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	diff --git a/include/rosa/agent/History.hpp b/include/rosa/agent/History.hpp
	index a10bb1e..8cca4a5 100644
	--- a/include/rosa/agent/History.hpp
	+++ b/include/rosa/agent/History.hpp
	@@ -1,613 +1,615 @@
	//===-- rosa/agent/History.hpp ----------------------------------- C++ --===//
	//
	// The RoSA Framework
	//
	// Distributed under the terms and conditions of the Boost Software License 1.0.
	// See accompanying file LICENSE.
	//
	// If you did not receive a copy of the license file, see
	// http://www.boost.org/LICENSE_1_0.txt.
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/History.hpp
	///
	/// \author David Juhasz (david.juhasz@tuwien.ac.at)
	///
	/// \date 2017
	///
	/// \brief Definition of history functionality.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_AGENT_HISTORY_HPP
	#define ROSA_AGENT_HISTORY_HPP

	#include "rosa/agent/Functionality.h"

	#include "rosa/config/config.h"

	#include "rosa/support/debug.hpp"
	#include "rosa/support/type_helper.hpp"

	#include <algorithm>
	#include <array>
	#include <limits>
	#include <vector>

	#include <math.h>

	namespace rosa {
	namespace agent {

	// @benedikt: todo: assert in history, which checks if push_back worked

	/// Retention policies defining what a \c rosa::agent::History instance should
	/// do when the number of recorded entries reached its capacity.
	enum class HistoryPolicy {
	SRWF, ///< Stop Recording When Full -- no new entry is recorded when full
	FIFO, ///< First In First Out -- overwrite the earliest entry with a new one
	LIFO ///< Last In First Out -- overwrite the latest entry with a new one
	};

	template <typename T, HistoryPolicy P> class History : public Functionality {

	public:
	History(void) noexcept = default;

	/// Destroys \p this object.
	virtual ~History(void) = default;

	/// Tells the retention policy applied to \p this object.
	///
	/// \return \c rosa::agent::History::P
	static constexpr HistoryPolicy policy(void) noexcept { return P; }

	/// Tells how many entries may be recorded by \c this object.
	///
	/// \note The number of entries that are actually recorded may be smaller.
	///
	/// \return The max number of entries that may be recorded
	virtual size_t maxLength(void) const noexcept = 0;

	/// Tells how many entries are currently recorded by \p this object.
	///
	/// \return number of entries currently recorded by \p this object.
	///
	/// \post The returned value cannot be larger than the capacity of \p this
	/// object:\code
	/// 0 <= numberOfEntries() && numberOfEntries <= lengthOfHistory()
	/// \endcode
	virtual size_t numberOfEntries(void) const noexcept = 0;

	/// Tells if \p this object has not recorded anything yet.
	///
	/// \return if \p this object has no entries recorded
	bool empty(void) const noexcept { return numberOfEntries() == 0; }

	/// Tells if the history reached it's maximum length
	///
	/// \return if the history reached it's maximum length.
	bool full(void) const noexcept { return numberOfEntries() == maxLength(); }

	/// Gives a constant lvalue reference to an entry stored in \p this object.
	///
	/// \note The recorded entries are indexed starting from the latest one.
	///
	/// \param I the index at which the stored entry to take from
	///
	/// \pre \p I is a valid index:\code
	/// 0 <= I && I < numberOfEntries()
	/// \endcode
	virtual const T &entry(const size_t I = 0) const noexcept = 0;

	/// Removes all entries recorded in \p this object.
	virtual void clear() noexcept = 0;

	private:
	/// Pushes a new entry into the history.
	///
	/// \note The earliest entry gets overwritten if the history is full.
	///
	/// \param V value to push into the history
	virtual void pushBack(const T &V) noexcept = 0;

	/// Replaces the most recent entry in the history.
	///
	/// \param V value to replace the most current value with
	virtual void replaceFront(const T &V) noexcept = 0;

	public:
	/// Adds a new entry to \p this object and tells if the operation was
	/// successful.
	///
	/// \note Success of the operation depends on the actual policy.
	///
	/// \param V value to store
	///
	/// \return if \p V was successfully stored
	bool addEntry(const T &V) noexcept {
	switch (P) {
	default:
	ROSA_CRITICAL("unkown HistoryPolicy");
	case HistoryPolicy::LIFO:
	if (full()) {
	replaceFront(V);
	return true;
	}
	case HistoryPolicy::SRWF:
	if (full()) {
	return false;
	}
	// \note Fall through to FIFO which unconditionally pushes the new entry.
	case HistoryPolicy::FIFO:
	// FIFO and SRWF not full.
	pushBack(V);
	return true;
	}
	}

	/// Tells the trend set by the entries recorded by \p this object.
	///
	/// The number of steps to go back when calculating the trend is defined as
	/// argument to the function.
	///
	/// \note The number of steps that can be made is limited by the number of
	/// entries recorded by \p this object.
	///
	/// \note The function is made a template only to be able to use
	/// \c std::enable_if.
	///
	/// \tparam X always use the default!
	///
	/// \param D number of steps to go back in history
	///
	/// \return trend set by analyzed entries
	///
	/// \pre Statically, \p this object stores signed arithmetic values:\code
	/// std::is_arithmetic<T>::value && std::is_signed<T>::value
	/// \endcode Dynamically, \p D is a valid number of steps to take:\code
	/// 0 <= D && D < lengthOfHistory()
	/// \endcode
	template <typename X = T>
	typename std::enable_if<
	std::is_arithmetic<X>::value && std::is_signed<X>::value, X>::type
	trend(const size_t D) const noexcept {
	STATIC_ASSERT((std::is_same<X, T>::value), "not default template arg");
	ASSERT(0 <= D && D < maxLength()); // Boundary check.
	if (numberOfEntries() < 2 \|\| D < 1) {
	// No entries for computing trend.
	return {}; // Zero element of \p T
	} else {
	// Here at least two entries.
	// \c S is the number of steps that can be done.
	const size_t S = std::min(numberOfEntries() - 1, D);
	size_t I = S;

