Reliability.h
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Reliability.h
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	//===-- rosa/agent/Reliability.h --------------------------------- C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/Reliability.h
	///
	/// \author Daniel Schnoell (daniel.schnoell@tuwien.ac.at)
	///
	/// \date 2019
	///
	/// \brief Definition of reliability functionality.
	///
	/// \note based on Maximilian Goetzinger (maxgot@utu.fi) code in
	/// CAM_Dirty_include SA-EWS2_Version... inside Agent.cpp
	///
	/// \note By defining and setting Reliability_trace_level it is possible to
	/// change the level to which it should be traced. \note All classes throw
	/// runtime errors if not all things are set
	///
	/// \note should the Reliability be capped?
	///
	///
	//===----------------------------------------------------------------------===//

	// make combination modular

	#ifndef ROSA_AGENT_RELIABILITY_H
	#define ROSA_AGENT_RELIABILITY_H

	#include "rosa/agent/CrossReliability.h"
	#include "rosa/agent/FunctionAbstractions.hpp"
	#include "rosa/agent/Functionality.h"
	#include "rosa/agent/RangeConfidence.hpp"

	#include <algorithm>
	#include <type_traits>
	#include <vector>

	/// 0 everything
	/// 1 vectors
	/// 2 outputs
	#define trace_everything 0
	#define trace_vectors 1
	#define trace_outputs 2

	#ifndef Reliability_trace_level
	#define Reliability_trace_level 0
	#endif
	#define trace_end "\n\n\n"

	namespace rosa {
	namespace agent {
	/// This is a struct with a few methods that make lowlevel/highlevel Reliability
	/// more readable \tparam StateType The datatype of the States \tparam
	/// ReliabilityType The datatype of the Reliability
	template <typename StateType, typename ReliabilityType> struct ConfOrRel {
	/// making both Template Arguments readable to make a few things easier
	typedef StateType _StateType;
	/// making both Template Arguments readable to make a few things easier
	typedef ReliabilityType _ReliabilityType;

	/// The actual place where the data is stored
	StateType score;
	/// The actual place where the data is stored
	ReliabilityType Reliability;

	ConfOrRel(StateType _score, ReliabilityType _Reliability)
	: score(_score), Reliability(_Reliability){};
	ConfOrRel(){};

	/// Pushes the Data in a Human readable form
	/// \param out The stream where it is written to
	/// \param c The struct itself
	friend std::ostream &operator<<(std::ostream &out, const ConfOrRel &c) {
	out << "Score: " << c.score << "\t Reliability: " << c.Reliability << " ";
	return out;
	}

	/// needed or it throws an clang diagnosic error
	typedef std::map<StateType, ReliabilityType>
	map; // needed or it throws an clang diagnosic error
	/// Filles the vector with the data inside the map
	/// \param me The vector to be filled
	/// \param data The data wich is to be pushed into the vector
	friend std::vector<ConfOrRel> &operator<<(std::vector<ConfOrRel> &me,
	map &&data) {
	for (auto tmp : data) {
	me.push_back(ConfOrRel(tmp.first, tmp.second));
	#if Reliability_trace_level <= trace_everything
	LOG_TRACE_STREAM << "\n" << ConfOrRel(tmp.first, tmp.second) << trace_end;
	#endif
	}
	return me;
	}

	/// This is to push the data inside a vector in a human readable way into the
	/// ostream \param out The ostream \param c The vector which is read
	friend std::ostream &operator<<(std::ostream &out,
	const std::vector<ConfOrRel> &c) {
	std::size_t index = 0;
	for (ConfOrRel data : c) {
	out << index << " : " << data << "\n";
	index++;
	}
	return out;
	}
	};

	/// This calculates the minimum of the Reliabilities & the given value
	/// \param me The vector with the Reliabilities
	/// \param value The comparing value
	template <typename Conf>
	std::vector<Conf> min(std::vector<Conf> me,
	typename Conf::_ReliabilityType value) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto tmp : me)
	tmp.Reliability = std::min(tmp.Reliability, value);
	return me;
	}
	/// This calculates the maximum of the Reliabilities & the given value
	/// \param me The vector with the Reliabilities
	/// \param value The comparing value
	template <typename Conf>
	std::vector<Conf> max(std::vector<Conf> me,
	typename Conf::_ReliabilityType value) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto tmp : me)
	tmp.Reliability = std::max(tmp.Reliability, value);
	return me;
	}
	/// This calculates the average of the Reliabilities & the given value
	/// \param me The vector with the Reliabilities
	/// \param value The comparing value
	template <typename Conf>
	std::vector<Conf> average(std::vector<Conf> me,
	typename Conf::_ReliabilityType value) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto tmp : me)
	tmp.Reliability = (tmp.Reliability + value) / 2;
	return me;
	}

