sp
/
tempest
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

Merge branch 'master' of https://srv-i2.informatik.rwth-aachen.de/scm/git/storm

main
Matthias Volk 9 years ago
parent
cc4d2f27d4 c1063f27cc
commit
a08106e7a2
7 changed files with 174 additions and 31 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 43
      resources/examples/testfiles/ma/jobscheduler.ma
  2. 1
      src/storm/modelchecker/multiobjective/pcaa/SparseMaPcaaWeightVectorChecker.cpp
  3. 14
      src/storm/modelchecker/multiobjective/pcaa/SparsePcaaParetoQuery.cpp
  4. 2
      src/storm/modelchecker/multiobjective/pcaa/SparsePcaaWeightVectorChecker.cpp
  5. 1
      src/storm/models/sparse/MarkovAutomaton.cpp
  6. 134
      src/test/modelchecker/SparseMaPcaaModelCheckerTest.cpp
  7. 10
      src/test/modelchecker/SparseMdpPcaaModelCheckerTest.cpp

43
resources/examples/testfiles/ma/jobscheduler.ma
View File

@ -0,0 +1,43 @@
// Stochastic Job Scheduling, based on []
// Encoding by Junges & Quatmann
// RWTH Aachen University
// Please cite Quatmann et al: Multi-objective Model Checking of Markov Automata
ma
const int x_j1 = 1;
const int x_j2 = 2;
const int x_j3 = 3;
formula is_running = r_j1 + r_j2 + r_j3 > 0;
formula num_finished = f_j1 + f_j2 + f_j3;
module main
r_j1 : [0..1];
r_j2 : [0..1];
r_j3 : [0..1];
f_j1 : [0..1];
f_j2 : [0..1];
f_j3 : [0..1];
<> (r_j1 = 1) -> x_j1 : (r_j1' = 0) & (r_j2' = 0) & (r_j3' = 0) & (f_j1' = 1);
<> (r_j2 = 1) -> x_j2 : (r_j1' = 0) & (r_j2' = 0) & (r_j3' = 0) & (f_j2' = 1);
<> (r_j3 = 1) -> x_j3 : (r_j1' = 0) & (r_j2' = 0) & (r_j3' = 0) & (f_j3' = 1);
[] (!is_running) & (num_finished = 2) & (f_j1 = 0) -> 1: (r_j1' = 1);
[] (!is_running) & (num_finished = 2) & (f_j2 = 0) -> 1: (r_j2' = 1);
[] (!is_running) & (num_finished = 2) & (f_j3 = 0) -> 1: (r_j3' = 1);
[] (!is_running) & (num_finished <= 1) & (f_j1 = 0) & (f_j2 = 0) -> 1: (r_j1' = 1) & (r_j2' = 1);
[] (!is_running) & (num_finished <= 1) & (f_j1 = 0) & (f_j3 = 0) -> 1: (r_j1' = 1) & (r_j3' = 1);
[] (!is_running) & (num_finished <= 1) & (f_j2 = 0) & (f_j3 = 0) -> 1: (r_j2' = 1) & (r_j3' = 1);
endmodule
init
r_j1 = 0 &
r_j2 = 0 &
r_j3 = 0 &
f_j1 = 0 &
f_j2 = 0 &
f_j3 = 0
endinit

1
src/storm/modelchecker/multiobjective/pcaa/SparseMaPcaaWeightVectorChecker.cpp
View File

@ -5,7 +5,6 @@
#include "storm/adapters/CarlAdapter.h"
#include "storm/models/sparse/MarkovAutomaton.h"
#include "storm/models/sparse/StandardRewardModel.h"
#include "storm/transformer/EndComponentEliminator.h"
#include "storm/utility/macros.h"
#include "storm/utility/vector.h"

14
src/storm/modelchecker/multiobjective/pcaa/SparsePcaaParetoQuery.cpp
View File

