FrankE
a2c9e575a2
- 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
83 lines
1.7 KiB
C++
83 lines
1.7 KiB
C++
#ifndef LUT_H
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#define LUT_H
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#include <vector>
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#include "../Math.h"
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#include "../DrawList.h"
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namespace Distribution {
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template <typename Scalar> class LUT {
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private:
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Scalar min;
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Scalar max;
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Scalar diff;
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/** number of samples between min and max */
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int numSamples;
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/** the look-up-table */
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std::vector<Scalar> samples;
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public:
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/** ctor */
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template <typename Distribution> LUT(const Distribution dist, const Scalar min, const Scalar max, const int numSamples) :
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min(min), max(max), diff(max-min), numSamples(numSamples) {
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buildLUT(dist);
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}
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/** get the probability of val from the LUT */
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Scalar getProbability(const Scalar val) const {
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int idx = ((val - min) * numSamples / diff);
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idx = Math::clamp(0, numSamples-1, idx);
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return samples[idx];
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}
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/** get a DrawList for this LUT to draw random values out of it */
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DrawList<Scalar> getDrawList() {
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DrawList<Scalar> dl;
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for (int idx = 0; idx < (int) samples.size(); ++idx) {
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const Scalar val = idxToVal(idx);
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const Scalar prob = samples[idx];
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dl.add(val, prob);
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}
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return dl;
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}
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protected:
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/** convert value [min:max] to index [0:numSamples] */
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inline int valToIdx(const Scalar val) const {
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return ((val - min) * numSamples / diff);
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}
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/** convert index [0:numSamples] to value [min:max] */
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inline Scalar idxToVal(const int idx) const {
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return min + (idx * diff / numSamples);
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}
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private:
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/** build the look-up-table */
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template <typename Distribution> void buildLUT(const Distribution dist) {
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samples.resize(numSamples);
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for (int idx = 0; idx < numSamples; ++idx) {
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const Scalar val = min + (idx * diff / numSamples);
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samples[idx] = dist.getProbability(val);
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}
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}
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};
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}
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#endif // LUT_H
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