diff --git a/examples/agent-functionalities/Reliability-functionality.cpp b/examples/agent-functionalities/Reliability-functionality.cpp index 358edba..1ff0437 100644 --- a/examples/agent-functionalities/Reliability-functionality.cpp +++ b/examples/agent-functionalities/Reliability-functionality.cpp @@ -1,245 +1,244 @@ //===- examples/agent-functionalities/Reliability-functionality.cpp *C++-*-===// // // The RoSA Framework // //===----------------------------------------------------------------------===// /// /// \file examples/agent-functionalities/Reliability-functionality.cpp /// /// \author Daniel Schnoell (daniel.schnoell@tuwien.ac.at ) /// /// \date 2019 /// /// \brief A simple example on defining \c rosa::Agent instances using /// Relianility Functionalities. /// //===----------------------------------------------------------------------===// - +#define Reliability_trace_level 5 #include "rosa/config/version.h" #include "rosa/core/Agent.hpp" #include "rosa/core/MessagingSystem.hpp" #include "rosa/support/log.h" #include "rosa/support/terminal_colors.h" #include "rosa/agent/Reliability.h" #include "rosa/agent/RangeConfidence.hpp" #include "rosa/agent/CrossReliability.h" #include #include using namespace rosa::agent; int main(void) { typedef double SensorValueType; typedef long StateType; typedef double ReliabilityType; // defining Range confidence - auto Confidence = new RangeConfidence({ + std::unique_ptr> Confidence(new RangeConfidence({ {0, PartialFunction({ {{0, 3}, std::make_shared> (0, 1.0/3)}, {{3, 6}, std::make_shared> (1, 0)}, {{6, 9}, std::make_shared> (3.0, -1.0/3)}, },0)}, {1, PartialFunction({ {{6, 9}, std::make_shared> (-2, 1.0/3)}, {{9, 12}, std::make_shared> (1, 0)}, {{12, 15}, std::make_shared> (5, -1.0/3)}, },0)}, {2, PartialFunction({ {{12, 15}, std::make_shared> (-4, 1.0/3)}, {{15, 18}, std::make_shared> (1, 0)}, {{18, 21}, std::make_shared> (7, -1.0/3)}, },0)} - }); + })); - Abstraction* Reliability = new LinearFunction(1,-1.0/9); + std::unique_ptr> Reliability(new LinearFunction(1,-1.0/9)); - auto ReliabilitySlope = new LinearFunction(1, -1.0/9); + std::unique_ptr> ReliabilitySlope(new LinearFunction(1, -1.0/9)); - auto TimeConfidence = new LinearFunction(1, -1.0/9); + std::unique_ptr> TimeConfidence(new LinearFunction(1, -1.0/9)); auto lowlevel = new LowLevel (); std::vector states; states.push_back(0); states.push_back(1); states.push_back(2); lowlevel->setConfidenceFunction(Confidence); lowlevel->setReliabilityFunction(Reliability); lowlevel->setReliabilitySlopeFunction(ReliabilitySlope); lowlevel->setTimeConfidenceFunction(TimeConfidence); lowlevel->setStates(states); lowlevel->setHistoryLength(2); lowlevel->setValueSetCounter(1); /* ----------------------------- Do Something ---------------------------------------------------------------- */ for ( int a= 0 ; a <10 ; a++) std::cout <<"a: " << a << "\n" << (lowlevel->feedback({{0,0},{1,0.3},{2,0.5}}),lowlevel->operator()(a)) << "\n"; /* ----------------------------- Cleanup --------------------------------------------------------------------- */ std::cout << "------------------------------------------------------------------------------------------------\n"; std::cout << "------------------------------------High level Test---------------------------------------------\n"; - auto Confidence2 = new RangeConfidence({ + std::unique_ptr> Confidence2(new RangeConfidence({ {0, PartialFunction({ {{0, 3}, std::make_shared> (0, 1.0/3)}, {{3, 6}, std::make_shared> (1, 0)}, {{6, 9}, std::make_shared> (3.0, -1.0/3)}, },0)}, {1, PartialFunction({ {{6, 9}, std::make_shared> (-2, 1.0/3)}, {{9, 12}, std::make_shared> (1, 0)}, {{12, 15}, std::make_shared> (5, -1.0/3)}, },0)}, {2, PartialFunction({ {{12, 15}, std::make_shared> (-4, 1.0/3)}, {{15, 18}, std::make_shared> (1, 0)}, {{18, 21}, std::make_shared> (7, -1.0/3)}, },0)} - }); + })); - Abstraction* Reliability2 = new LinearFunction(1,-1.0/9); + std::unique_ptr> Reliability2( new LinearFunction(1,-1.0/9)); - auto ReliabilitySlope2 = new LinearFunction(1, -1.0/9); + std::unique_ptr< Abstraction> ReliabilitySlope2(new LinearFunction(1, -1.0/9)); - auto TimeConfidence2 = new LinearFunction(1, -1.0/9); + std::unique_ptr> TimeConfidence2(new LinearFunction(1, -1.0/9)); auto lowlevel2 = new LowLevel (); std::vector states2; states2.push_back(0); states2.push_back(1); states2.push_back(2); lowlevel2->setConfidenceFunction(Confidence2); lowlevel2->setReliabilityFunction(Reliability2); lowlevel2->setReliabilitySlopeFunction(ReliabilitySlope2); lowlevel2->setTimeConfidenceFunction(TimeConfidence2); lowlevel2->setStates(states2); lowlevel2->setHistoryLength(2); lowlevel2->setValueSetCounter(1); HighLevel* highlevel=new HighLevel(); - CrossReliability* CrossReliability1= new CrossReliability(); + std::unique_ptr> CrossReliability1(new CrossReliability()); Abstraction* func1=new PartialFunction({ {{0, 1}, std::make_shared> (1, 0)}, {{1,2}, std::make_shared> (2, -1.0)}, },0); CrossReliability1->addCrossReliabilityProfile(0,1,func1); CrossReliability1->setCrossReliabilityMethod(CrossReliability::AVERAGE); CrossReliability1->setCrossReliabilityParameter(1); - CrossConfidence* CrossConfidence1= new CrossConfidence(); + std::unique_ptr> CrossConfidence1( new CrossConfidence()); Abstraction* func2=new PartialFunction({ {{0, 1}, std::make_shared> (1, 0)}, {{1,2}, std::make_shared> (2, -1.0)}, },0); CrossConfidence1->addCrossReliabilityProfile(0,1,func2); CrossConfidence1->setCrossReliabilityMethod(CrossConfidence::AVERAGE); CrossConfidence1->setCrossReliabilityParameter(1); highlevel->setFunction(CrossConfidence1); highlevel->setFunction(CrossReliability1); - highlevel->MaximumState=2; highlevel->addStates(0,states); highlevel->addStates(1,states); for ( int a= 0 ; a <21 ; a++) { auto out1=lowlevel->operator()(a),out2=lowlevel2->operator()(21-a); std::cout << "s1: " << out1 << "\ns2:" << out2 << "\n"; std::vector> tmp2; tmp2.push_back({0,out1.score,out1.Reliability}); tmp2.push_back({1,out2.score,out2.Reliability}); auto out_o=highlevel->operator()(tmp2); std::cout << "it: " << a << "\t rel: " << out_o.CrossReliability << "\n"; std::cout << "\t subs:\n"; for (auto q:out_o.CrossConfidence) { std::cout<< "\t\t id:" << q.first << "\n"; /* for(auto z: q.second) { std::cout << "\t\t\t score: " << z.score << "\tRel: " << z.Reliability << "\n"; tmp.push_back({z.score,z.Reliability}); } */ for(auto z: q.second) { std::cout << "\t\t\t score: " << z.score << "\tRel: " << z.Reliability << "\n"; } if(q.first==0) lowlevel->feedback(q.second); else lowlevel2->feedback(q.second); } } delete lowlevel; delete lowlevel2; } \ No newline at end of file diff --git a/include/rosa/agent/CrossReliability.h b/include/rosa/agent/CrossReliability.h index af67744..220fda7 100644 --- a/include/rosa/agent/CrossReliability.h +++ b/include/rosa/agent/CrossReliability.h @@ -1,347 +1,349 @@ //===-- rosa/delux/CrossReliability.h ---------------------------*- C++ -*-===// // // The RoSA Framework // //===----------------------------------------------------------------------===// /// /// \file rosa/delux/CrossReliability.h /// /// \author Daniel Schnoell /// /// \date 2019 /// /// \brief /// /// \todo there is 1 exception that needs to be handled correctly. /// \note the default search function is extremely slow maby this could be done /// via template for storage class and the functions/methods to efficiently find /// the correct LinearFunction //===----------------------------------------------------------------------===// #ifndef ROSA_AGENT_CROSSRELIABILITY_H #define ROSA_AGENT_CROSSRELIABILITY_H #include "rosa/agent/Abstraction.hpp" #include "rosa/agent/Functionality.h" #include "rosa/core/forward_declarations.h" // needed for id_t #include "rosa/support/log.h" // needed for error "handling" // nedded headers #include #include //assert #include // for static methods #include #include namespace rosa { namespace agent { /// Calculates the Cross Reliability /// \brief it uses the state represented by a numerical value and calculates the /// Reliability of a given agent( represented by there id ) in connection to all /// other given agents /// /// \note all combination of agents and there coresponding Cross Reliability /// function have to be specified template class CrossReliability : public Abstraction { using Abstraction = typename rosa::agent::Abstraction; struct Functionblock { bool exists = false; id_t A; id_t B; Abstraction *Funct; }; /// From Maxi in his code defined as 1 can be changed by set Type crossReliabilityParameter = 1; /// Stored Cross Reliability Functions std::vector Functions; /// Method which is used to combine the generated values Type (*Method)(std::vector values) = AVERAGE; //-------------------------------------------------------------------------------- // helper function /// evalues the absolute distance between two values /// \note this is actually the absolute distance but to ceep it somewhat /// conform with maxis code template Type_t AbsuluteValue(Type_t A, Type_t B) { static_assert(std::is_arithmetic::value); return ((A - B) < 0) ? B - A : A - B; } /// verry inefficient searchFunction Functionblock (*searchFunction)(std::vector vect, const id_t nameA, const id_t nameB) = [](std::vector vect, const id_t nameA, const id_t nameB) -> Functionblock { for (Functionblock tmp : vect) { if (tmp.A == nameA && tmp.B == nameB) return tmp; if (tmp.A == nameB && tmp.B == nameA) return tmp; } return Functionblock(); }; /// evaluest the corisponding LinearFunction thith the score difference /// \param nameA these two parameters are the unique identifiers /// \param nameB these two parameters are the unique identifiers /// for the LinerFunction /// /// \note If the block nameA nameB doesn't exist it logs the error and returns /// 0 /// \note it doesn't matter if they are swapped Type getCrossReliabilityFromProfile(id_t nameA, id_t nameB, StateType scoreDifference) { Functionblock block = searchFunction(Functions, nameA, nameB); if (!block.exists) { LOG_ERROR(("CrossReliability: Block:" + std::to_string(nameA) + "," + std::to_string(nameB) + "doesn't exist returning 0")); return 0; } return block.Funct->operator()(scoreDifference); } public: /// adds a Cross Reliability Profile used to get the Reliability of the state /// difference void addCrossReliabilityProfile(id_t idA, id_t idB, Abstraction *Function) { Functions.push_back({true, idA, idB, Function}); } /// sets the cross reliability parameter void setCrossReliabilityParameter(Type val) { crossReliabilityParameter = val; } /// sets the used method to combine the values void setCrossReliabilityMethod(Type (*Meth)(std::vector values)) { Method = Meth; } CrossReliability():Abstraction(0) {} - ~CrossReliability() { for (auto tmp : Functions) delete tmp.Funct; Functions.clear(); } /// Calculets the CrossReliability /// \note both Main and Slaveagents are represented by there data and an /// unique identifier /// /// \param MainAgent defines the value pair around which the Cross Reliability /// is calculated /// \param SlaveAgents defines all value pairs of the connected Agents it /// doesn't matter if Main agent exists inside this vector Type operator()(std::pair &&MainAgent, - std::vector> &&SlaveAgents); + std::vector> &SlaveAgents); /// predefined combination method static Type CONJUNCTION(std::vector values) { static_assert(std::is_arithmetic::value); // sanitny check return *std::min_element(values.begin(), values.end()); } /// predefined combination method static Type AVERAGE(std::vector values) { static_assert(std::is_arithmetic::value); // sanitny check return std::accumulate(values.begin(), values.end(), 0.0) / values.size(); } /// predefined combination method static Type DISJUNCTION(std::vector values) { static_assert(std::is_arithmetic::value); // sanitny check return *std::max_element(values.begin(), values.end()); } }; template inline Type CrossReliability:: operator()(std::pair &&MainAgent, - std::vector> &&SlaveAgents) { + std::vector> &SlaveAgents) { static_assert(std::is_arithmetic::value); // sanitny check static_assert(std::is_arithmetic::value); // sanitny check Type crossReliabiability; std::vector values; for (std::pair SlaveAgent : SlaveAgents) { if (SlaveAgent.first == MainAgent.first) continue; if (MainAgent.second == SlaveAgent.second) crossReliabiability = 1; else crossReliabiability = 1 / (crossReliabilityParameter * AbsuluteValue(MainAgent.second, SlaveAgent.second)); // profile