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Made use of this new cool rewardModel thing 

Former-commit-id: d670d09278
main
TimQu 10 years ago
parent
df850fe085
commit
5b1494b9a9
7 changed files with 132 additions and 96 deletions
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  1. 6
      src/builder/ExplicitPrismModelBuilder.cpp
  2. 118
      src/modelchecker/region/ApproximationModel.cpp
  3. 5
      src/modelchecker/region/ApproximationModel.h
  4. 36
      src/modelchecker/region/SparseDtmcRegionModelChecker.cpp
  5. 2
      src/modelchecker/region/SparseDtmcRegionModelChecker.h
  6. 10
      src/utility/constants.cpp
  7. 47
      test/functional/modelchecker/SparseDtmcRegionModelCheckerTest.cpp

6
src/builder/ExplicitPrismModelBuilder.cpp
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@ -460,7 +460,8 @@ namespace storm {
}
// Check that the resulting distribution is in fact a distribution.
STORM_LOG_THROW(!discreteTimeModel || comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Probabilities do not sum to one for command '" << command << "' (actually sum to " << probabilitySum << ").");
//STORM_LOG_THROW(!discreteTimeModel || comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Probabilities do not sum to one for command '" << command << "' (actually sum to " << probabilitySum << ").");
STORM_LOG_ERROR_COND(!discreteTimeModel || comparator.isOne(probabilitySum), "Probabilities do not sum to one for command '" << command << "' (actually sum to " << probabilitySum << ").");
}
}
@ -536,7 +537,8 @@ namespace storm {
}
// Check that the resulting distribution is in fact a distribution.
STORM_LOG_THROW(!discreteTimeModel || comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Sum of update probabilities do not some to one for some command (actually sum to " << probabilitySum << ").");
//STORM_LOG_THROW(!discreteTimeModel || comparator.isOne(probabilitySum), storm::exceptions::WrongFormatException, "Sum of update probabilities do not some to one for some command (actually sum to " << probabilitySum << ").");
STORM_LOG_ERROR_COND(!discreteTimeModel || comparator.isOne(probabilitySum), "Sum of update probabilities do not some to one for some command (actually sum to " << probabilitySum << ").");
// Dispose of the temporary maps.
delete currentTargetStates;

