diff --git a/apps/ccam/ccam.cpp b/apps/ccam/ccam.cpp index 7ae44de..76fc676 100644 --- a/apps/ccam/ccam.cpp +++ b/apps/ccam/ccam.cpp @@ -1,58 +1,116 @@ //===-- apps/ccam/ccam.cpp --------------------------------------*- C++ -*-===// // // The RoSA Framework -- Application CCAM // //===----------------------------------------------------------------------===// /// /// \file apps/ccam/ccam.cpp /// /// \author Maximilian Goetzinger (maximilian.goetzinger@tuwien.ac.at) /// /// \date 2019 /// /// \brief The application CCAM implements the case study from the paper: /// M. Goetzinger, N. TaheriNejad, H. A. Kholerdi, A. Jantsch, E. Willegger, /// T. Glatzl, A.M. Rahmani, T.Sauter, P. Liljeberg: Model - Free Condition /// Monitoring with Confidence //===----------------------------------------------------------------------===// #include "rosa/agent/FunctionAbstractions.hpp" #include "rosa/agent/SignalStateDetector.hpp" #include +using namespace rosa::agent; + int main(void) { // Just some tests :D std::vector vec = {7, 3, 5, 1, 9}; std::sort(vec.rbegin(), vec.rend()); // std::reverse(vec.begin(), vec.end()); for (auto it = vec.cbegin(); it != vec.cend(); ++it) { std::cout << *it << ' '; } - std::shared_ptr> PartFunc( - new rosa::agent::PartialFunction( + std::shared_ptr> PartFunc( + new PartialFunction( { {{0.f, 3.f}, - std::make_shared>( - 0.f, 1.f / 3)}, + std::make_shared>(0.f, 1.f / 3)}, {{3.f, 6.f}, - std::make_shared>( - 1.f, 0.f)}, + std::make_shared>(1.f, 0.f)}, {{6.f, 9.f}, - std::make_shared>( - 3.f, -1.f / 3)}, + std::make_shared>(3.f, -1.f / 3)}, }, 0)); - std::shared_ptr> StepFunc( - new rosa::agent::StepFunction(1 / 10)); + std::shared_ptr> StepFunc( + new StepFunction(1 / 10)); + + SignalStateDetector TestSigSD( + 10000, PartFunc, PartFunc, StepFunc, StepFunc, PartFunc, PartFunc, 10, 5, + 1000); - rosa::agent::SignalStateDetector TestSigSD( - PartFunc, PartFunc, StepFunc, StepFunc, PartFunc, PartFunc, 10, 5, 1000); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(50.3f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); + TestSigSD.detectSignalState(100.6f); return 0; } diff --git a/include/rosa/agent/FunctionAbstractions.hpp b/include/rosa/agent/FunctionAbstractions.hpp index bebfd77..a0f8585 100644 --- a/include/rosa/agent/FunctionAbstractions.hpp +++ b/include/rosa/agent/FunctionAbstractions.hpp @@ -1,351 +1,354 @@ //===-- rosa/agent/FunctionAbstractions.hpp ---------------------*- C++ -*-===// // // The RoSA Framework // //===----------------------------------------------------------------------===// /// /// \file rosa/agent/FunctionAbstractions.hpp /// /// \author Benedikt Tutzer (benedikt.tutzer@tuwien.ac.at) /// /// \date 2019 /// /// \brief Definition of *FunctionAbstractions* *functionality*. /// //===----------------------------------------------------------------------===// #ifndef ROSA_AGENT_FUNCTIONABSTRACTIONS_HPP #define ROSA_AGENT_FUNCTIONABSTRACTIONS_HPP #include "rosa/agent/Abstraction.hpp" #include "rosa/agent/Functionality.h" #include "rosa/support/debug.hpp" #include #include #include #include namespace rosa { namespace agent { /// Implements \c rosa::agent::Abstraction as a linear function, /// y = Coefficient * X + Intercept. /// /// \note This implementation is supposed to be used to represent a linear /// function from an arithmetic domain to an arithmetic range. This is enforced /// statically. /// /// \tparam D type of the functions domain /// \tparam R type of the functions range template class LinearFunction : public Abstraction { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::value), "LinearFunction not arithmetic T"); STATIC_ASSERT((std::is_arithmetic::value), "LinearFunction not to arithmetic"); protected: /// The Intercept of the linear function const D Intercept; /// The Coefficient of the linear function const D Coefficient; public: /// Creates an instance given the intercept and the coefficient of a linear /// function. /// /// \param Intercept the intercept of the linear function /// \param Coefficient the coefficient of the linear function LinearFunction(D Intercept, D Coefficient) noexcept : Abstraction(Intercept), Intercept(Intercept), Coefficient(Coefficient) {} /// Creates an instance given the two points on a linear function. /// /// \param x1 The x-value of the first point /// \param y1 The x-value of the first point /// \param x2 The y-value of the second point /// \param y2 The y-value of the second point LinearFunction(D x1, R y1, D x2, R y2) noexcept : Abstraction(y1 - x1 * (y1 - y2) / (x1 - x2), (y1 - y2) / (x1 - x2)) {} /// Creates an instance given the two points on a linear function. /// /// \param p1 The coordinates of the first point /// \param p2 The coordinates of the second point LinearFunction(std::pair p1, std::pair p2) noexcept : LinearFunction(p1.first, p1.second, p2.first, p2.second) {} /// Destroys \p this object. ~LinearFunction(void) = default; /// Checks wether the Abstraction evaluates to default at the given position /// As LinearFunctions can be evaluated everythwere, this is always false /// /// \param V the value at which to check if the function falls back to it's /// default value. /// /// \return false bool isDefaultAt(const D &V) const noexcept override { (void)V; return false; } /// Getter for member variable Intercept /// /// \return Intercept D getIntercept() const { return Intercept; } /// Setter for member variable Intercept /// /// \param Intercept the new Intercept void setIntercept(const D &Intercept) { this->Intercept = Intercept; } /// Getter for member variable Coefficient /// /// \return Coefficient D getCoefficient() const { return Coefficient; } /// Setter for member variable Coefficient /// /// \param Coefficient the new Intercept void setCoefficient(const D &Coefficient) { this->Coefficient = Coefficient; } /// Set Intercept and Coefficient from two points on the linear function /// /// \param x1 The x-value of the first point /// \param y1 The x-value of the first point /// \param x2 The y-value of the second point /// \param y2 The y-value of the second point void setFromPoints(D x1, R y1, D x2, R y2) { Coefficient = (y1 - y2) / (x1 - x2); Intercept = y1 - Coefficient * x1; } /// Set Intercept and Coefficient from two points on the linear function /// /// \param p1 The coordinates of the first point /// \param p2 The coordinates of the second point inline void setFromPoints(std::pair p1, std::pair p2) { setFromPoints(p1.first, p1.second, p2.first, p2.second); } /// Evaluates the linear function /// /// \param X the value at which to evaluate the function /// /// \return Coefficient*X + Intercept virtual R operator()(const D &X) const noexcept override { return Intercept + X * Coefficient; } }; /// Implements \c rosa::agent::Abstraction as a sine function, /// y = Amplitude * sin(Frequency * X + Phase) + Average. /// /// \note This implementation is supposed to be used to represent a sine /// function from an arithmetic domain to an arithmetic range. This is enforced /// statically. /// /// \tparam D type of the functions domain /// \tparam R type of the functions range template class SineFunction : public Abstraction { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::value), "SineFunction not arithmetic T"); STATIC_ASSERT((std::is_arithmetic::value), "SineFunction not to arithmetic"); protected: /// The frequency of the sine wave const D Frequency; /// The Ampiltude of the sine wave const D Amplitude; /// The Phase-shift of the sine wave const D Phase; /// The y-shift of the sine wave const D Average; public: /// Creates an instance. /// /// \param Frequency the frequency of the sine wave /// \param Amplitude the amplitude of the sine wave /// \param Phase the phase of the sine wave /// \param Average the average of the sine wave SineFunction(D Frequency, D Amplitude, D Phase, D Average) noexcept : Abstraction(Average), Frequency(Frequency), Amplitude(Amplitude), Phase(Phase), Average(Average) {} /// Destroys \p this object. ~SineFunction(void) = default; /// Checks wether the Abstraction evaluates to default at the given position /// As SineFunctions can be evaluated everythwere, this is always false /// /// \param V the value at which to check if the function falls back to it's /// default value. /// /// \return false bool isDefaultAt(const D &V) const noexcept override { (void)V; return false; } /// Evaluates the sine function /// /// \param X the value at which to evaluate the function /// \return the value of the sine-function at X virtual R operator()(const D &X) const noexcept override { return Amplitude * sin(Frequency * X + Phase) + Average; } }; /// Implements \c rosa::agent::PartialFunction as a step function from 0 to 1 /// with a ramp in between /// /// \tparam D type of the functions domain /// \tparam R type of the functions range template class StepFunction : public Abstraction { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::value), "abstracting not arithmetic"); STATIC_ASSERT((std::is_arithmetic::value), "abstracting not to arithmetic"); private: D Coefficient; D RightLimit; public: /// Creates an instance by Initializing the underlying \c Abstraction. /// /// \param Coefficient Coefficient of the ramp /// /// \pre Coefficient > 0 StepFunction(D Coefficient) : Abstraction(0), Coefficient(Coefficient), RightLimit(1.0f / Coefficient) { ASSERT(Coefficient > 0); } /// Destroys \p this object. ~StepFunction(void) = default; /// Setter for Coefficient /// /// \param Coefficient the new Coefficient void setCoefficient(const D &Coefficient) { ASSERT(Coefficient > 0); this->Coefficient = Coefficient; this->RightLimit = 1 / Coefficient; } /// Setter for RightLimit /// /// \param RightLimit the new RightLimit - void setRightLimit(const D &RightLimit) { - ASSERT(RightLimit > 0); - this->RightLimit = RightLimit; - this->Coefficient = 1 / RightLimit; + //@Benedikt: I had to change the name of the parameter from RightLimit to + // RightLimit_, because otherwise there was a "warning treaded as error: + // warning: C4458: declaration of 'RightLimit' hides class member" + void setRightLimit(const D &RightLimit_) { + ASSERT(RightLimit_ > 0); + this->RightLimit = RightLimit_; + this->Coefficient = 1 / RightLimit_; } /// Checks wether the Abstraction evaluates to default at the given position /// /// \param V the value at which to check if the function falls back to it's /// default value. /// /// \return false if the is negative, true otherwise bool isDefaultAt(const D &V) const noexcept override { return V > 0; } /// Executes the Abstraction /// /// \param V value to abstract /// /// \return the abstracted value R operator()(const D &V) const noexcept override { if (V <= 0) return 0; if (V >= RightLimit) return 1; return V * Coefficient; } }; /// Implements \c rosa::agent::Abstraction as a partial function from a domain /// to a range. /// /// \note This implementation is supposed to be used to represent a partial /// function from an arithmetic domain to an arithmetic range. This is enforced /// statically. /// /// A partial function is defined as a list of abstractions, where each /// abstraction is associated a range in which it is defined. These ranges must /// be mutually exclusive. /// /// \tparam D type of the functions domain /// \tparam R type of the functions range template class PartialFunction : public Abstraction { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::value), "abstracting not arithmetic"); STATIC_ASSERT((std::is_arithmetic::value), "abstracting not to arithmetic"); private: /// A \c rosa::agent::RangeAbstraction RA is used to represent the association /// from ranges to Abstractions. /// This returns the Abstraction that is defined for any given value, or /// a default Abstraction if no Abstraction is defined for that value. RangeAbstraction>> RA; public: /// Creates an instance by Initializing the underlying \c Abstraction. /// /// \param Map the mapping to do abstraction according to /// \param Default abstraction to abstract to by default /// /// \pre Each key defines a valid range such that `first <= second` and /// there are no overlapping ranges defined by the keys. PartialFunction( const std::map, std::shared_ptr>> &Map, const R Default) : Abstraction(Default), RA(Map, std::shared_ptr>(new Abstraction(Default))) { } /// Destroys \p this object. ~PartialFunction(void) = default; /// Checks wether the Abstraction evaluates to default at the given position /// /// \param V the value at which to check if the function falls back to it's /// default value. /// /// \return false if the value falls into a defined range and the Abstraction /// defined for that range does not fall back to it's default value. bool isDefaultAt(const D &V) const noexcept override { return RA.isDefaultAt(V) ? true : RA(V)->isDefaultAt(V); } /// Searches for an Abstraction for the given value and executes it for that /// value, if such an Abstraction is found. The default Abstraction is /// evaluated otherwise. /// /// \param V value to abstract /// /// \return the abstracted value based on the set mapping R operator()(const D &V) const noexcept override { return RA(V)->operator()(V); } }; } // End namespace agent } // End namespace rosa #endif // ROSA_AGENT_FUNCTIONABSTRACTIONS_HPP diff --git a/include/rosa/agent/History.hpp b/include/rosa/agent/History.hpp index 2426f9b..f8d66d1 100644 --- a/include/rosa/agent/History.hpp +++ b/include/rosa/agent/History.hpp @@ -1,536 +1,548 @@ //===-- 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 #include 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 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::value && std::is_signed::value /// \endcode Dynamically, \p D is a valid number of steps to take:\code /// 0 <= D && D < lengthOfHistory() /// \endcode template typename std::enable_if< std::is_arithmetic::value && std::is_signed::value, X>::type trend(const size_t D) const noexcept { STATIC_ASSERT((std::is_same::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::value /// \endcode Dynamically, \p D is a valid number of steps to