reliability Type crossReliabilityFromProfile = getCrossReliabilityFromProfile( MainAgent.first, SlaveAgent.first, AbsuluteValue(MainAgent.second, SlaveAgent.second)); values.push_back( std::max(crossReliabiability, crossReliabilityFromProfile)); } return Method(values); } /// Calculates the Cross Confidence /// \brief It uses the a theoretical state represented by a numerical value and /// calculates the Reliability of a given agent( represented by there id ) in /// connection to all other given agents this can be used to get a Confidence of /// the current state /// /// \note all combination of agents and there coresponding Cross Reliability /// function have to be specified template class CrossConfidence : public Abstraction { using Abstraction = typename rosa::agent::Abstraction; struct Functionblock { bool exists = false; id_t A; id_t B; Abstraction *Funct; }; /// From Maxi in his code defined as 1 can be changed by set Type crossReliabilityParameter = 1; /// Stored Cross Reliability Functions std::vector Functions; /// Method which is used to combine the generated values Type (*Method)(std::vector values) = AVERAGE; //-------------------------------------------------------------------------------- // helper function /// evalues the absolute distance between two values /// \note this is actually the absolute distance but to ceep it somewhat /// conform with maxis code template Type_t AbsuluteValue(Type_t A, Type_t B) { static_assert(std::is_arithmetic::value); return ((A - B) < 0) ? B - A : A - B; } /// verry inefficient searchFunction Functionblock (*searchFunction)(std::vector vect, const id_t nameA, const id_t nameB) = [](std::vector vect, const id_t nameA, const id_t nameB) -> Functionblock { for (Functionblock tmp : vect) { if (tmp.A == nameA && tmp.B == nameB) return tmp; if (tmp.A == nameB && tmp.B == nameA) return tmp; } return Functionblock(); }; /// evaluest the corisponding LinearFunction thith the score difference /// \param nameA these two parameters are the unique identifiers /// \param nameB these two parameters are the unique identifiers /// for the LinerFunction /// /// \note it doesn't matter if they are swapped Type getCrossReliabilityFromProfile(id_t nameA, id_t nameB, StateType scoreDifference) { Functionblock block = searchFunction(Functions, nameA, nameB); if (!block.exists) { LOG_ERROR(("CrossReliability: Block:" + std::to_string(nameA) + "," + std::to_string(nameB) + "doesn't exist returning 0")); return 0; } return block.Funct->operator()(scoreDifference); } public: /// adds a Cross Reliability Profile used to get the Reliability of the state /// difference void addCrossReliabilityProfile(id_t idA, id_t idB, Abstraction *Function) { Functions.push_back({true, idA, idB, Function}); } /// sets the cross reliability parameter void setCrossReliabilityParameter(Type val) { crossReliabilityParameter = val; } /// sets the used method to combine the values void setCrossReliabilityMethod(Type (*Meth)(std::vector values)) { Method = Meth; } + CrossConfidence():Abstraction(0){} + + ~CrossConfidence() { for (auto tmp : Functions) delete tmp.Funct; Functions.clear(); } Type operator()(id_t MainAgent, StateType TheoreticalValue, std::vector> &SlaveAgents); /// predefined combination method static Type CONJUNCTION(std::vector values) { static_assert(std::is_arithmetic::value); // sanitny check return *std::min_element(values.begin(), values.end()); } /// predefined combination method static Type AVERAGE(std::vector values) { static_assert(std::is_arithmetic::value); // sanitny check return std::accumulate(values.begin(), values.end(), 0.0) / values.size(); } /// predefined combination method static Type DISJUNCTION(std::vector values) { static_assert(std::is_arithmetic::value); // sanitny check return *std::max_element(values.begin(), values.end()); } }; template inline Type CrossConfidence:: operator()(id_t MainAgent, StateType TheoreticalValue, std::vector> &SlaveAgents) { static_assert(std::is_arithmetic::value); // sanitny check static_assert(std::is_arithmetic::value); // sanitny check Type crossReliabiability; std::vector values; for (std::pair SlaveAgent : SlaveAgents) { if (SlaveAgent.first == MainAgent) continue; if (TheoreticalValue == SlaveAgent.second) crossReliabiability = 1; else crossReliabiability = 1 / (crossReliabilityParameter * AbsuluteValue(TheoreticalValue, SlaveAgent.second)); // profile reliability Type crossReliabilityFromProfile = getCrossReliabilityFromProfile( MainAgent, SlaveAgent.first, AbsuluteValue(TheoreticalValue, SlaveAgent.second)); values.push_back( std::max(crossReliabiability, crossReliabilityFromProfile)); } return Method(values); } } // End namespace agent } // End namespace rosa #endif // ROSA_AGENT_CROSSRELIABILITY_H \ No newline at end of file diff --git a/include/rosa/agent/Reliability.h b/include/rosa/agent/Reliability.h index 94aaea3..06c0354 100644 --- a/include/rosa/agent/Reliability.h +++ b/include/rosa/agent/Reliability.h @@ -1,500 +1,489 @@ //===-- rosa/agent/Reliability.h --------------------------------*- C++ -*-===// // // The RoSA Framework // //===----------------------------------------------------------------------===// /// /// \file rosa/agent/Reliability.h /// /// \author Daniel Schnoell (danielschnoell@tuwien.ac.at) /// /// \date 2019 /// /// \brief Definition of *reliability* *functionality*. /// /// \note All classes throw runtime errors if not all things are set /// //===----------------------------------------------------------------------===// #ifndef ROSA_AGENT_RELIABILITY_H #define ROSA_AGENT_RELIABILITY_H #include "rosa/agent/FunctionAbstractions.hpp" #include "rosa/agent/Functionality.h" #include "rosa/agent/RangeConfidence.hpp" #include "rosa/agent/CrossReliability.h" #include #include #include /// 0 everything /// 1 vectors /// 2 outputs #define trace_everything 0 #define trace_vectors 1 #define trace_outputs 2 #ifndef Reliability_trace_level #define Reliability_trace_level 0 #endif #define trace_end "\n\n\n" namespace rosa { namespace agent { + /// This is a struct with a few methods that make lowlevel Reliability more readable + /// \tparam StateType The datatype of the States + /// \tparam ReliabilityType The datatype of the Reliability template< typename StateType,typename ReliabilityType> struct ConfOrRel { typedef StateType _StateType; typedef ReliabilityType _ReliabilityType; StateType score; ReliabilityType Reliability; ConfOrRel(StateType _score, ReliabilityType _Reliability) :score(_score), Reliability(_Reliability) {}; ConfOrRel() {}; + /// Pushes the Data in a Human readable form + /// \param out The stream where it is written to + /// \param c The struct itself friend std::ostream& operator << (std::ostream& out, const ConfOrRel& c) { out << "Score: " << c.score << "\t Reliability: " << c.Reliability << " "; return out; } typedef std::map map; // needed or it throws an clang diagnosic erroor + /// Filles the vector with the data inside the map + /// \param me The vector to be filled + /// \param data The data wich is to be pushed into the vector friend std::vector& operator<<(std::vector &me, map&& data) { for (auto tmp : data) { me.push_back(ConfOrRel(tmp.first, tmp.second)); #if Reliability_trace_level<=trace_everything LOG_TRACE_STREAM << "\n" << ConfOrRel(tmp.first, tmp.second) << trace_end; #endif } return me; } + /// This adds the Reliabilities of the same Scores + /// \param me The vector to wich is written to + /// \param other The other data vector friend std::vector operator+=(std::vector &me, std::vector other) { static_assert(std::is_arithmetic::value); for (auto tmp_me:me) for (auto tmp_other:other) { if (tmp_me.score == tmp_other.score) { tmp_me.Reliability =tmp_me.Reliability + tmp_other.Reliability; } } return me; } + /// This is to push the data inside a vector in a humanreadable way into the ostream + /// \param out The ostream + /// \param c The vector which is read friend std::ostream& operator << (std::ostream& out, const std::vector& c) { std::size_t index=0; for(ConfOrRel data:c) { out << index << " : " << data << "\n"; index++; } return out; } }; + /// This calculates the minimum of the Reliabilities & the given value + /// \param me The vector with the Reliabilites + /// \param value The comparing value