118
src/modelchecker/region/ApproximationModel.cpp
View File

@ -39,14 +39,12 @@ namespace storm {
//Now consider rewards
std::unordered_map<std::string, storm::models::sparse::StandardRewardModel<ConstantType>> rewardModels;
std::vector<std::size_t> stateRewardEntryToEvalTableMapping; //does a similar thing as matrixEntryToEvalTableMapping
std::vector<std::size_t> rewardEntryToEvalTableMapping; //does a similar thing as matrixEntryToEvalTableMapping
std::vector<std::size_t> transitionRewardEntryToEvalTableMapping; //does a similar thing as matrixEntryToEvalTableMapping
if(this->computeRewards){
boost::optional<std::vector<ConstantType>> stateRewards;
boost::optional<std::vector<ConstantType>> stateActionRewards;
boost::optional<storm::storage::SparseMatrix<ConstantType>> transitionRewards;
initializeRewards(parametricModel, probabilityMatrix, rowSubstitutions, stateRewards, transitionRewards, stateRewardEntryToEvalTableMapping, transitionRewardEntryToEvalTableMapping, constantEntryIndex);
rewardModels.insert(std::pair<std::string, storm::models::sparse::StandardRewardModel<ConstantType>>("", storm::models::sparse::StandardRewardModel<ConstantType>(std::move(stateRewards), std::move(stateActionRewards), std::move(transitionRewards))));
initializeRewards(parametricModel, probabilityMatrix, rowSubstitutions, stateActionRewards, rewardEntryToEvalTableMapping, transitionRewardEntryToEvalTableMapping, constantEntryIndex);
rewardModels.insert(std::pair<std::string, storm::models::sparse::StandardRewardModel<ConstantType>>("", storm::models::sparse::StandardRewardModel<ConstantType>(boost::optional<std::vector<ConstantType>>(), std::move(stateActionRewards))));
}
//Obtain other model ingredients and the approximation model itself
storm::models::sparse::StateLabeling labeling(parametricModel.getStateLabeling());
@ -71,18 +69,13 @@ namespace storm {
}
}
if(this->computeRewards){
//the same for state and transition rewards
auto approxModelStateRewardEntry = this->model->getUniqueRewardModel()->second.getStateRewardVector().begin();
for (std::size_t const& tableIndex : stateRewardEntryToEvalTableMapping){
//the same for rewards
auto approxModelRewardEntry = this->model->getUniqueRewardModel()->second.getStateActionRewardVector().begin();
for (std::size_t const& tableIndex : rewardEntryToEvalTableMapping){
if(tableIndex != constantEntryIndex){
this->stateRewardMapping.emplace_back(std::make_tuple(&(std::get<2>(this->rewardEvaluationTable[tableIndex])), &(std::get<3>(this->rewardEvaluationTable[tableIndex])), approxModelStateRewardEntry));
this->rewardMapping.emplace_back(std::make_tuple(&(std::get<2>(this->rewardEvaluationTable[tableIndex])), &(std::get<3>(this->rewardEvaluationTable[tableIndex])), approxModelRewardEntry));
}
++approxModelStateRewardEntry;
}
auto approxModelTransitionRewardEntry = this->model->getUniqueRewardModel()->second.getTransitionRewardMatrix().begin();
for (std::size_t const& tableIndex : transitionRewardEntryToEvalTableMapping){
this->transitionRewardMapping.emplace_back(std::make_tuple(&(std::get<2>(this->rewardEvaluationTable[tableIndex])), &(std::get<3>(this->rewardEvaluationTable[tableIndex])), approxModelTransitionRewardEntry));
++approxModelTransitionRewardEntry;
++approxModelRewardEntry;
}
//Get the sets of reward parameters that map to "CHOSEOPTIMAL".
this->choseOptimalRewardPars = std::vector<std::set<VariableType>>(this->rewardSubstitutions.size());
@ -158,61 +151,41 @@ namespace storm {
void SparseDtmcRegionModelChecker<ParametricType, ConstantType>::ApproximationModel::initializeRewards(storm::models::sparse::Dtmc<ParametricType> const& parametricModel,
storm::storage::SparseMatrix<ConstantType> const& probabilityMatrix,
std::vector<std::size_t> const& rowSubstitutions,
boost::optional<std::vector<ConstantType> >& stateRewards,
boost::optional<storm::storage::SparseMatrix<ConstantType> >& transitionRewards,
std::vector<std::size_t>& stateRewardEntryToEvalTableMapping,
boost::optional<std::vector<ConstantType>>& stateActionRewardVector,
std::vector<std::size_t>& rewardEntryToEvalTableMapping,
std::vector<std::size_t>& transitionRewardEntryToEvalTableMapping,
std::size_t const& constantEntryIndex) {
// run through the state reward vector of the parametric model.
// Constant entries can be set directly.
// For Parametric entries we have two cases:
// (1) make state rewards if the reward is independent of parameters that occur in probability functions.
// (2) make transition rewards otherwise.
//stateRewards
std::vector<ConstantType> stateRewardsAsVector(parametricModel.getNumberOfStates());
std::size_t numOfNonConstStateRewEntries=0;
//TransitionRewards
storm::storage::SparseMatrixBuilder<ConstantType> matrixBuilder(probabilityMatrix.getRowCount(), probabilityMatrix.getColumnCount(), 0, true, true, probabilityMatrix.getRowGroupCount());
std::size_t numOfNonConstTransitonRewEntries=0;
// For Parametric entries we set a dummy value and add one entry to the rewardEntryEvalTableMapping
std::vector<ConstantType> stateActionRewardsAsVector;
stateActionRewardsAsVector.reserve(probabilityMatrix.getRowCount());
rewardEntryToEvalTableMapping.reserve(probabilityMatrix.getRowCount());
std::size_t numOfNonConstRewEntries=0;
this->rewardSubstitutions.emplace_back(std::map<VariableType, TypeOfBound>()); //we want that the empty substitution is always the first one
for(std::size_t state=0; state<parametricModel.getNumberOfStates(); ++state){
matrixBuilder.newRowGroup(probabilityMatrix.getRowGroupIndices()[state]);
std::set<VariableType> occurringRewVariables;
std::set<VariableType> occurringProbVariables;
bool makeStateReward=true;
std::size_t evalTableIndex;
if(storm::utility::isConstant(parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state])){
stateRewardsAsVector[state]=storm::utility::regions::convertNumber<ConstantType>(storm::utility::regions::getConstantPart(parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state]));
stateRewardEntryToEvalTableMapping.emplace_back(constantEntryIndex);
} else {
//reward depends on parameters. Lets find out if probability parameters occur here.
