#include "src/generator/PrismNextStateGenerator.h"
#include <boost/container/flat_map.hpp>
#include "src/models/sparse/StateLabeling.h"
#include "src/storage/expressions/SimpleValuation.h"
#include "src/solver/SmtSolver.h"
#include "src/utility/constants.h"
#include "src/utility/macros.h"
#include "src/exceptions/InvalidArgumentException.h"
#include "src/exceptions/WrongFormatException.h"
namespace storm {
namespace generator {
template<typename ValueType, typename StateType>
PrismNextStateGenerator<ValueType, StateType>::PrismNextStateGenerator(storm::prism::Program const& program, NextStateGeneratorOptions const& options) : PrismNextStateGenerator<ValueType, StateType>(program.substituteConstants(), options, false) {
// Intentionally left empty.
}
template<typename ValueType, typename StateType>
PrismNextStateGenerator<ValueType, StateType>::PrismNextStateGenerator(storm::prism::Program const& program, NextStateGeneratorOptions const& options, bool flag) : NextStateGenerator<ValueType, StateType>(program.getManager(), options), program(program), rewardModels() {
STORM_LOG_TRACE("Creating next-state generator for PRISM program: " << program);
STORM_LOG_THROW(!this->program.specifiesSystemComposition(), storm::exceptions::WrongFormatException, "The explicit next-state generator currently does not support custom system compositions.");
// Only after checking validity of the program, we initialize the variable information.
this->checkValid(program);
this->variableInformation = VariableInformation(program);
if (this->options.isBuildAllRewardModelsSet()) {
for (auto const& rewardModel : this->program.getRewardModels()) {
rewardModels.push_back(rewardModel);
}
} else {
// Extract the reward models from the program based on the names we were given.
for (auto const& rewardModelName : this->options.getRewardModelNames()) {
if (this->program.hasRewardModel(rewardModelName)) {
rewardModels.push_back(this->program.getRewardModel(rewardModelName));
} else {
STORM_LOG_THROW(rewardModelName.empty(), storm::exceptions::InvalidArgumentException, "Cannot build unknown reward model '" << rewardModelName << "'.");
STORM_LOG_THROW(this->program.getNumberOfRewardModels() == 1, storm::exceptions::InvalidArgumentException, "Reference to standard reward model is ambiguous.");
STORM_LOG_THROW(this->program.getNumberOfRewardModels() > 0, storm::exceptions::InvalidArgumentException, "Reference to standard reward model is invalid, because there is no reward model.");
}
}
// If no reward model was yet added, but there was one that was given in the options, we try to build
// standard reward model.
if (rewardModels.empty() && !this->options.getRewardModelNames().empty()) {
rewardModels.push_back(this->program.getRewardModel(0));
}
}
// Determine whether any reward model has state action rewards.
for (auto const& rewardModel : rewardModels) {
hasStateActionRewards |= rewardModel.get().hasStateActionRewards();
}
// If there are terminal states we need to handle, we now need to translate all labels to expressions.
if (this->options.hasTerminalStates()) {
for (auto const& expressionOrLabelAndBool : this->options.getTerminalStates()) {
if (expressionOrLabelAndBool.first.isExpression()) {
this->terminalStates.push_back(std::make_pair(expressionOrLabelAndBool.first.getExpression(), expressionOrLabelAndBool.second));
} else {
if (program.hasLabel(expressionOrLabelAndBool.first.getLabel())) {
this->terminalStates.push_back(std::make_pair(this->program.getLabelExpression(expressionOrLabelAndBool.first.getLabel()), expressionOrLabelAndBool.second));
} else {
// If the label is not present in the program and is not a special one, we raise an error.
STORM_LOG_THROW(expressionOrLabelAndBool.first.getLabel() == "init" || expressionOrLabelAndBool.first.getLabel() == "deadlock", storm::exceptions::InvalidArgumentException, "Terminal states refer to illegal label '" << expressionOrLabelAndBool.first.getLabel() << "'.");
}
}
}
}
}
template<typename ValueType, typename StateType>
void PrismNextStateGenerator<ValueType, StateType>::checkValid(storm::prism::Program const& program) {
// If the program still contains undefined constants and we are not in a parametric setting, assemble an appropriate error message.
