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	diff --git a/include/rosa/agent/History.hpp b/include/rosa/agent/History.hpp
	index 4b834c2..d1cc791 100644
	--- a/include/rosa/agent/History.hpp
	+++ b/include/rosa/agent/History.hpp
	@@ -1,579 +1,580 @@
	//===-- rosa/agent/History.hpp ----------------------------------- C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \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 <array>
	#include <limits>
	#include <vector>
	+#include <algorithm>

	namespace rosa {
	namespace agent {

	/// 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 {}

	/// 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;
	}
	};

	/// 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> {

	//@benedikt: if i dont make these public, I cannot iterate from outside
	// through the history. E.g., "for (auto &SavedSignalState :
	// DetectedSignalStates)" at line ~297 in "SignalStateDetector.hpp". Do you
	// have an idea to make this in a better/more beautiful way?
	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>::size;
	using std::vector<T>::max_size;
	using std::vector<T>::resize;
	using std::vector<T>::push_back;
	using std::vector<T>::pop_back;
	using std::vector<T>::operator[];

	/// The current length of the DynamicLengthHistory.
	size_t Length;

	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 setting an initial length
	DynamicLengthHistory(size_t Length) noexcept : Length(Length) {
	this->resize(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 { return size(); }
	+ 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 the element which shall be deleted.
	// @benedikt: is this ok like that? should there be some "error handling"?
	// checking if V is not null, or if V is member of the vector?
	void deleteEntry(T &V) { erase(std::find(begin(), end(), V)); }

	/// 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.
	//@benedikt: please check if it is right
	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.
	//@benedikt: please check if it is right
	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);
	}
	};

	/// 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 9cde3d9..6c9de2e 100644
	--- a/include/rosa/agent/SignalState.hpp
	+++ b/include/rosa/agent/SignalState.hpp
	@@ -1,474 +1,473 @@
	//===-- 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/FunctionAbstractions.hpp"
	#include "rosa/agent/Functionality.h"
	#include "rosa/agent/History.hpp"
	#include "rosa/support/math.hpp"

	#include <cstdarg>

	namespace rosa {
	namespace agent {

	/// Signal state conditions defining how the condition of a \c
	/// rosa::agent::SignalState is saved in \c rosa::agent::SignalStateInformation.
	enum class SignalStateCondition {
	STABLE, ///< The signal state is stable
	DRIFTING, ///< The signal state is drifting
	UNKNOWN ///< The signal state is unknown
	};

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

	/// The signal state ID saved as an unsigned integer number
	unsigned int SignalStateID;
	/// The SignalStateConfidence shows the overall confidence value of the signal
	/// state.
	CONFDATATYPE SignalStateConfidence;
	/// The SignalStateCondition shows the condition of a signal state (stable or
	/// drifting)
	SignalStateCondition SignalStateCondition;
	/// The SignalStateIsValid saves the number of samples which have been
	/// inserted into the state after entering it.
	unsigned int NumberOfInsertedSamplesAfterEntrance;
	/// The SignalStateIsValid shows whether a signal state is valid or invalid.
	/// In this context, valid means that enough samples which are in close
	/// proximitry have been inserted into the signal state.
	bool SignalStateIsValid;
	/// The SignalStateJustGotValid shows whether a signal state got valid
	/// (toggled from invalid to valid) during the current inserted sample.
	bool SignalStateJustGotValid;
	/// The SignalStateIsValidAfterReentrance shows whether a signal state is
	/// valid after the variable changed back to it again.
	bool SignalStateIsValidAfterReentrance;
	/// The SignalIsStableNotDrifting shows whether a signa is stable and not
	/// drifting.
	bool SignalIsStable;
	};

	/// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
	-/// data in that the confidence values are given, \param PROCDATATYPE 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");

	private:
	// For the convinience to write a shorter data type name
	using PartFuncPointer =
	std::shared_ptr<PartialFunction<INDATATYPE, CONFDATATYPE>>;
	// @Benedikt: are INDATATYPE, CONFDATATYPE right here?
	using StepFuncPointer =
	std::shared_ptr<StepFunction<INDATATYPE, CONFDATATYPE>>;

