FHWS/FtmPrologic
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Refactored code to walk multiple runs

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This commit is contained in:
Markus Bullmann
2019-10-08 16:46:22 +02:00
parent 08be3e9af5
commit 8236069094
7 changed files with 130 additions and 78 deletions
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122
code/main.cpp
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@@ -50,7 +50,7 @@ std::vector<std::tuple<float, float, float>> getFtmValues(Offline::FileReader& f
if (wifi.getAP().getMAC() == nuc)
{
Point3 apPos = Settings::data.CurrentPath.NUCs.find(wifi.getAP().getMAC())->second.position;
Point3 apPos = Settings::CurrentPath.NUCs.find(wifi.getAP().getMAC())->second.position;
float apDist = gtPos.getDistance(apPos);
float ftmDist = wifi.getFtmDist();
float rssi = wifi.getRSSI();
@@ -155,9 +155,9 @@ void exportFtmValues(Offline::FileReader& fr, Interpolator<uint64_t, Point3>& gt
auto wifi = fr.getWifiFtm()[e.idx].data;
int nucid = Settings::data.CurrentPath.NUCs.at(wifi.getAP().getMAC()).ID;
float ftm_offset = Settings::data.CurrentPath.NUCs.at(wifi.getAP().getMAC()).ftm_offset;
float rssi_pathloss = Settings::data.CurrentPath.NUCs.at(wifi.getAP().getMAC()).rssi_pathloss;
int nucid = Settings::CurrentPath.NUCs.at(wifi.getAP().getMAC()).ID;
float ftm_offset = Settings::CurrentPath.NUCs.at(wifi.getAP().getMAC()).ftm_offset;
float rssi_pathloss = Settings::CurrentPath.NUCs.at(wifi.getAP().getMAC()).rssi_pathloss;
float rssiDist = LogDistanceModel::rssiToDistance(-40, rssi_pathloss, wifi.getRSSI());
float ftmDist = wifi.getFtmDist() + ftm_offset; //in m; plus static offset
@@ -165,7 +165,7 @@ void exportFtmValues(Offline::FileReader& fr, Interpolator<uint64_t, Point3>& gt
int numMeas = wifi.getNumAttemptedMeasurements();
int numSuccessMeas = wifi.getNumSuccessfulMeasurements();
Point3 apPos = Settings::data.CurrentPath.NUCs.find(wifi.getAP().getMAC())->second.position;
Point3 apPos = Settings::CurrentPath.NUCs.find(wifi.getAP().getMAC())->second.position;
float apDist = gtPos.getDistance(apPos);
fs << ts.ms() << ";" << nucid << ";" << apDist << ";" << rssiDist << ";" << ftmDist << ";" << ftmStdDev << ";" << numMeas << ";" << numSuccessMeas << "\n";
@@ -214,6 +214,13 @@ static CombinedStats<float> run(Settings::DataSetup setup, int walkIdx, std::str
std::ofstream errorFile;
errorFile.open (evalDir.string() + "/" + std::to_string(walkIdx) + "_" + std::to_string(t) + ".csv");
// Output dir
auto outputDir = std::filesystem::path(Settings::outputDir);
outputDir.append(Settings::CurrentPath.name + "_" + std::to_string(walkIdx));
if (!std::filesystem::exists(outputDir)) {
std::filesystem::create_directories(outputDir);
}
// wifi
auto kalmanMap = std::make_shared<std::unordered_map<MACAddress, Kalman>>();
@@ -245,10 +252,10 @@ static CombinedStats<float> run(Settings::DataSetup setup, int walkIdx, std::str
plot.setGroundTruth(gtPath);
plot.setView(30, 0);
// APs Positions
plot.addCircle(100000 + 0, Settings::data.CurrentPath.nucInfo(0).position.xy(), 0.05);
plot.addCircle(100000 + 1, Settings::data.CurrentPath.nucInfo(1).position.xy(), 0.05);
plot.addCircle(100000 + 2, Settings::data.CurrentPath.nucInfo(2).position.xy(), 0.05);
plot.addCircle(100000 + 3, Settings::data.CurrentPath.nucInfo(3).position.xy(), 0.05);