take:\code /// 0 <= D && D < lengthOfHistory() /// \endcode template typename std::enable_if::value, size_t>::type averageAbsDiff(const size_t D) const noexcept { STATIC_ASSERT((std::is_same::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 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 class StaticLengthHistory : public History, private std::array { // Bring into scope inherited functions that are used. using std::array::max_size; using std::array::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::policy; using History::empty; using History::full; using History::addEntry; using History::trend; using History::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::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 StaticLengthHistory &operator<<(StaticLengthHistory &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 class DynamicLengthHistory : public History, private std::vector { + //@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::erase; using std::vector::begin; using std::vector::end; using std::vector::rbegin; using std::vector::rend; using std::vector::size; using std::vector::max_size; using std::vector::resize; using std::vector::push_back; using std::vector::pop_back; using std::vector::operator[]; /// The current length of the DynamicLengthHistory. size_t Length; public: using History::policy; using History::empty; using History::full; using History::addEntry; using History::trend; using History::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(); } /// 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)); } + 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 DynamicLengthHistory &operator<<(DynamicLengthHistory &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 dcbcba4..3a68820 100644 --- a/include/rosa/agent/SignalState.hpp +++ b/include/rosa/agent/SignalState.hpp @@ -1,420 +1,380 @@ //===-- 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 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 struct SignalStateInformation { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::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 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; }; -// @Benedikt: now there are 4 datatypes. Do you think we can merge PROCDATATYPE -// and PROCDATATYPE somehow? /// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of /// data in that the confidence values are given, \param PROCDATATYPE type of /// the relative distance and the type of data in which DABs are saved. template class SignalState : public Functionality { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::value), "input data type not arithmetic"); STATIC_ASSERT((std::is_arithmetic::value), "confidence data type is not to arithmetic"); STATIC_ASSERT( (std::is_arithmetic::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>; + // @Benedikt: are INDATATYPE, CONFDATATYPE right here? using StepFuncPointer = std::shared_ptr>; /// SignalStateInfo is a struct SignalStateInformation that contains /// information about the current state. SignalStateInformation 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 SampleHistory; /// DAB is a (usually) small history of the last sample values of which a /// average is calculated if the DAB is full. DynamicLengthHistory DAB; /// DABHistory is a history in that the last DABs (to be exact, the averages /// of the last DABs) are stored. DynamicLengthHistory DABHistory; /// 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 SignalStateIsValidAfterReentrance shows whether a signal state is /// valid after the variable changed back to it again. bool SignalStateIsValidAfterReentrance; 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, + 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, - unsigned int SampleHistorySize, unsigned int DABSize, - unsigned int DABHistorySize) noexcept - : SignalStateInfo(SignalStateID, 0, SignalStateCondition::UNKNOWN, false, - false), + PartFuncPointer FuzzyFunctionSignalIsStable) noexcept + : SignalStateInfo{SignalStateID, 0, SignalStateCondition::UNKNOWN, + false, false, false}, SampleHistory(SampleHistorySize), DAB(DABSize), DABHistory(DABHistorySize), FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches), FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches), FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches), FuzzyFunctionNumOfSamplesMismatches( FuzzyFunctionNumOfSamplesMismatches), FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting), FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable) {} /// Destroys \p this object. ~SignalState(void) = default; void leaveSignalState(void) noexcept { DAB.clear(); SignalStateIsValidAfterReentrance = false; } SignalStateInformation insertSample(INDATATYPE Sample) noexcept { SampleHistory.addEntry(Sample); DAB.addEntry(Sample); if (DAB.full()) { PROCDATATYPE AvgOfDAB = DAB.template average(); DABHistory.addEntry(AvgOfDAB); DAB.clear(); } + //@Benedikt: Do I really have to cast here? FuzzyFunctionNumOfSamplesMatches->setRightLimit( - SampleHistory->numberOfEntries()); + static_cast(SampleHistory.numberOfEntries())); FuzzyFunctionNumOfSamplesMismatches->setRightLimit( - SampleHistory->numberOfEntries()); + static_cast(SampleHistory.numberOfEntries())); // TODO: calculate whether signal state is valid and properly set // SignalStateIsValid, SignalStateJustGotValid, // SignalStateIsValidAfterReentrance // TODO: check current signal state whether it drifts // TODO: write in SignalStateInfo 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 - RelativeDistanceHistory; + RelativeDistanceHistory(SampleHistory.maxLength()); // calculate distances to all history samples for (auto &HistorySample : SampleHistory) { - PROCDATATYPE RelativeDistance = relativeDistance(Sample, HistorySample); + PROCDATATYPE RelativeDistance = + relativeDistance(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(RelativeDistanceHistory[Case]); + ConfidenceFromRelativeDistance = FuzzyFunctionSampleMatches->operator()( + RelativeDistanceHistory[Case]); } - ConfidenceOfWorstFittingSample = fuzzyAND(ConfidenceOfWorstFittingSample, - ConfidenceFromRelativeDistance); - - // @benedikt: change old-style cast to one of these: reinterpret_cast, - // static_cast, dynamic_cast or const_cast. Which should I use? Or should - // the HistSampleCounter variable already be CONFDATATYPE type? - ConfidenceOfBestCase = fuzzyOR( - ConfidenceOfBestCase, - fuzzyAND(ConfidenceOfWorstFittingSample, - FuzzyFunctionNumOfSamplesMatches((CONFDATATYPE)Case + 1))); + ConfidenceOfWorstFittingSample = fuzzyAND( + 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( + 2, ConfidenceOfBestCase, + fuzzyAND(2, ConfidenceOfWorstFittingSample, + FuzzyFunctionNumOfSamplesMatches->operator()( + static_cast(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 - RelativeDistanceHistory; + RelativeDistanceHistory(SampleHistory.maxLength()); // calculate distances to all history samples for (auto &HistorySample : SampleHistory) { - RelativeDistanceHistory.addEntry(relativeDistance(Sample, HistorySample)); + RelativeDistanceHistory.addEntry( + relativeDistance(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; - unsigned int Case = 1; // 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(RelativeDistanceHistory[Case]); + FuzzyFunctionSampleMismatches->operator()( + RelativeDistanceHistory[Case]); + // FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]); } - ConfidenceOfBestFittingSample = fuzzyOR(ConfidenceOfBestFittingSample, - ConfidenceFromRelativeDistance); - - // @benedikt: change old-style cast to one of these: reinterpret_cast, - // static_cast, dynamic_cast or const_cast. Which should I use? Or should - // the HistSampleCounter variable already be CONFDATATYPE type? - ConfidenceOfWorstCase = fuzzyAND( - ConfidenceOfWorstCase, - fuzzyOR(ConfidenceOfBestFittingSample, - FuzzyFunctionNumOfSamplesMismatches((CONFDATATYPE)Case + 1))); + //@benedikt: do i have to pass the number 2 to tell the function how many + // arguments are following? + ConfidenceOfBestFittingSample = fuzzyOR( + 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( + 2, ConfidenceOfWorstCase, + fuzzyOR(2, ConfidenceOfBestFittingSample, + FuzzyFunctionNumOfSamplesMismatches->operator()( + static_cast(Case) + 1))); } return ConfidenceOfWorstCase; } /// Gives information about the current signal state. /// /// \return a struct SignalStateInformation that contains information about /// the current signal state. SignalStateInformation signalStateInformation(void) noexcept { return SignalStateInfo; } - -private: - // @David: Where should these next functions (fuzzyAND, fuzzyOR, - // relativeDistance) moved to (I guess we will use them also somewhere else)? - - // copied from the internet and adapted - // (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c) - CONFDATATYPE fuzzyAND(int n_args, ...) noexcept { - 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; - } - - // copied from the internet - // (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c) - CONFDATATYPE fuzzyOR(int n_args, ...) noexcept { - 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); - std::max(a, max); - } - va_end(ap); - return max; - } - - PROCDATATYPE relativeDistance(INDATATYPE SampleValue, - INDATATYPE HistoryValue) noexcept { - PROCDATATYPE Dist = HistoryValue - SampleValue; - - if (Dist == 0) { - return 