//If this is the case, the reward depends on the nondeterministic choices and should be given as transition rewards.
storm::utility::regions::gatherOccurringVariables(parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state], occurringRewVariables);
for(auto const& entry : parametricModel.getTransitionMatrix().getRow(state)){
storm::utility::regions::gatherOccurringVariables(entry.getValue(), occurringProbVariables);
}
for( auto const& rewVar : occurringRewVariables){
if(occurringProbVariables.find(rewVar)!=occurringProbVariables.end()){
makeStateReward=false;
break;
}
}
if(makeStateReward){
//Get the corresponding substitution and substitutionIndex
std::map<VariableType, TypeOfBound> rewardSubstitution;
for(auto const& rewardVar : occurringRewVariables){
rewardSubstitution.insert(std::make_pair(rewardVar, TypeOfBound::CHOSEOPTIMAL));
ConstantType reward = storm::utility::regions::convertNumber<ConstantType>(storm::utility::regions::getConstantPart(parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state]));
//Add one of these entries for every row in the row group of state
for(auto matrixRow=probabilityMatrix.getRowGroupIndices()[state]; matrixRow<probabilityMatrix.getRowGroupIndices()[state+1]; ++matrixRow){
stateActionRewardsAsVector.emplace_back(reward);
rewardEntryToEvalTableMapping.emplace_back(constantEntryIndex);
}
std::size_t substitutionIndex=storm::utility::vector::findOrInsert(this->rewardSubstitutions, std::move(rewardSubstitution));
//insert table entry and dummy data in the stateRewardVector
std::size_t tableIndex=storm::utility::vector::findOrInsert(this->rewardEvaluationTable, std::tuple<std::size_t, ParametricType, ConstantType, ConstantType>(substitutionIndex, parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state], storm::utility::zero<ConstantType>(), storm::utility::zero<ConstantType>()));
stateRewardEntryToEvalTableMapping.emplace_back(tableIndex);
stateRewardsAsVector[state]=storm::utility::zero<ConstantType>();
++numOfNonConstStateRewEntries;
evalTableIndex = constantEntryIndex;
} else {
storm::utility::regions::gatherOccurringVariables(parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state], occurringRewVariables);
//For each row in the row group of state, we get the corresponding substitution, substitutionIndex and tableIndex
// We might find out that the reward is independent of the probability variables (and will thus be independent of nondeterministic choices)
// In that case, the reward function and the substitution will not change and thus we can use the same table index
bool rewardDependsOnProbVars=true;
std::size_t tableIndex;
for(auto matrixRow=probabilityMatrix.getRowGroupIndices()[state]; matrixRow<probabilityMatrix.getRowGroupIndices()[state+1]; ++matrixRow){
//Get the corresponding substitution and substitutionIndex
if(rewardDependsOnProbVars){ //always executed in first iteration
rewardDependsOnProbVars=false;
std::map<VariableType, TypeOfBound> rewardSubstitution;
for(auto const& rewardVar : occurringRewVariables){
typename std::map<VariableType, TypeOfBound>::iterator const substitutionIt=this->probabilitySubstitutions[rowSubstitutions[matrixRow]].find(rewardVar);
@ -220,26 +193,21 @@ namespace storm {
rewardSubstitution.insert(std::make_pair(rewardVar, TypeOfBound::CHOSEOPTIMAL));
} else {
rewardSubstitution.insert(*substitutionIt);
rewardDependsOnProbVars=true;
}
}
std::size_t substitutionIndex=storm::utility::vector::findOrInsert(this->rewardSubstitutions, std::move(rewardSubstitution));
//insert table entries and dummy data
std::size_t tableIndex=storm::utility::vector::findOrInsert(this->rewardEvaluationTable, std::tuple<std::size_t, ParametricType, ConstantType, ConstantType>(substitutionIndex, parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state], storm::utility::zero<ConstantType>(), storm::utility::zero<ConstantType>()));
for(auto const& matrixEntry : probabilityMatrix.getRow(matrixRow)){
transitionRewardEntryToEvalTableMapping.emplace_back(tableIndex);
matrixBuilder.addNextValue(matrixRow, matrixEntry.getColumn(), storm::utility::zero<ConstantType>());
++numOfNonConstTransitonRewEntries;
tableIndex=storm::utility::vector::findOrInsert(this->rewardEvaluationTable, std::tuple<std::size_t, ParametricType, ConstantType, ConstantType>(substitutionIndex, parametricModel.getUniqueRewardModel()->second.getStateRewardVector()[state], storm::utility::zero<ConstantType>(), storm::utility::zero<ConstantType>()));
}
}
stateRewardsAsVector[state]=storm::utility::zero<ConstantType>();
stateRewardEntryToEvalTableMapping.emplace_back(constantEntryIndex);
//insert table entries and dummy data
stateActionRewardsAsVector.emplace_back(storm::utility::zero<ConstantType>());
rewardEntryToEvalTableMapping.emplace_back(tableIndex);
++numOfNonConstRewEntries;
}
}
}
stateRewards=std::move(stateRewardsAsVector);
this->stateRewardMapping.reserve(numOfNonConstStateRewEntries);
transitionRewards=matrixBuilder.build();
this->transitionRewardMapping.reserve(numOfNonConstTransitonRewEntries);
stateActionRewardVector=std::move(stateActionRewardsAsVector);
this->rewardMapping.reserve(numOfNonConstRewEntries);
}
@ -343,20 +311,14 @@ namespace storm {
//write the reward values into the model
switch(optDir){
case storm::solver::OptimizationDirection::Minimize:
for(auto& mappingTriple : this->stateRewardMapping){
for(auto& mappingTriple : this->rewardMapping){
*std::get<2>(mappingTriple)=*std::get<0>(mappingTriple);
}
for(auto& mappingTriple : this->transitionRewardMapping){
std::get<2>(mappingTriple)->setValue(*(std::get<0>(mappingTriple)));
}
break;
case storm::solver::OptimizationDirection::Maximize:
for(auto& mappingTriple : this->stateRewardMapping){
for(auto& mappingTriple : this->rewardMapping){
*std::get<2>(mappingTriple)=*std::get<1>(mappingTriple);
}
for(auto& mappingTriple : this->transitionRewardMapping){
std::get<2>(mappingTriple)->setValue(*(std::get<1>(mappingTriple)));
}
break;
default:
STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "The given optimality Type is not supported.");

