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museumLoc/main.cpp
2018-05-15 09:53:43 +02:00

329 lines
12 KiB
C++
Executable File

//#include "main.h"
#include "navMesh/mesh.h"
#include "navMesh/filter.h"
#include "Settings.h"
#include "navMesh/meshPlotter.h"
#include "Plotty.h"
#include <memory>
#include <thread>
#include <experimental/filesystem>
#include <Indoor/floorplan/v2/FloorplanReader.h>
#include <Indoor/sensors/radio/model/WiFiModelLogDistCeiling.h>
#include <Indoor/sensors/offline/FileReader.h>
#include <Indoor/geo/Heading.h>
#include <Indoor/geo/Point2.h>
#include <Indoor/sensors/imu/TurnDetection.h>
#include <Indoor/sensors/imu/StepDetection.h>
#include <Indoor/sensors/imu/MotionDetection.h>
#include <Indoor/sensors/pressure/RelativePressure.h>
#include <Indoor/data/Timestamp.h>
#include <Indoor/sensors/radio/setup/WiFiOptimizerLogDistCeiling.h>
#include <Indoor/math/stats/Statistics.h>
#include <Indoor/smc/filtering/resampling/ParticleFilterResamplingSimpleImpoverishment.h>
#include <sys/stat.h>
Stats::Statistics<float> run(Settings::DataSetup setup, int numFile, std::string folder) {
// reading file
Floorplan::IndoorMap* map = Floorplan::Reader::readFromFile(setup.map);
Offline::FileReader fr(setup.training[numFile]);
WiFiFingerprints fingerprints(setup.fingerprints);
std::ifstream inp(setup.wifiModel, std::ifstream::binary);
// ground truth
std::vector<int> gtPath;
for(int i = 0; i < setup.numGTPoints; ++i){gtPath.push_back(i);}
Interpolator<uint64_t, Point3> gtInterpolator = fr.getGroundTruthPath(map, gtPath);
Stats::Statistics<float> errorStats;
// error file
const long int t = static_cast<long int>(time(NULL));
auto evalDir = std::experimental::filesystem::path(Settings::errorDir);
evalDir.append(folder);
if (!std::experimental::filesystem::exists(evalDir)) {
std::experimental::filesystem::create_directory(evalDir);
}
std::ofstream errorFile;
errorFile.open (evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t) + ".csv");
// wifi
WiFiModelLogDistCeiling WiFiModel(map);
// with optimization
if(Settings::WiFiModel::optimize){
if (!inp.good() || (inp.peek()&&0) || inp.eof()) {
Assert::isFalse(fingerprints.getFingerprints().empty(), "no fingerprints available!");
WiFiOptimizer::LogDistCeiling opt(map, Settings::WiFiModel::vg_calib);
for (const WiFiFingerprint& fp : fingerprints.getFingerprints()) {
opt.addFingerprint(fp);
}
const WiFiOptimizer::LogDistCeiling::APParamsList res = opt.optimizeAll(opt.NONE);
for (const WiFiOptimizer::LogDistCeiling::APParamsMAC& ap : res.get()) {
const WiFiModelLogDistCeiling::APEntry entry(ap.params.getPos(), ap.params.txp, ap.params.exp, ap.params.waf);
WiFiModel.addAP(ap.mac, entry);
}
WiFiModel.saveXML(setup.wifiModel);
} else {
WiFiModel.loadXML(setup.wifiModel);
}
} else {
// without optimization
WiFiModel.loadAPs(map, Settings::WiFiModel::TXP, Settings::WiFiModel::EXP, Settings::WiFiModel::WAF);
Assert::isFalse(WiFiModel.getAllAPs().empty(), "no AccessPoints stored within the map.xml");
}
// mesh
NM::NavMeshSettings set;
MyNavMesh mesh;
MyNavMeshFactory fac(&mesh, set);
fac.build(map);
const Point3 srcPath0(26, 43, 7.5);
const Point3 srcPath1(62, 38, 1.7);
const Point3 srcPath2(62, 38, 1.8);
const Point3 srcPath3(62, 38, 1.8);
// add shortest-path to destination
//const Point3 dst(51, 45, 1.7);
//const Point3 dst(25, 45, 0);
//NM::NavMeshDijkstra::stamp<MyNavMeshTriangle>(mesh, dst);