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

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

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

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

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

	/// 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.
	PartFuncPointer 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).
	PartFuncPointer FuzzyFunctionSignalIsStable;

	/// 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;

	public:
	// @Maxi doxygen per default doesn't display private attributes of a class. So
	// I copied them to the constructor. So the user has more information.
	/// Creates an instance by setting all parameters
	/// \param SignalStateID The Id of the SignalStateinfo \c
	/// SignalStateInformation.
	///
	/// \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(unsigned int SignalStateID, unsigned int SampleHistorySize,
	unsigned int DABSize, unsigned int DABHistorySize,
	PartFuncPointer FuzzyFunctionSampleMatches,
	PartFuncPointer FuzzyFunctionSampleMismatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMismatches,
	PartFuncPointer FuzzyFunctionSignalIsDrifting,
	PartFuncPointer FuzzyFunctionSignalIsStable) noexcept
	- : SignalStateInfo{SignalStateID,
	- 0,
	- SignalStateCondition::UNKNOWN,
	- 0,
	- false,
	- false,
	+ : SignalStateInfo{SignalStateID, 0, SignalStateCondition::UNKNOWN, 0,
	+ false, false,
	+ false, //@maxi added the Signal is stable bool
	false},
	- SampleHistory(SampleHistorySize),
	- LowestConfidenceMatchingHistory(SampleHistorySize),
	- HighestConfidenceMismatchingHistory(SampleHistorySize), DAB(DABSize),
	- DABHistory(DABHistorySize),
	+
	+
	FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
	FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
	FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
	FuzzyFunctionNumOfSamplesMismatches(
	FuzzyFunctionNumOfSamplesMismatches),
	FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
	- FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable) {}
	+ FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable),
	+ 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.SignalStateIsValidAfterReentrance = false;
	}

	SignalStateInformation<CONFDATATYPE>
	insertSample(INDATATYPE Sample) noexcept {

	validateSignalState(Sample);

	SampleHistory.addEntry(Sample);

	DAB.addEntry(Sample);
	if (DAB.full()) {
	PROCDATATYPE AvgOfDAB = DAB.template average<PROCDATATYPE>();
	DABHistory.addEntry(AvgOfDAB);
	DAB.clear();
	}

	//@Benedikt: Do I really have to cast here?
	FuzzyFunctionNumOfSamplesMatches->setRightLimit(
	static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
	FuzzyFunctionNumOfSamplesMismatches->setRightLimit(
	static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));

	checkSignalStability();

	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 =
	relativeDistance<INDATATYPE, PROCDATATYPE>(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.

	for (unsigned int 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
	//@benedikt: check if your partialfunctions can take infinity as
	// argument
	//@benedikt: same as before "->operator()"
	ConfidenceFromRelativeDistance = 0;
	} else {
	ConfidenceFromRelativeDistance = FuzzyFunctionSampleMatches->operator()(
	RelativeDistanceHistory[Case]);
	}

	ConfidenceOfWorstFittingSample = fuzzyAND<CONFDATATYPE>(
	2, ConfidenceOfWorstFittingSample, ConfidenceFromRelativeDistance);
	//@benedikt: do i have to pass the number 2 to tell the function how many
	// arguments are following?
	//@benedikt: same as before with "->operator()"
	ConfidenceOfBestCase = fuzzyOR<CONFDATATYPE>(
	2, ConfidenceOfBestCase,
	fuzzyAND<CONFDATATYPE>(2, ConfidenceOfWorstFittingSample,
	FuzzyFunctionNumOfSamplesMatches->operator()(
	static_cast<CONFDATATYPE>(Case) + 1)));
	}

	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(
	relativeDistance<INDATATYPE, PROCDATATYPE>(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;

	// 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.
	// TODO (future): to accelerate -> don't go until end. Confidences will only
	// get higher. See comment in "CONFDATATYPE
	// confidenceSampleMatchesSignalState(INDATATYPE Sample)".
	for (unsigned int Case = 0;
	Case < RelativeDistanceHistory.numberOfEntries(); Case++) {

