326 lines
12 KiB
C++
326 lines
12 KiB
C++
//#include "main.h"
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#include "mesh.h"
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#include "filter.h"
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#include "Settings.h"
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#include "meshPlotter.h"
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#include "Plotty.h"
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#include <memory>
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#include <thread>
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#include <filesystem>
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#include <chrono>
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#include <Indoor/floorplan/v2/FloorplanReader.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/PoseDetection.h>
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#include <Indoor/sensors/imu/MotionDetection.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/math/stats/Statistics.h>
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#include "FtmKalman.h"
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#include "mainFtm.h"
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#include <sys/stat.h>
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using namespace std::chrono_literals;
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static Stats::Statistics<float> run(Settings::DataSetup setup, int numFile, std::string folder) {
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// reading file
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std::string currDir = std::filesystem::current_path().string();
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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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// ground truth
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std::vector<int> gtPath = setup.gtPath;
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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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double distance = 0;
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for(int 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(NULL));
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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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// wifi
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auto kalmanMap = std::make_shared<std::unordered_map<MACAddress, Kalman>>();
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kalmanMap->insert({ Settings::NUC1, Kalman(1, setup.NUCs.at(Settings::NUC1).kalman_measStdDev) });
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kalmanMap->insert({ Settings::NUC2, Kalman(2, setup.NUCs.at(Settings::NUC2).kalman_measStdDev) });
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kalmanMap->insert({ Settings::NUC3, Kalman(3, setup.NUCs.at(Settings::NUC3).kalman_measStdDev) });
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kalmanMap->insert({ Settings::NUC4, Kalman(4, setup.NUCs.at(Settings::NUC4).kalman_measStdDev) });
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// mesh
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NM::NavMeshSettings set;
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set.maxQuality_m = 0.10; // because of narrow hallways and small rooms reduce min. triangle size (default is 0.2)
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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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const Point3 srcPath0(9.8, 24.9, 0); // fixed start pos
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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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plot.setView(30, 0);
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plot.plot();
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// particle-filter
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const int numParticles = 5000;
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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>();
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eval->kalmanMap = kalmanMap;
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auto trans = std::make_unique<MyPFTrans>(mesh);
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//auto trans = std::make_unique<MyPFTransStatic>();
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auto resample = std::make_unique<SMC::ParticleFilterResamplingSimple<MyState>>();
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auto estimate = std::make_unique<SMC::ParticleFilterEstimationWeightedAverage<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(0.85);
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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(&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 i = 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(e.ts);
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if (e.type == Offline::Sensor::WIFI_FTM) {
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auto ftm = fr.getWifiFtm()[e.idx].data;
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float ftm_offset = Settings::data.CurrentPath.NUCs.at(ftm.getAP().getMAC()).ftm_offset;
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float ftmDist = ftm.getFtmDist() + ftm_offset; // in m; plus static offset
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auto& kalman = kalmanMap->at(ftm.getAP().getMAC());
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float predictDist = kalman.predict(ts, ftmDist);
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ftm.setFtmDist(predictDist);
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obs.wifi.insert_or_assign(ftm.getAP().getMAC(), ftm);
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} else if (e.type == Offline::Sensor::WIFI) {
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//obs.wifi = fr.getWiFiGroupedByTime()[e.idx].data;
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//ctrl.wifi = fr.getWiFiGroupedByTime()[e.idx].data;
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} else if (e.type == Offline::Sensor::ACC) {
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if (sd.add(ts, fr.getAccelerometer()[e.idx].data)) {
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++ctrl.numStepsSinceLastEval;
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}
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const Offline::TS<AccelerometerData>& _acc = fr.getAccelerometer()[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()[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()[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()[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()[e.idx].data);
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obs.activity = act.get();
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}
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if (ctrl.numStepsSinceLastEval > 0)
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//if (ts - lastTimestamp >= Timestamp::fromMS(500))
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//if (obs.wifi.size() == 4)
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{
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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(0,0,0.1);
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lastTimestamp = ts;
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ctrl.lastEstimate = est.pos.pos;
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// draw wifi ranges
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for (auto& ftm : obs.wifi)
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{
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int nucid = Settings::data.CurrentPath.NUCs.at(ftm.second.getAP().getMAC()).ID;
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if (nucid == 1)
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{
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Point3 apPos = Settings::data.CurrentPath.NUCs.find(ftm.first)->second.position;
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//plot.addCircle(nucid, apPos.xy(), ftm.second.getFtmDist());
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}
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}
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obs.wifi.clear();
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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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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((int) act.get());
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//plot.splot.getView().setEnabled(false);
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//plot.splot.getView().setCamera(0, 0);
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//plot.splot.getView().setEqualXY(true);
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plot.plot();
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//std::this_thread::sleep_for(500ms);
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// error calc
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// float err_m = gtPos.getDistance(est.pos.pos);
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// errorStats.add(err_m);
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// errorFile << ts.ms() << " " << err_m << "\n";
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//error calc with penalty for wrong floor
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double errorFactor = 3.0;
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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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}
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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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return errorStats;
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}
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int main(int argc, char** argv)
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{
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mainFtm(argc, argv);
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return 0;
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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 = "prologic/tmp";
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for(int i = 0; i < 2; ++i){
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tmp = run(Settings::data.CurrentPath, 0, 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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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;
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std::cout << "==========================================================" << std::endl;
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//EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS
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std::ofstream finalStatisticFile;
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finalStatisticFile.open (Settings::errorDir + evaluationName + ".csv", std::ios_base::app);
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finalStatisticFile << "========================================================== \n";
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finalStatisticFile << "Average of all statistical data: \n";
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finalStatisticFile << "Median: " << statsMedian.getAvg() << "\n";
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finalStatisticFile << "Average: " << statsAVG.getAvg() << "\n";
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finalStatisticFile << "Standard Deviation: " << statsSTD.getAvg() << "\n";
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finalStatisticFile << "75 Quantil: " << statsQuantil.getAvg() << "\n";
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finalStatisticFile << "========================================================== \n";
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finalStatisticFile.close();
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//std::this_thread::sleep_for(std::chrono::seconds(60));
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}
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