template - std::vector& min(std::vector &me,typename Conf::_ReliabilityType value ) + std::vector min(std::vector me,typename Conf::_ReliabilityType value ) { static_assert(std::is_arithmetic::value); for (auto tmp:me) tmp.Reliability = std::min(tmp.Reliability,value); return me; } /// This is the Reliability Functionality for a low level Agent /// \tparam SensorValueType Datatype of the Sensor value ( Typically double or float) /// \tparam StateType Datatype of the State ( Typically long or int) /// \tparam ReliabilityType Datatype of the Reliability ( Typically double or float) /// /// use the () operator to get the reliability and feed the information from the master back to this /// \note all pointer for the functionalities will be deleted when this is object ist destroyed template class LowLevel { public: typedef ConfOrRel ConfOrRel; /// Calculates the Conf/ Reliability /// \param SensorValue The current Values of the Sensor /// /// \return Reliability of the current Value ConfOrRel operator()(SensorValueType SensorValue) { #if Reliability_trace_level<=trace_outputs LOG_TRACE_STREAM << "\nTrace level is set to: " << Reliability_trace_level <<"\n" << "Will trace: " << ((Reliability_trace_level==trace_outputs)? "outputs" : (Reliability_trace_level==trace_vectors)? "vectors" : (Reliability_trace_level==trace_everything)? "everything" : "undefined" ) < ActuallPossibleScores; std::vector possibleScores; ReliabilityType inputReliability =getRelibility(SensorValue, previousSensorValue, valueSetCounter); #if Reliability_trace_level<=trace_vectors LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end; #endif ActuallPossibleScores << Confidence->operator()(SensorValue); ActuallPossibleScores = min(ActuallPossibleScores,inputReliability); ActuallPossibleScores += ValuesFromMaster; saveInHistory(ActuallPossibleScores); possibleScores = getAllPossibleScoresBasedOnHistory(possibleScores); std::sort(possibleScores.begin(), possibleScores.end(), [](ConfOrRel A, ConfOrRel B)-> bool { static_assert(std::is_arithmetic::value); return A.Reliability > B.Reliability; } ); previousSensorValue = SensorValue; PreviousSensorValueExists = true; #if Reliability_trace_level<=trace_vectors LOG_TRACE_STREAM << "\nActuallPossibleScores:\n" << ActuallPossibleScores << trace_end; LOG_TRACE_STREAM << "\npossibleScores:\n" << possibleScores << trace_end; #endif #if Reliability_trace_level<=trace_outputs LOG_TRACE_STREAM << "\noutput lowlevel: " << possibleScores.at(0) << trace_end; #endif return possibleScores.at(0); } /// Needed feedback from the Master /// \param ValuesFromMaster The Scores + Reliability from the Master for this Agent void feedback(std::vector ValuesFromMaster) { this->ValuesFromMaster = ValuesFromMaster; } /// This is the setter for Confidence Function /// \param Confidence A pointer to the Functional for the Confidence - void setConfidenceFunction(RangeConfidence* Confidence) + void setConfidenceFunction(std::unique_ptr> &Confidence) { - this->Confidence = Confidence; + this->Confidence = std::move(Confidence); } /// This is the setter for Reliability Function /// \param Reliability A pointer to the Functional for the Reliability - void setReliabilityFunction(Abstraction* Reliability) + void setReliabilityFunction(std::unique_ptr> &Reliability) { - this->Reliability = Reliability; + this->Reliability = std::move(Reliability); } /// This is the setter for ReliabilitySlope Function /// \param ReliabilitySlope A pointer to the Functional for the ReliabilitySlope - void setReliabilitySlopeFunction(Abstraction* ReliabilitySlope) + void setReliabilitySlopeFunction(std::unique_ptr> &ReliabilitySlope) { - this->ReliabilitySlope = ReliabilitySlope; + this->ReliabilitySlope = std::move(ReliabilitySlope); } /// This is the setter for TimeConfidence Function /// \param TimeConfidence A pointer to the Functional for the TimeConfidence - void setTimeConfidenceFunction(Abstraction* TimeConfidence) + void setTimeConfidenceFunction(std::unique_ptr> &TimeConfidence) { - this->TimeConfidence = TimeConfidence; + this->TimeConfidence = std::move(TimeConfidence); } /// This is the setter for all possible