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
This commit is contained in:
2016-08-29 08:18:44 +02:00
parent 99ee95ce7b
commit a2c9e575a2
94 changed files with 8298 additions and 257 deletions

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@@ -6,5 +6,6 @@
#include "distribution/Logistic.h"
#include "distribution/Uniform.h"
#include "distribution/VonMises.h"
#include "distribution/Region.h"
#endif // DISTRIBUTIONS_H

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@@ -47,6 +47,11 @@ public:
;
}
/** change the seed */
void setSeed(const uint64_t seed) {
gen.seed(seed);
}
/** reset */
void reset() {
cumProbability = 0;

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@@ -50,7 +50,8 @@ public:
// interpolate
const int idx1 = (idx2 > 0) ? (idx2 - 1) : (idx2);
const float percent = (key - entries[idx1].key) / (float) (entries[idx2].key - entries[idx1].key);
return entries[idx1].value + (entries[idx2].value - entries[idx1].value) * percent;
const Value res = entries[idx1].value + (entries[idx2].value - entries[idx1].value) * percent;
return res;
}

43
math/Median.h Normal file
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@@ -0,0 +1,43 @@
#ifndef MEDIAN_H
#define MEDIAN_H
#include <vector>
#include <algorithm>
template <typename Scalar> class Median {
private:
/** all scalar values in a sorted order (ascending) */
std::vector<Scalar> sorted;
public:
/** add the given scalar value to the median calculation */
void add(const Scalar value) {
const auto idx = std::upper_bound( sorted.begin(), sorted.end(), value );
sorted.insert( idx, value );
}
/** get the median of all added values */
float get() const {
if (sorted.size() % 2 == 1) { // odd
const int idx = sorted.size()/2;
return sorted[idx];
} else { // even
const int idx0 = sorted.size()/2 - 1;
return (sorted[idx0] + sorted[idx0+1]) / 2;
}
}
};
#endif // MEDIAN_H

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@@ -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 */

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@@ -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);

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@@ -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