5
src/modelchecker/region/ApproximationModel.h
View File

@ -59,7 +59,7 @@ namespace storm {
};
void initializeProbabilities(storm::models::sparse::Dtmc<ParametricType> const& parametricModel, storm::storage::SparseMatrix<ConstantType>& probabilityMatrix, std::vector<std::size_t>& rowSubstitutions, std::vector<std::size_t>& matrixEntryToEvalTableMapping, std::size_t const& constantEntryIndex);
void initializeRewards(storm::models::sparse::Dtmc<ParametricType> const& parametricModel, storm::storage::SparseMatrix<ConstantType> const& probabilityMatrix, std::vector<std::size_t> const& rowSubstitutions, boost::optional<std::vector<ConstantType>>& stateRewards, boost::optional<storm::storage::SparseMatrix<ConstantType>>& transitionRewards, std::vector<std::size_t>& stateRewardEntryToEvalTableMapping, std::vector<std::size_t>& transitionRewardEntryToEvalTableMapping, std::size_t const& constantEntryIndex);
void initializeRewards(storm::models::sparse::Dtmc<ParametricType> const& parametricModel, storm::storage::SparseMatrix<ConstantType> const& probabilityMatrix, std::vector<std::size_t> const& rowSubstitutions, boost::optional<std::vector<ConstantType>>& stateActionRewardVector, std::vector<std::size_t>& stateRewardEntryToEvalTableMapping, std::vector<std::size_t>& transitionRewardEntryToEvalTableMapping, std::size_t const& constantEntryIndex);
//Vector has one entry for every (non-constant) matrix entry.
//pair.first points to an entry in the evaluation table,
@ -67,8 +67,7 @@ namespace storm {
std::vector<std::pair<ConstantType*, typename storm::storage::SparseMatrix<ConstantType>::iterator>> probabilityMapping;
//similar for the rewards. But now the first entry points to a minimal and the second one to a maximal value.
//The third entry points to the state reward vector and the transitionRewardMatrix, respectively.
std::vector<std::tuple<ConstantType*, ConstantType*, typename std::vector<ConstantType>::iterator>> stateRewardMapping;
std::vector<std::tuple<ConstantType*, ConstantType*, typename storm::storage::SparseMatrix<ConstantType>::iterator>> transitionRewardMapping;
std::vector<std::tuple<ConstantType*, ConstantType*, typename std::vector<ConstantType>::iterator>> rewardMapping;
//Vector has one (unique) entry for every occurring pair of a non-constant function and
// a substitution, i.e., a mapping of variables to a TypeOfBound