0; - } else { - Dist = Dist / SampleValue; - if (Dist < 0) { - //@benedikt: 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 agent } // End namespace rosa #endif // ROSA_AGENT_SIGNALSTATE_HPP diff --git a/include/rosa/agent/SignalStateDetector.hpp b/include/rosa/agent/SignalStateDetector.hpp index b306ede..d1ebec5 100644 --- a/include/rosa/agent/SignalStateDetector.hpp +++ b/include/rosa/agent/SignalStateDetector.hpp @@ -1,367 +1,357 @@ //===-- 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/SignalState.hpp" #include 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 is the type of input data, \tparam CONFDATATYPE is type -/// of -/// data in that the confidence values are given -template +/// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of +/// data in that the confidence values are given, \param PROCDATATYPE type of +/// the relative distance and the type of data in which DABs are saved. +template class SignalStateDetector : public Functionality { // Make sure the actual type arguments are matching our expectations. STATIC_ASSERT((std::is_arithmetic::value), "input data type not arithmetic"); STATIC_ASSERT((std::is_arithmetic::value), "confidence abstraction type is not to arithmetic"); private: // For the convinience to write a shorter data type name using PartFuncPointer = std::shared_ptr>; using StepFuncPointer = std::shared_ptr>; - using SignalStatePtr = std::shared_ptr>; - using SignalStateInfoPtr = - std::shared_ptr>; + using SignalStatePtr = + std::shared_ptr>; /// 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. - // TODO: make it to history - DynamicLengthHistory - DetectedSignalStates; - // std::vector DetectedSignalStates; + DynamicLengthHistory 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(PartFuncPointer FuzzyFunctionSampleMatches, + 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), FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches), FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches), FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches), FuzzyFunctionNumOfSamplesMismatches( FuzzyFunctionNumOfSamplesMismatches), FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting), FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable), SampleHistorySize(SampleHistorySize), DABSize(DABSize), - DABHistorySize(DABHistorySize) {} + DABHistorySize(DABHistorySize), + DetectedSignalStates(MaximumNumberOfSignalStates) {} /// Destroys \p this object. ~SignalStateDetector(void) = default; /// Detects a 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 signal /// states. /// /// \param Sample is the actual sample of the observed signal. /// /// \return the signal state ID as unsigend integer type. Signal state IDs /// start with number 1; that means if there is no current signal state, the /// return value is 0. unsigned int detectSignalState(INDATATYPE Sample) noexcept { - SignalStateInfoPtr SignalStateInfo = detectSignalState__debug(Sample); - return SignalStateInfo->SignalStateID; + SignalStateInformation SignalStateInfo = + detectSignalState__debug(Sample); + return SignalStateInfo.SignalStateID; } /// Gives information about the current signal state. /// /// \return a the signal state ID (as unsigned integer type) of the current /// signal state. Signal state IDs start with number 1; that means if there is /// no current signal state, the return value is 0. unsigned int currentSignalStateInformation(void) noexcept { - SignalStateInfoPtr SignalStateInfo = currentSignalStateInformation__debug(); + SignalStateInformation SignalStateInfo = + currentSignalStateInformation__debug(); if (SignalStateInfo) { - return SignalStateInfo->SignalStateID; + return SignalStateInfo.SignalStateID; } else { return 0; } } /// 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: - // TODO: change exlaination! it is not totally right - //@maxi \param is there to Document a specific parameter of a method/function - // this method doesn't have any parameters. /// Creates a new signal state and adds it to the signal state vector in which /// all known states are saved. /// - /// \param SampleHistorySize the (maximum) size of the sample history. - /// \param DABSize the size of a DAB. - /// \param DABHistorySize the (maximum) size of the DAB history. - /// \param FuzzyFunctionSampleMatches the - /// \param FuzzyFunctionSampleMismatches - /// \param FuzzyFunctionNumOfSamplesMatches - /// \param FuzzyFunctionNumOfSamplesMismatches - /// /// \return a pointer to the newly created signal state or NULL if no state /// could be created. SignalStatePtr createNewSignalState(void) noexcept { - SignalStatePtr S = new (std::nothrow) SignalState( + SignalStatePtr S(new