diff --git a/examples/agent-functionalities/Reliability-functionality/Reliability-functionality.cpp b/examples/agent-functionalities/Reliability-functionality/Reliability-functionality.cpp index 8c2f8f7..93aba31 100644 --- a/examples/agent-functionalities/Reliability-functionality/Reliability-functionality.cpp +++ b/examples/agent-functionalities/Reliability-functionality/Reliability-functionality.cpp @@ -1,247 +1,247 @@ //===- 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 Relianility Functionalities. /// //===----------------------------------------------------------------------===// #define Reliability_trace_level 5 #include "rosa/config/version.h" #include "rosa/support/log.h" #include "rosa/agent/CrossCombinator.h" #include "rosa/agent/RangeConfidence.hpp" #include "rosa/agent/ReliabilityConfidenceCombinator.h" #include #include using namespace rosa::agent; int main(void) { typedef double SensorValueType; typedef long StateType; typedef double ReliabilityType; 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)}})); std::unique_ptr> Reliability( new LinearFunction(1, -1.0 / 3)); std::unique_ptr> ReliabilitySlope( new LinearFunction(1, -1.0 / 3)); std::unique_ptr> TimeConfidence( new LinearFunction(1, -1.0 / 3)); auto lowlevel = new ReliabilityAndConfidenceCombinator(); 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 * ---------------------------------------------------------------- */ std::cout << "Testing the lowlevel component with static feedback telling it " "that the most lickely state is 2.\n"; for (int a = 0; a < 30; a++) std::cout << "a: " << a << "\n" << (lowlevel->feedback({{0, 0}, {1, 0.3}, {2, 0.8}}), - lowlevel->mostLikelySoreAndReliability(a)) + lowlevel->mostLikelyIdentifierAndReliability(a)) << "\n"; std::cout << "---------------------------------------------------------------" "---------------------------------\n"; std::cout << "------------------------------------High level " "Test---------------------------------------------\n"; std::cout << "Configured in a way that the Master thinks that both Sensors " "should have the same State.\n While feeding both the \"opposite\" " "values one acending the other decending from the maximum.\n"; 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)}})); std::unique_ptr> Reliability2( new LinearFunction(1, -1.0 / 9)); std::unique_ptr> ReliabilitySlope2( new LinearFunction(1, -1.0 / 9)); std::unique_ptr> TimeConfidence2( new LinearFunction(1, -1.0 / 9)); auto lowlevel2 = new ReliabilityAndConfidenceCombinator(); 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); CrossCombinator *highlevel = new CrossCombinator(); std::unique_ptr> func1(new PartialFunction( { {{0, 1}, std::make_shared>(1, 0)}, {{1, 2}, std::make_shared>(2, -1.0)}, }, 0)); highlevel->addCrossReliabilityProfile(0, 1, func1); highlevel->setCrossReliabilityCombinatorMethod( CrossCombinator::AVERAGE); highlevel->setCrossReliabilityParameter(1); highlevel->addStates(0, states); highlevel->addStates(1, states); for (int a = 0; a < 21; a++) { - auto out1 = lowlevel->mostLikelySoreAndReliability(a), - out2 = lowlevel2->mostLikelySoreAndReliability((int)21 - a); + auto out1 = lowlevel->mostLikelyIdentifierAndReliability(a), + out2 = lowlevel2->mostLikelyIdentifierAndReliability((int)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}); + tmp2.push_back({0, out1.Identifier, out1.Reliability}); + tmp2.push_back({1, out2.Identifier, 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}); + std::cout << "\t\t\t Identifier: " << z.Identifier << "\tRel: " << z.Reliability + << "\n"; tmp.push_back({z.Identifier,z.Reliability}); } */ for (auto z : q.second) { - std::cout << "\t\t\t score: " << z.score << "\tRel: " << z.Reliability + std::cout << "\t\t\t Identifier: " << z.Identifier << "\tRel: " << z.Reliability << "\n"; } if (q.first == 0) lowlevel->feedback(q.second); else lowlevel2->feedback(q.second); } } /* ----------------------------- Cleanup * --------------------------------------------------------------------- */ delete highlevel; delete lowlevel; delete lowlevel2; } \ No newline at end of file diff --git a/include/rosa/agent/CrossCombinator.h b/include/rosa/agent/CrossCombinator.h index 2dcb741..12596b7 100644 --- a/include/rosa/agent/CrossCombinator.h +++ b/include/rosa/agent/CrossCombinator.h @@ -1,539 +1,538 @@ //===-- 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 maybe 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/agent/ReliabilityConfidenceCombinator.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 { -template -std::vector> & -operator<<(std::vector> &me, - std::vector> Values) { +template +std::vector> & +operator<<(std::vector> &me, + std::vector> Values) { for (auto tmp : Values) { - std::pair tmp2; + std::pair tmp2; tmp2.first = std::get<0>(tmp); tmp2.second = std::get<1>(tmp); me.push_back(tmp2); } return me; } /// This is the Combinator class for cross reliabilities it has many functions /// with different purposes -/// \brief It takes the scores and reliabilities of all given ids and calculates +/// \brief It takes the Identifiers and reliabilities of all given ids and calculates /// the Reliability of them together. Also it can creates the feedback that is /// needed by the \c ReliabilityAndConfidenceCombinator, which is a kind of /// confidence. /// -/// \tparam StateType Datatype of the State ( Typically double or float) +/// \tparam IdentifierType Datatype of the State ( Typically double or float) /// \tparam ReliabilityType Datatype of the Reliability ( /// Typically long or int) /// /// \note This class is commonly in a master slave relationship as master with /// \c ReliabilityAndConfidenceCombinator. The \c operator()() combines the /// Reliability of all connected Slaves and uses that as its own Reliability /// also creates the feedback for the Slaves. /// /// \note more information about how the Reliability and feedback is /// created at \c operator()() , \c getCombinedCrossReliability() , \c /// getCombinedInputReliability() , \c getOutputReliability() [ this is the /// commonly used Reliability ], \c getCrossConfidence() [ this is the feedback /// for all Slaves ] -template class CrossCombinator { +template class CrossCombinator { public: - static_assert(std::is_arithmetic::value, - "HighLevel: StateType has to be an arithmetic type\n"); + static_assert(std::is_arithmetic::value, + "HighLevel: IdentifierType has to be an arithmetic type\n"); static_assert(std::is_arithmetic::value, "HighLevel: ReliabilityType has to be an arithmetic type\n"); // --------------------------------------------------------------------------- // useful definitions // --------------------------------------------------------------------------- /// typedef To shorten the writing. /// \c ConfOrRel - typedef ConfOrRel ConfOrRel; + using ConfOrRel = ConfOrRel; /// To shorten the writing. using Abstraction = - typename rosa::agent::Abstraction; + typename rosa::agent::Abstraction; /// The return type for the \c operator()() Method struct returnType { ReliabilityType CrossReliability; std::map> CrossConfidence; }; // ------------------------------------------------------------------------- // Relevant Methods // ------------------------------------------------------------------------- /// Calculates the Reliability and the CrossConfidences for each id for all /// of there states. /// /// \param Values It gets the States and Reliabilities of /// all connected Slaves inside a vector. /// /// \return it returns a struct \c returnType containing the \c /// getCombinedCrossReliability() and \c getCrossConfidence() returnType - operator()(std::vector> Values) { + operator()(std::vector> Values) { return {getOutputReliability(Values), getCrossConfidence(Values)}; } /// returns the combined via \c CombinedCrossRelCombinationMethod \c /// setCombinedCrossRelCombinationMethod() Cross Reliability for all ids \c /// CrossReliability() \param Values the used Values ReliabilityType getCombinedCrossReliability( - std::vector> Values) { + std::vector> Values) { ReliabilityType combinedCrossRel = -1; - std::vector> Agents; + std::vector> Agents; Agents << Values; for (auto Value : Values) { id_t id = std::get<0>(Value); - StateType sc = std::get<1>(Value); + IdentifierType sc = std::get<1>(Value); // calculate the cross reliability for this slave agent ReliabilityType realCrossReliabilityOfSlaveAgent = CrossReliability( {id, sc}, - Agents); // AVERAGE, MULTIPLICATION, CONJUNCTION (best to worst: - // AVERAGE = CONJUNCTION > MULTIPLICATION >> ) + Agents); if (combinedCrossRel != -1) combinedCrossRel = CombinedCrossRelCombinationMethod( combinedCrossRel, realCrossReliabilityOfSlaveAgent); else combinedCrossRel = realCrossReliabilityOfSlaveAgent; } return combinedCrossRel; } /// returns the combined via \c CombinedInputRelCombinationMethod \c /// setCombinedInputRelCombinationMethod() input relibility \param Values the /// used Values ReliabilityType getCombinedInputReliability( - std::vector> Values) { + std::vector> Values) { ReliabilityType combinedInputRel = -1; - std::vector> Agents; + std::vector> Agents; Agents << Values; for (auto Value : Values) { ReliabilityType rel = std::get<2>(Value); if (combinedInputRel != -1) combinedInputRel = CombinedInputRelCombinationMethod(combinedInputRel, rel); else combinedInputRel = rel; } return combinedInputRel; } /// returns the combination via \c OutputReliabilityCombinationMethod \c /// setOutputReliabilityCombinationMethod() of the Cross reliability and /// input reliability \param Values the used Values ReliabilityType getOutputReliability( - std::vector> Values) { + std::vector> Values) { return OutputReliabilityCombinationMethod( getCombinedInputReliability(Values), getCombinedCrossReliability(Values)); } /// retruns the crossConfidence for all ids \c CrossConfidence() /// \param Values the used Values std::map> getCrossConfidence( - std::vector> Values) { + std::vector> Values) { - std::vector> Agents; + std::vector> Agents; std::map> output; std::vector output_temporary; Agents << Values; for (auto Value : Values) { id_t id = std::get<0>(Value); output_temporary.clear(); - for (StateType thoScore : States[id]) { + for (IdentifierType thoIdentifier : States[id]) { ConfOrRel data; - data.score = thoScore; - data.Reliability = CrossConfidence(id, thoScore, Agents); + data.Identifier = thoIdentifier; + data.Reliability = CrossConfidence(id, thoIdentifier, Agents); output_temporary.push_back(data); } output.insert({id, output_temporary}); } return output; } /// Calculates the Cross Confidence /// \brief it uses the state represented by a numerical value and calculates /// the Confidence of a given agent( represented by there id ) for a given /// state in connection to all other given agents /// /// \note all combination of agents and there corresponding Cross Reliability /// function have to be specified ReliabilityType - CrossConfidence(id_t MainAgent, StateType TheoreticalValue, - std::vector> &SlaveAgents) { + CrossConfidence(id_t MainAgent, IdentifierType TheoreticalValue, + std::vector> &SlaveAgents) { ReliabilityType crossReliabiability; std::vector values; - for (std::pair SlaveAgent : SlaveAgents) { + 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 ReliabilityType crossReliabilityFromProfile = getCrossReliabilityFromProfile( MainAgent, SlaveAgent.first, AbsuluteValue(TheoreticalValue, SlaveAgent.second)); values.push_back( std::max(crossReliabiability, crossReliabilityFromProfile)); } return Method(values); } /// 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 corresponding Cross Reliability /// function have to be specified ReliabilityType - CrossReliability(std::pair &&MainAgent, - std::vector> &SlaveAgents) { + CrossReliability(std::pair &&MainAgent, + std::vector> &SlaveAgents) { ReliabilityType crossReliabiability; std::vector values; - for (std::pair SlaveAgent : SlaveAgents) { + 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 ReliabilityType crossReliabilityFromProfile = getCrossReliabilityFromProfile( MainAgent.first, SlaveAgent.first, AbsuluteValue(MainAgent.second, SlaveAgent.second)); values.push_back( std::max(crossReliabiability, crossReliabilityFromProfile)); } return Method(values); } // -------------------------------------------------------------------------- // Defining the class // -------------------------------------------------------------------------- /// adds a Cross Reliability Profile used to get the Reliability of the state /// difference /// \param idA The id of the one \c Agent ( idealy the id of \c Unit to make /// it absolutly