@ -7,7 +7,7 @@
#include "storm/modelchecker/results/ParetoCurveCheckResult.h"
#include "storm/utility/constants.h"
#include "storm/utility/vector.h"
#include "storm/settings//SettingsManager.h"
#include "storm/settings/SettingsManager.h"
#include "storm/settings/modules/MultiObjectiveSettings.h"
#include "storm/settings/modules/GeneralSettings.h"
@ -22,7 +22,10 @@ namespace storm {
// Set the precision of the weight vector checker
typename SparseModelType::ValueType weightedPrecision = storm::utility::convertNumber<typename SparseModelType::ValueType>(storm::settings::getModule<storm::settings::modules::MultiObjectiveSettings>().getPrecision());
weightedPrecision /= typename SparseModelType::ValueType(2);
weightedPrecision /= storm::utility::sqrt(storm::utility::convertNumber<typename SparseModelType::ValueType, uint_fast64_t>(this->objectives.size()));
// multiobjPrecision / sqrt(numObjectives) is the largest possible value for which termination is guaranteed.
// Lets be a little bit more precise to reduce the number of required iterations.
weightedPrecision *= storm::utility::convertNumber<typename SparseModelType::ValueType>(0.9);
this->weightVectorChecker->setWeightedPrecision(weightedPrecision);
}
@ -35,9 +38,10 @@ namespace storm {
// obtain the data for the checkresult
std::vector<std::vector<typename SparseModelType::ValueType>> paretoOptimalPoints;
paretoOptimalPoints.reserve(this->refinementSteps.size());
for(auto const& step : this->refinementSteps) {
paretoOptimalPoints.push_back(storm::utility::vector::convertNumericVector<typename SparseModelType::ValueType>(this->transformPointToOriginalModel(step.lowerBoundPoint)));
std::vector<Point> vertices = this->underApproximation->getVertices();
paretoOptimalPoints.reserve(vertices.size());
for(auto const& vertex : vertices) {
paretoOptimalPoints.push_back(storm::utility::vector::convertNumericVector<typename SparseModelType::ValueType>(this->transformPointToOriginalModel(vertex)));
}
return std::unique_ptr<CheckResult>(new ParetoCurveCheckResult<typename SparseModelType::ValueType>(this->originalModel.getInitialStates().getNextSetIndex(0),
std::move(paretoOptimalPoints),

2
src/storm/modelchecker/multiobjective/pcaa/SparsePcaaWeightVectorChecker.cpp
View File

@ -117,7 +117,7 @@ namespace storm {
template <class SparseModelType>
void SparsePcaaWeightVectorChecker<SparseModelType>::unboundedWeightedPhase(std::vector<ValueType> const& weightedRewardVector) {
if(this->objectivesWithNoUpperTimeBound.empty()) {
if(this->objectivesWithNoUpperTimeBound.empty() || !storm::utility::vector::hasNonZeroEntry(weightedRewardVector)) {
this->weightedResult = std::vector<ValueType>(model.getNumberOfStates(), storm::utility::zero<ValueType>());
this->scheduler = storm::storage::TotalScheduler(model.getNumberOfStates());
return;

1
src/storm/models/sparse/MarkovAutomaton.cpp
View File

@ -349,6 +349,7 @@ namespace storm {
optionalChoiceLabeling = storm::utility::vector::filterVector(optionalChoiceLabeling.get(), keepStates);
}
//TODO update reward models according to kept states
STORM_LOG_WARN_COND(this->getRewardModels().empty(), "Conversion of MA to CTMC does not preserve rewards.");
std::unordered_map<std::string, RewardModelType> rewardModels = this->getRewardModels();
return std::make_shared<storm::models::sparse::Ctmc<ValueType, RewardModelType>>(std::move(rateMatrix), std::move(stateLabeling), std::move(rewardModels), std::move(optionalChoiceLabeling));