// debug show
//MeshPlotter dbg;
//dbg.addFloors(map);
//dbg.addOutline(map);
//dbg.addMesh(mesh);
//dbg.addDijkstra(mesh);
//dbg.draw();
Plotty plot(map);
plot.buildFloorplan();
plot.setGroundTruth(gtPath);
// particle-filter
const int numParticles = 5000;
//auto init = std::make_unique<MyPFInitFixed>(&mesh, srcPath1); // known position
auto init = std::make_unique<MyPFInitUniform>(&mesh); // uniform distribution
auto eval = std::make_unique<MyPFEval>(WiFiModel);
auto trans = std::make_unique<MyPFTrans>(mesh, WiFiModel);
//auto resample = std::make_unique<SMC::ParticleFilterResamplingSimple<MyState>>();
//auto resample = std::make_unique<SMC::ParticleFilterResamplingSimpleImpoverishment<MyState, MyNavMeshTriangle>>();
auto resample = std::make_unique<SMC::ParticleFilterResamplingKLD<MyState>>();
auto estimate = std::make_unique<SMC::ParticleFilterEstimationBoxKDE<MyState>>(map, 0.2, Point2(1,1));
//auto estimate = std::make_unique<SMC::ParticleFilterEstimationWeightedAverage<MyState>>();
//auto estimate = std::make_unique<SMC::ParticleFilterEstimationMax<MyState>>();
// setup
MyFilter pf(numParticles, std::move(init));
pf.setEvaluation(std::move(eval));
pf.setTransition(std::move(trans));
pf.setResampling(std::move(resample));
pf.setEstimation(std::move(estimate));
pf.setNEffThreshold(0.85);
// sensors
MyControl ctrl;
MyObservation obs;
StepDetection sd;
PoseDetection pd;
TurnDetection td(&pd);
RelativePressure relBaro;
ActivityDetector act;
relBaro.setCalibrationTimeframe( Timestamp::fromMS(5000) );
Timestamp lastTimestamp = Timestamp::fromMS(0);
// parse each sensor-value within the offline data
for (const Offline::Entry& e : fr.getEntries()) {
const Timestamp ts = Timestamp::fromMS(e.ts);
if (e.type == Offline::Sensor::WIFI) {
obs.wifi = fr.getWiFiGroupedByTime()[e.idx].data;
ctrl.wifi = fr.getWiFiGroupedByTime()[e.idx].data;
} else if (e.type == Offline::Sensor::ACC) {
if (sd.add(ts, fr.getAccelerometer()[e.idx].data)) {
++ctrl.numStepsSinceLastEval;
}
const Offline::TS<AccelerometerData>& _acc = fr.getAccelerometer()[e.idx];
pd.addAccelerometer(ts, _acc.data);
//simpleActivity walking / standing
act.add(ts, fr.getAccelerometer()[e.idx].data);
} else if (e.type == Offline::Sensor::GYRO) {
const Offline::TS<GyroscopeData>& _gyr = fr.getGyroscope()[e.idx];
const float delta_gyro = td.addGyroscope(ts, _gyr.data);
ctrl.headingChangeSinceLastEval += delta_gyro;
} else if (e.type == Offline::Sensor::BARO) {
relBaro.add(ts, fr.getBarometer()[e.idx].data);
obs.relativePressure = relBaro.getPressureRealtiveToStart();
obs.sigmaPressure = relBaro.getSigma();
//simpleActivity stairs up / down
act.add(ts, fr.getBarometer()[e.idx].data);
obs.activity = act.get();
}
if (ctrl.numStepsSinceLastEval > 0) {
obs.currentTime = ts;
ctrl.currentTime = ts;
// if(ctrl.numStepsSinceLastEval > 0){
// pf.updateTransitionOnly(&ctrl);
// }
MyState est = pf.update(&ctrl, obs); //pf.updateEvaluationOnly(obs);
ctrl.afterEval();
Point3 gtPos = gtInterpolator.get(static_cast<uint64_t>(ts.ms())) + Point3(0,0,0.1);
lastTimestamp = ts;
ctrl.lastEstimate = est.pos.pos;
//plot
//dbg.showParticles(pf.getParticles());
//dbg.setCurPos(est.pos.pos);
//dbg.setGT(gtPos);
//dbg.addEstimationNode(est.pos.pos);
//dbg.addGroundTruthNode(gtPos);
//dbg.setTimeInMinute(static_cast<int>(ts.sec()) / 60, static_cast<int>(static_cast<int>(ts.sec())%60));
