1#ifndef STORM_MODELS_SPARSE_CTMC_H_
2#define STORM_MODELS_SPARSE_CTMC_H_
14template<
class ValueType,
typename RewardModelType = StandardRewardModel<ValueType>>
25 std::unordered_map<std::string, RewardModelType>
const& rewardModels = std::unordered_map<std::string, RewardModelType>());
35 std::unordered_map<std::string, RewardModelType>&& rewardModels = std::unordered_map<std::string, RewardModelType>());
82 std::vector<ValueType> exitRates;
This class represents a continuous-time Markov chain.
Ctmc & operator=(Ctmc< ValueType, RewardModelType > const &ctmc)=default
storm::storage::SparseMatrix< ValueType > computeProbabilityMatrix() const
Ctmc & operator=(Ctmc< ValueType, RewardModelType > &&ctmc)=default
virtual void reduceToStateBasedRewards() override
Converts the transition rewards of all reward models to state-based rewards.
Ctmc(Ctmc< ValueType, RewardModelType > const &ctmc)=default
Ctmc(Ctmc< ValueType, RewardModelType > &&ctmc)=default
std::vector< ValueType > const & getExitRateVector() const
Retrieves the vector of exit rates of the model.
The base class of all sparse deterministic models.
This class manages the labeling of the state space with a number of (atomic) labels.
A class that holds a possibly non-square matrix in the compressed row storage format.