	// Compute trend with linear regression.
	size_t SumIndices = 0;
	T SumEntries = {};
	T SumSquareEntries = {};
	T SumProduct = {};
	while (I > 0) {
	// \note Indexing for the regression starts in the past.
	const size_t Index = S - I;
	const T Entry = entry(--I);
	SumIndices += Index;
	SumEntries += Entry;
	SumSquareEntries += Entry * Entry;
	SumProduct += Entry * Index;
	}

	return (SumProduct * S - SumEntries * SumIndices) /
	(SumSquareEntries * S - SumEntries * SumEntries);
	}
	}

	/// Tells the average absolute difference between consecutive entries recorded
	/// by \p this object
	/// The number of steps to go back when calculating the average is defined as
	/// argument to the function.
	///
	/// \note The number of steps that can be made is limited by the number of
	/// entries recorded by \p this object.
	///
	/// \note The function is made a template only to be able to use
	/// \c std::enable_if.
	///
	/// \tparam X always use the default!
	///
	/// \param D number of steps to go back in history
	///
	/// \pre Statically, \p this object stores arithmetic values:\code
	/// std::is_arithmetic<T>::value
	/// \endcode Dynamically, \p D is a valid number of steps to take:\code
	/// 0 <= D && D < lengthOfHistory()
	/// \endcode
	template <typename X = T>
	typename std::enable_if<std::is_arithmetic<X>::value, size_t>::type
	averageAbsDiff(const size_t D) const noexcept {
	STATIC_ASSERT((std::is_same<X, T>::value), "not default template arg");
	ASSERT(0 <= D && D < maxLength()); // Boundary check.
	if (numberOfEntries() < 2 \|\| D < 1) {
	// No difference to average.
	return {}; // Zero element of \p T
	} else {
	// Here at least two entries.
	// \c S is the number of steps that can be done.
	const size_t S = std::min(numberOfEntries() - 1, D);

	// Sum up differences as non-negative values only, hence using an
	// unsigned variable for that.
	size_t Diffs = {}; // Init to zero.
	// Count down entry indices and sum up all the absolute differences.
	size_t I = S;
	T Last = entry(I);
	while (I > 0) {
	T Next = entry(--I);
	Diffs += Last < Next ? Next - Last : Last - Next;
	Last = Next;
	}
	// Return the average of the summed differences.
	return Diffs / S;
	}
	}

	/// Tells the average of all entries recorded by \p this object
	///
	/// \tparam R type of the result
	template <typename R> R average() const noexcept {
	R Average = 0;
	for (size_t I = 0; I < numberOfEntries(); I++) {
	Average += entry(I);
	}
	Average /= numberOfEntries();
	return Average;
	}

	/// Tells the sigma of all entries recorded by \p this object
	///
	/// \tparam R type of the result
	template <typename R> R sigma() const noexcept {
	R Average = average();
	R Sigma = 0;
	for (size_t I = 0; I < numberOfEntries(); I++) {
	Sigma += pow((entry(I)-Average),2);
	}
	Sigma = sqrt(1.0/numberOfEntries()*Sigma);
	return Sigma;
	}
	-
	- // Experiment
	- // Note from Benedikt: I think this will not return the median because the
	- // history is not sorted
	- template <typename R> R median() const noexcept {
	- if (numberOfEntries() % 2 == 0) {
	- return (entry(numberOfEntries() / 2 - 1) + entry(numberOfEntries() / 2)) /
	- 2;
	- } else {
	- return entry(numberOfEntries() / 2);
	- }
	- }
	};

	/// Implements history by recording and storing values.
	/// The length of the underlying std::array is static and must be set at
	/// compile-time
	///
	/// \note Not thread-safe implementation, which should not be a problem as any
	/// instance of \c rosa::agent::Functionality is an internal component of a
	/// \c rosa::Agent, which is the basic unit of concurrency.
	///
	/// \tparam T type of values to store
	/// \tparam N number of values to store at most
	/// \tparam P retention policy to follow when capacity is reached
	///
	/// \invariant The size of the underlying \c std::array is `N + 1`:\code
	/// max_size() == N + 1 && N == max_size() - 1
	/// \endcode
	template <typename T, size_t N, HistoryPolicy P>
	class StaticLengthHistory : public History<T, P>, private std::array<T, N + 1> {

	// Bring into scope inherited functions that are used.
	using std::array<T, N + 1>::max_size;
	using std::array<T, N + 1>::operator[];

	/// The index of the first data element in the circular buffer.
	size_t Data;

	/// The index of the first empty slot in the circular buffer.
	size_t Space;

	public:
	using History<T, P>::policy;
	using History<T, P>::empty;
	using History<T, P>::full;
	using History<T, P>::addEntry;
	using History<T, P>::trend;
	using History<T, P>::averageAbsDiff;

	/// Creates an instances by initializing the indices for the circular buffer.
	StaticLengthHistory(void) noexcept : Data(0), Space(0) {}

	/// Destroys \p this object.
	~StaticLengthHistory(void) override = default;

	/// Tells how many entries may be recorded by \c this object.
	///
	/// \note The number of entries that are actually recorded may be smaller.
	///
	/// \return \c rosa::agent::History::N
	size_t maxLength(void) const noexcept override { return N; }

	/// Tells how many entries are currently recorded by \p this object.
	///
	/// \return number of entries currently recorded by \p this object.
	///
	/// \post The returned value cannot be larger than the capacity of \p this
	/// object:\code
	/// 0 <= numberOfEntries() && numberOfEntries <= lengthOfHistory()
	/// \endcode
	size_t numberOfEntries(void) const noexcept override {
	return Data <= Space ? Space - Data : max_size() - Data + Space;
	}

	/// Gives a constant lvalue reference to an entry stored in \p this object.
	///
	/// \note The recorded entries are indexed starting from the latest one.
	///
	/// \param I the index at which the stored entry to take from
	///
	/// \pre \p I is a valid index:\code
	/// 0 <= I && I < numberOfEntries()
	/// \endcode
	const T &entry(const size_t I = 0) const noexcept override {
	ASSERT(0 <= I && I < numberOfEntries()); // Boundary check.
	// Position counted back from the last recorded entry.
	typename std::make_signed<const size_t>::type Pos = Space - (1 + I);
	// Actual index wrapped around to the end of the buffer if negative.
	return (*this)[Pos >= 0 ? Pos : max_size() + Pos];
	}