	/// This calculates the average of the Reliabilities & the given value
	/// \param me The vector with the Reliabilities
	/// \param value The comparing value
	template <typename Conf>
	std::vector<Conf> mult(std::vector<Conf> me,
	typename Conf::_ReliabilityType value) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto tmp : me)
	tmp.Reliability = tmp.Reliability * value / 2;
	return me;
	}

	/// This average's the Reliabilities of the same Scores
	template <typename Conf>
	std::vector<Conf> average(std::vector<Conf> A, std::vector<Conf> B) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto &tmp_me : A)
	for (auto &tmp_other : B) {
	if (tmp_me.score == tmp_other.score) {
	tmp_me.Reliability = (tmp_me.Reliability + tmp_other.Reliability) / 2;
	}
	}
	return A;
	}
	/// This min's the Reliabilities of the same Scores
	template <typename Conf>
	std::vector<Conf> min(std::vector<Conf> A, std::vector<Conf> B) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto &tmp_me : A)
	for (auto &tmp_other : B) {
	if (tmp_me.score == tmp_other.score) {
	tmp_me.Reliability =
	std::min(tmp_me.Reliability + tmp_other.Reliability);
	}
	}
	return A;
	}
	/// This max's the Reliabilities of the same Scores
	template <typename Conf>
	std::vector<Conf> max(std::vector<Conf> A, std::vector<Conf> B) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto &tmp_me : A)
	for (auto &tmp_other : B) {
	if (tmp_me.score == tmp_other.score) {
	tmp_me.Reliability =
	std::max(tmp_me.Reliability + tmp_other.Reliability);
	}
	}
	return A;
	}
	/// This mult's the Reliabilities of the same Scores
	template <typename Conf>
	std::vector<Conf> mult(std::vector<Conf> A, std::vector<Conf> B) {
	static_assert(std::is_arithmetic<typename Conf::_ReliabilityType>::value);
	for (auto &tmp_me : A)
	for (auto &tmp_other : B) {
	if (tmp_me.score == tmp_other.score) {
	tmp_me.Reliability = tmp_me.Reliability * tmp_other.Reliability;
	}
	}
	return A;
	}

	/// This is the combinator for Reliability and confidences it takes the
	/// Sensor value, its "History" and feedback from \c
	/// CrossCombinator to calculate different Reliabilities.
	/// \tparam SensorValueType Datatype of the Sensor value ( Typically
	/// double or float) \tparam StateType Datatype of the State ( Typically long or
	/// int)
	/// \tparam ReliabilityType Datatype of the Reliability (
	/// Typically double or float)
	///
	/// \note more information about how it calculates
	/// the Reliabilities
	/// \verbatim
	///----------------------------------------------------------------------------------
	///
	///
	/// ->Reliability---> getInputReliability()
	/// \| \|
	/// \| V
	/// Sensor Value ---\| PossibleScoreCombinationMethod -> next line
	/// \| A \|
	/// \| \| V
	/// ->Confidence--- getPossibleScores()
	///
	///-----------------------------------------------------------------------------------
	///
	/// feedback
	/// \|
	/// V
	/// ValuesFromMaster
	/// \| -> History ---\|
	/// V \| V
	/// here -> FeedbackCombinatorMethod --------> HistoryCombinatorMethod->nextline
	/// \| \|
	/// V V
	/// getpossibleScoresWithMasterFeedback() getPossibleScoresWithHistory()
	///
	///----------------------------------------------------------------------------------
	///
	/// here -> sort -> most likely -> mostLikelySoreAndReliability()
	///
	/// ---------------------------------------------------------------------------------
	/// \endverbatim
	/// the mentioned methods are early outs so if two ore more of them are run in
	/// the same step they will be interpreted as different time steps
	/// <pre>
	/// Default values for Combinators:
	/// InputReliabilityCombinator = combinationMin;
	/// PossibleScoreCombinationMethod = PossibleScoreCombinationMethodMin;
	/// FeedbackCombinatorMethod = FeedbackCombinatorMethodAverage;
	/// HistoryCombinatorMethod = HistoryCombinatorMethodMax;
	/// </pre>
	///
	///
	///
	template <typename SensorValueType, typename StateType,
	typename ReliabilityType>
	class ReliabilityAndConfidenceCombinator {
	public:
	static_assert(std::is_arithmetic<SensorValueType>::value,
	"LowLevel: SensorValueType has to an arithmetic type\n");
	static_assert(std::is_arithmetic<StateType>::value,
	"LowLevel: StateType has to an arithmetic type\n");
	static_assert(std::is_arithmetic<ReliabilityType>::value,
	"LowLevel: ReliabilityType has to an arithmetic type\n");