#ifdef STORM_HAVE_CARL
if (!std::is_same<ValueType, storm::RationalFunction>::value && program.hasUndefinedConstants()) {
#else
if (program.hasUndefinedConstants()) {
#endif
std::vector<std::reference_wrapper<storm::prism::Constant const>> undefinedConstants = program.getUndefinedConstants();
std::stringstream stream;
bool printComma = false;
for (auto const& constant : undefinedConstants) {
if (printComma) {
stream << ", ";
} else {
printComma = true;
}
stream << constant.get().getName() << " (" << constant.get().getType() << ")";
}
stream << ".";
STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "Program still contains these undefined constants: " + stream.str());
}
#ifdef STORM_HAVE_CARL
else if (std::is_same<ValueType, storm::RationalFunction>::value && !program.hasUndefinedConstantsOnlyInUpdateProbabilitiesAndRewards()) {
STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "The program contains undefined constants that appear in some places other than update probabilities and reward value expressions, which is not admitted.");
}
#endif
}
template<typename ValueType, typename StateType>
ModelType PrismNextStateGenerator<ValueType, StateType>::getModelType() const {
switch (program.getModelType()) {
case storm::prism::Program::ModelType::DTMC: return ModelType::DTMC;
case storm::prism::Program::ModelType::CTMC: return ModelType::CTMC;
case storm::prism::Program::ModelType::MDP: return ModelType::MDP;
case storm::prism::Program::ModelType::MA: return ModelType::MA;
default:
STORM_LOG_THROW(false, storm::exceptions::WrongFormatException, "Invalid model type.");
}
}
template<typename ValueType, typename StateType>
bool PrismNextStateGenerator<ValueType, StateType>::isDeterministicModel() const {
return program.isDeterministicModel();
}
template<typename ValueType, typename StateType>
bool PrismNextStateGenerator<ValueType, StateType>::isDiscreteTimeModel() const {
return program.isDiscreteTimeModel();
}
template<typename ValueType, typename StateType>
std::vector<StateType> PrismNextStateGenerator<ValueType, StateType>::getInitialStates(StateToIdCallback const& stateToIdCallback) {
// Prepare an SMT solver to enumerate all initial states.
storm::utility::solver::SmtSolverFactory factory;
std::unique_ptr<storm::solver::SmtSolver> solver = factory.create(program.getManager());
std::vector<storm::expressions::Expression> rangeExpressions = program.getAllRangeExpressions();
for (auto const& expression : rangeExpressions) {
solver->add(expression);
}
solver->add(program.getInitialConstruct().getInitialStatesExpression());
// Proceed ss long as the solver can still enumerate initial states.
std::vector<StateType> initialStateIndices;
while (solver->check() == storm::solver::SmtSolver::CheckResult::Sat) {
// Create fresh state.
CompressedState initialState(this->variableInformation.getTotalBitOffset());
// Read variable assignment from the solution of the solver. Also, create an expression we can use to
// prevent the variable assignment from being enumerated again.
storm::expressions::Expression blockingExpression;
std::shared_ptr<storm::solver::SmtSolver::ModelReference> model = solver->getModel();
for (auto const& booleanVariable : this->variableInformation.booleanVariables) {
bool variableValue = model->getBooleanValue(booleanVariable.variable);
storm::expressions::Expression localBlockingExpression = variableValue ? !booleanVariable.variable : booleanVariable.variable;
blockingExpression = blockingExpression.isInitialized() ? blockingExpression || localBlockingExpression : localBlockingExpression;
initialState.set(booleanVariable.bitOffset, variableValue);
}
for (auto const& integerVariable : this->variableInformation.integerVariables) {
int_fast64_t variableValue = model->getIntegerValue(integerVariable.variable);
storm::expressions::Expression localBlockingExpression = integerVariable.variable != model->getManager().integer(variableValue);
blockingExpression = blockingExpression.isInitialized() ? blockingExpression || localBlockingExpression : localBlockingExpression;
initialState.setFromInt(integerVariable.bitOffset, integerVariable.bitWidth, static_cast<uint_fast64_t>(variableValue - integerVariable.lowerBound));
}
// Register initial state and return it.
StateType id = stateToIdCallback(initialState);
initialStateIndices.push_back(id);
// Block the current initial state to search for the next one.
if (!blockingExpression.isInitialized()) {
break;
}
solver->add(blockingExpression);
}
return initialStateIndices;
}
template<typename ValueType, typename StateType>
StateBehavior<ValueType, StateType> PrismNextStateGenerator<ValueType, StateType>::expand(StateToIdCallback const& stateToIdCallback) {
// Prepare the result, in case we return early.