	/// Removes all entries recorded in \p this object.
	void clear() noexcept override {
	Data = 0;
	Space = 0;
	}

	private:
	/// Pushes a new entry into the circular buffer.
	///
	/// \note The earliest entry gets overwritten if the buffer is full.
	///
	/// \param V value to push into the buffer
	void pushBack(const T &V) noexcept override {
	// Store value to the first empty slot and step Space index.
	(*this)[Space] = V;
	Space = (Space + 1) % max_size();
	if (Data == Space) {
	// Buffer was full, step Data index.
	Data = (Data + 1) % max_size();
	}
	}

	/// Replaces the most recent entry in the history.
	///
	/// \param V value to replace the most current value with
	void replaceFront(const T &V) noexcept override {
	(*this)[(Space - 1) % max_size()] = V;
	}
	};

	/// Adds a new entry to a \c rosa::agent::History instance.
	///
	/// \note The result of \c rosa::agent::History::addEntry is ignored.
	///
	/// \tparam T type of values stored in \p H
	/// \tparam N number of values \p H is able to store
	/// \tparam P retention policy followed by \p H when capacity is reached
	///
	/// \param H to add a new entry to
	/// \param V value to add to \p H
	///
	/// \return \p H after adding \p V to it
	template <typename T, size_t N, HistoryPolicy P>
	StaticLengthHistory<T, N, P> &operator<<(StaticLengthHistory<T, N, P> &H,
	const T &V) noexcept {
	H.addEntry(V);
	return H;
	}

	/// Implements DynamicLengthHistory by recording and storing values.
	///
	/// \note Not thread-safe implementation, which should not be a problem as any
	/// instance of \c rosa::agent::Functionality is an internal component of a
	/// \c rosa::Agent, which is the basic unit of concurrency.
	///
	/// \tparam T type of values to store
	/// \tparam P retention policy to follow when capacity is reached
	template <typename T, HistoryPolicy P>
	class DynamicLengthHistory : public History<T, P>, private std::vector<T> {

	private:
	// Bring into scope inherited functions that are used.
	using std::vector<T>::size;
	using std::vector<T>::resize;
	using std::vector<T>::push_back;
	using std::vector<T>::pop_back;
	using std::vector<T>::max_size;
	/// The current length of the DynamicLengthHistory.
	size_t Length;

	public:
	// Bring into scope inherited functions that are used.
	using std::vector<T>::erase;
	using std::vector<T>::begin;
	using std::vector<T>::end;
	using std::vector<T>::rbegin;
	using std::vector<T>::rend;
	using std::vector<T>::operator[];

	// Bring into scope inherited functions that are used.
	using History<T, P>::policy;
	using History<T, P>::empty;
	using History<T, P>::full;
	using History<T, P>::addEntry;
	using History<T, P>::trend;
	using History<T, P>::averageAbsDiff;

	/// Creates an instances by setting an initial length
	DynamicLengthHistory(size_t Length) noexcept : Length(Length) {}

	/// Destroys \p this object.
	~DynamicLengthHistory(void) override = default;

	/// Tells how many entries may be recorded by \c this object.
	///
	/// \note The number of entries that are actually recorded may be smaller.
	///
	/// \return \c rosa::agent::DynamicLengthHistory::N
	size_t maxLength(void) const noexcept override { return Length; }

	/// Tells how many entries are currently recorded by \p this object.
	///
	/// \return number of entries currently recorded by \p this object.
	///
	/// \post The returned value cannot be larger than the capacity of \p this
	/// object:\code
	/// 0 <= numberOfEntries() && numberOfEntries <=
	/// lengthOfHistory() \endcode
	size_t numberOfEntries(void) const noexcept override { return size(); }

	/// Gives a constant lvalue reference to an entry stored in \p this object.
	///
	/// \note The recorded entries are indexed starting from the latest one.
	///
	/// \param I the index at which the stored entry to take from
	///
	/// \pre \p I is a valid index:\code
	/// 0 <= I && I < numberOfEntries()
	/// \endcode
	const T &entry(const size_t I = 0) const noexcept override {
	ASSERT(0 <= I && I < numberOfEntries()); // Boundary check.
	return this->operator[](size() - I - 1);
	}

	/// Removes all entries recorded in \p this object.
	void clear() noexcept override { erase(begin(), end()); }

	/// Sort all entries in ascending order.
	void sortAscending(void) noexcept { std::sort(begin(), end()); }

	/// Sort all entries in descending order.
	void sortDescending(void) noexcept { std::sort(rbegin(), rend()); }

	/// Delets one element of the history.
	///
	/// \param V the element which shall be deleted.
	void deleteEntry(T &V) {
	auto it = std::find(begin(), end(), V);

	if (it != end()) {
	erase(it);
	}
	}

	/// Gives back the lowest entry of the history.
	///
	/// \return the lowest entry. In case of an empty history, the maximum value
	/// of the chosen data type is returned.
	T lowestEntry() {
	auto it = std::min_element(begin(), end());

	if (it == end()) {
	return std::numeric_limits<T>::max();
	} else {
	return *it;
	}
	}

	/// Gives back the highest entry of the history.
	///
	/// \return the highest entry. In case of an empty history, the minimum value
	/// of the chosen data type is returned.
	T highestEntry() {
	auto it = std::max_element(begin(), end());

	if (it == end()) {
	return std::numeric_limits<T>::min();
	} else {
	return *it;
	}
	}

	private:
	/// Pushes a new entry into the circular buffer.
	///
	/// \note The earliest entry gets overwritten if the buffer is full.
	///
	/// \param V value to push into the buffer
	void pushBack(const T &V) noexcept override {
	if (full()) {
	erase(begin());
	}
	push_back(V);
	}