plot.addCircle(100000 + 0, Settings::CurrentPath.nucInfo(0).position.xy(), 0.1);
plot.addCircle(100000 + 1, Settings::CurrentPath.nucInfo(1).position.xy(), 0.1);
plot.addCircle(100000 + 2, Settings::CurrentPath.nucInfo(2).position.xy(), 0.1);
plot.addCircle(100000 + 3, Settings::CurrentPath.nucInfo(3).position.xy(), 0.1);
plot.plot();
// particle-filter
@@ -283,8 +290,8 @@ static CombinedStats<float> run(Settings::DataSetup setup, int walkIdx, std::str
std::vector<int> timestamps;
std::vector<std::array<float, 4>> gtDistances, ftmDistances, rssiDistances; // distance per AP
Plotta::Plotta errorPlot("errorPlot", Settings::plotDataDir + "errorData.py");
Plotta::Plotta distsPlot("distsPlot", Settings::plotDataDir + "distances.py");
Plotta::Plotta errorPlot("errorPlot", outputDir.string() + "/errorData.py");
Plotta::Plotta distsPlot("distsPlot", outputDir.string() + "/distances.py");
for (const Offline::Entry& e : fr.getEntries())
{
@@ -305,10 +312,10 @@ static CombinedStats<float> run(Settings::DataSetup setup, int walkIdx, std::str
Point2 gtPos = gtInterpolator.get(static_cast<uint64_t>(ts.ms())).xy();
plot.setGroundTruth(Point3(gtPos.x, gtPos.y, 0.1));
gtDistances.push_back({ gtPos.getDistance(Settings::data.CurrentPath.nucInfo(0).position.xy()),
gtPos.getDistance(Settings::data.CurrentPath.nucInfo(1).position.xy()),
gtPos.getDistance(Settings::data.CurrentPath.nucInfo(2).position.xy()),
gtPos.getDistance(Settings::data.CurrentPath.nucInfo(3).position.xy()) });
gtDistances.push_back({ gtPos.getDistance(Settings::CurrentPath.nucInfo(0).position.xy()),
gtPos.getDistance(Settings::CurrentPath.nucInfo(1).position.xy()),
gtPos.getDistance(Settings::CurrentPath.nucInfo(2).position.xy()),
gtPos.getDistance(Settings::CurrentPath.nucInfo(3).position.xy()) });
Point3 estPos;
float distErrorFtm = 0;
@@ -339,10 +346,10 @@ static CombinedStats<float> run(Settings::DataSetup setup, int walkIdx, std::str
{
WiFiMeasurement wifi2 = obs.ftm[i];
Point3 apPos = Settings::data.CurrentPath.nuc(wifi2.getAP().getMAC()).position;
Point3 apPos = Settings::CurrentPath.nuc(wifi2.getAP().getMAC()).position;
K::GnuplotColor color;
switch (Settings::data.CurrentPath.nuc(wifi2.getAP().getMAC()).ID)
switch (Settings::CurrentPath.nuc(wifi2.getAP().getMAC()).ID)
{
case 1: color = K::GnuplotColor::fromRGB(0, 255, 0); break;
case 2: color = K::GnuplotColor::fromRGB(0, 0, 255); break;
@@ -390,6 +397,18 @@ static CombinedStats<float> run(Settings::DataSetup setup, int walkIdx, std::str
printErrorStats(errorStats);
std::ofstream plot_out;
plot_out.open(outputDir.string() + "/plot.gp");
plot.clearDistanceCircles();
plot.saveToFile(plot_out);
std::ofstream errorStats_out;
errorStats_out.open(outputDir.string() + "/error_stats.txt");
printErrorStats(errorStats_out, errorStats);
errorPlot.frame();
//system("pause");
return errorStats;
@@ -417,45 +436,58 @@ int main(int argc, char** argv)
CombinedStats<float> tmp;
std::string evaluationName = "prologic/tmp";
std::vector<Settings::DataSetup> setupsToRun = { Settings::data.Path7,
Settings::data.Path8,
Settings::data.Path9 };
for (size_t walkIdx = 0; walkIdx < 1 /*Settings::data.CurrentPath.training.size()*/; walkIdx++)
for (Settings::DataSetup setupToRun : setupsToRun)
{
std::cout << "Executing walk " << walkIdx << "\n";
for (int i = 0; i < 5; ++i)
Settings::CurrentPath = setupToRun;