36
src/modelchecker/region/SparseDtmcRegionModelChecker.cpp
View File

@ -76,15 +76,17 @@ namespace storm {
std::chrono::high_resolution_clock::time_point timeSpecifyFormulaStart = std::chrono::high_resolution_clock::now();
STORM_LOG_THROW(this->canHandle(*formula), storm::exceptions::InvalidArgumentException, "Tried to specify a formula that can not be handled.");
//Note: canHandle already ensures that the formula has the right shape.
this->specifiedFormula = formula;
this->isResultConstant=false;
this->isResultInfinity=false;
this->simpleFormula=nullptr;
this->isApproximationApplicable=false;
this->smtSolver=nullptr;
this->approximationModel=nullptr;
this->samplingModel=nullptr;
this->reachabilityFunction=nullptr;
//Note: canHandle already ensures that the formula has the right shape.
this->specifiedFormula = formula;
// set some information regarding the formula and model. Also computes a more simple version of the model
preprocess();
if(!this->isResultConstant){
@ -154,7 +156,6 @@ namespace storm {
storm::storage::sparse::state_type initialState = *(this->model.getInitialStates() % maybeStates).begin();
// We then build the submatrix that only has the transitions of the maybe states.
storm::storage::SparseMatrix<ParametricType> submatrix = this->model.getTransitionMatrix().getSubmatrix(false, maybeStates, maybeStates);
// Eliminate all states with only constant outgoing transitions
// Convert the reduced matrix to a more flexible format to be able to perform state elimination more easily.
auto flexibleTransitions = this->eliminationModelChecker.getFlexibleSparseMatrix(submatrix);
@ -355,11 +356,20 @@ namespace storm {
//maybeStates: Compute the subset of states that has a reachability reward less than infinity.
storm::storage::BitVector statesWithProbability1 = storm::utility::graph::performProb1(this->model.getBackwardTransitions(), storm::storage::BitVector(this->model.getNumberOfStates(), true), targetStates);
maybeStates = ~targetStates & statesWithProbability1;
// If the initial state is known to have 0 reward or an infinite reward value, we can directly set the reachRewardFunction.
//Compute the new state reward vector
stateRewards=rewardModel->getTotalRewardVector(maybeStates.getNumberOfSetBits(), this->model.getTransitionMatrix(), maybeStates);
// If the initial state is known to have 0 reward or an infinite reachability reward value, we can directly set the reachRewardFunction.
storm::storage::sparse::state_type initialState = *this->model.getInitialStates().begin();
if (!maybeStates.get(initialState)) {
STORM_LOG_WARN("The expected reward of the initial state is constant (infinity or zero)");
this->reachabilityFunction = std::make_shared<ParametricType>(statesWithProbability1.get(initialState) ? storm::utility::zero<ParametricType>() : storm::utility::infinity<ParametricType>());
if(statesWithProbability1.get(initialState)){
this->reachabilityFunction = std::make_shared<ParametricType>(storm::utility::zero<ParametricType>());
} else {
this->reachabilityFunction = std::make_shared<ParametricType>(storm::utility::one<ParametricType>());
this->isResultInfinity=true;
}
this->isResultConstant=true;
return; //nothing else to do...
}
@ -414,9 +424,6 @@ namespace storm {
}
}
STORM_LOG_WARN_COND(!this->isResultConstant, "For the given property, the reachability Value is constant, i.e., independent of the region");
//Everything is fine, so we can now compute the new state reward vector
stateRewards=rewardModel->getTotalRewardVector(maybeStates.getNumberOfSetBits(), this->model.getTransitionMatrix(), maybeStates);
}
@ -508,8 +515,7 @@ namespace storm {
if(!done && this->isResultConstant){
STORM_LOG_DEBUG("Checking a region although the result is constant, i.e., independent of the region. This makes sense none.");
STORM_LOG_THROW(storm::utility::isConstant(*getReachabilityFunction()), storm::exceptions::UnexpectedException, "The result was assumed to be constant but it isn't.");
if(valueIsInBoundOfFormula(this->getReachabilityValue<CoefficientType>(region.getSomePoint(), true))){
if(valueIsInBoundOfFormula(this->getReachabilityValue<ConstantType>(region.getSomePoint(), true))){
region.setCheckResult(RegionCheckResult::ALLSAT);
}
else{
@ -750,7 +756,15 @@ namespace storm {
template<typename ParametricType, typename ConstantType>
template<typename ValueType>
ValueType SparseDtmcRegionModelChecker<ParametricType, ConstantType>::getReachabilityValue(std::map<VariableType, CoefficientType> const& point, bool evaluateFunction) {
if(evaluateFunction || this->isResultConstant){
if(this->isResultConstant){
//Todo: remove workaround (infinity<storm::RationalFunction() does not work)
if(this->isResultInfinity){
return storm::utility::infinity<ValueType>();
}
STORM_LOG_THROW(storm::utility::isConstant(*getReachabilityFunction()), storm::exceptions::UnexpectedException, "The result was assumed to be constant but it isn't.");
return storm::utility::regions::convertNumber<ValueType>(storm::utility::regions::getConstantPart(*getReachabilityFunction()));
}
if(evaluateFunction){
return storm::utility::regions::convertNumber<ValueType>(storm::utility::regions::evaluateFunction(*getReachabilityFunction(), point));
} else {
getSamplingModel()->instantiate(point);