States /// \param states A vertor for all states void setStates(std::vector states) { this->States=states; } /// This sets the Maximum length of the Histpry /// \param length The length void setHistoryLength(std::size_t length) { this->HistoryMaxSize=length; } /// This sets the Value set Counter /// \param ValueSetCounter the new Value void setValueSetCounter(unsigned int ValueSetCounter) { this->valueSetCounter=ValueSetCounter; } - /// deletes all given pointers - ~LowLevel() - { - delete Confidence; - Confidence = nullptr; - - delete Reliability; - Reliability = nullptr; - - delete ReliabilitySlope; - ReliabilitySlope = nullptr; - - delete TimeConfidence; - TimeConfidence = nullptr; - } - private: std::vector> History; std::size_t HistoryMaxSize; std::vector ValuesFromMaster; SensorValueType previousSensorValue; unsigned int valueSetCounter; std::vector States; bool PreviousSensorValueExists = false; - RangeConfidence* Confidence = nullptr; - Abstraction* Reliability = nullptr; - Abstraction* ReliabilitySlope = nullptr; - Abstraction* TimeConfidence = nullptr; + std::unique_ptr> Confidence; + std::unique_ptr> Reliability; + std::unique_ptr> ReliabilitySlope; + std::unique_ptr> TimeConfidence; /*--------------------------------- needed Funktions -----------------------------------------------------*/ /// returns the Reliability /// \param actualValue The Value of the Sensor /// \param lastValue of the Sensor this is stored in the class - /// \param valueSetCounter Todo + /// \param valueSetCounter It has an effect on the difference of the current and last value This might not be needed anymore ReliabilityType getRelibility(SensorValueType actualValue, SensorValueType lastValue, unsigned int valueSetCounter) { static_assert(std::is_arithmetic::value); ReliabilityType relAbs = Reliability->operator()(actualValue); if (PreviousSensorValueExists) { ReliabilityType relSlo = ReliabilitySlope->operator()((lastValue - actualValue) / (SensorValueType)valueSetCounter); // calculate signal input reliability // NOTE: options would be multiply, average, AND (best to worst: // average = AND > multiply) rel = relAbs * relSlo; rel = (relAbs + // relSlo)/2; return std::min(relAbs, relSlo); } else return relAbs; } /// adabts the possible Scores by checking the History and combines those values currently with max /// \param possibleScores This is returned from the Master std::vector getAllPossibleScoresBasedOnHistory(std::vector possibleScores) { //iterate through all history entries std::size_t posInHistory = 0; for (auto pShE = History.begin(); pShE < History.end(); pShE++, posInHistory++) { //iterate through all possible scores of each history entry for (ConfOrRel& pSh : *pShE) { - //printf("a3\n"); - StateType historyScore = pSh.score; ReliabilityType historyConf = pSh.Reliability; //combine each history score with the confidence of time //NOTE: multiplication, AND, or average would be alternatives (best to worst: multiplication = AND = average) historyConf = historyConf * TimeConfidence->operator()(posInHistory); //historyConf = (historyConf + TimeConfidence(posInHistory)) / 2; //historyConf = std::min(historyConf, TimeConfidence(posInHistory)); - //printf("a4\n"); bool foundScore = false; for (ConfOrRel& pS : possibleScores) { if (pS.score == historyScore) { //calculate confidence for score //NOTE: multiplication, AND, or average would be alternatives (best to worst: AND >> average = multiplication ) //pS->confOrRel = pS->confOrRel * historyConf; //pS->confOrRel = (pS->confOrRel + historyConf) / 2; pS.Reliability = std::max(pS.Reliability, historyConf); foundScore = true; } } if (foundScore == false) { ConfOrRel possibleScore; possibleScore.score = historyScore; possibleScore.Reliability = historyConf; possibleScores.push_back(possibleScore); } } } return possibleScores; } /// saves the Scores in the History /// \param actualPossibleScores The Scores which should be saved + /// + /// \note Does the History realy make sence if the values are to smal it only stores something if its empty and not if it isn't completly filled void saveInHistory(std::vector actualPossibleScores) { //check if