	/// Typedef to shorten the writing.
	/// \c ConfOrRel
	typedef ConfOrRel<StateType, ReliabilityType> ConfOrRel;

	/// Calculates the input reliability by combining Reliability of the Sensor
	/// and the Slope Reliability \param SensorValue The sensor Value \note to set
	/// the combination method \c setInputReliabilityCombinator()
	auto getInputReliability(SensorValueType SensorValue) {
	auto inputReliability =
	getReliability(SensorValue, previousSensorValue, valueSetCounter);
	previousSensorValue = SensorValue;
	PreviousSensorValueExists = true;
	return inputReliability;
	}

	/// Calculates the Reliability
	/// \param SensorValue The current Values of the Sensor
	///
	/// \return Reliability and Score of the current SensorValue
	///
	ConfOrRel mostLikelySoreAndReliability(SensorValueType SensorValue) {
	#if Reliability_trace_level <= trace_outputs
	LOG_TRACE_STREAM << "\nTrace level is set to: " << Reliability_trace_level
	<< "\n"
	<< "Will trace: "
	<< ((Reliability_trace_level == trace_outputs)
	? "outputs"
	: (Reliability_trace_level == trace_vectors)
	? "vectors"
	: (Reliability_trace_level ==
	trace_everything)
	? "everything"
	: "undefined")
	<< trace_end;
	#endif

	std::vector<ConfOrRel> ActuallPossibleScores;
	std::vector<ConfOrRel> possibleScores;
	ReliabilityType inputReliability = getInputReliability(SensorValue);

	#if Reliability_trace_level <= trace_vectors
	LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end;
	#endif

	possibleScores << Confidence->operator()(SensorValue);

	possibleScores =
	PossibleScoreCombinationMethod(possibleScores, inputReliability);
	possibleScores = FeedbackCombinatorMethod(possibleScores, ValuesFromMaster);

	saveInHistory(possibleScores);
	#if Reliability_trace_level <= trace_vectors
	LOG_TRACE_STREAM << "\nActuallPossibleScores:\n"
	<< possibleScores << trace_end;
	LOG_TRACE_STREAM << "\npossibleScores:\n" << possibleScores << trace_end;
	#endif
	possibleScores.clear();

	possibleScores = getAllPossibleScoresBasedOnHistory();

	std::sort(possibleScores.begin(), possibleScores.end(),
	[](ConfOrRel A, ConfOrRel B) -> bool {
	return A.Reliability > B.Reliability;
	});

	#if Reliability_trace_level <= trace_outputs
	LOG_TRACE_STREAM << "\noutput lowlevel: " << possibleScores.at(0)
	<< trace_end;
	#endif
	return possibleScores.at(0);
	}

	/// Calculates the possible Scores
	/// \param SensorValue the Sensor Value
	/// \brief it combines the input reliability and the confidence of the Sensor.
	/// The use combination method can be set using \c
	/// setPossibleScoreCombinationMethod()
	auto getPossibleScores(SensorValueType SensorValue) {
	std::vector<ConfOrRel> possibleScores;
	ReliabilityType inputReliability = getInputReliability(SensorValue);

	// get input rel()
	#if Reliability_trace_level <= trace_vectors
	LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end;
	#endif

	possibleScores << Confidence->operator()(SensorValue);
	possibleScores =
	PossibleScoreCombinationMethod(possibleScores, inputReliability);
	return possibleScores;
	}