	/// Replaces the most recent entry in the history.
	///
	/// \param V value to replace the most current value with
	void replaceFront(const T &V) noexcept override {
	(void)pop_back();
	push_back(V);
	}

	public:
	/// Resizes the History length. If the new length is smaller than the number
	/// of currently stored values, values are deleted according to the
	/// HistoryPolicy.
	///
	/// @param NewLength The new Length of the History.
	void setLength(size_t NewLength) noexcept {
	Length = NewLength;
	if (NewLength < numberOfEntries()) {
	switch (P) {
	default:
	ROSA_CRITICAL("unkown HistoryPolicy");
	case HistoryPolicy::LIFO:
	case HistoryPolicy::SRWF:
	// Delete last numberOfEntries() - NewLength items from the back
	erase(begin() + NewLength, end());
	break;
	case HistoryPolicy::FIFO:
	// Delete last numberOfEntries() - NewLength items from the front
	erase(begin(), begin() + (numberOfEntries() - NewLength));
	break;
	}
	}
	this->resize(Length);
	}
	+
	+ // Calculates the median of the history
	+ // \return the median of the history
	+ template <typename R> R median() noexcept {
	+ sortAscending();
	+ if (numberOfEntries() == 0) {
	+ return 0;
	+ } else if (numberOfEntries() % 2 == 0) {
	+ return (entry(numberOfEntries() / 2 - 1) + entry(numberOfEntries() / 2)) /
	+ 2;
	+ } else {
	+ return entry(numberOfEntries() / 2);
	+ }
	+ }
	};

	/// Adds a new entry to a \c rosa::agent::DynamicLengthHistory instance.
	///
	/// \note The result of \c rosa::agent::DynamicLengthHistory::addEntry is
	/// ignored.
	///
	/// \tparam T type of values stored in \p H
	/// \tparam P retention policy followed by \p H when capacity is reached
	///
	/// \param H to add a new entry to
	/// \param V value to add to \p H
	///
	/// \return \p H after adding \p V to it
	template <typename T, HistoryPolicy P>
	DynamicLengthHistory<T, P> &operator<<(DynamicLengthHistory<T, P> &H,
	const T &V) noexcept {
	H.addEntry(V);
	return H;
	}
	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_HISTORY_HPP
	diff --git a/include/rosa/agent/SignalState.hpp b/include/rosa/agent/SignalState.hpp
	index ccad719..2cfc654 100644
	--- a/include/rosa/agent/SignalState.hpp
	+++ b/include/rosa/agent/SignalState.hpp
	@@ -1,684 +1,684 @@
	//===-- rosa/agent/SignalState.hpp ------------------------------- C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/SignalState.hpp
	///
	/// \author Maximilian Götzinger (maximilian.goetzinger@tuwien.ac.at)
	///
	/// \date 2019
	///
	/// \brief Definition of signal state functionality.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_AGENT_SIGNALSTATE_HPP
	#define ROSA_AGENT_SIGNALSTATE_HPP

	#include "rosa/agent/DistanceMetrics.hpp"
	#include "rosa/agent/FunctionAbstractions.hpp"
	#include "rosa/agent/Functionality.h"
	#include "rosa/agent/History.hpp"
	#include "rosa/agent/State.hpp"

	#include "rosa/support/math.hpp"

	namespace rosa {
	namespace agent {

	/// Signal properties defining the properties of the signal which is monitored
	/// by \c rosa::agent::SignalStateDetector and is saved in \c
	/// rosa::agent::SignalStateInformation.
	enum SignalProperties : uint8_t {
	INPUT = 0, ///< The signal is an input signal
	OUTPUT = 1 ///< The signal is an output signal
	};

	/// TODO: write description
	template <typename CONFDATATYPE>
	struct SignalStateInformation : StateInformation<CONFDATATYPE> {
	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
	"confidence type is not to arithmetic");

	/// ConfidenceOfMatchingState is the confidence how good the new sample
	/// matches the state.
	CONFDATATYPE ConfidenceOfMatchingState;

	/// ConfidenceOfMatchingState is the confidence how bad the new sample
	/// matches the state.
	CONFDATATYPE ConfidenceOfMismatchingState;

	/// The SignalProperty saves whether the monitored signal is an input our
	/// output signal.
	SignalProperties SignalProperty;

	/// The SignalStateIsValid saves the number of samples which have been
	/// inserted into the state after entering it.
	uint32_t NumberOfInsertedSamplesAfterEntrance;

	public:
	SignalStateInformation(unsigned int SignalStateID,
	SignalProperties _SignalProperty) {
	this->StateID = SignalStateID;
	this->SignalProperty = _SignalProperty;
	this->StateCondition = StateConditions::UNKNOWN;
	this->NumberOfInsertedSamplesAfterEntrance = 0;
	this->StateIsValid = false;
	this->StateJustGotValid = false;
	this->StateIsValidAfterReentrance = false;
	this->ConfidenceStateIsValid = 0;
	this->ConfidenceStateIsInvalid = 0;
	this->ConfidenceStateIsStable = 0;
	this->ConfidenceStateIsDrifting = 0;
	}

	SignalStateInformation() = default;
	};

	/// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
	/// data in that the confidence values are given, \tparam PROCDATATYPE type of
	/// the relative distance and the type of data in which DABs are saved.
	template <typename INDATATYPE, typename CONFDATATYPE, typename PROCDATATYPE>
	class SignalState : public Functionality {

	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<INDATATYPE>::value),
	"input data type not arithmetic");
	STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
	"confidence data type is not to arithmetic");
	STATIC_ASSERT(
	(std::is_arithmetic<PROCDATATYPE>::value),
	"process data type (DAB and Relative Distance) is not to arithmetic");

	public:
	// The metric to calculate the distance between two points
	using DistanceMetricAbstraction =
	Abstraction<std::pair<INDATATYPE, INDATATYPE>, PROCDATATYPE> &;
	// For the convinience to write a shorter data type name
	using PartFuncReference = PartialFunction<INDATATYPE, CONFDATATYPE> &;
	// using PartFuncReference2 = ;
	using StepFuncReference = StepFunction<INDATATYPE, CONFDATATYPE> &;

	private:
	/// SignalStateInfo is a struct of SignalStateInformation that contains
	/// information about the current signal state.
	SignalStateInformation<CONFDATATYPE> SignalStateInfo;

