huge commit

- worked on about everything
- grid walker using plugable modules
- wifi models
- new distributions
- worked on geometric data-structures
- added typesafe timestamps
- worked on grid-building
- added sensor-classes
- added sensor analysis (step-detection, turn-detection)
- offline data reader
- many test-cases

math/distribution/LUT.h

@@ -3,6 +3,7 @@
 
 #include <vector>
 #include "../Math.h"
+#include "../DrawList.h"
 
 namespace Distribution {
 
@@ -38,6 +39,29 @@ namespace Distribution {
 			return samples[idx];
 		}
 
+		/** get a DrawList for this LUT to draw random values out of it */
+		DrawList<Scalar> getDrawList() {
+			DrawList<Scalar> dl;
+			for (int idx = 0; idx < (int) samples.size(); ++idx) {
+				const Scalar val = idxToVal(idx);
+				const Scalar prob = samples[idx];
+				dl.add(val, prob);
+			}
+			return dl;
+		}
+
+protected:
+
+		/** convert value [min:max] to index [0:numSamples] */
+		inline int valToIdx(const Scalar val) const {
+			return ((val - min) * numSamples / diff);
+		}
+
+		/** convert index [0:numSamples] to value [min:max] */
+		inline Scalar idxToVal(const int idx) const {
+			return min + (idx * diff / numSamples);
+		}
+
 	private:
 
 		/** build the look-up-table */

math/distribution/Normal.h

@@ -4,6 +4,7 @@
 #include <cmath>
 #include <random>
 #include "../Random.h"
+#include "../../Assertions.h"
 
 namespace Distribution {
 
@@ -46,6 +47,7 @@ namespace Distribution {
 
 		/** get the probability for the given value */
 		static T getProbability(const T mu, const T sigma, const T val) {
+			Assert::isTrue(sigma > 0, "sigma must be >= 0");
 			const T a = 1.0 / (sigma * std::sqrt(2.0 * M_PI));
 			const T b = -0.5 * ((val-mu)/sigma) * ((val-mu)/sigma);
 			return a * std::exp(b);

math/distribution/Region.h

@@ -0,0 +1,51 @@
+#ifndef DIST_REGION_H
+#define DIST_REGION_H
+
+#include <cmath>
+#include <random>
+#include "../Random.h"
+#include "../../Assertions.h"
+#include "Normal.h"
+
+namespace Distribution {
+
+	/** normal distribution */
+	template <typename T> class Region {
+
+	private:
+
+		const T mu;
+		const T a;
+		const T h;
+		const T sigma;
+
+	public:
+
+		/** ctor */
+		Region(const T mu, const T a) : mu(mu), a(a), h(1.0/(2*2*a)), sigma(std::exp(0) / (2*h*std::sqrt(2*M_PI))) {
+
+		}
+
+		/** get probability for the given value */
+		T getProbability(const T val) const {
+			const T diff = std::abs(val - mu);
+			if (diff < a)	{return h;}
+			//if (diff < a+b)	{const float p = 1.0f-(diff-a)/b; return p*h;}
+			//return 0;
+			const T diff2 = ((val - mu) < 0) ? (val - mu + a) : (val - mu - a);
+			return Distribution::Normal<T>::getProbability(0, sigma, diff2) / 2;
+
+		}
+
+		/** get the probability for the given value */
+		static T getProbability(const T mu, const T a, const T val) {
+			Region<T> dist(mu, a);
+			return dist.getProbability(val);
+		}
+
+	};
+
+}
+
+
+#endif // DIST_REGION_H