	/// return the Possible Values with the feedback in mind
	/// \param SensorValue The sensor Value
	/// \brief it combines the input reliability and the confidence of the Sensor.
	/// The combines them with FeedbackCombinatorMethod and returns the result.
	auto getpossibleScoresWithMasterFeedback(SensorValueType SensorValue) {
	std::vector<ConfOrRel> possibleScores;
	ReliabilityType inputReliability = getInputReliability(SensorValue);

	// get input rel()
	#if Reliability_trace_level <= trace_vectors
	LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end;
	#endif

	possibleScores << Confidence->operator()(SensorValue);

	possibleScores =
	PossibleScoreCombinationMethod(possibleScores, inputReliability);

	// set comb method with values from master ( class :: min \| max \| average \|
	// mult \| [] ()-> {} )
	possibleScores = FeedbackCombinatorMethod(possibleScores, ValuesFromMaster);
	return possibleScores;
	}

	/// returns all possible Scores and Reliabilities with the History in mind
	/// \param SensorValue the Sensor value
	/// how this is done is described at the class.
	auto getPossibleScoresWithHistory(SensorValueType SensorValue) {
	std::vector<ConfOrRel> ActuallPossibleScores;
	std::vector<ConfOrRel> possibleScores;
	ReliabilityType inputReliability = getInputReliability(SensorValue);

	// get input rel()
	#if Reliability_trace_level <= trace_vectors
	LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end;
	#endif

	possibleScores << Confidence->operator()(SensorValue);

	possibleScores =
	PossibleScoreCombinationMethod(possibleScores, inputReliability);
	possibleScores = FeedbackCombinatorMethod(possibleScores, ValuesFromMaster);

	saveInHistory(possibleScores);
	#if Reliability_trace_level <= trace_vectors
	LOG_TRACE_STREAM << "\nActuallPossibleScores:\n"
	<< possibleScores << trace_end;
	LOG_TRACE_STREAM << "\npossibleScores:\n" << possibleScores << trace_end;
	#endif
	possibleScores.clear();

	return getAllPossibleScoresBasedOnHistory();
	}

	/// feedback for this functionality most commonly it comes from a Master Agent
	/// \param ValuesFromMaster The Scores + Reliability for the feedback
	/// \brief This input kind of resembles a confidence but not
	/// directly it more or less says: compared to the other Scores inside the
	/// System these are the Scores with the Reliability that you have.
	void feedback(std::vector<ConfOrRel> ValuesFromMaster) {
	this->ValuesFromMaster = ValuesFromMaster;
	}

	//
	// ----------------------Reliability and Confidence Function setters----------
	//
	/// This is the setter for Confidence Function
	/// \param Confidence A pointer to the Functional for the \c Confidence of the
	/// Sensor value
	void setConfidenceFunction(
	std::unique_ptr<RangeConfidence<ReliabilityType, StateType,
	SensorValueType>> &Confidence) {
	this->Confidence = std::move(Confidence);
	}

	/// This is the setter for Reliability Function
	/// \param Reliability A pointer to the Functional for the Reliability
	/// \brief The Reliability takes the current Sensor value and return the
	/// Reliability of the value.
	void setReliabilityFunction(
	std::unique_ptr<Abstraction<SensorValueType, ReliabilityType>>
	&Reliability) {
	this->Reliability = std::move(Reliability);
	}

	/// This is the setter for ReliabilitySlope Function
	/// \param ReliabilitySlope A pointer to the Functional for the
	/// ReliabilitySlope
	/// \brief The ReliabilitySlope takes the difference of the current Sensor
	/// Value to the last one and tells you how likely the change is.
	void setReliabilitySlopeFunction(
	std::unique_ptr<Abstraction<SensorValueType, ReliabilityType>>
	&ReliabilitySlope) {
	this->ReliabilitySlope = std::move(ReliabilitySlope);
	}

	/// This is the setter for TimeConfidence Function
	/// \param TimeConfidence A pointer to the Functional for the TimeConfidence
	/// \brief The time function takes the position in the History with greater
	/// equals older and return a Reliability of how "relevant" it is.
	void setTimeConfidenceFunction(
	std::unique_ptr<Abstraction<std::size_t, ReliabilityType>>
	&TimeConfidence) {
	this->TimeConfidence = std::move(TimeConfidence);
	}