	CONFDATATYPE ConfidenceFromRelativeDistance;

	if (std::isinf(RelativeDistanceHistory[Case])) {
	ConfidenceFromRelativeDistance = 1;
	} else {
	//@benedikt: I had to change the following line. The outcommented line
	// was the original one. I think it is ugly like that (new line). Do you
	// have an idea how to make it better/more beautiful?
	ConfidenceFromRelativeDistance =
	FuzzyFunctionSampleMismatches->operator()(
	RelativeDistanceHistory[Case]);
	// FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]);
	}

	//@benedikt: do i have to pass the number 2 to tell the function how many
	// arguments are following?
	ConfidenceOfBestFittingSample = fuzzyOR<CONFDATATYPE>(
	2, ConfidenceOfBestFittingSample, ConfidenceFromRelativeDistance);

	//@benedikt: do i have to pass the number 2 to tell the function how many
	// arguments are following?
	//@benedikt: same as before with "->operator()"
	ConfidenceOfWorstCase = fuzzyAND<CONFDATATYPE>(
	2, ConfidenceOfWorstCase,
	fuzzyOR<CONFDATATYPE>(2, ConfidenceOfBestFittingSample,
	FuzzyFunctionNumOfSamplesMismatches->operator()(
	static_cast<CONFDATATYPE>(Case) + 1)));
	}

	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.
	//@benedikt: same with "->operator()"
	LowestConfidenceMatching =
	fuzzyAND<CONFDATATYPE>(2, LowestConfidenceMatching,
	FuzzyFunctionSampleMatches->operator()(
	relativeDistance<INDATATYPE, PROCDATATYPE>(
	Sample, HistorySample)));
	//@benedikt: same with "->operator()"
	HighestConfidenceMismatching =
	fuzzyOR<CONFDATATYPE>(2, HighestConfidenceMismatching,
	FuzzyFunctionSampleMismatches->operator()(
	relativeDistance<INDATATYPE, PROCDATATYPE>(
	Sample, HistorySample)));
	}
	LowestConfidenceMatchingHistory.addEntry(LowestConfidenceMatching);
	HighestConfidenceMismatchingHistory.addEntry(HighestConfidenceMismatching);

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

	//@benedikt: same with "->operator()"
	CONFDATATYPE ConfidenceSignalStateIsValid = fuzzyAND<CONFDATATYPE>(
	2, LowestConfidenceMatching,
	FuzzyFunctionNumOfSamplesMatches->operator()(static_cast<INDATATYPE>(
	SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));
	//@benedikt: same with "->operator()"
	CONFDATATYPE ConfidenceSignalStateIsInvalid = fuzzyOR<CONFDATATYPE>(
	2, HighestConfidenceMismatching,
	FuzzyFunctionNumOfSamplesMismatches->operator()(static_cast<INDATATYPE>(
	SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));

	if (ConfidenceSignalStateIsValid > ConfidenceSignalStateIsInvalid) {
	if (SignalStateInfo.SignalStateIsValid) {
	SignalStateInfo.SignalStateJustGotValid = false;
	} else {
	SignalStateInfo.SignalStateJustGotValid = true;
	}
	SignalStateInfo.SignalStateIsValid = true;
	SignalStateInfo.SignalStateIsValidAfterReentrance = true;
	}
	}

	void checkSignalStability(void) {
	CONFDATATYPE ConfidenceSignalIsStable;
	CONFDATATYPE ConfidenceSignalIsDrifting;

	if (DABHistory.numberOfEntries() >= 2) {
	//@benedikt: same "->operator()"
	ConfidenceSignalIsStable = FuzzyFunctionSignalIsStable->operator()(
	relativeDistance<INDATATYPE, PROCDATATYPE>(
	DABHistory[DABHistory.numberOfEntries() - 1], DABHistory[0]));
	//@benedikt: same "->operator()"
	ConfidenceSignalIsDrifting = FuzzyFunctionSignalIsDrifting->operator()(
	relativeDistance<INDATATYPE, PROCDATATYPE>(
	DABHistory[DABHistory.numberOfEntries() - 1], DABHistory[0]));
	} else {
	// QUESTION: is it ok to say stable = 1 and drift = 0, when I simply don't
	// know because the state is so new. Is there an option for saying don't
	// know?
	ConfidenceSignalIsStable = 1;
	ConfidenceSignalIsDrifting = 0;
	}