the reliability of at least one possible score is high enough bool atLeastOneRelIsHigh = false; for (ConfOrRel pS : actualPossibleScores) { if (pS.Reliability > 0.5) { atLeastOneRelIsHigh = true; } } //save possible scores if at least one possible score is high enough (or if the history is empty) if (History.size() < 1 || atLeastOneRelIsHigh == true) { History.insert(History.begin(),actualPossibleScores); //if history size is higher than allowed, savo oldest element while (History.size() > HistoryMaxSize) { //delete possibleScoreHistory.back(); History.pop_back(); } } } }; /// This is the Reliability Functionality for the Highlevel Agent /// \tparam StateType Datatype of the State ( Typically double or float) /// \tparam ReliabilityType Datatype of the Reliability ( Typically long or int) /// /// use the () operator to calculate the Reliability and all cross confidences for all slaves - /// \note all pouinter to Funcionalities get deleted upon termitation of the object + /// \note all pointer to Funcionalities get deleted upon deletion of the object template class HighLevel { public: typedef ConfOrRel ConfOrRel; struct returnType { ReliabilityType CrossReliability; std::map> CrossConfidence; }; - StateType MaximumState; - returnType operator()(std::vector> &Values) { StateType EWS = 0; ReliabilityType combinedInputRel = 1; ReliabilityType combinedCrossRel = 1; ReliabilityType outputReliability; std::vector> Agents; std::map> output; std::vector output_temporary; for (auto tmp : Values) { std::pair tmp2; tmp2.first = std::get<0>(tmp); tmp2.second = std::get<1>(tmp); Agents.push_back(tmp2); } for (auto Value : Values) { id_t id = std::get<0>(Value); StateType sc = std::get<1>(Value); ReliabilityType rel = std::get<2>(Value); EWS = EWS + sc; combinedInputRel = std::min(combinedInputRel, rel); //calculate the cross reliability for this slave agent ReliabilityType realCrossReliabilityOfSlaveAgent = CrossReliability->operator()({id,sc }, Agents); //AVERAGE, MULTIPLICATION, CONJUNCTION (best to worst: AVERAGE = CONJUNCTION > MULTIPLICATION >> ) output_temporary.clear(); for (StateType thoScore:States[id]) { //calculate the cross reliability for this slave agent ConfOrRel data; data.score = thoScore; data.Reliability = CrossConfidence->operator()(id, thoScore, Agents); output_temporary.push_back(data); } output.insert({ std::get<0>(Value),output_temporary }); combinedCrossRel = std::min(combinedCrossRel, realCrossReliabilityOfSlaveAgent); } //combine cross reliabilites and input reliabilites of all slave agents //NOTE: options would be multiply, average, AND (best to worst: ) //outputReliability = combinedInputRel * combinedCrossRel; //outputReliability = (combinedInputRel + combinedCrossRel) / 2; outputReliability = std::min(combinedInputRel, combinedCrossRel); return { outputReliability,output }; } /// This is the setter for CrossReliability Function /// \param CrossReliability A pointer to the Functional for the CrossReliability - void setFunction(CrossReliability* CrossReliability) + void setFunction(std::unique_ptr> &CrossReliability) { - this->CrossReliability = CrossReliability; + this->CrossReliability = std::move(CrossReliability); } /// This is the setter for CrossConfidence Function /// \param CrossConfidence A pointer to the Functional for the CrossConfidence - void setFunction(CrossConfidence * CrossConfidence) + void setFunction(std::unique_ptr> &CrossConfidence) { - this->CrossConfidence = CrossConfidence; + this->CrossConfidence = std::move(CrossConfidence); } /// This the adder for the states /// \param States id spezific states this will be copied void addStates( id_t id, std::vector States) { this->States.insert({id,States}); } - - /// deletes all given pointers - ~HighLevel() - { - delete CrossReliability; - CrossConfidence = nullptr; - delete CrossConfidence; - CrossConfidence = nullptr; - } - private: - CrossReliability* CrossReliability = nullptr; - CrossConfidence * CrossConfidence = nullptr; + std::unique_ptr> CrossReliability; + std::unique_ptr> CrossConfidence ; std::map> States; }; } // namespace agent }// namespace rosa #endif // !ROSA_AGENT_RELIABILITY_H