StateBehavior<ValueType, StateType> result;
// First, construct the state rewards, as we may return early if there are no choices later and we already
// need the state rewards then.
for (auto const& rewardModel : rewardModels) {
ValueType stateRewardValue = storm::utility::zero<ValueType>();
if (rewardModel.get().hasStateRewards()) {
for (auto const& stateReward : rewardModel.get().getStateRewards()) {
if (this->evaluator.asBool(stateReward.getStatePredicateExpression())) {
stateRewardValue += ValueType(this->evaluator.asRational(stateReward.getRewardValueExpression()));
}
}
}
result.addStateReward(stateRewardValue);
}
// If a terminal expression was set and we must not expand this state, return now.
if (!this->terminalStates.empty()) {
for (auto const& expressionBool : this->terminalStates) {
if (this->evaluator.asBool(expressionBool.first) == expressionBool.second) {
return result;
}
}
}
// Get all choices for the state.
result.setExpanded();
std::vector<Choice<ValueType>> allChoices = getUnlabeledChoices(*this->state, stateToIdCallback);
std::vector<Choice<ValueType>> allLabeledChoices = getLabeledChoices(*this->state, stateToIdCallback);
for (auto& choice : allLabeledChoices) {
allChoices.push_back(std::move(choice));
}
std::size_t totalNumberOfChoices = allChoices.size();
// If there is not a single choice, we return immediately, because the state has no behavior (other than
// the state reward).
if (totalNumberOfChoices == 0) {
return result;
}
// If the model is a deterministic model, we need to fuse the choices into one.
if (this->isDeterministicModel() && totalNumberOfChoices > 1) {
Choice<ValueType> globalChoice;
// For CTMCs, we need to keep track of the total exit rate to scale the action rewards later. For DTMCs
// this is equal to the number of choices, which is why we initialize it like this here.
ValueType totalExitRate = this->isDiscreteTimeModel() ? static_cast<ValueType>(totalNumberOfChoices) : storm::utility::zero<ValueType>();
// Iterate over all choices and combine the probabilities/rates into one choice.
for (auto const& choice : allChoices) {
for (auto const& stateProbabilityPair : choice) {
if (this->isDiscreteTimeModel()) {
globalChoice.addProbability(stateProbabilityPair.first, stateProbabilityPair.second / totalNumberOfChoices);
} else {
globalChoice.addProbability(stateProbabilityPair.first, stateProbabilityPair.second);
}
}
if (hasStateActionRewards && !this->isDiscreteTimeModel()) {
totalExitRate += choice.getTotalMass();
}
if (this->options.isBuildChoiceLabelsSet()) {
globalChoice.addChoiceLabels(choice.getChoiceLabels());
}
}
// Now construct the state-action reward for all selected reward models.
for (auto const& rewardModel : rewardModels) {
ValueType stateActionRewardValue = storm::utility::zero<ValueType>();
if (rewardModel.get().hasStateActionRewards()) {
for (auto const& stateActionReward : rewardModel.get().getStateActionRewards()) {
for (auto const& choice : allChoices) {
if (stateActionReward.getActionIndex() == choice.getActionIndex() && this->evaluator.asBool(stateActionReward.getStatePredicateExpression())) {
stateActionRewardValue += ValueType(this->evaluator.asRational(stateActionReward.getRewardValueExpression())) * choice.getTotalMass() / totalExitRate;
}
}
}
}
globalChoice.addChoiceReward(stateActionRewardValue);
}
// Move the newly fused choice in place.
allChoices.clear();
allChoices.push_back(std::move(globalChoice));
}
// Move all remaining choices in place.
for (auto& choice : allChoices) {
result.addChoice(std::move(choice));
}
return result;
}
template<typename ValueType, typename StateType>
CompressedState PrismNextStateGenerator<ValueType, StateType>::applyUpdate(CompressedState const& state, storm::prism::Update const& update) {
CompressedState newState(state);
// NOTE: the following process assumes that the assignments of the update are ordered in such a way that the
// assignments to boolean variables precede the assignments to all integer variables and that within the
// types, the assignments to variables are ordered (in ascending order) by the expression variables.