	SignalStateInfo.SignalIsStable =
	ConfidenceSignalIsStable >= ConfidenceSignalIsDrifting;
	}
	};

	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_SIGNALSTATE_HPP
	diff --git a/include/rosa/agent/SignalStateDetector.hpp b/include/rosa/agent/SignalStateDetector.hpp
	index aa1acfb..b608dc0 100644
	--- a/include/rosa/agent/SignalStateDetector.hpp
	+++ b/include/rosa/agent/SignalStateDetector.hpp
	@@ -1,285 +1,285 @@
	//===-- rosa/agent/SignalStateDetector.hpp ----------------------- C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/SignalStateDetector.hpp
	///
	/// \author Maximilian Götzinger (maximilian.goetzinger@tuwien.ac.at)
	///
	/// \date 2019
	///
	/// \brief Definition of signal state detector functionality.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_AGENT_SIGNALSTATEDETECTOR_HPP
	#define ROSA_AGENT_SIGNALSTATEDETECTOR_HPP

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

	#include <vector>

	namespace rosa {
	namespace agent {

	/// Implements \c rosa::agent::SignalStateDetector as a functionality that
	/// detects signal states given on input samples.
	///
	/// \note This implementation is supposed to be used for samples of an
	/// arithmetic type.
	///
	/// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
	-/// data in that the confidence values are given, \param PROCDATATYPE 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,
	HistoryPolicy HP>
	class SignalStateDetector : 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 abstraction type is not to arithmetic");

	private:
	// For the convinience to write a shorter data type name
	using PartFuncPointer =
	std::shared_ptr<PartialFunction<INDATATYPE, CONFDATATYPE>>;
	using StepFuncPointer =
	std::shared_ptr<StepFunction<INDATATYPE, CONFDATATYPE>>;
	using SignalStatePtr =
	std::shared_ptr<SignalState<INDATATYPE, CONFDATATYPE, PROCDATATYPE>>;

	/// The NextSignalStateID is a counter variable which stores the ID which the
	/// next signal state shall have.
	unsigned int NextSignalStateID;

	/// The SignalStateHasChanged is a flag that show whether a signal has changed
	/// its state.
	bool SignalStateHasChanged;

	/// The CurrentSignalState is a pointer to the (saved) signal state in which
	/// the actual variable (signal) of the observed system is.
	SignalStatePtr CurrentSignalState;

	/// The DetectedSignalStates is vector in that all detected signal states are
	/// saved.
	DynamicLengthHistory<SignalStatePtr, HP> DetectedSignalStates;

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

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

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

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

	/// The FuzzyFunctionSignalIsDrifting is the fuzzy function that gives the
	/// confidence how likely it is that the signal is drifting.
	PartFuncPointer FuzzyFunctionSignalIsDrifting;

	/// The FuzzyFunctionSignalIsStable is the fuzzy function that gives the
	/// confidence how likely it is that the signal is stable (not drifting).
	PartFuncPointer FuzzyFunctionSignalIsStable;

	/// SampleHistorySize is the (maximum) size of the sample history.
	unsigned int SampleHistorySize;
	/// DABSize the size of a DAB (Discrete Average Block).
	unsigned int DABSize;
	/// DABHistorySize is the (maximum) size of the DAB history.
	unsigned int DABHistorySize;

	public:
	/// Creates an instance by setting all parameters
	/// \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 Sets the History size which will be used by \c
	/// SignalState.
	///
	/// \param DABSize Sets the DAB size which will be used by \c SignalState.
	///
	/// \param DABHistorySize Sets the size which will be used by \c SignalState.
	///
	SignalStateDetector(unsigned int MaximumNumberOfSignalStates,
	PartFuncPointer FuzzyFunctionSampleMatches,
	PartFuncPointer FuzzyFunctionSampleMismatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMismatches,
	PartFuncPointer FuzzyFunctionSignalIsDrifting,
	PartFuncPointer FuzzyFunctionSignalIsStable,
	unsigned int SampleHistorySize, unsigned int DABSize,
	unsigned int DABHistorySize) noexcept
	: NextSignalStateID(1), SignalStateHasChanged(false),
	CurrentSignalState(NULL),
	+ DetectedSignalStates(MaximumNumberOfSignalStates),
	FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
	FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
	FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
	FuzzyFunctionNumOfSamplesMismatches(
	FuzzyFunctionNumOfSamplesMismatches),
	FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
	FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable),
	SampleHistorySize(SampleHistorySize), DABSize(DABSize),
	- DABHistorySize(DABHistorySize),
	- DetectedSignalStates(MaximumNumberOfSignalStates) {}
	+ DABHistorySize(DABHistorySize) {}