2
src/modelchecker/region/SparseDtmcRegionModelChecker.h
View File

@ -257,6 +257,8 @@ namespace storm {
bool isApproximationApplicable;
// a flag that is true iff the resulting reachability function is constant
bool isResultConstant;
// workaround to represent that the result is infinity (utility::infinity<storm::RationalFunction>() does not work at this moment)
bool isResultInfinity;
// the smt solver that is used to prove properties with the help of the reachabilityFunction
std::shared_ptr<storm::solver::Smt2SmtSolver> smtSolver;

10
src/utility/constants.cpp
View File

@ -4,6 +4,7 @@
#include "src/storage/sparse/StateType.h"
#include "src/settings/SettingsManager.h"
#include "src/settings/modules/GeneralSettings.h"
#include "src/utility/macros.h"
#include "src/adapters/CarlAdapter.h"
@ -74,8 +75,16 @@ namespace storm {
template<>
storm::RationalFunction infinity() {
// FIXME: this does not work.
STORM_LOG_ERROR("Tried to get infinity as a rational function, which does not seem to work");
return storm::RationalFunction(carl::rationalize<storm::RationalNumber>(std::numeric_limits<double>::infinity()));
}
template<>
storm::RationalNumber infinity() {
// FIXME: this does not work.
STORM_LOG_ERROR("Tried to get infinity as a rational number, which does not seem to work");
return carl::rationalize<storm::RationalNumber>(std::numeric_limits<double>::infinity());
}
#endif
template<typename ValueType>
@ -221,6 +230,7 @@ namespace storm {
template RationalNumber one();
template RationalNumber zero();
template RationalNumber infinity();
template bool isOne(Interval const& value);
template bool isZero(Interval const& value);