SignalState( NextSignalStateID, SampleHistorySize, DABSize, DABHistorySize, FuzzyFunctionSampleMatches, FuzzyFunctionSampleMismatches, - FuzzyFunctionNumOfSamplesMatches, FuzzyFunctionNumOfSamplesMismatches); + FuzzyFunctionNumOfSamplesMatches, FuzzyFunctionNumOfSamplesMismatches, + FuzzyFunctionSignalIsDrifting, FuzzyFunctionSignalIsStable)); // @benedikt: todo: assert in history, which checks if push_back worked DetectedSignalStates.addEntry(S); return S; } #ifdef SIGNALSTATEDETECTORDEBUGMODE public: #else private: #endif // SIGNALSTATEDETECTORDEBUGMODE // @maxi is this a debug method or is it a method that will be used and // you simply want to have access to it in debug mode? // debug -> extend the preprocessor around the function // access -> remove the __debug from the name ( it is confusing) // if you want to have it marked as a debug method for auto // complete you can do something like this : // //#ifdef STATEDETECTORDEBUGMODE // public: // StateInfoPtr debug_detectState(INDATATYPE Sample) { // return detectState(Sample); // } //#endif // STATEDETECTORDEBUGMODE // private : // StateInfoPtr detectState(INDATATYPE Sample) { ... // /// 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). // TODO: return something const.. cannot remember exactly (ask benedikt) // // maybe: you are returning a pointer to the state info so who ever has that // pointer can actually change the information if you want to return only the // *current info* return a copy of the state info // like this: // // StateInfoPtr detectState__debug(INDATATYPE Sample) -> // StateInformation detectState__debug(INDATATYPE Sample) // // return CurrentState->stateInformation(); -> // return *(CurrentState->stateInformation()); - SignalStateInfoPtr detectSignalState__debug(INDATATYPE Sample) noexcept { + SignalStateInformation + detectSignalState__debug(INDATATYPE Sample) noexcept { if (!CurrentSignalState) { ASSERT(DetectedSignalStates.empty()); SignalStatePtr S = createNewSignalState(); CurrentSignalState = S; } else { CONFDATATYPE ConfidenceSampleMatchesSignalState = - CurrentSignalState->confSampleMatchesSignalState(Sample); + CurrentSignalState->confidenceSampleMatchesSignalState(Sample); CONFDATATYPE ConfidenceSampleMismatchesSignalState = - CurrentSignalState->confSampleMismatchesSignalState(Sample); + CurrentSignalState->confidenceSampleMismatchesSignalState(Sample); if (ConfidenceSampleMatchesSignalState > ConfidenceSampleMismatchesSignalState) { SignalStateHasChanged = false; } else { SignalStateHasChanged = true; - if (CurrentSignalState->signalStateInformation()->SignalStateIsValid) { + if (CurrentSignalState->signalStateInformation().SignalStateIsValid) { CurrentSignalState->leaveSignalState(); } else { //@benedikt: changed from vector to history. can i still do the next // line? - DetectedSignalStates.erase(std::find(DetectedSignalStates.begin(), - DetectedSignalStates.end(), - CurrentSignalState)); + 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) { - CONFDATATYPE ConfidenceSampleMatchesSignalState = - SavedSignalState->confSampleMatchesSignalState(Sample); - CONFDATATYPE ConfidenceSampleMismatchesSignalState = - SavedSignalState->confSampleMismatchesSignalState(Sample); + 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 SignalStateInfo = CurrentSignalState->insertSample(Sample); if (SignalStateInfo.SignalStateJustGotValid) { NextSignalStateID++; } return SignalStateInfo; } #ifdef SIGNALSTATEDETECTORDEBUGMODE public: #else private: #endif // SIGNALSTATEDETECTORDEBUGMODE /// 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 currentSignalStateInformation__debug(void) noexcept { if (CurrentSignalState) { return CurrentSignalState->signalStateInformation(); } else { return NULL; } } }; } // 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 f88a13d..705a08c 100644 --- a/include/rosa/support/math.hpp +++ b/include/rosa/support/math.hpp @@ -1,57 +1,131 @@ //===-- 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. /// //===----------------------------------------------------------------------===// #ifndef ROSA_SUPPORT_MATH_HPP #define ROSA_SUPPORT_MATH_HPP +#include #include +#include #include #include #include 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 ::value>> T nextRepresentableFloatingPoint(const T V) { return std::nextafter(V, std::numeric_limits::infinity()); } +// copied from the internet and adapted +// (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 +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; +} + +/// 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 +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; +} + +template +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