>(act.get()));
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plot.plot();
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//error calc with penalty for wrong floor
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float errorFactor = 3.0f;
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Point3 gtPosError = Point3(gtPos.x, gtPos.y, errorFactor * gtPos.z);
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Point3 estError = Point3(est.pos.pos.x, est.pos.pos.y, errorFactor * est.pos.pos.z);
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float err_m = gtPosError.getDistance(estError);
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errorStats.add(err_m);
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errorFile << ts.ms() << " " << err_m << "\n";
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//stuff for drawing
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// plot.gp << "set terminal png size 1280,720\n";
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// plot.gp.setOutput("/tmp/videoSparkasse/" + std::to_string(i++) + ".png");
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// int degree = ((30 - i) % 360);
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// if (degree < 0){degree += 360;}
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// plot.gp << "set view 63,"<< degree << "\n";
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// plot.gp << "set autoscale xy\n";
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// plot.gp << "set autoscale z\n";
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// plot.plot();
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}
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}
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// get someting on console
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std::cout << "Statistical Analysis Filtering: " << std::endl;
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std::cout << "Median: " << errorStats.getMedian() << " Average: " << errorStats.getAvg() << " Std: " << errorStats.getStdDev() << std::endl;
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// save the statistical data in file
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errorFile << "========================================================== \n";
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errorFile << "Average of all statistical data: \n";
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errorFile << "Median: " << errorStats.getMedian() << "\n";
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errorFile << "Average: " << errorStats.getAvg() << "\n";
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errorFile << "Standard Deviation: " << errorStats.getStdDev() << "\n";
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errorFile << "75 Quantil: " << errorStats.getQuantile(0.75) << "\n";
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errorFile.close();
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//activityFile << "===================================================== \n";
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//activityFile << "Falsche Zustandswechsel: " << numFalseActivityChange;
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activityFile.close();
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/* plot in gp file */
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std::ofstream plotFile;
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plotFile.open(evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t) + ".gp");
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plot.saveToFile(plotFile);
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plotFile.close();
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//save also a png image, just for a better overview
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plot.printOverview(evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t));
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plot.plot();
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plot.closeStream();
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return errorStats;
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}
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int main() {
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Stats::Statistics<float> statsAVG;
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Stats::Statistics<float> statsMedian;
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Stats::Statistics<float> statsSTD;
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Stats::Statistics<float> statsQuantil;
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Stats::Statistics<float> tmp;
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std::string evaluationName = "Test_ParticleFilter_Standard";
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for(int i = 0; i < 1; ++i){
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for(unsigned long j = 0; j < Settings::data.Path0.training.size(); ++j){
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tmp = run(Settings::data.Path0, j, evaluationName);
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statsMedian.add(tmp.getMedian());
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statsAVG.add(tmp.getAvg());
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statsSTD.add(tmp.getStdDev());
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statsQuantil.add(tmp.getQuantile(0.75));
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}
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// for(int j = 0; j < Settings::data.Path1.training.size(); ++j){
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// tmp = run(Settings::data.Path1, j, evaluationName);
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// statsMedian.add(tmp.getMedian());
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// statsAVG.add(tmp.getAvg());
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// statsSTD.add(tmp.getStdDev());
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// statsQuantil.add(tmp.getQuantile(0.75));
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// }
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// for(int j = 0; j < Settings::data.Path2.training.size(); ++j){
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// tmp = run(Settings::data.Path2, j, evaluationName);
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// statsMedian.add(tmp.getMedian());
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// statsAVG.add(tmp.getAvg());
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// statsSTD.add(tmp.getStdDev());
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// statsQuantil.add(tmp.getQuantile(0.75));
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// }
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// for(int j = 0; j < Settings::data.Path3.training.size(); ++j){
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// tmp = run(Settings::data.Path3, j, evaluationName);
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// statsMedian.add(tmp.getMedian());
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// statsAVG.add(tmp.getAvg());
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// statsSTD.add(tmp.getStdDev());
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// statsQuantil.add(tmp.getQuantile(0.75));
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// }
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// for(int j = 0; j < 1; ++j){
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// tmp = run(Settings::data.Stairs, j, evaluationName);
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// statsMedian.add(tmp.getMedian());
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// statsAVG.add(tmp.getAvg());
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// statsSTD.add(tmp.getStdDev());
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// statsQuantil.add(tmp.getQuantile(0.75));
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// }
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std::cout << "Iteration " << i << " completed" << std::endl;
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}
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std::cout << "==========================================================" << std::endl;
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std::cout << "Average of all statistical data: " << std::endl;
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std::cout << "Median: " << statsMedian.getAvg() << std::endl;
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std::cout << "Average: " << statsAVG.getAvg() << std::endl;
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std::cout << "Standard Deviation: " << statsSTD.getAvg() << std::endl;
|
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std::cout << "75 Quantil: " << statsQuantil.getAvg() << std::endl;
|
||||
std::cout << "==========================================================" << std::endl;
|
||||
|
||||
//EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS
|
||||
std::ofstream finalStatisticFile;
|
||||
finalStatisticFile.open (Settings::errorDir + evaluationName + ".csv", std::ios_base::app);
|
||||
|
||||
finalStatisticFile << "========================================================== \n";
|
||||
finalStatisticFile << "Average of all statistical data: \n";
|
||||
finalStatisticFile << "Median: " << statsMedian.getAvg() << "\n";
|
||||
finalStatisticFile << "Average: " << statsAVG.getAvg() << "\n";
|
||||
finalStatisticFile << "Standard Deviation: " << statsSTD.getAvg() << "\n";
|
||||
finalStatisticFile << "75 Quantil: " << statsQuantil.getAvg() << "\n";
|
||||
finalStatisticFile << "========================================================== \n";
|
||||
|
||||
finalStatisticFile.close();
|
||||
|
||||
//std::this_thread::sleep_for(std::chrono::seconds(60));
|
||||
|
||||
}
|
||||
Reference in New Issue
Block a user