#ifndef EVAL1_H
#define EVAL1_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 <Indoor/grid/walk/GridWalkSimpleControl.h>

#include <KLib/math/filter/particles/resampling/ParticleFilterResamplingSimple.h>
#include <KLib/math/filter/particles/resampling/ParticleFilterResamplingPercent.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 Eval1 : public EvalBase {

public:

	Eval1() {


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

		std::vector<int> wp = path1; std::reverse(wp.begin(), wp.end());

		MyGridNode& start = (MyGridNode&)grid.getNodeFor( conv(floors.gtwp[wp.front()]) );
		MyGridNode& end = (MyGridNode&)grid.getNodeFor( conv(floors.gtwp[wp.back()]) );

		//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);
		GridWalkSimpleControl<MyGridNode>* walk = new GridWalkSimpleControl<MyGridNode>();

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

		// path1
		//sr = new SensorReader("./measurements/path1/1/1454345312844.csv"); // forward
		//srt = new SensorReaderTurn("./measurements/path1/1/Turns.txt");
		//srs = new SensorReaderStep("./measurements/path1/1/Steps2.txt");
		sr = new SensorReader("./measurements/path1/2/1454345421125.csv"); // backward
		srt = new SensorReaderTurn("./measurements/path1/2/Turns.txt");
		srs = new SensorReaderStep("./measurements/path1/2/Steps2.txt");

		// path2
		//sr = new SensorReader("./measurements/path2/1/1454345775306.csv"); // forward
		//srt = new SensorReaderTurn("./measurements/path2/1/Turns.txt");
		//srs = new SensorReaderStep("./measurements/path2/1/Steps2.txt");
		//sr = new SensorReader("./measurements/path2/2/1454346071347.csv"); // backward
		//srt = new SensorReaderTurn("./measurements/path2/2/Turns.txt");
		//srs = new SensorReaderStep("./measurements/path2/2/Steps2.txt");

		// path3
//		sr = new SensorReader("./measurements/path3/1/1454345546308.csv"); // forward
//		srt = new SensorReaderTurn("./measurements/path3/1/Turns.txt");
//		srs = new SensorReaderStep("./measurements/path3/1/Steps2.txt");
//		sr = new SensorReader("./measurements/path3/2/1454345622819.csv"); // backward
//		srt = new SensorReaderTurn("./measurements/path3/2/Turns.txt");
//		srs = new SensorReaderStep("./measurements/path3/2/Steps2.txt");


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

	}

	//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, true, true, true, true);		// TODO: STEP TURN
		pf->setEvaluation( std::move(eval) );

		// resampling step?
		pf->setNEffThreshold(1.0);
		pf->setResampling( std::unique_ptr<K::ParticleFilterResamplingSimple<MyState>>(new K::ParticleFilterResamplingSimple<MyState>()) );
		//pf->setResampling( std::unique_ptr<K::ParticleFilterResamplingPercent<MyState>>(new K::ParticleFilterResamplingPercent<MyState>(0.10)) );

		// 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>(0.50f)));

	}

};

#endif // EVAL1_H