current TeX

CMakeLists.txt

@@ -62,7 +62,7 @@ ADD_DEFINITIONS(
 	-fstack-protector-all
 
 	-g3
-	-O0
+	-O2
 	-march=native
 
 	-DWITH_TESTS

main.cpp

@@ -785,7 +785,7 @@ void paperOutputs() {
 	}
 
 	/** plot wifi eval results */
-	if (1 == 1) {
+	if (1 == 0) {
 
 		WiFiFingerprints fps;
 		fps.load(Settings::fCalib);
@@ -1254,11 +1254,11 @@ int main(void) {
 		Floorplan::IndoorMap* map = Floorplan::Reader::readFromFile(Settings::fMap);
 
 
-		plotAllWalks(map);
+	//plotAllWalks(map);
 
 	//compareAll();
 
-		return 0;
+	//return 0;
 
 	//testWAF();
 	//sleep(1);
@@ -1266,7 +1266,7 @@ int main(void) {
 	//const float rssi = LogDistanceModel::distanceToRssi(-100, 0, 999);
 	//int i = 0; (void) i;
 
-		paperOutputs();		return 0;
+	//	paperOutputs();		return 0;
 
 	//showFingerprintsFor(Settings::fMap, Settings::fCalib, "D8:84:66:4A:4A:D0");
 	//showModelFor(Settings::fMap, Settings::wifiEachOptParPos_multimodel, "D8:84:66:4A:4A:D0");
@@ -1455,7 +1455,7 @@ int main(void) {
 
 
 	// wifi vs ground-truth distance error
-	if (1 == 0) {
+	if (1 == 1) {
 
 		std::vector<std::string> files = {
 			Settings::path1a, Settings::path1b,
@@ -1486,9 +1486,26 @@ int main(void) {
 
 		std::cout << "num scans: " << numScans << std::endl;
 
-		// stats as table
+		// different VAP settings
 		if (1 == 1) {
 
+			EvalWiFiPaths ewp(Settings::fMap);
+
+			ewp.vap->setMinOccurences(2);
+			ewp.loadModel(Settings::wifiEachOptPar, "0");
+			ewp.walks(files, gtIndices);
+
+			ewp.vap->setMinOccurences(0);
+			ewp.loadModel(Settings::wifiEachOptPar, "1");
+			ewp.walks(files, gtIndices);
+
+			sleep(10000);
+
+		}
+
+		// stats as table
+		if (1 == 0) {
+
 			EvalWiFiPaths ewp(Settings::fMap);
 			ewp.loadModel(Settings::wifiAllFixed, "0");
 			ewp.walks(files, gtIndices);
@@ -1514,7 +1531,7 @@ int main(void) {
 		}
 
 		// stats as GFX
-		if (1 == 1) {
+		if (1 == 0) {
 
 			EvalWiFiPaths ewp(Settings::fMap);
 			ewp.loadModel(Settings::wifiAllFixed, "\\noOptEmpiric{}");

tex/chapters/experiments.tex

@@ -542,10 +542,15 @@
 		Removing this (valid) information will increase the error for such situations.
 		
 		However, incorporating additional knowledge provided by virtual \docAP{}s (see section \ref{sec:vap}) mitigated this issues.
-		If only one out of six virtual networks is seen, this observation is likely to be erroneous, no matter
-		what the corresponding signal strength indicates. This approach improved the location estimation especially
-		for areas where a transmitter was hardly seen within the reference measurements and its optimization is thus
-		expected to be inaccurate.		
+		If e.g. only one out of six virtual networks is seen, this observation is likely to be erroneous, no matter
+		what the corresponding signal strength indicates.
+		As those occasions are relatively seldom, the impact is a minor one.
+		Nevertheless, depending on the used prediction model, a handful of major estimation errors were prevented.
+		Additionally, among all examined models and walks, there was none where this approached lead to increased error values.
+		
+		%This approach improved the location estimation especially
+		%for areas where a transmitter was hardly seen within the reference measurements and its optimization is thus
+		%expected to be inaccurate.		
 		
 		Using a smaller $\sigma$ or a stricter exponential distribution for the model vs. scan comparison in \refeq{eq:wifiProb}
 		had a positive effect on the misclassification error for some of the walks, but also slightly increased the overall estimation error.

wifi/EvalWiFiPaths.h

@@ -42,7 +42,7 @@
 /** evaluate just the wifi error for several given paths */
 class EvalWiFiPaths {
 
-private:
+public:
 
 	Floorplan::IndoorMap* map;
 	BBox3 mapBBox;