//dbg.draw();
plot.showParticles(pf.getParticles());
plot.setCurEst(est.pos.pos);
plot.setGroundTruth(gtPos);
plot.addEstimationNode(est.pos.pos);
plot.setActivity((int) act.get());
//plot.plot();
// error calc
float err_m = gtPos.getDistance(est.pos.pos);
errorStats.add(err_m);
errorFile << ts.ms() << " " << err_m << "\n";
//dbg.gp.setOutput("/tmp/123/" + std::to_string(i) + ".png");
//dbg.gp.setTerminal("pngcairo", K::GnuplotSize(60, 30));
}
}
// get someting on console
std::cout << "Statistical Analysis Filtering: " << std::endl;
std::cout << "Median: " << errorStats.getMedian() << " Average: " << errorStats.getAvg() << " Std: " << errorStats.getStdDev() << std::endl;
// save the statistical data in file
errorFile << "========================================================== \n";
errorFile << "Average of all statistical data: \n";
errorFile << "Median: " << errorStats.getMedian() << "\n";
errorFile << "Average: " << errorStats.getAvg() << "\n";
errorFile << "Standard Deviation: " << errorStats.getStdDev() << "\n";
errorFile << "75 Quantil: " << errorStats.getQuantile(0.75) << "\n";
errorFile.close();
/* plot in gp file */
std::ofstream plotFile;
plotFile.open(evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t) + ".gp");
plot.saveToFile(plotFile);
plotFile.close();
//save also a png image, just for a better overview
plot.printOverview(evalDir.string() + "/" + std::to_string(numFile) + "_" + std::to_string(t));
plot.plot();
return errorStats;
}
int main(int argc, char** argv) {
Stats::Statistics<float> statsAVG;
Stats::Statistics<float> statsMedian;
Stats::Statistics<float> statsSTD;
Stats::Statistics<float> statsQuantil;
Stats::Statistics<float> tmp;
std::string evaluationName = "museum/tmp";
for(int i = 0; i < 1; ++i){
//TODO: in transition die distance über KLD noch einkommentieren als Test
// for(int j = 0; j < Settings::data.Path0.training.size(); ++j){
// tmp = run(Settings::data.Path0, j, evaluationName);
// statsMedian.add(tmp.getMedian());
// statsAVG.add(tmp.getAvg());
// statsSTD.add(tmp.getStdDev());
// statsQuantil.add(tmp.getQuantile(0.75));
// }
// for(int j = 0; j < Settings::data.Path1.training.size(); ++j){
// tmp = run(Settings::data.Path1, j, evaluationName);
// statsMedian.add(tmp.getMedian());
// statsAVG.add(tmp.getAvg());
// statsSTD.add(tmp.getStdDev());
// statsQuantil.add(tmp.getQuantile(0.75));
// }
// for(int j = 0; j < Settings::data.Path2.training.size(); ++j){
// tmp = run(Settings::data.Path2, j, evaluationName);
// statsMedian.add(tmp.getMedian());
// statsAVG.add(tmp.getAvg());
// statsSTD.add(tmp.getStdDev());
// statsQuantil.add(tmp.getQuantile(0.75));
// }
for(int j = 0; j < Settings::data.Path3.training.size(); ++j){
tmp = run(Settings::data.Path3, j, evaluationName);
statsMedian.add(tmp.getMedian());
statsAVG.add(tmp.getAvg());
statsSTD.add(tmp.getStdDev());
statsQuantil.add(tmp.getQuantile(0.75));
}
std::cout << "Iteration " << i << " completed" << std::endl;;
}
std::cout << "==========================================================" << std::endl;
std::cout << "Average of all statistical data: " << std::endl;
std::cout << "Median: " << statsMedian.getAvg() << std::endl;
std::cout << "Average: " << statsAVG.getAvg() << std::endl;
std::cout << "Standard Deviation: " << statsSTD.getAvg() << std::endl;
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));
}