	/// The metric to calculate the distance between two points
	DistanceMetricAbstraction DistanceMetric;

	/// The FuzzyFunctionSampleMatches is the fuzzy function that gives the
	/// confidence how good the new sample matches another sample in the sample
	/// history.
	PartFuncReference FuzzyFunctionSampleMatches;

	/// The FuzzyFunctionSampleMismatches is the fuzzy function that gives the
	/// confidence how bad the new sample matches another sample in the sample
	/// history.
	PartFuncReference FuzzyFunctionSampleMismatches;

	/// The FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
	/// confidence how many samples from the sampe history match the new sample.
	StepFuncReference FuzzyFunctionNumOfSamplesMatches;

	/// The FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives
	/// the confidence how many samples from the sampe history mismatch the new
	/// sample.
	StepFuncReference FuzzyFunctionNumOfSamplesMismatches;

	/// The FuzzyFunctionSampleValid is the fuzzy function that gives the
	/// confidence how good one matches another sample in the sample
	/// history. This is done to evaluate whether a state is valid.
	PartFuncReference FuzzyFunctionSampleValid;

	/// The FuzzyFunctionSampleInvalid is the fuzzy function that gives the
	/// confidence how bad one sample matches another sample in the sample
	/// history. This is done to evaluate whether a state is invalid.
	PartFuncReference FuzzyFunctionSampleInvalid;

	/// The FuzzyFunctionNumOfSamplesValid is the fuzzy function that gives the
	/// confidence how many samples from the sample history match another sample.
	/// This is done to evaluate whether a state is valid.
	StepFuncReference FuzzyFunctionNumOfSamplesValid;

	/// The FuzzyFunctionNumOfSamplesInvalid is the fuzzy function that gives
	/// the confidence how many samples from the sample history mismatch another
	/// sample. This is done to evaluate whether a state is invalid.
	StepFuncReference FuzzyFunctionNumOfSamplesInvalid;

	/// The FuzzyFunctionSignalIsDrifting is the fuzzy function that gives the
	/// confidence how likely it is that the signal (resp. the state of a signal)
	/// is drifting.
	PartFuncReference FuzzyFunctionSignalIsDrifting;

	/// The FuzzyFunctionSignalIsStable is the fuzzy function that gives the
	/// confidence how likely it is that the signal (resp. the state of a signal)
	/// is stable (not drifting).
	PartFuncReference FuzzyFunctionSignalIsStable;

	/// TODO: description
	PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionLookBack;
	/// TODO: description
	PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionHistoryDesicion;
	/// TODO: description
	uint32_t DriftLookbackRange;

	/// SampleHistory is a history in that the last sample values are stored.
	DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO> SampleHistory;
	/// DAB is a (usually) small history of the last sample values of which a
	/// average is calculated if the DAB is full.
	DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF> DAB;
	/// DABHistory is a history in that the last DABs (to be exact, the averages
	/// of the last DABs) are stored.
	DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO> DABHistory;

	/// LowestConfidenceMatchingHistory is a history in that the lowest confidence
	/// for the current sample matches all history samples are saved.
	DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO>
	LowestConfidenceMatchingHistory;
	/// HighestConfidenceMatchingHistory is a history in that the highest
	/// confidence for the current sample matches all history samples are saved.
	DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO>
	HighestConfidenceMismatchingHistory;

	/// TempConfidenceMatching is the confidence how good a sample matches the
	/// state. However, the value of this variable is only needed temporarly.
	CONFDATATYPE TempConfidenceMatching = 0;

	/// TempConfidenceMatching is the confidence how bad a sample matches the
	/// state. However, the value of this variable is only needed temporarly.
	CONFDATATYPE TempConfidenceMismatching = 0;

	public:
	/// Creates an instance by setting all parameters
	/// \param SignalStateID The Id of the SignalStateinfo \c
	/// SignalStateInformation.
	///
	/// \param DistanceMetric the distance metric to calculate the distance
	/// between two points
	///
	/// \param FuzzyFunctionSampleMatches The FuzzyFunctionSampleMatches is the
	/// fuzzy function that gives the confidence how good the new sample matches
	/// another sample in the sample history.
	///
	/// \param FuzzyFunctionSampleMismatches The FuzzyFunctionSampleMismatches is
	/// the fuzzy function that gives the confidence how bad the new sample
	/// matches another sample in the sample history.
	///
	/// \param FuzzyFunctionNumOfSamplesMatches The
	/// FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
	/// confidence how many samples from the sampe history match the new sample.
	///
	/// \param FuzzyFunctionNumOfSamplesMismatches The
	/// FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives the
	/// confidence how many samples from the sampe history mismatch the new
	/// sample.
	///
	/// \param FuzzyFunctionSignalIsDrifting The FuzzyFunctionSignalIsDrifting is
	/// the fuzzy function that gives the confidence how likely it is that the
	/// signal (resp. the state of a signal) is drifting.
	///
	/// \param FuzzyFunctionSignalIsStable The FuzzyFunctionSignalIsStable is the
	/// fuzzy function that gives the confidence how likely it is that the signal
	/// (resp. the state of a signal) is stable (not drifting).
	///
	/// \param SampleHistorySize Size of the Sample History \c
	/// DynamicLengthHistory . SampleHistory is a history in that the last sample
	/// values are stored.
	///
	/// \param DABSize Size of DAB \c DynamicLengthHistory . DAB is a (usually)
	/// small history of the last sample values of which a average is calculated
	/// if the DAB is full.
	///
	/// \param DABHistorySize Size of the DABHistory \c DynamicLengthHistory .
	/// DABHistory is a history in that the last DABs (to be exact, the averages
	/// of the last DABs) are stored.
	///
	SignalState(
	uint32_t SignalStateID, SignalProperties SignalProperty,
	uint32_t SampleHistorySize, uint32_t DABSize, uint32_t DABHistorySize,
	DistanceMetricAbstraction DistanceMetric,
	PartFuncReference FuzzyFunctionSampleMatches,
	PartFuncReference FuzzyFunctionSampleMismatches,
	StepFuncReference FuzzyFunctionNumOfSamplesMatches,
	StepFuncReference FuzzyFunctionNumOfSamplesMismatches,
	PartFuncReference FuzzyFunctionSampleValid,
	PartFuncReference FuzzyFunctionSampleInvalid,
	StepFuncReference FuzzyFunctionNumOfSamplesValid,
	StepFuncReference FuzzyFunctionNumOfSamplesInvalid,
	// SAVE CHANGES
	PartFuncReference FuzzyFunctionSignalIsDrifting,
	PartFuncReference FuzzyFunctionSignalIsStable,
	PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionLookBack,
	// - SAVE CHANGES
	PartialFunction<uint32_t, float>
	&FuzzyFunctionSignalConditionHistoryDesicion,
	uint32_t DriftLookbackRange) noexcept
	: SignalStateInfo{SignalStateID, SignalProperty},
	DistanceMetric(DistanceMetric),
	FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
	FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
	FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
	FuzzyFunctionNumOfSamplesMismatches(
	FuzzyFunctionNumOfSamplesMismatches),
	FuzzyFunctionSampleValid(FuzzyFunctionSampleValid),
	FuzzyFunctionSampleInvalid(FuzzyFunctionSampleInvalid),
	FuzzyFunctionNumOfSamplesValid(FuzzyFunctionNumOfSamplesValid),
	FuzzyFunctionNumOfSamplesInvalid(FuzzyFunctionNumOfSamplesInvalid),
	FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
	FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable),
	// SAVE CHANGES
	FuzzyFunctionSignalConditionLookBack(
	FuzzyFunctionSignalConditionLookBack),
	FuzzyFunctionSignalConditionHistoryDesicion(
	FuzzyFunctionSignalConditionHistoryDesicion),
	DriftLookbackRange(DriftLookbackRange),
	// - SAVE CHANGES
	SampleHistory(SampleHistorySize), DAB(DABSize),
	DABHistory(DABHistorySize),
	LowestConfidenceMatchingHistory(SampleHistorySize),
	HighestConfidenceMismatchingHistory(SampleHistorySize) {}