unique ) /// /// \param idB The id of the other \c Agent /// /// \param Function A unique pointer to an \c Abstraction it would use the - /// difference in score for its input + /// difference in Identifier for its input void addCrossReliabilityProfile(id_t idA, id_t idB, std::unique_ptr &Function) { Abstraction *ptr = Function.release(); Functions.push_back({true, idA, idB, ptr}); } /// sets the cross reliability parameter void setCrossReliabilityParameter(ReliabilityType val) { crossReliabilityParameter = val; } /// This is the adder for the states /// \param id The id of the Agent of the states /// \param States id specific states. this will be copied So that if Slaves /// have different States they can be used correctly. /// \brief The States of all connected lowlevel Agents has to be known to be /// able to iterate over them - void addStates(id_t id, std::vector States) { + void addStates(id_t id, std::vector States) { this->States.insert({id, States}); } // ------------------------------------------------------------------------- // Combinator Settings // ------------------------------------------------------------------------- /// sets the used method to combine the values /// \param Meth The Function which defines the combination method. predef: \c /// CONJUNCTION() \c AVERAGE() \c DISJUNCTION() void setCrossReliabilityCombinatorMethod( ReliabilityType (*Meth)(std::vector values)) { Method = Meth; } /// sets the combination method for the combined cross reliability /// \param Meth the method which should be used. predef: \c /// CombinedCrossRelCombinationMethodMin() \c /// CombinedCrossRelCombinationMethodMax() \c /// CombinedCrossRelCombinationMethodMult() \c /// CombinedCrossRelCombinationMethodAverage() void setCombinedCrossRelCombinationMethod( ReliabilityType (*Meth)(ReliabilityType, ReliabilityType)) { CombinedCrossRelCombinationMethod = Meth; } /// sets the combined input rel method /// \param Meth the method which should be used predef: \c /// CombinedInputRelCombinationMethodMin() \c /// CombinedInputRelCombinationMethodMax() \c /// CombinedInputRelCombinationMethodMult() \c /// CombinedInputRelCombinationMethodAverage() void setCombinedInputRelCombinationMethod( ReliabilityType (*Meth)(ReliabilityType, ReliabilityType)) { CombinedInputRelCombinationMethod = Meth; } /// sets the used OutputReliabilityCombinationMethod /// \param Meth the used Method. predef: \c /// OutputReliabilityCombinationMethodMin() \c /// OutputReliabilityCombinationMethodMax() \c /// OutputReliabilityCombinationMethodMult() \c /// OutputReliabilityCombinationMethodAverage() void setOutputReliabilityCombinationMethod( ReliabilityType (*Meth)(ReliabilityType, ReliabilityType)) { OutputReliabilityCombinationMethod = Meth; } // ------------------------------------------------------------------------- // Predefined Functions // ------------------------------------------------------------------------- /// predefined combination method static ReliabilityType CONJUNCTION(std::vector values) { return *std::min_element(values.begin(), values.end()); } /// predefined combination method static ReliabilityType AVERAGE(std::vector values) { return std::accumulate(values.begin(), values.end(), 0.0) / values.size(); } /// predefined combination method static ReliabilityType DISJUNCTION(std::vector values) { return *std::max_element(values.begin(), values.end()); } /// predefined combination Method static ReliabilityType CombinedCrossRelCombinationMethodMin(ReliabilityType A, ReliabilityType B) { return std::min(A, B); } /// predefined combination Method static ReliabilityType CombinedCrossRelCombinationMethodMax(ReliabilityType A, ReliabilityType B) { return std::max(A, B); } /// predefined combination Method static ReliabilityType CombinedCrossRelCombinationMethodMult(ReliabilityType A, ReliabilityType B) { return A * B; } /// predefined combination Method static ReliabilityType CombinedCrossRelCombinationMethodAverage(ReliabilityType A, ReliabilityType B) { return (A + B) / 2; } /// predefined combination Method static ReliabilityType CombinedInputRelCombinationMethodMin(ReliabilityType A, ReliabilityType B) { return std::min(A, B); } /// predefined combination Method static ReliabilityType CombinedInputRelCombinationMethodMax(ReliabilityType A, ReliabilityType B) { return std::max(A, B); } /// predefined combination Method static ReliabilityType CombinedInputRelCombinationMethodMult(ReliabilityType A, ReliabilityType B) { return A * B; } /// predefined combination Method static ReliabilityType CombinedInputRelCombinationMethodAverage(ReliabilityType A, ReliabilityType B) { return (A + B) / 2; } /// predefined combination method static ReliabilityType OutputReliabilityCombinationMethodMin(ReliabilityType A, ReliabilityType B) { return std::min(A, B); } /// predefined combination method static ReliabilityType OutputReliabilityCombinationMethodMax(ReliabilityType A, ReliabilityType B) { return std::max(A, B); } /// predefined combination method static ReliabilityType OutputReliabilityCombinationMethodMult(ReliabilityType A, ReliabilityType B) { return A * B; } /// predefined combination method static ReliabilityType OutputReliabilityCombinationMethodAverage(ReliabilityType A, ReliabilityType B) { return (A + B) / 2; } // ------------------------------------------------------------------------- // Cleanup // ------------------------------------------------------------------------- ~CrossCombinator() { for (auto tmp : Functions) delete tmp.Funct; Functions.clear(); } // -------------------------------------------------------------------------- // Needed stuff and stored stuff // -------------------------------------------------------------------------- private: struct Functionblock { bool exists = false; id_t A; id_t B; Abstraction *Funct; }; - std::map> States; + std::map> States; /// From Maxi in his code defined as 1 can be changed by set ReliabilityType crossReliabilityParameter = 1; /// Stored Cross Reliability Functions std::vector Functions; /// Method which is used to combine the generated values ReliabilityType (*Method)(std::vector values) = AVERAGE; ReliabilityType (*CombinedCrossRelCombinationMethod)( ReliabilityType, ReliabilityType) = CombinedCrossRelCombinationMethodMin; ReliabilityType (*CombinedInputRelCombinationMethod)( ReliabilityType, ReliabilityType) = CombinedInputRelCombinationMethodMin; ReliabilityType (*OutputReliabilityCombinationMethod)( ReliabilityType, ReliabilityType) = OutputReliabilityCombinationMethodMin; //-------------------------------------------------------------------------------- // helper function /// evaluates the absolute Value of two values /// \note this is actually the absolute distance but to keep it somewhat /// conform with maxis code template Type_t AbsuluteValue(Type_t A, Type_t B) { return ((A - B) < 0) ? B - A : A - B; } /// very 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(); }; - /// evaluates the corresponding LinearFunction with the score difference + /// evaluates the corresponding LinearFunction with the Identifier 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 ReliabilityType getCrossReliabilityFromProfile(id_t nameA, id_t nameB, - StateType scoreDifference) { + IdentifierType IdentifierDifference) { 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); + return block.Funct->operator()(IdentifierDifference); } }; } // End namespace agent } // End namespace rosa #endif // ROSA_AGENT_CROSSRELIABILITY_H \ No newline at end of file diff --git a/include/rosa/agent/ReliabilityConfidenceCombinator.h b/include/rosa/agent/ReliabilityConfidenceCombinator.h index f6a5b57..1efb7dd 100644 --- a/include/rosa/agent/ReliabilityConfidenceCombinator.h +++ b/include/rosa/agent/ReliabilityConfidenceCombinator.h @@ -1,762 +1,758 @@ //===-- rosa/agent/ReliabilityConfidenceCombinator.h ------------*- C++ -*-===// // // The RoSA Framework // //===----------------------------------------------------------------------===// /// /// \file rosa/agent/ReliabilityConfidenceCombinator.h /// /// \author Daniel Schnoell (daniel.schnoell@tuwien.ac.at) /// /// \date 2019 /// /// \brief Definition of *ReliabilityConfidenceCombinator* *functionality*. /// /// \note based on Maximilian Goetzinger (maxgot@utu.fi) code in /// CAM_Dirty_include SA-EWS2_Version... inside Agent.cpp /// /// \note By defining and setting Reliability_trace_level it is possible to /// change the level to which it should be traced. \note All classes throw /// runtime errors if not all things are set /// /// \note should the Reliability be capped? /// /// //===----------------------------------------------------------------------===// - #ifndef ROSA_AGENT_ReliabilityConfidenceCombinator_H #define ROSA_AGENT_ReliabilityConfidenceCombinator_H #include "rosa/core/forward_declarations.h" // needed for id_t -#include "rosa/support/log.h" +#include "rosa/support/log.h" #include "rosa/agent/FunctionAbstractions.hpp" #include "rosa/agent/Functionality.h" #include "rosa/agent/RangeConfidence.hpp" #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 Reliability Combinator -/// more readable \tparam StateType The datatype of the States \tparam +/// more readable \tparam IdentifierType The datatype of the States \tparam /// ReliabilityType The datatype of the Reliability -template struct ConfOrRel { +template struct ConfOrRel { /// making both Template Arguments readable to make a few things easier - typedef StateType _StateType; + using _IdentifierType = IdentifierType; /// making both Template Arguments readable to make a few things easier - typedef ReliabilityType _ReliabilityType; + using _ReliabilityType = ReliabilityType; /// The actual place where the data is stored - StateType score; + IdentifierType Identifier; /// The actual place where the data is stored ReliabilityType Reliability; - ConfOrRel(StateType _score, ReliabilityType _Reliability) - : score(_score), Reliability(_Reliability){}; + ConfOrRel(IdentifierType _Identifier, ReliabilityType _Reliability) + : Identifier(_Identifier), 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 << " "; + out << "Identifier: " << c.Identifier << "\t Reliability: " << c.Reliability << " "; return out; } /// needed or it throws an clang diagnosic error - typedef std::map - map; // needed or it throws an clang diagnosic error + using map = std::map; // needed or it throws an + // clang diagnosic error /// Filles the vector with the data inside the map /// \param me The vector to be filled /// \param data The data wich is to be pushed into the vector friend std::vector &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 is to push the data inside a vector in a human readable way into the /// ostream \param out The ostream \param c The vector which is read friend std::ostream &operator<<(std::ostream &out, const std::vector &c) { std::size_t index = 0; for (ConfOrRel data : c) { out << index << " : " << data << "\n"; index++; } return out; } }; /// This calculates the minimum of the Reliabilities & the given value /// \param me The vector with the Reliabilities /// \param value The comparing value template 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 calculates the maximum of the Reliabilities & the given value /// \param me The vector with the Reliabilities /// \param value The comparing value template std::vector max(std::vector me, typename Conf::_ReliabilityType value) { static_assert(std::is_arithmetic::value); for (auto tmp : me) tmp.Reliability = std::max(tmp.Reliability, value); return me; } /// This calculates the average of the Reliabilities & the given value /// \param me The vector with the Reliabilities /// \param value The comparing value template std::vector average(std::vector me, typename Conf::_ReliabilityType value) { static_assert(std::is_arithmetic::value); for (auto tmp : me) tmp.Reliability = (tmp.Reliability + value) / 2; return me; } /// This calculates the average of the Reliabilities & the given value /// \param me The vector with the Reliabilities /// \param value The comparing value template std::vector mult(std::vector me, typename Conf::_ReliabilityType value) { static_assert(std::is_arithmetic::value); for (auto tmp : me) tmp.Reliability = tmp.Reliability * value / 2; return me; } -/// This average's the Reliabilities of the same Scores +/// This average's the Reliabilities of the same Identifiers template std::vector average(std::vector A, std::vector B) { static_assert(std::is_arithmetic::value); for (auto &tmp_me : A) for (auto &tmp_other : B) { - if (tmp_me.score == tmp_other.score) { + if (tmp_me.Identifier == tmp_other.Identifier) { tmp_me.Reliability = (tmp_me.Reliability + tmp_other.Reliability) / 2; } } return A; } -/// This min's the Reliabilities of the same Scores +/// This min's the Reliabilities of the same Identifiers template std::vector min(std::vector A, std::vector B) { static_assert(std::is_arithmetic::value); for (auto &tmp_me : A) for (auto &tmp_other : B) { - if (tmp_me.score == tmp_other.score) { + if (tmp_me.Identifier == tmp_other.Identifier) { tmp_me.Reliability = std::min(tmp_me.Reliability + tmp_other.Reliability); } } return A; } -/// This max's the Reliabilities of the same Scores +/// This max's the Reliabilities of the same Identifiers template std::vector max(std::vector A, std::vector B) { static_assert(std::is_arithmetic::value); for (auto &tmp_me : A) for (auto &tmp_other : B) { - if (tmp_me.score == tmp_other.score) { + if (tmp_me.Identifier == tmp_other.Identifier) { tmp_me.Reliability = std::max(tmp_me.Reliability + tmp_other.Reliability); } } return A; } -/// This mult's the Reliabilities of the same Scores +/// This mult's the Reliabilities of the same Identifiers template std::vector mult(std::vector A, std::vector B) { static_assert(std::is_arithmetic::value); for (auto &tmp_me : A) for (auto &tmp_other : B) { - if (tmp_me.score == tmp_other.score) { + if (tmp_me.Identifier == tmp_other.Identifier) { tmp_me.Reliability = tmp_me.Reliability * tmp_other.Reliability; } } return A; } /// This is the combinator for Reliability and confidences it takes the /// Sensor value, its "History" and feedback from \c /// CrossCombinator to calculate different Reliabilities. /// \tparam SensorValueType Datatype of the Sensor value ( Typically -/// double or float) \tparam StateType Datatype of the State ( Typically long or +/// double or float) \tparam IdentifierType Datatype of the State ( Typically long or /// int) /// \tparam ReliabilityType Datatype of the Reliability ( /// Typically double or float) /// /// \note more information about how it calculates /// the Reliabilities /// \verbatim ///---------------------------------------------------------------------------------- /// /// /// ->Reliability---> getInputReliability() /// | | /// | V -/// Sensor Value ---| PossibleScoreCombinationMethod -> next line +/// Sensor Value ---| PossibleIdentifierCombinationMethod -> next line /// | A | /// | | V -/// ->Confidence--- getPossibleScores() +/// ->Confidence--- getPossibleIdentifiers() /// ///----------------------------------------------------------------------------------- /// /// feedback /// | /// V /// ValuesFromMaster /// | -> History ---| /// V | V /// here -> FeedbackCombinatorMethod --------> HistoryCombinatorMethod->nextline /// | | /// V V -/// getpossibleScoresWithMasterFeedback() getPossibleScoresWithHistory() +/// getpossibleIdentifiersWithMasterFeedback() getPossibleIdentifiersWithHistory() /// ///---------------------------------------------------------------------------------- /// -/// here -> sort -> most likely -> mostLikelySoreAndReliability() +/// here -> sort -> most likely -> mostLikelyIdentifierAndReliability() /// /// --------------------------------------------------------------------------------- /// \endverbatim /// the mentioned methods are early outs so if two ore more of them are run in /// the same step they will be interpreted as different time steps /// 
 /// Default values for Combinators:
 ///	InputReliabilityCombinator		= combinationMin;
-///	PossibleScoreCombinationMethod	= PossibleScoreCombinationMethodMin;
+///	PossibleIdentifierCombinationMethod	= PossibleIdentifierCombinationMethodMin;
 /// FeedbackCombinatorMethod		= FeedbackCombinatorMethodAverage;
 /// HistoryCombinatorMethod			= HistoryCombinatorMethodMax;
 ///
/// /// /// -template class ReliabilityAndConfidenceCombinator { public: static_assert(std::is_arithmetic::value, "LowLevel: SensorValueType has to an arithmetic type\n"); - static_assert(std::is_arithmetic::value, - "LowLevel: StateType has to an arithmetic type\n"); + static_assert(std::is_arithmetic::value, + "LowLevel: IdentifierType has to an arithmetic type\n"); static_assert(std::is_arithmetic::value, "LowLevel: ReliabilityType has to an arithmetic type\n"); /// Typedef to shorten the writing. /// \c ConfOrRel - typedef ConfOrRel ConfOrRel; + using ConfOrRel = ConfOrRel; /// Calculates the input reliability by combining Reliability of the Sensor /// and the Slope Reliability \param SensorValue The sensor Value \note to set /// the combination method \c setInputReliabilityCombinator() auto getInputReliability(SensorValueType SensorValue) { auto inputReliability = getReliability(SensorValue, previousSensorValue, valueSetCounter); previousSensorValue = SensorValue; PreviousSensorValueExists = true; return inputReliability; } /// Calculates the Reliability /// \param SensorValue The current Values of the Sensor /// - /// \return Reliability and Score of the current SensorValue + /// \return Reliability and Identifier of the current SensorValue /// - ConfOrRel mostLikelySoreAndReliability(SensorValueType SensorValue) { + ConfOrRel mostLikelyIdentifierAndReliability(SensorValueType SensorValue) { #if Reliability_trace_level <= trace_outputs LOG_TRACE_STREAM << "\nTrace level is set to: " << Reliability_trace_level << "\n" << "Will trace: " << ((Reliability_trace_level == trace_outputs) ? "outputs" : (Reliability_trace_level == trace_vectors) ? "vectors" : (Reliability_trace_level == trace_everything) ? "everything" : "undefined") << trace_end; #endif - std::vector ActuallPossibleScores; - std::vector possibleScores; + std::vector ActuallPossibleIdentifiers; + std::vector possibleIdentifiers; ReliabilityType inputReliability = getInputReliability(SensorValue); #if Reliability_trace_level <= trace_vectors LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end; #endif - possibleScores << Confidence->operator()(SensorValue); + possibleIdentifiers << Confidence->operator()(SensorValue); - possibleScores = - PossibleScoreCombinationMethod(possibleScores, inputReliability); - possibleScores = FeedbackCombinatorMethod(possibleScores, ValuesFromMaster); + possibleIdentifiers = + PossibleIdentifierCombinationMethod(possibleIdentifiers, inputReliability); + possibleIdentifiers = FeedbackCombinatorMethod(possibleIdentifiers, ValuesFromMaster); - saveInHistory(possibleScores); + saveInHistory(possibleIdentifiers); #if Reliability_trace_level <= trace_vectors - LOG_TRACE_STREAM << "\nActuallPossibleScores:\n" - << possibleScores << trace_end; - LOG_TRACE_STREAM << "\npossibleScores:\n" << possibleScores << trace_end; + LOG_TRACE_STREAM << "\nActuallPossibleIdentifiers:\n" + << possibleIdentifiers << trace_end; + LOG_TRACE_STREAM << "\npossibleIdentifiers:\n" << possibleIdentifiers << trace_end; #endif - possibleScores.clear(); + possibleIdentifiers.clear(); - possibleScores = getAllPossibleScoresBasedOnHistory(); + possibleIdentifiers = getAllPossibleIdentifiersBasedOnHistory(); - std::sort(possibleScores.begin(), possibleScores.end(), + std::sort(possibleIdentifiers.begin(), possibleIdentifiers.end(), [](ConfOrRel A, ConfOrRel B) -> bool { return A.Reliability > B.Reliability; }); #if Reliability_trace_level <= trace_outputs - LOG_TRACE_STREAM << "\noutput lowlevel: " << possibleScores.at(0) + LOG_TRACE_STREAM << "\noutput lowlevel: " << possibleIdentifiers.at(0) << trace_end; #endif - return possibleScores.at(0); + return possibleIdentifiers.at(0); } - /// Calculates the possible Scores + /// Calculates the possible Identifiers /// \param SensorValue the Sensor Value /// \brief it combines the input reliability and the confidence of the Sensor. /// The use combination method can be set using \c - /// setPossibleScoreCombinationMethod() - auto getPossibleScores(SensorValueType SensorValue) { - std::vector possibleScores; + /// setPossibleIdentifierCombinationMethod() + auto getPossibleIdentifiers(SensorValueType SensorValue) { + std::vector possibleIdentifiers; ReliabilityType inputReliability = getInputReliability(SensorValue); - // get input rel() #if Reliability_trace_level <= trace_vectors LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end; #endif - possibleScores << Confidence->operator()(SensorValue); - possibleScores = - PossibleScoreCombinationMethod(possibleScores, inputReliability); - return possibleScores; + possibleIdentifiers << Confidence->operator()(SensorValue); + possibleIdentifiers = + PossibleIdentifierCombinationMethod(possibleIdentifiers, inputReliability); + return possibleIdentifiers; } /// return the Possible Values with the feedback in mind /// \param SensorValue The sensor Value /// \brief it combines the input reliability and the confidence of the Sensor. /// The combines them with FeedbackCombinatorMethod and returns the result. - auto getpossibleScoresWithMasterFeedback(SensorValueType SensorValue) { - std::vector possibleScores; + auto getpossibleIdentifiersWithMasterFeedback(SensorValueType SensorValue) { + std::vector possibleIdentifiers; ReliabilityType inputReliability = getInputReliability(SensorValue); - // get input rel() #if Reliability_trace_level <= trace_vectors LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end; #endif - possibleScores << Confidence->operator()(SensorValue); + possibleIdentifiers << Confidence->operator()(SensorValue); - possibleScores = - PossibleScoreCombinationMethod(possibleScores, inputReliability); + possibleIdentifiers = + PossibleIdentifierCombinationMethod(possibleIdentifiers, inputReliability); - possibleScores = FeedbackCombinatorMethod(possibleScores, ValuesFromMaster); - return possibleScores; + possibleIdentifiers = FeedbackCombinatorMethod(possibleIdentifiers, ValuesFromMaster); + return possibleIdentifiers; } - /// returns all possible Scores and Reliabilities with the History in mind + /// returns all possible Identifiers and Reliabilities with the History in mind /// \param SensorValue the Sensor value /// how this is done is described at the class. - auto getPossibleScoresWithHistory(SensorValueType SensorValue) { - std::vector ActuallPossibleScores; - std::vector possibleScores; + auto getPossibleIdentifiersWithHistory(SensorValueType SensorValue) { + std::vector ActuallPossibleIdentifiers; + std::vector possibleIdentifiers; ReliabilityType inputReliability = getInputReliability(SensorValue); - // get input rel() #if Reliability_trace_level <= trace_vectors LOG_TRACE_STREAM << "\ninput Rel: " << inputReliability << trace_end; #endif - possibleScores << Confidence->operator()(SensorValue); + possibleIdentifiers << Confidence->operator()(SensorValue); - possibleScores = - PossibleScoreCombinationMethod(possibleScores, inputReliability); - possibleScores = FeedbackCombinatorMethod(possibleScores, ValuesFromMaster); + possibleIdentifiers = + PossibleIdentifierCombinationMethod(possibleIdentifiers, inputReliability); + possibleIdentifiers = FeedbackCombinatorMethod(possibleIdentifiers, ValuesFromMaster); - saveInHistory(possibleScores); + saveInHistory(possibleIdentifiers); #if Reliability_trace_level <= trace_vectors - LOG_TRACE_STREAM << "\nActuallPossibleScores:\n" - << possibleScores << trace_end; - LOG_TRACE_STREAM << "\npossibleScores:\n" << possibleScores << trace_end; + LOG_TRACE_STREAM << "\nActuallPossibleIdentifiers:\n" + << possibleIdentifiers << trace_end; + LOG_TRACE_STREAM << "\npossibleIdentifiers:\n" << possibleIdentifiers << trace_end; #endif - possibleScores.clear(); + possibleIdentifiers.clear(); - return getAllPossibleScoresBasedOnHistory(); + return getAllPossibleIdentifiersBasedOnHistory(); } /// feedback for this functionality most commonly it comes from a Master Agent - /// \param ValuesFromMaster The Scores + Reliability for the feedback + /// \param ValuesFromMaster The Identifiers + Reliability for the feedback /// \brief This input kind of resembles a confidence but not - /// directly it more or less says: compared to the other Scores inside the - /// System these are the Scores with the Reliability that you have. + /// directly it more or less says: compared to the other Identifiers inside the + /// System these are the Identifiers with the Reliability that you have. void feedback(std::vector ValuesFromMaster) { this->ValuesFromMaster = ValuesFromMaster; } // // ----------------------Reliability and Confidence Function setters---------- // /// This is the setter for Confidence Function /// \param Confidence A pointer to the Functional for the \c Confidence of the /// Sensor value void setConfidenceFunction( - std::unique_ptr> &Confidence) { this->Confidence = std::move(Confidence); } /// This is the setter for Reliability Function /// \param Reliability A pointer to the Functional for the Reliability /// \brief The Reliability takes the current Sensor value and return the /// Reliability of the value. void setReliabilityFunction( std::unique_ptr> &Reliability) { this->Reliability = std::move(Reliability); } /// This is the setter for ReliabilitySlope Function /// \param ReliabilitySlope A pointer to the Functional for the /// ReliabilitySlope /// \brief The ReliabilitySlope takes the difference of the current Sensor /// Value to the last one and tells you how likely the change is. void setReliabilitySlopeFunction( std::unique_ptr> &ReliabilitySlope) { this->ReliabilitySlope = std::move(ReliabilitySlope); } /// This is the setter for TimeConfidence Function /// \param TimeConfidence A pointer to the Functional for the TimeConfidence /// \brief The time function takes the position in the History with greater /// equals older and return a Reliability of how "relevant" it is. void setTimeConfidenceFunction( std::unique_ptr> &TimeConfidence) { this->TimeConfidence = std::move(TimeConfidence); } /// This is the setter for all possible States /// \param states A vector containing all states /// \brief This exists even though \c State Type is an arithmetic Type because /// the states do not need to be "next" to each other ( ex. states={ 1 7 24 }) - void setStates(std::vector states) { this->States = states; } + void setStates(std::vector states) { this->States = states; } /// This sets the Maximum length of the History /// \param length The length void setHistoryLength(std::size_t length) { this->HistoryMaxSize = length; } /// This sets the Value set Counter /// \param ValueSetCounter the new Value /// \note This might actually be only an artifact. It is only used to get the /// reliability from the \c ReliabilitySlope [ ReliabilitySlope->operator()( /// (lastValue - actualValue) / (SensorValueType)valueSetCounter) ] void setValueSetCounter(unsigned int ValueSetCounter) { this->valueSetCounter = ValueSetCounter; } // // ----------------combinator setters----------------------------------------- // /// This sets the combination method used by the History /// \param Meth the method which should be used. predefined \c /// HistoryCombinatorMethodMin() \c HistoryCombinatorMethodMax() \c /// HistoryCombinatorMethodMult() \c HistoryCombinatorMethodAverage() void setHistoryCombinatorMethod(ReliabilityType (*Meth)(ReliabilityType, ReliabilityType)) { HistoryCombinatorMethod = Meth; } - /// sets the predefined method for the combination of the possible scores and + /// sets the predefined method for the combination of the possible Identifiers and /// the master \param Meth the method predefined ones are /// \c FeedbackCombinatorMethodAverage() \c FeedbackCombinatorMethodMin() \c /// FeedbackCombinatorMethodMax() \c FeedbackCombinatorMethodMult() void setFeedbackCombinatorMethod(std::vector (*Meth)( std::vector, std::vector)) { FeedbackCombinatorMethod = Meth; } - /// Sets the used combination method for Possible Scores + /// Sets the used combination method for Possible Identifiers /// \param Meth a Pointer for the used Method. Predefined methods \c - /// PossibleScoreCombinationMethodMin() \c PossibleScoreCombinationMethodMax() - /// \c PossibleScoreCombinationMethodAverage() - void setPossibleScoreCombinationMethod( + /// PossibleIdentifierCombinationMethodMin() \c PossibleIdentifierCombinationMethodMax() + /// \c PossibleIdentifierCombinationMethodAverage() + void setPossibleIdentifierCombinationMethod( std::vector (*Meth)(std::vector, ReliabilityType)) { - PossibleScoreCombinationMethod = Meth; + PossibleIdentifierCombinationMethod = Meth; } /// sets the input reliability combinator method /// \param method the to be used method /// \note there are predefined methods \c combinationMin() \c combinationMax() /// \c combinationAverage() void setInputReliabilityCombinator( ReliabilityType (*method)(ReliabilityType, ReliabilityType)) { InputReliabilityCombinator = method; } // // ----------------predefined combinators------------------------------------ // /// predefined Method static ReliabilityType HistoryCombinatorMethodMin(ReliabilityType A, ReliabilityType B) { return std::min(A, B); } /// predefined Method static ReliabilityType HistoryCombinatorMethodMax(ReliabilityType A, ReliabilityType B) { return std::max(A, B); } /// predefined Method static ReliabilityType HistoryCombinatorMethodMult(ReliabilityType A, ReliabilityType B) { return A * B; } /// predefined Method static ReliabilityType HistoryCombinatorMethodAverage(ReliabilityType A, ReliabilityType B) { return (A + B) / 2; } /// predefined method static std::vector FeedbackCombinatorMethodAverage(std::vector A, std::vector B) { return average(A, B); } /// predefined method static std::vector FeedbackCombinatorMethodMin(std::vector A, std::vector B) { return min(A, B); } /// predefined method static std::vector FeedbackCombinatorMethodMax(std::vector A, std::vector B) { return max(A, B); } /// predefined method static std::vector FeedbackCombinatorMethodMult(std::vector A, std::vector B) { return mult(A, B); } - /// Predefined combination method for possible Scores + /// Predefined combination method for possible Identifiers static std::vector - PossibleScoreCombinationMethodMin(std::vector A, + PossibleIdentifierCombinationMethodMin(std::vector A, ReliabilityType B) { return min(A, B); } - /// Predefined combination method for possible Scores + /// Predefined combination method for possible Identifiers static std::vector - PossibleScoreCombinationMethodMax(std::vector A, + PossibleIdentifierCombinationMethodMax(std::vector A, ReliabilityType B) { return max(A, B); } - /// Predefined combination method for possible Scores + /// Predefined combination method for possible Identifiers static std::vector - PossibleScoreCombinationMethodAverage(std::vector A, + PossibleIdentifierCombinationMethodAverage(std::vector A, ReliabilityType B) { return average(A, B); } - /// Predefined combination method for possible Scores + /// Predefined combination method for possible Identifiers static std::vector - PossibleScoreCombinationMethodMult(std::vector A, + PossibleIdentifierCombinationMethodMult(std::vector