	/// This is the setter for all possible States
	/// \param states A vector containing all states
	/// \brief This exists even though \c State Type is an arithmetic Type because
	/// the states do not need to be "next" to each other ( ex. states={ 1 7 24 })
	void setStates(std::vector<StateType> states) { this->States = states; }

	/// This sets the Maximum length of the History
	/// \param length The length
	void setHistoryLength(std::size_t length) { this->HistoryMaxSize = length; }

	/// This sets the Value set Counter
	/// \param ValueSetCounter the new Value
	/// \note This might actually be only an artifact. It is only used to get the
	/// reliability from the \c ReliabilitySlope [ ReliabilitySlope->operator()(
	/// (lastValue - actualValue) / (SensorValueType)valueSetCounter) ]
	void setValueSetCounter(unsigned int ValueSetCounter) {
	this->valueSetCounter = ValueSetCounter;
	}

	//
	// ----------------combinator setters-----------------------------------------
	//

	/// This sets the combination method used by the History
	/// \param Meth the method which should be used. predefined \c
	/// HistoryCombinatorMethodMin() \c HistoryCombinatorMethodMax() \c
	/// HistoryCombinatorMethodMult() \c HistoryCombinatorMethodAverage()
	void setHistoryCombinatorMethod(ReliabilityType (*Meth)(ReliabilityType,
	ReliabilityType)) {
	HistoryCombinatorMethod = Meth;
	}

	/// sets the predefined method for the combination of the possible scores and
	/// the master \param Meth the method predefined ones are
	/// \c FeedbackCombinatorMethodAverage() \c FeedbackCombinatorMethodMin() \c
	/// FeedbackCombinatorMethodMax() \c FeedbackCombinatorMethodMult()
	void setFeedbackCombinatorMethod(std::vector<ConfOrRel> (*Meth)(
	std::vector<ConfOrRel>, std::vector<ConfOrRel>)) {
	FeedbackCombinatorMethod = Meth;
	}

	/// Sets the used combination method for Possible Scores
	/// \param Meth a Pointer for the used Method. Predefined methods \c
	/// PossibleScoreCombinationMethodMin() \c PossibleScoreCombinationMethodMax()
	/// \c PossibleScoreCombinationMethodAverage()
	void setPossibleScoreCombinationMethod(
	std::vector<ConfOrRel> (*Meth)(std::vector<ConfOrRel>, ReliabilityType)) {
	PossibleScoreCombinationMethod = Meth;
	}

	/// sets the input reliability combinator method
	/// \param method the to be used method
	/// \note there are predefined methods \c combinationMin() \c combinationMax()
	/// \c combinationAverage()
	void setInputReliabilityCombinator(
	ReliabilityType (*method)(ReliabilityType, ReliabilityType)) {
	InputReliabilityCombinator = method;
	}

	//
	// ----------------predefined combinators------------------------------------
	//
	/// predefined Method
	static ReliabilityType HistoryCombinatorMethodMin(ReliabilityType A,
	ReliabilityType B) {
	return std::min(A, B);
	}
	/// predefined Method
	static ReliabilityType HistoryCombinatorMethodMax(ReliabilityType A,
	ReliabilityType B) {
	return std::max(A, B);
	}
	/// predefined Method
	static ReliabilityType HistoryCombinatorMethodMult(ReliabilityType A,
	ReliabilityType B) {
	return A * B;
	}
	/// predefined Method
	static ReliabilityType HistoryCombinatorMethodAverage(ReliabilityType A,
	ReliabilityType B) {
	return (A + B) / 2;
	}

	/// predefined method
	static std::vector<ConfOrRel>
	FeedbackCombinatorMethodAverage(std::vector<ConfOrRel> A,
	std::vector<ConfOrRel> B) {
	return average(A, B);
	}
	/// predefined method
	static std::vector<ConfOrRel>
	FeedbackCombinatorMethodMin(std::vector<ConfOrRel> A,
	std::vector<ConfOrRel> B) {
	return min(A, B);
	}
	/// predefined method
	static std::vector<ConfOrRel>
	FeedbackCombinatorMethodMax(std::vector<ConfOrRel> A,
	std::vector<ConfOrRel> B) {
	return max(A, B);
	}
	/// predefined method
	static std::vector<ConfOrRel>
	FeedbackCombinatorMethodMult(std::vector<ConfOrRel> A,
	std::vector<ConfOrRel> B) {
	return mult(A, B);
	}

