#ifndef EVAL_H
#define EVAL_H

#include "EvalBase.h"
#include "../DijkstraMapper.h"
#include <Indoor/grid/walk/GridWalkRandomHeadingUpdate.h>
#include <Indoor/grid/walk/GridWalkRandomHeadingUpdateAdv.h>
#include <Indoor/grid/walk/GridWalkPushForward.h>
#include <Indoor/grid/walk/GridWalkLightAtTheEndOfTheTunnel.h>
#include <KLib/math/filter/particles/resampling/ParticleFilterResamplingSimple.h>
#include <KLib/math/filter/particles/estimation/ParticleFilterEstimationWeightedAverage.h>
#include <KLib/math/filter/particles/estimation/ParticleFilterEstimationRegionalWeightedAverage.h>
#include <KLib/math/filter/particles/estimation/ParticleFilterEstimationOrderedWeightedAverage.h>

class Eval : public EvalBase {

public:



//	Eval() {


//		pf = new K::ParticleFilter<MyState, MyControl, MyObservation>( MiscSettings::numParticles, std::unique_ptr<MyInitializer>(new MyInitializer(grid, 1120, 150, 3*350, 90)) );

//		MyGridNode& start = (MyGridNode&)grid.getNodeFor(GridPoint(500,300,floors.h0.cm()));
//		MyGridNode& end = (MyGridNode&)grid.getNodeFor(GridPoint(7000,5000,floors.h3.cm()));

//		//GridWalkRandomHeadingUpdate<MyGridNode>* walk = new GridWalkRandomHeadingUpdate<MyGridNode>();
//		GridWalkRandomHeadingUpdateAdv<MyGridNode>* walk = new GridWalkRandomHeadingUpdateAdv<MyGridNode>();
//		//GridWalkPushForward<MyGridNode>* walk = new GridWalkPushForward<MyGridNode>();
//		//GridWalkLightAtTheEndOfTheTunnel<MyGridNode>* walk = new GridWalkLightAtTheEndOfTheTunnel<MyGridNode>(grid, DijkstraMapper(grid), end);

//		pf->setTransition( std::unique_ptr<MyTransition>( new MyTransition(grid, *walk)) );

//		sr = new SensorReader("./measurements/13/Galaxy/Path2/1433588396094.csv");
//		srt = new SensorReaderTurn("./measurements/13/Galaxy/Path2/Turns.txt");
//		srs = new SensorReaderStep("./measurements/13/Galaxy/Path2/Steps2.txt");

//		gtw = getGroundTruthWay(*sr, floors.gtwp, way2);

//	}

//	//wifi also uniform dist 0/1 fuer bereiche die OK sind?
//	//steps hochzaehlen weil mehr als einer in einer transition??
//	//increase regional average region

//	void setEval1() {


//		runName = "TODO";

//		// the particle filter's evaluation method
//		std::unique_ptr<MyEvaluation> eval = std::unique_ptr<MyEvaluation>( new MyEvaluation() );
//		eval.get()->setUsage(true, false, false, true, true);
//		pf->setEvaluation( std::move(eval) );

//		// resampling step?
//		pf->setNEffThreshold(1.0);
//		pf->setResampling( std::unique_ptr<K::ParticleFilterResamplingSimple<MyState>>(new K::ParticleFilterResamplingSimple<MyState>()) );

//		// state estimation step
//		//pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationWeightedAverage<MyState>>(new K::ParticleFilterEstimationWeightedAverage<MyState>()));
//		//pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new K::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
//		pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationOrderedWeightedAverage<MyState>>(new K::ParticleFilterEstimationOrderedWeightedAverage<MyState>(0.33f)));

//	}



};

#endif // EVAL_H