	/// Destroys \p this object.
	~SignalState(void) = default;

	void leaveSignalState(void) noexcept {
	DAB.clear();
	SignalStateInfo.NumberOfInsertedSamplesAfterEntrance = 0;
	SignalStateInfo.StateIsValidAfterReentrance = false;
	}

	SignalStateInformation<CONFDATATYPE>
	insertSample(INDATATYPE Sample) noexcept {

	SignalStateInfo.NumberOfInsertedSamplesAfterEntrance++;

	validateSignalState(Sample);

	SampleHistory.addEntry(Sample);

	DAB.addEntry(Sample);
	if (DAB.full()) {

	// TODO: make soring inside of median
	// TODO: make better outlier removal!
	// std::sort(DAB.begin(), DAB.end());
	// DAB.erase(DAB.begin(), DAB.begin() + 1);
	// DAB.erase(DAB.end() - 1, DAB.end());
	// PROCDATATYPE AvgOfDAB = DAB.template median<PROCDATATYPE>();
	- PROCDATATYPE AvgOfDAB = DAB.template average<PROCDATATYPE>();
	+ PROCDATATYPE AvgOfDAB = DAB.template median<PROCDATATYPE>();

	DABHistory.addEntry(AvgOfDAB);
	DAB.clear();
	}

	FuzzyFunctionNumOfSamplesMatches.setRightLimit(
	static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
	FuzzyFunctionNumOfSamplesMismatches.setRightLimit(
	static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));

	checkSignalStability();

	SignalStateInfo.ConfidenceOfMatchingState = TempConfidenceMatching;
	SignalStateInfo.ConfidenceOfMismatchingState = TempConfidenceMismatching;

	return SignalStateInfo;
	}

	/// Gives the confidence how likely the new sample matches the signal state.
	///
	/// \param Sample is the actual sample of the observed signal.
	///
	/// \return the confidence of the new sample is matching the signal state.
	CONFDATATYPE
	confidenceSampleMatchesSignalState(INDATATYPE Sample) noexcept {

	CONFDATATYPE ConfidenceOfBestCase = 0;

	DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::FIFO>
	RelativeDistanceHistory(SampleHistory.maxLength());

	// Calculate distances to all history samples.
	for (auto &HistorySample : SampleHistory) {
	PROCDATATYPE RelativeDistance =
	DistanceMetric(std::make_pair(Sample, HistorySample));
	RelativeDistanceHistory.addEntry(RelativeDistance);
	}

	// Sort all calculated distances so that the lowest distance (will get the
	// highest confidence) is at the beginning.
	RelativeDistanceHistory.sortAscending();

	CONFDATATYPE ConfidenceOfWorstFittingSample = 1;

	// Case 1 means that one (the best fitting) sample of the history is
	// compared with the new sample. Case 2 means the two best history samples
	// are compared with the new sample. And so on.
	// TODO (future): to accelerate . don't start with 1 start with some higher
	// number because a low number (i guess lower than 5) will definetely lead
	// to a low confidence. except the history is not full.

	// Case 1 means that one (the best fitting) sample of the history is
	// compared with the new sample. Case 2 means the two best history samples
	// are compared with the new sample. And so on.
	for (uint32_t Case = 0; Case < RelativeDistanceHistory.numberOfEntries();
	Case++) {

	CONFDATATYPE ConfidenceFromRelativeDistance;

	if (std::isinf(RelativeDistanceHistory[Case])) {
	// TODO (future): if fuzzy is defined in a way that infinity is not 0 it
	// would be a problem.
	ConfidenceFromRelativeDistance = 0;
	} else {
	ConfidenceFromRelativeDistance =
	FuzzyFunctionSampleMatches(RelativeDistanceHistory[Case]);
	}
	ConfidenceOfWorstFittingSample = fuzzyAND(ConfidenceOfWorstFittingSample,
	ConfidenceFromRelativeDistance);