	/// Predefined combination method for possible Scores
	static std::vector<ConfOrRel>
	PossibleScoreCombinationMethodMin(std::vector<ConfOrRel> A,
	ReliabilityType B) {
	return min(A, B);
	}
	/// Predefined combination method for possible Scores
	static std::vector<ConfOrRel>
	PossibleScoreCombinationMethodMax(std::vector<ConfOrRel> A,
	ReliabilityType B) {
	return max(A, B);
	}

	/// Predefined combination method for possible Scores
	static std::vector<ConfOrRel>
	PossibleScoreCombinationMethodAverage(std::vector<ConfOrRel> A,
	ReliabilityType B) {
	return average(A, B);
	}

	/// Predefined combination method for possible Scores
	static std::vector<ConfOrRel>
	PossibleScoreCombinationMethodMult(std::vector<ConfOrRel> A,
	ReliabilityType B) {
	return mult(A, B);
	}

	/// The predefined min combinator method
	static ReliabilityType combinationMin(ReliabilityType A, ReliabilityType B) {
	return std::min(A, B);
	}

	/// The predefined max combinator method
	static ReliabilityType combinationMax(ReliabilityType A, ReliabilityType B) {
	return std::max(A, B);
	}

	/// The predefined average combinator method
	static ReliabilityType combinationAverage(ReliabilityType A,
	ReliabilityType B) {
	return (A + B) / 2;
	}

	/// The predefined average combinator method
	static ReliabilityType combinationMult(ReliabilityType A, ReliabilityType B) {
	return A * B;
	}

	private:
	std::vector<std::vector<ConfOrRel>> History;
	std::size_t HistoryMaxSize;
	std::vector<ConfOrRel> ValuesFromMaster;

	SensorValueType previousSensorValue;
	unsigned int valueSetCounter;
	std::vector<StateType> States;
	bool PreviousSensorValueExists = false;

	std::unique_ptr<RangeConfidence<ReliabilityType, StateType, SensorValueType>>
	Confidence;
	std::unique_ptr<Abstraction<SensorValueType, ReliabilityType>> Reliability;
	std::unique_ptr<Abstraction<SensorValueType, ReliabilityType>>
	ReliabilitySlope;
	std::unique_ptr<Abstraction<std::size_t, ReliabilityType>> TimeConfidence;

	// combination functions
	ReliabilityType (*InputReliabilityCombinator)(
	ReliabilityType, ReliabilityType) = combinationMin;

	std::vector<ConfOrRel> (*PossibleScoreCombinationMethod)(
	std::vector<ConfOrRel>,
	ReliabilityType) = PossibleScoreCombinationMethodMin;

	std::vector<ConfOrRel> (*FeedbackCombinatorMethod)(std::vector<ConfOrRel>,
	std::vector<ConfOrRel>) =
	FeedbackCombinatorMethodAverage;

	ReliabilityType (*HistoryCombinatorMethod)(ReliabilityType, ReliabilityType) =
	HistoryCombinatorMethodMax;

	/*--------------------------------- needed Functions
	* -----------------------------------------------------*/

	/// returns the Reliability
	/// \param actualValue The Value of the Sensor
	/// \param lastValue of the Sensor this is stored in the class
	/// \param valueSetCounter It has an effect on the difference of the current
	/// and last value This might not be needed anymore
	/// \brief it returns the combination the \c Reliability function and \c
	/// ReliabilitySlope if the previous value exists. if it doesn't it only
	/// returns the \c Reliability function value.
	ReliabilityType getReliability(SensorValueType actualValue,
	SensorValueType lastValue,
	unsigned int valueSetCounter) {
	ReliabilityType relAbs = Reliability->operator()(actualValue);
	if (PreviousSensorValueExists) {
	ReliabilityType relSlo = ReliabilitySlope->operator()(
	(lastValue - actualValue) / (SensorValueType)valueSetCounter);

	return InputReliabilityCombinator(relAbs, relSlo);
	} else
	return relAbs;
	}

	/// adapts the possible Scores by checking the History and combines those
	/// values. currently with max
	/// \brief combines the historic values with the \c TimeConfidence function
	/// and returns the maximum Reliability for all Scores.
	std::vector<ConfOrRel> getAllPossibleScoresBasedOnHistory() {
	// iterate through all history entries
	std::size_t posInHistory = 0;
	std::vector<ConfOrRel> possibleScores;
	for (auto pShE = History.begin(); pShE < History.end();
	pShE++, posInHistory++) {

