87 lines
5.1 KiB

#ifndef STORM_MODELS_SPARSE_NONDETERMINISTICMODEL_H_
#define STORM_MODELS_SPARSE_NONDETERMINISTICMODEL_H_
#include "src/models/sparse/Model.h"
#include "src/utility/OsDetection.h"
namespace storm {
namespace models {
namespace sparse {
/*!
* The base class of sparse nondeterministic models.
*/
template<class ValueType, typename RewardModelType = StandardRewardModel<ValueType>>
class NondeterministicModel: public Model<ValueType, RewardModelType> {
public:
/*!
* Constructs a model from the given data.
*
* @param modelType The type of the model.
* @param transitionMatrix The matrix representing the transitions in the model.
* @param stateLabeling The labeling of the states.
* @param rewardModels A mapping of reward model names to reward models.
* @param optionalChoiceLabeling A vector that represents the labels associated with the choices of each state.
*/
NondeterministicModel(storm::models::ModelType const& modelType,
storm::storage::SparseMatrix<ValueType> const& transitionMatrix,
storm::models::sparse::StateLabeling const& stateLabeling,
std::unordered_map<std::string, RewardModelType> const& rewardModels = std::unordered_map<std::string, RewardModelType>(),
boost::optional<std::vector<LabelSet>> const& optionalChoiceLabeling = boost::optional<std::vector<LabelSet>>());
/*!
* Constructs a model by moving the given data.
*
* @param modelType The type of the model.
* @param transitionMatrix The matrix representing the transitions in the model.
* @param stateLabeling The labeling of the states.
* @param rewardModels A mapping of reward model names to reward models.
* @param optionalChoiceLabeling A vector that represents the labels associated with the choices of each state.
*/
NondeterministicModel(storm::models::ModelType const& modelType,
storm::storage::SparseMatrix<ValueType>&& transitionMatrix,
storm::models::sparse::StateLabeling&& stateLabeling,
std::unordered_map<std::string, RewardModelType>&& rewardModels = std::unordered_map<std::string, RewardModelType>(),
boost::optional<std::vector<LabelSet>>&& optionalChoiceLabeling = boost::optional<std::vector<LabelSet>>());
NondeterministicModel(NondeterministicModel<ValueType, RewardModelType> const& other) = default;
NondeterministicModel& operator=(NondeterministicModel<ValueType, RewardModelType> const& other) = default;
#ifndef WINDOWS
NondeterministicModel(NondeterministicModel<ValueType, RewardModelType>&& other) = default;
NondeterministicModel& operator=(NondeterministicModel<ValueType, RewardModelType>&& other) = default;
#endif
/*!
* Retrieves the number of (nondeterministic) choices in the model.
*
* @return The number of (nondeterministic) choices in the model.
*/
uint_fast64_t getNumberOfChoices() const;
/*!
* Retrieves the vector indicating which matrix rows represent non-deterministic choices of a certain state.
*
* @return The vector indicating which matrix rows represent non-deterministic choices of a certain state.
*/
std::vector<uint_fast64_t> const& getNondeterministicChoiceIndices() const;
/*!
* @param state State for which we want to know how many choices it has
*
* @return The number of non-deterministic choices for the given state
*/
uint_fast64_t getNumberOfChoices(uint_fast64_t state) const;
virtual void reduceToStateBasedRewards() override;
virtual void printModelInformationToStream(std::ostream& out) const;
virtual void writeDotToStream(std::ostream& outStream, bool includeLabeling = true, storm::storage::BitVector const* subsystem = nullptr, std::vector<ValueType> const* firstValue = nullptr, std::vector<ValueType> const* secondValue = nullptr, std::vector<uint_fast64_t> const* stateColoring = nullptr, std::vector<std::string> const* colors = nullptr, std::vector<uint_fast64_t>* scheduler = nullptr, bool finalizeOutput = true) const;
};
} // namespace sparse
} // namespace models
} // namespace storm
#endif /* STORM_MODELS_SPARSE_NONDETERMINISTICMODEL_H_ */