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

	/// Detects the signal state to which the new sample belongs or create a new
	/// signal state if the new sample does not match to any of the saved states.
	///
	/// \param Sample is the actual sample of the observed signal.
	///
	/// \return the information of the current signal state (signal state ID and
	/// other parameters).
	SignalStateInformation<CONFDATATYPE>
	detectSignalState(INDATATYPE Sample) noexcept {

	if (!CurrentSignalState) {
	ASSERT(DetectedSignalStates.empty());

	SignalStatePtr S = createNewSignalState();
	CurrentSignalState = S;
	} else {
	CONFDATATYPE ConfidenceSampleMatchesSignalState =
	CurrentSignalState->confidenceSampleMatchesSignalState(Sample);
	CONFDATATYPE ConfidenceSampleMismatchesSignalState =
	CurrentSignalState->confidenceSampleMismatchesSignalState(Sample);

	if (ConfidenceSampleMatchesSignalState >
	ConfidenceSampleMismatchesSignalState) {
	SignalStateHasChanged = false;
	} else {
	SignalStateHasChanged = true;

	if (CurrentSignalState->signalStateInformation().SignalStateIsValid) {
	CurrentSignalState->leaveSignalState();
	} else {
	//@benedikt: changed from vector to history. can i still do the next
	// line?
	DetectedSignalStates.deleteEntry(CurrentSignalState);
	}

	// TODO (future): additionally save averages to enable fast iteration
	// through recorded signl state history (maybe sort vector based on
	// these
	// average values)
	CurrentSignalState = nullptr;

	//@benedikt: same question
	for (auto &SavedSignalState : DetectedSignalStates) {
	if (SavedSignalState != CurrentSignalState) {
	ConfidenceSampleMatchesSignalState =
	SavedSignalState->confidenceSampleMatchesSignalState(Sample);
	ConfidenceSampleMismatchesSignalState =
	SavedSignalState->confidenceSampleMismatchesSignalState(Sample);

	if (ConfidenceSampleMatchesSignalState >
	ConfidenceSampleMismatchesSignalState) {
	// TODO (future): maybe it would be better to compare
	// ConfidenceSampleMatchesSignalState of all signal states in the
	// vector in order to find the best matching signal state.
	CurrentSignalState = SavedSignalState;
	break;
	}
	}
	}

	if (!CurrentSignalState) {
	SignalStatePtr S = createNewSignalState();
	CurrentSignalState = S;
	}
	}
	}

	SignalStateInformation<CONFDATATYPE> SignalStateInfo =
	CurrentSignalState->insertSample(Sample);

	if (SignalStateInfo.SignalStateJustGotValid) {
	NextSignalStateID++;
	}

	return SignalStateInfo;
	}

	/// Gives information about the current signal state.
	///
	/// \return a struct SignalStateInformation that contains information about
	/// the current signal state or NULL if no current signal state exists.
	SignalStateInformation<CONFDATATYPE>
	currentSignalStateInformation(void) noexcept {
	if (CurrentSignalState) {
	return CurrentSignalState->signalStateInformation();
	} else {
	return NULL;
	}
	}

	/// Gives information whether a signal state change has happened or not.
	///
	/// \return true if a signal state change has happened, and false if not.
	bool signalStateHasChanged(void) noexcept { return SignalStateHasChanged; }

	private:
	/// Creates a new signal state and adds it to the signal state vector in which
	/// all known states are saved.
	///
	/// \return a pointer to the newly created signal state or NULL if no state
	/// could be created.
	SignalStatePtr createNewSignalState(void) noexcept {
	SignalStatePtr S(new SignalState<INDATATYPE, CONFDATATYPE, PROCDATATYPE>(
	NextSignalStateID, SampleHistorySize, DABSize, DABHistorySize,
	FuzzyFunctionSampleMatches, FuzzyFunctionSampleMismatches,
	FuzzyFunctionNumOfSamplesMatches, FuzzyFunctionNumOfSamplesMismatches,
	FuzzyFunctionSignalIsDrifting, FuzzyFunctionSignalIsStable));