47
test/functional/modelchecker/SparseDtmcRegionModelCheckerTest.cpp
View File

@ -182,6 +182,53 @@ TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew) {
storm::settings::mutableRegionSettings().resetModes();
}
TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew_Infty) {
std::string const& programFile = STORM_CPP_BASE_PATH "/examples/pdtmc/brp_rewards/brp_16_2.pm";
std::string const& formulaAsString = "R>2.5 [F \"success\" ]";
std::string const& constantsAsString = "";
//Build model, formula, region model checker
boost::optional<storm::prism::Program> program=storm::parser::PrismParser::parse(programFile).simplify().simplify();
program->checkValidity();
storm::parser::FormulaParser formulaParser(program.get().getManager().getSharedPointer());
std::vector<std::shared_ptr<storm::logic::Formula>> formulas = formulaParser.parseFromString(formulaAsString);
typename storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options options=storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options(*formulas[0]);
options.addConstantDefinitionsFromString(program.get(), constantsAsString);
options.preserveFormula(*formulas[0]);
std::shared_ptr<storm::models::sparse::Model<storm::RationalFunction>> model = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::translateProgram(program.get(), options)->as<storm::models::sparse::Model<storm::RationalFunction>>();
ASSERT_EQ(storm::models::ModelType::Dtmc, model->getType());
std::shared_ptr<storm::models::sparse::Dtmc<storm::RationalFunction>> dtmc = model->template as<storm::models::sparse::Dtmc<storm::RationalFunction>>();
storm::modelchecker::SparseDtmcRegionModelChecker<storm::RationalFunction, double> modelchecker(*dtmc);
ASSERT_TRUE(modelchecker.canHandle(*formulas[0]));
modelchecker.specifyFormula(formulas[0]);
//start testing
auto allSatRegion=storm::modelchecker::SparseDtmcRegionModelChecker<storm::RationalFunction, double>::ParameterRegion::parseRegion("");
EXPECT_EQ(storm::utility::infinity<double>(), modelchecker.getReachabilityValue<double>(allSatRegion.getLowerBounds(), false)); //instantiation of sampling model
EXPECT_EQ(storm::utility::infinity<double>(), modelchecker.getReachabilityValue<double>(allSatRegion.getLowerBounds(), true)); //instantiation of sampling model
//test approximative method
storm::settings::mutableRegionSettings().modifyModes(storm::settings::modules::RegionSettings::ApproxMode::TESTFIRST, storm::settings::modules::RegionSettings::SampleMode::INSTANTIATE, storm::settings::modules::RegionSettings::SmtMode::OFF);
ASSERT_TRUE(storm::settings::regionSettings().doApprox());
ASSERT_TRUE(storm::settings::regionSettings().doSample());
ASSERT_FALSE(storm::settings::regionSettings().doSmt());
modelchecker.checkRegion(allSatRegion);
EXPECT_EQ((storm::modelchecker::SparseDtmcRegionModelChecker<storm::RationalFunction, double>::RegionCheckResult::ALLSAT), allSatRegion.getCheckResult());
//test smt method (the regions need to be created again, because the old ones have some information stored in their internal state)
auto allSatRegionSmt=storm::modelchecker::SparseDtmcRegionModelChecker<storm::RationalFunction, double>::ParameterRegion::parseRegion("");
storm::settings::mutableRegionSettings().modifyModes(storm::settings::modules::RegionSettings::ApproxMode::OFF, storm::settings::modules::RegionSettings::SampleMode::EVALUATE, storm::settings::modules::RegionSettings::SmtMode::FUNCTION);
ASSERT_FALSE(storm::settings::regionSettings().doApprox());
ASSERT_TRUE(storm::settings::regionSettings().doSample());
ASSERT_TRUE(storm::settings::regionSettings().doSmt());
modelchecker.checkRegion(allSatRegionSmt);
//smt EXPECT_EQ((storm::modelchecker::SparseDtmcRegionModelChecker<storm::RationalFunction, double>::RegionCheckResult::ALLSAT), allSatRegionSmt.getCheckResult());
storm::settings::mutableRegionSettings().resetModes();
}
TEST(SparseDtmcRegionModelCheckerTest, Brp_Rew_4Par) {
std::string const& programFile = STORM_CPP_BASE_PATH "/examples/pdtmc/brp_rewards/brp_16_2.pm";

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