	ConfidenceOfBestCase =
	fuzzyOR(ConfidenceOfBestCase,
	fuzzyAND(ConfidenceOfWorstFittingSample,
	FuzzyFunctionNumOfSamplesMatches(
	static_cast<CONFDATATYPE>(Case) + 1)));
	}

	TempConfidenceMatching = ConfidenceOfBestCase;

	return ConfidenceOfBestCase;
	}

	/// Gives the confidence how likely the new sample mismatches the signal
	/// state.
	///
	/// \param Sample is the actual sample of the observed signal.
	///
	/// \return the confidence of the new sample is mismatching the signal state.
	CONFDATATYPE
	confidenceSampleMismatchesSignalState(INDATATYPE Sample) noexcept {

	float ConfidenceOfWorstCase = 1;

	DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::FIFO>
	RelativeDistanceHistory(SampleHistory.maxLength());

	// Calculate distances to all history samples.
	for (auto &HistorySample : SampleHistory) {
	RelativeDistanceHistory.addEntry(
	DistanceMetric(std::make_pair(Sample, HistorySample)));
	}

	// Sort all calculated distances so that the highest distance (will get the
	// lowest confidence) is at the beginning.
	RelativeDistanceHistory.sortDescending();

	CONFDATATYPE ConfidenceOfBestFittingSample = 0;

	// TODO (future): to accelerate -> don't go until end. Confidences will only
	// get higher. See comment in "CONFDATATYPE
	// confidenceSampleMatchesSignalState(INDATATYPE Sample)".

	// Case 1 means that one (the worst fitting) sample of the history is
	// compared with the new sample. Case 2 means the two worst history samples
	// are compared with the new sample. And so on.
	for (uint32_t Case = 0; Case < RelativeDistanceHistory.numberOfEntries();
	Case++) {

	CONFDATATYPE ConfidenceFromRelativeDistance;

	if (std::isinf(RelativeDistanceHistory[Case])) {
	ConfidenceFromRelativeDistance = 1;
	} else {
	ConfidenceFromRelativeDistance =
	FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]);
	}

	ConfidenceOfBestFittingSample = fuzzyOR(ConfidenceOfBestFittingSample,
	ConfidenceFromRelativeDistance);

	ConfidenceOfWorstCase =
	fuzzyAND(ConfidenceOfWorstCase,
	fuzzyOR(ConfidenceOfBestFittingSample,
	FuzzyFunctionNumOfSamplesMismatches(
	static_cast<CONFDATATYPE>(Case) + 1)));
	}

	TempConfidenceMismatching = ConfidenceOfWorstCase;

	return ConfidenceOfWorstCase;
	}

	/// Gives information about the current signal state.
	///
	/// \return a struct SignalStateInformation that contains information about
	/// the current signal state.
	SignalStateInformation<CONFDATATYPE> signalStateInformation(void) noexcept {
	return SignalStateInfo;
	}

	private:
	void validateSignalState(INDATATYPE Sample) {
	// TODO (future): WorstConfidenceDistance and BestConfidenceDistance could
	// be set already in "CONFDATATYPE
	// confidenceSampleMatchesSignalState(INDATATYPE Sample)" and "CONFDATATYPE
	// confidenceSampleMismatchesSignalState(INDATATYPE Sample)" when the new
	// sample is compared to all history samples. This would save a lot time
	// because the comparisons are done only once. However, it has to be asured
	// that the these two functions are called before the insertation, and the
	// FuzzyFunctions for validation and matching have to be the same!
	CONFDATATYPE LowestConfidenceMatching = 1;
	CONFDATATYPE HighestConfidenceMismatching = 0;

	for (auto &HistorySample : SampleHistory) {
	// TODO (future): think about using different fuzzy functions for
	// validation and matching.
	LowestConfidenceMatching =
	fuzzyAND(LowestConfidenceMatching,
	FuzzyFunctionSampleMatches(
	DistanceMetric(std::make_pair(Sample, HistorySample))));

	HighestConfidenceMismatching =
	fuzzyOR(HighestConfidenceMismatching,
	FuzzyFunctionSampleMismatches(
	DistanceMetric(std::make_pair(Sample, HistorySample))));
	}
	LowestConfidenceMatchingHistory.addEntry(LowestConfidenceMatching);
	HighestConfidenceMismatchingHistory.addEntry(HighestConfidenceMismatching);

	LowestConfidenceMatching = LowestConfidenceMatchingHistory.lowestEntry();
	HighestConfidenceMismatching =
	HighestConfidenceMismatchingHistory.highestEntry();

	SignalStateInfo.ConfidenceStateIsValid =
	fuzzyAND(LowestConfidenceMatching,
	FuzzyFunctionNumOfSamplesValid(static_cast<INDATATYPE>(
	SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));

	SignalStateInfo.ConfidenceStateIsInvalid =
	fuzzyOR(HighestConfidenceMismatching,
	FuzzyFunctionNumOfSamplesInvalid(static_cast<INDATATYPE>(
	SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));

	if (SignalStateInfo.ConfidenceStateIsValid >
	SignalStateInfo.ConfidenceStateIsInvalid) {

	if (SignalStateInfo.StateIsValid) {
	SignalStateInfo.StateJustGotValid = false;
	} else {
	SignalStateInfo.StateJustGotValid = true;
	}

	SignalStateInfo.StateIsValid = true;
	SignalStateInfo.StateIsValidAfterReentrance = true;
	}
	}

	void checkSignalStability(void) {

	/*
	std::cout << "LookbackTest: " << std::endl;
	for (unsigned int t = 1; t <= DriftLookbackRange + 5; t++) {
	std::cout << "t=" << t
	<< " -> c=" << FuzzyFunctionSignalConditionLookBack(t)
	<< std::endl;

	//(*FuzzyFunctionTimeSystemFunctioning)(
	// static_cast<INDATATYPE>(TimeOfDisparity));
	}
	getchar();
	*/
	SignalStateInfo.ConfidenceStateIsStable = 0;
	SignalStateInfo.ConfidenceStateIsDrifting = 0;