for (size_t walkIdx = 0; walkIdx < 1 /*Settings::CurrentPath.training.size()*/; walkIdx++)
{
std::cout << "Start of iteration " << i << "\n";
std::cout << "Executing walk " << walkIdx << "\n";
for (int i = 0; i < 1; ++i)
{
std::cout << "Start of iteration " << i << "\n";
tmp = run(Settings::data.CurrentPath, walkIdx, evaluationName);
tmp = run(Settings::CurrentPath, walkIdx, evaluationName);
statsAVG.ftm.add(tmp.ftm.getAvg());
statsMedian.ftm.add(tmp.ftm.getMedian());
statsSTD.ftm.add(tmp.ftm.getStdDev());
statsQuantil.ftm.add(tmp.ftm.getQuantile(0.75));
statsAVG.ftm.add(tmp.ftm.getAvg());
statsMedian.ftm.add(tmp.ftm.getMedian());
statsSTD.ftm.add(tmp.ftm.getStdDev());
statsQuantil.ftm.add(tmp.ftm.getQuantile(0.75));
statsAVG.rssi.add(tmp.rssi.getAvg());
statsMedian.rssi.add(tmp.rssi.getMedian());
statsSTD.rssi.add(tmp.rssi.getStdDev());
statsQuantil.rssi.add(tmp.rssi.getQuantile(0.75));
statsAVG.rssi.add(tmp.rssi.getAvg());
statsMedian.rssi.add(tmp.rssi.getMedian());
statsSTD.rssi.add(tmp.rssi.getStdDev());
statsQuantil.rssi.add(tmp.rssi.getQuantile(0.75));
std::cout << "Iteration " << i << " completed" << std::endl;
std::cout << "Iteration " << i << " completed" << std::endl;
}
}
std::cout << "Results for path " << Settings::CurrentPath.name << std::endl;
std::cout << "==========================================================" << std::endl;
std::cout << "Average of all statistical data FTM: " << std::endl;
std::cout << "Median: " << statsMedian.ftm.getAvg() << std::endl;
std::cout << "Average: " << statsAVG.ftm.getAvg() << std::endl;
std::cout << "Standard Deviation: " << statsSTD.ftm.getAvg() << std::endl;
std::cout << "75 Quantil: " << statsQuantil.ftm.getAvg() << std::endl;
std::cout << "==========================================================" << std::endl;
std::cout << "==========================================================" << std::endl;
std::cout << "Average of all statistical data RSSI: " << std::endl;
std::cout << "Median: " << statsMedian.rssi.getAvg() << std::endl;
std::cout << "Average: " << statsAVG.rssi.getAvg() << std::endl;
std::cout << "Standard Deviation: " << statsSTD.rssi.getAvg() << std::endl;
std::cout << "75 Quantil: " << statsQuantil.rssi.getAvg() << std::endl;
std::cout << "==========================================================" << std::endl;
}
std::cout << "==========================================================" << std::endl;
std::cout << "Average of all statistical data FTM: " << std::endl;
std::cout << "Median: " << statsMedian.ftm.getAvg() << std::endl;
std::cout << "Average: " << statsAVG.ftm.getAvg() << std::endl;
std::cout << "Standard Deviation: " << statsSTD.ftm.getAvg() << std::endl;
std::cout << "75 Quantil: " << statsQuantil.ftm.getAvg() << std::endl;
std::cout << "==========================================================" << std::endl;
std::cout << "==========================================================" << std::endl;
std::cout << "Average of all statistical data RSSI: " << std::endl;
std::cout << "Median: " << statsMedian.rssi.getAvg() << std::endl;
std::cout << "Average: " << statsAVG.rssi.getAvg() << std::endl;
std::cout << "Standard Deviation: " << statsSTD.rssi.getAvg() << std::endl;
std::cout << "75 Quantil: " << statsQuantil.rssi.getAvg() << std::endl;
std::cout << "==========================================================" << std::endl;