// This is guaranteed for PRISM models, by sorting the assignments as soon as an update is created.
auto assignmentIt = update.getAssignments().begin();
auto assignmentIte = update.getAssignments().end();
// Iterate over all boolean assignments and carry them out.
auto boolIt = this->variableInformation.booleanVariables.begin();
for (; assignmentIt != assignmentIte && assignmentIt->getExpression().hasBooleanType(); ++assignmentIt) {
while (assignmentIt->getVariable() != boolIt->variable) {
++boolIt;
}
newState.set(boolIt->bitOffset, this->evaluator.asBool(assignmentIt->getExpression()));
}
// Iterate over all integer assignments and carry them out.
auto integerIt = this->variableInformation.integerVariables.begin();
for (; assignmentIt != assignmentIte && assignmentIt->getExpression().hasIntegerType(); ++assignmentIt) {
while (assignmentIt->getVariable() != integerIt->variable) {
++integerIt;
}
int_fast64_t assignedValue = this->evaluator.asInt(assignmentIt->getExpression());
STORM_LOG_THROW(assignedValue <= integerIt->upperBound, storm::exceptions::WrongFormatException, "The update " << update << " leads to an out-of-bounds value (" << assignedValue << ") for the variable '" << assignmentIt->getVariableName() << "'.");
STORM_LOG_THROW(assignedValue >= integerIt->lowerBound, storm::exceptions::WrongFormatException, "The update " << update << " leads to an out-of-bounds value (" << assignedValue << ") for the variable '" << assignmentIt->getVariableName() << "'.");
newState.setFromInt(integerIt->bitOffset, integerIt->bitWidth, assignedValue - integerIt->lowerBound);
STORM_LOG_ASSERT(static_cast<int_fast64_t>(newState.getAsInt(integerIt->bitOffset, integerIt->bitWidth)) + integerIt->lowerBound == assignedValue, "Writing to the bit vector bucket failed (read " << newState.getAsInt(integerIt->bitOffset, integerIt->bitWidth) << " but wrote " << assignedValue << ").");
}
// Check that we processed all assignments.
STORM_LOG_ASSERT(assignmentIt == assignmentIte, "Not all assignments were consumed.");
return newState;
}
template<typename ValueType, typename StateType>
boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> PrismNextStateGenerator<ValueType, StateType>::getActiveCommandsByActionIndex(uint_fast64_t const& actionIndex) {
boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> result((std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>()));
// Iterate over all modules.
for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
storm::prism::Module const& module = program.getModule(i);
// If the module has no command labeled with the given action, we can skip this module.
if (!module.hasActionIndex(actionIndex)) {
continue;
}
std::set<uint_fast64_t> const& commandIndices = module.getCommandIndicesByActionIndex(actionIndex);
// If the module contains the action, but there is no command in the module that is labeled with
// this action, we don't have any feasible command combinations.
if (commandIndices.empty()) {
return boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>>();
}
std::vector<std::reference_wrapper<storm::prism::Command const>> commands;
// Look up commands by their indices and add them if the guard evaluates to true in the given state.
for (uint_fast64_t commandIndex : commandIndices) {
storm::prism::Command const& command = module.getCommand(commandIndex);
if (this->evaluator.asBool(command.getGuardExpression())) {
commands.push_back(command);
}
}
// If there was no enabled command although the module has some command with the required action label,
// we must not return anything.
if (commands.size() == 0) {
return boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>>();
}
result.get().push_back(std::move(commands));
}
return result;
}
template<typename ValueType, typename StateType>
std::vector<Choice<ValueType>> PrismNextStateGenerator<ValueType, StateType>::getUnlabeledChoices(CompressedState const& state, StateToIdCallback stateToIdCallback) {
std::vector<Choice<ValueType>> result;
// Iterate over all modules.
for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
storm::prism::Module const& module = program.getModule(i);
// Iterate over all commands.
for (uint_fast64_t j = 0; j < module.getNumberOfCommands(); ++j) {
storm::prism::Command const& command = module.getCommand(j);
// Only consider unlabeled commands.
if (command.isLabeled()) continue;
// Skip the command, if it is not enabled.
if (!this->evaluator.asBool(command.getGuardExpression())) {
continue;
}
result.push_back(Choice<ValueType>(command.getActionIndex(), command.isMarkovian()));
Choice<ValueType>& choice = result.back();
// Remember the command labels only if we were asked to.
if (this->options.isBuildChoiceLabelsSet()) {
choice.addChoiceLabel(command.getGlobalIndex());
}
// Iterate over all updates of the current command.