	/*
	std::cout << "ConfidenceStateIsStable (before): "
	<< SignalStateInfo.ConfidenceStateIsStable << std::endl;
	std::cout << "ConfidenceStateIsDrifting (before): "
	<< SignalStateInfo.ConfidenceStateIsDrifting << std::endl;
	*/

	bool DriftDirectionIsUp = true;

	if (DABHistory.numberOfEntries() >= 2) {

	// SAVE CHANGES
	INDATATYPE CurrentDAB = DABHistory[DABHistory.numberOfEntries() - 1];
	INDATATYPE DAB2Compare = DABHistory[0];

	// ########### TODO HERE: calculating up_down

	uint32_t DriftDnCounter = 0;
	uint32_t DriftUpCounter = 0;

	// EXPERIMENTING
	for (unsigned int t = 1;
	t <= DriftLookbackRange && t < DABHistory.numberOfEntries(); t++) {

	DAB2Compare = DABHistory[DABHistory.numberOfEntries() - (t + 1)];

	// TODO: make the following also for distance measurement when comparing
	// sample with state and validate state
	/*
	// sigma correction
	if (NormalizedDistanceMetric<INDATATYPE, PROCDATATYPE>
	*NormalizableDistanceMetric = dynamic_cast<
	NormalizedDistanceMetric<INDATATYPE, PROCDATATYPE> *>(
	DistanceMetric)) {
	// old was safely casted to NewType
	NormalizableDistanceMetric->setNorm(
	// TODO: (1) Sigma von Sample
	// History(!) abholen, (2) irgendwas mit Sigma hier reinschreiben,
	// und (3) überlegen wegen zweiter History (länger) für
	// Sigmaberechnung
	);
	}
	*/

	float dist = DistanceMetric(std::make_pair(CurrentDAB, DAB2Compare));

	// AVG
	SignalStateInfo.ConfidenceStateIsStable +=
	FuzzyFunctionSignalIsStable(dist);
	SignalStateInfo.ConfidenceStateIsDrifting +=
	FuzzyFunctionSignalIsDrifting(dist);
	// TODO: move following outside of the loop with
	// "if(DriftLookbackRange<=DABHistory.numberOfEntries())"
	if (t == DriftLookbackRange) {
	SignalStateInfo.ConfidenceStateIsStable /= DriftLookbackRange;
	SignalStateInfo.ConfidenceStateIsDrifting /= DriftLookbackRange;
	} else if (t == DABHistory.numberOfEntries() - 1) {
	SignalStateInfo.ConfidenceStateIsStable /=
	DABHistory.numberOfEntries();
	SignalStateInfo.ConfidenceStateIsDrifting /=
	DABHistory.numberOfEntries();
	}

	/*
	// AND
	SignalStateInfo.ConfidenceStateIsStable =
	fuzzyOR(SignalStateInfo.ConfidenceStateIsStable,
	fuzzyAND(FuzzyFunctionSignalIsStable(dist),
	FuzzyFunctionSignalConditionLookBack(t)));

	SignalStateInfo.ConfidenceStateIsDrifting =
	fuzzyOR(SignalStateInfo.ConfidenceStateIsDrifting,
	fuzzyAND(FuzzyFunctionSignalIsDrifting(dist),
	FuzzyFunctionSignalConditionLookBack(t)));
	*/
	/*
	// MULTI
	SignalStateInfo.ConfidenceStateIsStable =
	fuzzyOR(SignalStateInfo.ConfidenceStateIsStable,
	FuzzyFunctionSignalIsStable(
	relativeDistance<INDATATYPE, PROCDATATYPE>(
	CurrentDAB, DAB2Compare)) *
	FuzzyFunctionSignalConditionLookBack(t));

	SignalStateInfo.ConfidenceStateIsDrifting =
	fuzzyOR(SignalStateInfo.ConfidenceStateIsDrifting,
	FuzzyFunctionSignalIsDrifting(
	relativeDistance<INDATATYPE, PROCDATATYPE>(
	CurrentDAB, DAB2Compare)) *
	FuzzyFunctionSignalConditionLookBack(t));
	*/

	if (CurrentDAB > DAB2Compare)
	DriftUpCounter++;
	else if (CurrentDAB < DAB2Compare)
	DriftDnCounter++;
	}
	// TODO: change something because it is biased if the are equal
	DriftDirectionIsUp = DriftUpCounter > DriftDnCounter;

	// following outcommented block was the published code
	/*
	SignalStateInfo.ConfidenceStateIsStable =
	FuzzyFunctionSignalIsStable(
	relativeDistance<INDATATYPE, PROCDATATYPE>(CurrentDAB,
	DAB2Compare));
	SignalStateInfo.ConfidenceStateIsDrifting =
	FuzzyFunctionSignalIsDrifting(
	relativeDistance<INDATATYPE, PROCDATATYPE>(CurrentDAB,
	DAB2Compare));
	// TODO: think about a better solution with different confidences
	// (stable, up, down, ...)
	DriftDirectionIsUp = CurrentDAB > DAB2Compare;
	*/
	// - SAVE CHANGES
	}

	/*
	std::cout << "ConfidenceStateIsStable (after): "
	<< SignalStateInfo.ConfidenceStateIsStable << std::endl;
	std::cout << "ConfidenceStateIsDrifting (after): "
	<< SignalStateInfo.ConfidenceStateIsDrifting << std::endl;
	*/

	if (SignalStateInfo.ConfidenceStateIsStable >
	SignalStateInfo.ConfidenceStateIsDrifting) {
	SignalStateInfo.StateCondition = StateConditions::STABLE;
	} else if (SignalStateInfo.ConfidenceStateIsStable <
	SignalStateInfo.ConfidenceStateIsDrifting) {

	if (DriftDirectionIsUp) {
	SignalStateInfo.StateCondition = StateConditions::DRIFTING_UP;
	} else {
	SignalStateInfo.StateCondition = StateConditions::DRIFTING_DN;
	}
	/*
	SignalStateInfo.StateCondition = StateConditions::DRIFTING;
	*/
	} else {
	SignalStateInfo.StateCondition = StateConditions::UNKNOWN;
	}
	}
	}; // namespace agent

	} // namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_SIGNALSTATE_HPP

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