A, ReliabilityType B) { return mult(A, B); } /// The predefined min combinator method static ReliabilityType combinationMin(ReliabilityType A, ReliabilityType B) { return std::min(A, B); } /// The predefined max combinator method static ReliabilityType combinationMax(ReliabilityType A, ReliabilityType B) { return std::max(A, B); } /// The predefined average combinator method static ReliabilityType combinationAverage(ReliabilityType A, ReliabilityType B) { return (A + B) / 2; } /// The predefined average combinator method static ReliabilityType combinationMult(ReliabilityType A, ReliabilityType B) { return A * B; } private: std::vector> History; std::size_t HistoryMaxSize; std::vector ValuesFromMaster; SensorValueType previousSensorValue; unsigned int valueSetCounter; - std::vector States; + std::vector States; bool PreviousSensorValueExists = false; - std::unique_ptr> + std::unique_ptr> Confidence; std::unique_ptr> Reliability; std::unique_ptr> ReliabilitySlope; std::unique_ptr> TimeConfidence; // combination functions ReliabilityType (*InputReliabilityCombinator)( ReliabilityType, ReliabilityType) = combinationMin; - std::vector (*PossibleScoreCombinationMethod)( + std::vector (*PossibleIdentifierCombinationMethod)( std::vector, - ReliabilityType) = PossibleScoreCombinationMethodMin; + ReliabilityType) = PossibleIdentifierCombinationMethodMin; std::vector (*FeedbackCombinatorMethod)(std::vector, std::vector) = FeedbackCombinatorMethodAverage; ReliabilityType (*HistoryCombinatorMethod)(ReliabilityType, ReliabilityType) = HistoryCombinatorMethodMax; /*--------------------------------- needed Functions * -----------------------------------------------------*/ /// returns the Reliability /// \param actualValue The Value of the Sensor /// \param lastValue of the Sensor this is stored in the class /// \param valueSetCounter It has an effect on the difference of the current /// and last value This might not be needed anymore /// \brief it returns the combination the \c Reliability function and \c /// ReliabilitySlope if the previous value exists. if it doesn't it only /// returns the \c Reliability function value. ReliabilityType getReliability(SensorValueType actualValue, SensorValueType lastValue, unsigned int valueSetCounter) { ReliabilityType relAbs = Reliability->operator()(actualValue); if (PreviousSensorValueExists) { ReliabilityType relSlo = ReliabilitySlope->operator()( (lastValue - actualValue) / (SensorValueType)valueSetCounter); return InputReliabilityCombinator(relAbs, relSlo); } else return relAbs; } - /// adapts the possible Scores by checking the History and combines those + /// adapts the possible Identifiers by checking the History and combines those /// values. currently with max /// \brief combines the historic values with the \c TimeConfidence function - /// and returns the maximum Reliability for all Scores. - std::vector getAllPossibleScoresBasedOnHistory() { + /// and returns the maximum Reliability for all Identifiers. + std::vector getAllPossibleIdentifiersBasedOnHistory() { // iterate through all history entries std::size_t posInHistory = 0; - std::vector possibleScores; + std::vector possibleIdentifiers; for (auto pShE = History.begin(); pShE < History.end(); pShE++, posInHistory++) { - // iterate through all possible scores of each history entry + // iterate through all possible Identifiers of each history entry for (ConfOrRel &pSh : *pShE) { - StateType historyScore = pSh.score; + IdentifierType historyIdentifier = pSh.Identifier; ReliabilityType historyConf = pSh.Reliability; historyConf = historyConf * TimeConfidence->operator()(posInHistory); - bool foundScore = false; - for (ConfOrRel &pS : possibleScores) { + bool foundIdentifier = false; + for (ConfOrRel &pS : possibleIdentifiers) { - if (pS.score == historyScore) { + if (pS.Identifier == historyIdentifier) { pS.Reliability = HistoryCombinatorMethod(pS.Reliability, historyConf); - foundScore = true; + foundIdentifier = true; } } - if (foundScore == false) { + if (foundIdentifier == false) { - ConfOrRel possibleScore; - possibleScore.score = historyScore; - possibleScore.Reliability = historyConf; + ConfOrRel possibleIdentifier; + possibleIdentifier.Identifier = historyIdentifier; + possibleIdentifier.Reliability = historyConf; - possibleScores.push_back(possibleScore); + possibleIdentifiers.push_back(possibleIdentifier); } } } - return possibleScores; + return possibleIdentifiers; } - /// saves the Scores in the History - /// \brief It checks the incoming scores if any have a Reliability greater + /// saves the Identifiers in the History + /// \brief It checks the incoming Identifiers if any have a Reliability greater /// than 0.5 all of them get saved inside the History and then the /// History get shortened to the maximal length. It only saves the Value if /// the History is empty. /// - /// \param actualPossibleScores The Scores which should be saved + /// \param actualPossibleIdentifiers The Identifiers which should be saved /// /// \note Does the History really make sense if the values are to small it /// only stores something if it's empty and not if it isn't completely filled - void saveInHistory(std::vector actualPossibleScores) { + void saveInHistory(std::vector actualPossibleIdentifiers) { - // check if the reliability of at least one possible score is high enough + // check if the reliability of at least one possible Identifier is high enough bool atLeastOneRelIsHigh = false; - for (ConfOrRel pS : actualPossibleScores) { + for (ConfOrRel pS : actualPossibleIdentifiers) { if (pS.Reliability > 0.5) { atLeastOneRelIsHigh = true; } } - // save possible scores if at least one possible score is high enough (or if + // save possible Identifiers if at least one possible Identifier is high enough (or if // the history is empty) if (History.size() < 1 || atLeastOneRelIsHigh == true) { - History.insert(History.begin(), actualPossibleScores); + History.insert(History.begin(), actualPossibleIdentifiers); // if history size is higher than allowed, save oldest element while (History.size() > HistoryMaxSize) { - // delete possibleScoreHistory.back(); + // delete possibleIdentifierHistory.back(); History.pop_back(); } } } }; } // namespace agent } // namespace rosa #endif // !ROSA_AGENT_ReliabilityConfidenceCombinator_H