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80 lines
8.4 KiB
80 lines
8.4 KiB
#ifndef STORM_MODELCHECKER_SPARSE_MARKOVAUTOMATON_CSL_MODELCHECKER_HELPER_H_
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#define STORM_MODELCHECKER_SPARSE_MARKOVAUTOMATON_CSL_MODELCHECKER_HELPER_H_
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#include "storm/storage/BitVector.h"
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#include "storm/storage/MaximalEndComponent.h"
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#include "storm/solver/OptimizationDirection.h"
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#include "storm/solver/MinMaxLinearEquationSolver.h"
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#include "storm/utility/NumberTraits.h"
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namespace storm {
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namespace modelchecker {
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namespace helper {
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class SparseMarkovAutomatonCslHelper {
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public:
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template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
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static std::vector<ValueType> computeBoundedUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::pair<double, double> const& boundsPair, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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template <typename ValueType, typename std::enable_if<!storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
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static std::vector<ValueType> computeBoundedUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::pair<double, double> const& boundsPair, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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template <typename ValueType>
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static std::vector<ValueType> computeUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, storm::storage::BitVector const& phiStates, storm::storage::BitVector const& psiStates, bool qualitative, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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template <typename ValueType, typename RewardModelType>
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static std::vector<ValueType> computeReachabilityRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, RewardModelType const& rewardModel, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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template <typename ValueType>
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static std::vector<ValueType> computeLongRunAverageProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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template <typename ValueType>
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static std::vector<ValueType> computeReachabilityTimes(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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private:
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template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
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static void computeBoundedReachabilityProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRates, storm::storage::BitVector const& goalStates, storm::storage::BitVector const& markovianNonGoalStates, storm::storage::BitVector const& probabilisticNonGoalStates, std::vector<ValueType>& markovianNonGoalValues, std::vector<ValueType>& probabilisticNonGoalValues, ValueType delta, uint_fast64_t numberOfSteps, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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template <typename ValueType, typename std::enable_if<!storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
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static void computeBoundedReachabilityProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRates, storm::storage::BitVector const& goalStates, storm::storage::BitVector const& markovianNonGoalStates, storm::storage::BitVector const& probabilisticNonGoalStates, std::vector<ValueType>& markovianNonGoalValues, std::vector<ValueType>& probabilisticNonGoalValues, ValueType delta, uint_fast64_t numberOfSteps, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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/*!
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* Computes the long-run average value for the given maximal end component of a Markov automaton.
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*
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* @param dir Sets whether the long-run average is to be minimized or maximized.
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* @param transitionMatrix The transition matrix of the underlying Markov automaton.
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* @param markovianStates A bit vector storing all markovian states.
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* @param exitRateVector A vector with exit rates for all states. Exit rates of probabilistic states are
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* assumed to be zero.
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* @param goalStates A bit vector indicating which states are to be considered as goal states.
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* @param mec The maximal end component to consider for computing the long-run average.
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* @return The long-run average of being in a goal state for the given MEC.
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*/
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template <typename ValueType>
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static ValueType computeLraForMaximalEndComponent(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& goalStates, storm::storage::MaximalEndComponent const& mec);
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/*!
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* Computes the expected reward that is gained from each state before entering any of the goal states.
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*
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* @param dir Indicates whether minimal or maximal rewards are to be computed.
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* @param transitionMatrix The transition matrix of the underlying Markov automaton.
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* @param backwardTransitions The reversed transition relation of the underlying Markov automaton.
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* @param goalStates The goal states that define until which point rewards are gained.
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* @param stateRewards A vector that defines the reward gained in each state. For probabilistic states,
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* this is an instantaneous reward that is fully gained and for Markovian states the actually gained
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* reward is dependent on the expected time to stay in the state, i.e. it is gouverned by the exit rate
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* of the state.
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* @return A vector that contains the expected reward for each state of the model.
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*/
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template <typename ValueType>
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static std::vector<ValueType> computeExpectedRewards(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, storm::storage::BitVector const& goalStates, std::vector<ValueType> const& stateRewards, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
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};
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}
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}
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}
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#endif /* STORM_MODELCHECKER_SPARSE_MARKOVAUTOMATON_CSL_MODELCHECKER_HELPER_H_ */
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