	// iterate through all possible scores of each history entry
	for (ConfOrRel &pSh : *pShE) {

	StateType historyScore = pSh.score;
	ReliabilityType historyConf = pSh.Reliability;

	historyConf = historyConf * TimeConfidence->operator()(posInHistory);

	bool foundScore = false;
	for (ConfOrRel &pS : possibleScores) {

	if (pS.score == historyScore) {

	pS.Reliability =
	HistoryCombinatorMethod(pS.Reliability, historyConf);

	foundScore = true;
	}
	}

	if (foundScore == false) {

	ConfOrRel possibleScore;
	possibleScore.score = historyScore;
	possibleScore.Reliability = historyConf;

	possibleScores.push_back(possibleScore);
	}
	}
	}

	return possibleScores;
	}

	/// saves the Scores in the History
	/// \brief It checks the incoming scores if any have a Reliability greater
	/// than 0.5 all of them get saved inside the History and then the
	/// History get shortened to the maximal length. It only saves the Value if
	/// the History is empty.
	///
	/// \param actualPossibleScores The Scores which should be saved
	///
	/// \note Does the History really make sense if the values are to small it
	/// only stores something if it's empty and not if it isn't completely filled
	void saveInHistory(std::vector<ConfOrRel> actualPossibleScores) {

	// check if the reliability of at least one possible score is high enough
	bool atLeastOneRelIsHigh = false;
	for (ConfOrRel pS : actualPossibleScores) {
	if (pS.Reliability > 0.5) {
	atLeastOneRelIsHigh = true;
	}
	}
	// save possible scores if at least one possible score is high enough (or if
	// the history is empty)
	if (History.size() < 1 \|\| atLeastOneRelIsHigh == true) {
	History.insert(History.begin(), actualPossibleScores);

	// if history size is higher than allowed, save oldest element
	while (History.size() > HistoryMaxSize) {
	// delete possibleScoreHistory.back();
	History.pop_back();
	}
	}
	}
	};



	/// This is the Reliability Functionality for the highlevel Agent.
	/// \brief It takes the scores and reliabilities of all connected lowlevel
	/// Agents and calculates the Reliability of them together. Also it creates the
	/// feedback that is needed by the \c ReliabilityForLowLevelAgents, which is a
	/// kind of confidence.
	///
	/// \tparam StateType Datatype of the State ( Typically double or float)
	/// \tparam ReliabilityType Datatype of the Reliability (
	/// Typically long or int)
	///
	/// \note A highlevel Agent is commonly in a master slave relationship with the
	/// lowlevel Agents as the master. It combines the Reliability of all connected
	/// Slaves and uses that as its own Reliability.
	///
	/// \note more information about how the Reliability and feedback is
	/// created at \c operator()()
	// State Type rename
	// merge cross rel/conf darein
	template <typename StateType, typename ReliabilityType> class CrossCombinator {
	public:
	static_assert(std::is_arithmetic<StateType>::value,
	"HighLevel: StateType has to be an arithmetic type\n");
	static_assert(std::is_arithmetic<ReliabilityType>::value,
	"HighLevel: ReliabilityType has to be an arithmetic type\n");

	/// typedef To shorten the writing.
	/// \c ConfOrRel
	typedef ConfOrRel<StateType, ReliabilityType> ConfOrRel;

	/// typedef of the input type for the operator() defined explicitly to
	/// simplify interaction
	///
	typedef std::vector<std::tuple<id_t, StateType, ReliabilityType>> InputType;

	/// The return type for the \c operator()() Method
	struct returnType {
	ReliabilityType CrossReliability;
	std::map<id_t, std::vector<ConfOrRel>> CrossConfidence;
	};