ValueType probabilitySum = storm::utility::zero<ValueType>();
for (uint_fast64_t k = 0; k < command.getNumberOfUpdates(); ++k) {
storm::prism::Update const& update = command.getUpdate(k);
// Obtain target state index and add it to the list of known states. If it has not yet been
// seen, we also add it to the set of states that have yet to be explored.
StateType stateIndex = stateToIdCallback(applyUpdate(state, update));
// Update the choice by adding the probability/target state to it.
ValueType probability = this->evaluator.asRational(update.getLikelihoodExpression());
choice.addProbability(stateIndex, probability);
probabilitySum += probability;
}
// Create the state-action reward for the newly created choice.
for (auto const& rewardModel : rewardModels) {
ValueType stateActionRewardValue = storm::utility::zero<ValueType>();
if (rewardModel.get().hasStateActionRewards()) {
for (auto const& stateActionReward : rewardModel.get().getStateActionRewards()) {
if (stateActionReward.getActionIndex() == choice.getActionIndex() && this->evaluator.asBool(stateActionReward.getStatePredicateExpression())) {
stateActionRewardValue += ValueType(this->evaluator.asRational(stateActionReward.getRewardValueExpression()));
}
}
}
choice.addChoiceReward(stateActionRewardValue);
}
// Check that the resulting distribution is in fact a distribution.
STORM_LOG_THROW(!program.isDiscreteTimeModel() || this->comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Probabilities do not sum to one for command '" << command << "' (actually sum to " << probabilitySum << ").");
}
}
return result;
}
template<typename ValueType, typename StateType>
std::vector<Choice<ValueType>> PrismNextStateGenerator<ValueType, StateType>::getLabeledChoices(CompressedState const& state, StateToIdCallback stateToIdCallback) {
std::vector<Choice<ValueType>> result;
for (uint_fast64_t actionIndex : program.getSynchronizingActionIndices()) {
boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> optionalActiveCommandLists = getActiveCommandsByActionIndex(actionIndex);
// Only process this action label, if there is at least one feasible solution.
if (optionalActiveCommandLists) {
std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>> const& activeCommandList = optionalActiveCommandLists.get();
std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>::const_iterator> iteratorList(activeCommandList.size());
// Initialize the list of iterators.
for (size_t i = 0; i < activeCommandList.size(); ++i) {
iteratorList[i] = activeCommandList[i].cbegin();
}
// As long as there is one feasible combination of commands, keep on expanding it.
bool done = false;
while (!done) {
boost::container::flat_map<CompressedState, ValueType>* currentTargetStates = new boost::container::flat_map<CompressedState, ValueType>();
boost::container::flat_map<CompressedState, ValueType>* newTargetStates = new boost::container::flat_map<CompressedState, ValueType>();
currentTargetStates->emplace(state, storm::utility::one<ValueType>());
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
storm::prism::Command const& command = *iteratorList[i];
for (uint_fast64_t j = 0; j < command.getNumberOfUpdates(); ++j) {
storm::prism::Update const& update = command.getUpdate(j);
for (auto const& stateProbabilityPair : *currentTargetStates) {
// Compute the new state under the current update and add it to the set of new target states.
CompressedState newTargetState = applyUpdate(stateProbabilityPair.first, update);
// If the new state was already found as a successor state, update the probability
// and otherwise insert it.
auto targetStateIt = newTargetStates->find(newTargetState);
if (targetStateIt != newTargetStates->end()) {
targetStateIt->second += stateProbabilityPair.second * this->evaluator.asRational(update.getLikelihoodExpression());
} else {
newTargetStates->emplace(newTargetState, stateProbabilityPair.second * this->evaluator.asRational(update.getLikelihoodExpression()));
}
}
}
// If there is one more command to come, shift the target states one time step back.
if (i < iteratorList.size() - 1) {
delete currentTargetStates;
currentTargetStates = newTargetStates;
newTargetStates = new boost::container::flat_map<CompressedState, ValueType>();
}
}
// At this point, we applied all commands of the current command combination and newTargetStates
// contains all target states and their respective probabilities. That means we are now ready to
// add the choice to the list of transitions.
result.push_back(Choice<ValueType>(actionIndex));
// Now create the actual distribution.