	// @benedikt: todo: assert in history, which checks if push_back worked
	DetectedSignalStates.addEntry(S);

	return S;
	}
	};

	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_SIGNALSTATEDETECTOR_HPP
	diff --git a/include/rosa/support/math.hpp b/include/rosa/support/math.hpp
	index 705a08c..8483f65 100644
	--- a/include/rosa/support/math.hpp
	+++ b/include/rosa/support/math.hpp
	@@ -1,131 +1,201 @@
	//===-- rosa/support/math.hpp ------------------------------------ C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/support/math.hpp
	///
	/// \author David Juhasz (david.juhasz@tuwien.ac.at)
	///
	/// \date 2017
	///
	/// \brief Math helpers.
	///
	//===----------------------------------------------------------------------===//

	+// !!!!!! Please check lines 60 - 180 forward !!!!!!!!!!!!!!
	+
	#ifndef ROSA_SUPPORT_MATH_HPP
	#define ROSA_SUPPORT_MATH_HPP

	+#include "debug.hpp"
	#include <algorithm>
	+#include <array>
	#include <cmath>
	#include <cstdarg>
	#include <cstdlib>
	#include <limits>
	#include <type_traits>

	namespace rosa {

	/// Computes log base 2 of a number.
	///
	/// \param N the number to compute log base 2 for
	///
	/// \return log base 2 of \p N
	constexpr size_t log2(const size_t N) {
	return ((N < 2) ? 1 : 1 + log2(N / 2));
	}

	/// Tells the next representable floating point value.
	///
	/// \tparam T type to operate on
	///
	/// \note The second type argument enforces \p T being a floating point type,
	/// always use the default value!
	///
	/// \param V value to which find the next representable one
	///
	/// \return the next representable value of type \p T after value \p V
	///
	/// \pre Type \p T must be a floating point type, which is enforced by
	/// `std::enable_if` in the second type argument.
	template <typename T,
	typename = std::enable_if_t<std::is_floating_point<T>::value>>
	T nextRepresentableFloatingPoint(const T V) {
	return std::nextafter(V, std::numeric_limits<T>::infinity());
	}

	+#if false
	// copied from the internet and adapted
	-// (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	+//
	+(https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	/// Conjuncts two or more values with each other.
	///
	/// \param two or more values of the same datatype
	///
	/// \return the conjunction of the values given as parameter.
	template <typename CONFDATATYPE>
	CONFDATATYPE fuzzyAND(int n_args, ...) noexcept {
	// TODO: check datatype, if there are at least two arguments, and if they are
	// between 0 and 1
	// David suggests: nstead of a variadic argument, you could pass the values as
	// an std::array (with a template argument for the length). When you pass the
	// values as a container, you can simply use std::max_element and
	// std::min_element to have a one-liner implementation of the these fuzzy
	// functions.
	va_list ap;
	va_start(ap, n_args);
	CONFDATATYPE min = va_arg(ap, CONFDATATYPE);
	for (int i = 2; i <= n_args; i++) {
	CONFDATATYPE a = va_arg(ap, CONFDATATYPE);
	min = std::min(a, min);
	}
	va_end(ap);
	return min;
	}
	+#else
	+
	+template <typename CONFDATATYPE, std::size_t size>
	+CONFDATATYPE fuzzyAND(std::array<CONFDATATYPE, size> Data) noexcept {
	+ STATIC_ASSERT(std::is_arithmetic<CONFDATATYPE>::value,
	+ "Type of FuzzyAnd is not arithmetic");
	+ STATIC_ASSERT(size > 1, "Number of Arguments is to little");
	+ for (auto tmp : Data)
	+ ASSERT(tmp <= 1 && tmp >= 0);
	+ return *std::min_element(Data.begin(), Data.end());
	+}
	+
	+#if false // safer
	+template <typename CONFDATATYPE, typename... _CONFDATATYPE>
	+std::enable_if_t<
	+ std::conjunction_v<std::is_same<CONFDATATYPE, _CONFDATATYPE>...>,
	+ CONFDATATYPE>
	+fuzzyAND(CONFDATATYPE Data, _CONFDATATYPE... Datan) noexcept {
	+ return fuzzyAND(
	+ std::array<CONFDATATYPE, sizeof...(Datan) + 1>{Data, Datan...});
	+}
	+#else
	+template <typename CONFDATATYPE, typename... _CONFDATATYPE>
	+CONFDATATYPE fuzzyAND(CONFDATATYPE Data, _CONFDATATYPE... Datan) noexcept {
	+ return fuzzyAND(
	+ std::array<CONFDATATYPE, sizeof...(Datan) + 1>{Data, Datan...});
	+}
	+#endif
	+
	+#endif
	+