	/// Calculates the Reliability and the Cross Confidences for each lowlevel
	/// Agent for all of there states.
	///
	/// \param Values It gets the States and Reliabilities of
	/// all connected Slaves inside a vector.
	///
	/// \return it returns a struct \c returnType containing the CrossReliability
	/// and all CrossConfidence's
	///
	/// \brief To calculate the Reliability it combines [\c std::min() ] the \c
	/// CrossReliability of all connected Agents. To calculate the feedback it
	/// iterates over all Agents and their states and uses the \c CrossConfidence
	/// Function to play what if with the states.
	returnType operator()(
	std::vector<std::tuple<id_t, StateType, ReliabilityType>> &Values) {

	ReliabilityType combinedInputRel = 1;
	ReliabilityType combinedCrossRel = 1;
	ReliabilityType outputReliability;

	std::vector<std::pair<id_t, StateType>> Agents;
	std::map<id_t, std::vector<ConfOrRel>> output;
	std::vector<ConfOrRel> output_temporary;

	for (auto tmp : Values) {
	std::pair<id_t, StateType> tmp2;
	tmp2.first = std::get<0>(tmp);
	tmp2.second = std::get<1>(tmp);
	Agents.push_back(tmp2);
	}

	for (auto Value : Values) {
	id_t id = std::get<0>(Value);
	StateType sc = std::get<1>(Value);
	ReliabilityType rel = std::get<2>(Value);

	// combination method ([])
	// get input reliability
	combinedInputRel = std::min(combinedInputRel, rel);

	// calculate the cross reliability for this slave agent
	ReliabilityType realCrossReliabilityOfSlaveAgent =
	CrossReliability->operator()(
	{id, sc},
	Agents); // AVERAGE, MULTIPLICATION, CONJUNCTION (best to worst:
	// AVERAGE = CONJUNCTION > MULTIPLICATION >> )

	// get cross confidence
	output_temporary.clear();
	for (StateType thoScore : States[id]) {
	// calculate the cross reliability for this slave agent
	ConfOrRel data;
	data.score = thoScore;
	data.Reliability = CrossConfidence->operator()(id, thoScore, Agents);
	output_temporary.push_back(data);
	}

	output.insert({id, output_temporary});
	// set combination method
	// get combined cross reliability
	combinedCrossRel =
	std::min(combinedCrossRel, realCrossReliabilityOfSlaveAgent);
	}

	// combine cross reliabilites and input reliabilites of all slave agents
	// NOTE: options would be multiply, average, AND (best to worst: )
	// outputReliability = combinedInputRel * combinedCrossRel;
	// outputReliability = (combinedInputRel + combinedCrossRel) / 2;
	// set combination method
	// get output reliability
	outputReliability = std::min(combinedInputRel, combinedCrossRel);
	return {outputReliability, output};
	}

	/// This is the setter for CrossReliability Function
	/// \param CrossReliability A pointer to the Functional for the
	/// CrossReliability
	/// \brief This is needed to calculate the Reliability. It uses this on all
	/// values of all lowlevel Agnets.
	void setCrossReliability(
	std::unique_ptr<CrossReliability<StateType, ReliabilityType>>
	&CrossReliability) {
	this->CrossReliability = std::move(CrossReliability);
	}

	/// This is the setter for CrossConfidence Function
	/// \param CrossConfidence A pointer to the Functional for the \c
	/// CrossConfidence \brief This is needed for the feedback for the \c
	/// ReliabilityForLowLevelAgents.
	void setCrossConfidence(
	std::unique_ptr<CrossConfidence<StateType, ReliabilityType>>
	&CrossConfidence) {
	this->CrossConfidence = std::move(CrossConfidence);
	}

	/// This is the adder for the states
	/// \param id The id of the Agent of the states
	/// \param States id specific states. this will be copied So that if Slaves
	/// have different States they can be used correctly.
	/// \brief The States of all connected lowlevel Agents has to be known to be
	/// able to iterate over them
	void addStates(id_t id, std::vector<StateType> States) {
	this->States.insert({id, States});
	}

	private:
	std::unique_ptr<CrossReliability<StateType, ReliabilityType>>
	CrossReliability;
	std::unique_ptr<CrossConfidence<StateType, ReliabilityType>> CrossConfidence;

	std::map<id_t, std::vector<StateType>> States;
	};

	} // namespace agent
	} // namespace rosa
	#endif // !ROSA_AGENT_RELIABILITY_H

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