Choice<ValueType>& choice = result.back();
// Remember the command labels only if we were asked to.
if (this->options.isBuildChoiceLabelsSet()) {
// Add the labels of all commands to this choice.
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
choice.addChoiceLabel(iteratorList[i]->get().getGlobalIndex());
}
}
// Add the probabilities/rates to the newly created choice.
ValueType probabilitySum = storm::utility::zero<ValueType>();
for (auto const& stateProbabilityPair : *newTargetStates) {
StateType actualIndex = stateToIdCallback(stateProbabilityPair.first);
choice.addProbability(actualIndex, stateProbabilityPair.second);
probabilitySum += stateProbabilityPair.second;
}
// Check that the resulting distribution is in fact a distribution.
STORM_LOG_THROW(!program.isDiscreteTimeModel() || !this->comparator.isConstant(probabilitySum) || this->comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Sum of update probabilities do not some to one for some command (actually sum to " << probabilitySum << ").");
// Create the state-action reward for the newly created choice.
for (auto const& rewardModel : rewardModels) {
ValueType stateActionRewardValue = storm::utility::zero<ValueType>();
if (rewardModel.get().hasStateActionRewards()) {
for (auto const& stateActionReward : rewardModel.get().getStateActionRewards()) {
if (stateActionReward.getActionIndex() == choice.getActionIndex() && this->evaluator.asBool(stateActionReward.getStatePredicateExpression())) {
stateActionRewardValue += ValueType(this->evaluator.asRational(stateActionReward.getRewardValueExpression()));
}
}
}
choice.addChoiceReward(stateActionRewardValue);
}
// Dispose of the temporary maps.
delete currentTargetStates;
delete newTargetStates;
// Now, check whether there is one more command combination to consider.
bool movedIterator = false;
for (int_fast64_t j = iteratorList.size() - 1; !movedIterator && j >= 0; --j) {
++iteratorList[j];
if (iteratorList[j] != activeCommandList[j].end()) {
movedIterator = true;
} else {
// Reset the iterator to the beginning of the list.
iteratorList[j] = activeCommandList[j].begin();
}
}
done = !movedIterator;
}
}
}
return result;
}
template<typename ValueType, typename StateType>
storm::models::sparse::StateLabeling PrismNextStateGenerator<ValueType, StateType>::label(storm::storage::BitVectorHashMap<StateType> const& states, std::vector<StateType> const& initialStateIndices, std::vector<StateType> const& deadlockStateIndices) {
// Gather a vector of labels and their expressions.
std::vector<std::pair<std::string, storm::expressions::Expression>> labels;
if (this->options.isBuildAllLabelsSet()) {
for (auto const& label : program.getLabels()) {
labels.push_back(std::make_pair(label.getName(), label.getStatePredicateExpression()));
}
} else {
for (auto const& labelName : this->options.getLabelNames()) {
if (program.hasLabel(labelName)) {
labels.push_back(std::make_pair(labelName, program.getLabelExpression(labelName)));
} else {
STORM_LOG_THROW(labelName == "init" || labelName == "deadlock", storm::exceptions::InvalidArgumentException, "Cannot build labeling for unknown label '" << labelName << "'.");
}
}
}
return NextStateGenerator<ValueType, StateType>::label(states, initialStateIndices, deadlockStateIndices, labels);
}
template<typename ValueType, typename StateType>
std::size_t PrismNextStateGenerator<ValueType, StateType>::getNumberOfRewardModels() const {
return rewardModels.size();
}
template<typename ValueType, typename StateType>
RewardModelInformation PrismNextStateGenerator<ValueType, StateType>::getRewardModelInformation(uint64_t const& index) const {
storm::prism::RewardModel const& rewardModel = rewardModels[index].get();
return RewardModelInformation(rewardModel.getName(), rewardModel.hasStateRewards(), rewardModel.hasStateActionRewards(), rewardModel.hasTransitionRewards());
}
template class PrismNextStateGenerator<double>;
#ifdef STORM_HAVE_CARL
template class PrismNextStateGenerator<storm::RationalNumber>;
template class PrismNextStateGenerator<storm::RationalFunction>;
#endif
}
}