	+#if false //can't compile
	/// Disjuncts two or more values with each other.
	///
	-/// \param two or more values of the same datatype
	+///
	///
	/// \return the disjunction of the values given as parameter.
	// copied from the internet
	// (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	template <typename CONFDATATYPE>
	CONFDATATYPE fuzzyOR(int n_args, ...) noexcept {
	// TODO: check datatype and if they are between 0 and 1
	// David suggests: nstead of a variadic argument, you could pass the values as
	// an std::array (with a template argument for the length). When you pass the
	// values as a container, you can simply use std::max_element and
	// std::min_element to have a one-liner implementation of the these fuzzy
	// functions.
	va_list ap;
	va_start(ap, n_args);
	CONFDATATYPE max = va_arg(ap, CONFDATATYPE);
	for (int i = 2; i <= n_args; i++) {
	CONFDATATYPE a = va_arg(ap, CONFDATATYPE);
	max = std::max(a, max);
	}
	va_end(ap);
	return max;
	}
	+#else
	+
	+
	+template <typename CONFDATATYPE, std::size_t size>
	+CONFDATATYPE fuzzyOR(std::array<CONFDATATYPE, size> Data) noexcept {
	+ STATIC_ASSERT(std::is_arithmetic<CONFDATATYPE>::value,
	+ "Type of FuzzyAnd is not arithmetic");
	+ STATIC_ASSERT(size > 1, "Number of Arguments is to little");
	+ for (auto tmp : Data)
	+ ASSERT(tmp <= 1 && tmp >= 0);
	+ return *std::max_element(Data.begin(), Data.end());
	+}
	+
	+#if false // safer
	+template <typename CONFDATATYPE, typename... _CONFDATATYPE>
	+std::enable_if_t<
	+ std::conjunction_v<std::is_same<CONFDATATYPE, _CONFDATATYPE>...>,
	+ CONFDATATYPE>
	+fuzzyOR(CONFDATATYPE Data, _CONFDATATYPE... Datan) noexcept {
	+ return fuzzyOR(
	+ std::array<CONFDATATYPE, sizeof...(Datan) + 1>{Data, Datan...});
	+}
	+#else
	+template <typename CONFDATATYPE, typename... _CONFDATATYPE>
	+CONFDATATYPE fuzzyOR(CONFDATATYPE Data, _CONFDATATYPE... Datan) noexcept {
	+ return fuzzyOR(
	+ std::array<CONFDATATYPE, sizeof...(Datan) + 1>{Data, Datan...});
	+}
	+#endif
	+
	+
	+#endif

	template <typename INDATATYPE, typename PROCDATATYPE>
	PROCDATATYPE relativeDistance(INDATATYPE NewValue,
	INDATATYPE HistoryValue) noexcept {
	PROCDATATYPE Dist = HistoryValue - NewValue;

	if (Dist == 0) {
	return 0;
	} else {
	Dist = Dist / NewValue;
	if (Dist < 0) {
	// TODO: I guess this multiplication here should not be done because
	// it could be that the distance fuzzy functions are not symetrical
	//(negative and positive side)
	Dist = Dist * (-1);
	}
	return (Dist);
	}
	}

	} // End namespace rosa

	#endif // ROSA_SUPPORT_MATH_HPP

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