134
src/test/modelchecker/SparseMaPcaaModelCheckerTest.cpp
View File

@ -11,6 +11,7 @@
#include "storm/storage/geometry/Polytope.h"
#include "storm/storage/geometry/Hyperrectangle.h"
#include "storm/settings/modules/GeneralSettings.h"
#include "storm/settings/modules/MultiObjectiveSettings.h"
#include "storm/settings/SettingsManager.h"
#include "storm/utility/storm.h"
@ -42,7 +43,7 @@ TEST(SparseMaPcaaModelCheckerTest, serverRationalNumbers) {
std::vector<storm::RationalNumber> q = {q1, q2};
auto expectedAchievableValues = storm::storage::geometry::Polytope<storm::RationalNumber>::createDownwardClosure(std::vector<std::vector<storm::RationalNumber>>({p,q}));
EXPECT_TRUE(expectedAchievableValues->contains(result->asParetoCurveCheckResult<storm::RationalNumber>().getUnderApproximation()));
EXPECT_TRUE(result->asParetoCurveCheckResult<storm::RationalNumber>().getUnderApproximation()->contains(expectedAchievableValues));
EXPECT_TRUE(result->asParetoCurveCheckResult<storm::RationalNumber>().getOverApproximation()->contains(expectedAchievableValues));
}*/
@ -51,32 +52,137 @@ TEST(SparseMaPcaaModelCheckerTest, server) {
std::string programFile = STORM_TEST_RESOURCES_DIR "/ma/server.ma";
std::string formulasAsString = "multi(Tmax=? [ F \"error\" ], Pmax=? [ F \"processB\" ]) "; // pareto
// formulasAsString += "; \n multi(..)";
// programm, model, formula
storm::prism::Program program = storm::parseProgram(programFile);
program = storm::utility::prism::preprocess(program, "");
std::vector<std::shared_ptr<storm::logic::Formula const>> formulas = storm::parseFormulasForPrismProgram(formulasAsString, program);
std::shared_ptr<storm::models::sparse::MarkovAutomaton<double>> ma = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::MarkovAutomaton<double>>();
storm::modelchecker::SparseMarkovAutomatonCslModelChecker<storm::models::sparse::MarkovAutomaton<double>> checker(*ma);
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isParetoCurveCheckResult());
// we do our checks with rationals to avoid numerical issues when doing polytope computations...
std::vector<double> p = {11.0/6.0, 1.0/2.0};
std::vector<double> q = {29.0/18.0, 2.0/3.0};
auto expectedAchievableValues = storm::storage::geometry::Polytope<double>::createDownwardClosure(std::vector<std::vector<double>>({p,q}));
auto expectedAchievableValues = storm::storage::geometry::Polytope<storm::RationalNumber>::createDownwardClosure(
std::vector<std::vector<storm::RationalNumber>>({storm::utility::vector::convertNumericVector<storm::RationalNumber>(p),
storm::utility::vector::convertNumericVector<storm::RationalNumber>(q)}));
// due to precision issues, we enlarge one of the polytopes before checking containement
std::vector<double> lb = {-storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision(), -storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision()};
std::vector<double> ub = {storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision(), storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision()};
auto bloatingBox = storm::storage::geometry::Hyperrectangle<double>(lb,ub).asPolytope();
EXPECT_TRUE(expectedAchievableValues->minkowskiSum(bloatingBox)->contains(result->asParetoCurveCheckResult<double>().getUnderApproximation()));
EXPECT_TRUE(result->asParetoCurveCheckResult<double>().getUnderApproximation()->minkowskiSum(bloatingBox)->contains(expectedAchievableValues));
storm::RationalNumber eps = storm::utility::convertNumber<storm::RationalNumber>(storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
std::vector<storm::RationalNumber> lb(2,-eps), ub(2,eps);
auto bloatingBox = storm::storage::geometry::Hyperrectangle<storm::RationalNumber>(lb,ub).asPolytope();
EXPECT_TRUE(expectedAchievableValues->minkowskiSum(bloatingBox)->contains(result->asParetoCurveCheckResult<double>().getUnderApproximation()->convertNumberRepresentation<storm::RationalNumber>()));
EXPECT_TRUE(result->asParetoCurveCheckResult<double>().getOverApproximation()->convertNumberRepresentation<storm::RationalNumber>()->minkowskiSum(bloatingBox)->contains(expectedAchievableValues));
}
TEST(SparseMaPcaaModelCheckerTest, jobscheduler_pareto_3Obj) {
std::string programFile = STORM_TEST_RESOURCES_DIR "/ma/jobscheduler.ma";
std::string formulasAsString = "multi(Tmin=? [ F num_finished=3 ], Pmax=? [ F<=0.2 num_finished=2 ], Pmin=? [ F f_j1=1 & f_j3=0 ]) ";
storm::prism::Program program = storm::parseProgram(programFile);
program = storm::utility::prism::preprocess(program, "");
std::vector<std::shared_ptr<storm::logic::Formula const>> formulas = storm::parseFormulasForPrismProgram(formulasAsString, program);
std::shared_ptr<storm::models::sparse::MarkovAutomaton<double>> ma = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::MarkovAutomaton<double>>();
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isParetoCurveCheckResult());
std::vector<double> j12 = {1.266666667,0.1617571721,0.5};
std::vector<double> j13 = {1.283333333,0.1707737575,0.25};
std::vector<double> j23 = {1.333333333,0.1978235137,0.1};
// we do our checks with rationals to avoid numerical issues when doing polytope computations...
auto expectedAchievableValues = storm::storage::geometry::Polytope<storm::RationalNumber>::createDownwardClosure(
std::vector<std::vector<storm::RationalNumber>>({storm::utility::vector::convertNumericVector<storm::RationalNumber>(j12),
storm::utility::vector::convertNumericVector<storm::RationalNumber>(j13),
storm::utility::vector::convertNumericVector<storm::RationalNumber>(j23)}));
// due to precision issues, we enlarge one of the polytopes before checking containement
storm::RationalNumber eps = storm::utility::convertNumber<storm::RationalNumber>(storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
std::vector<storm::RationalNumber> lb(3,-eps), ub(3,eps);
auto bloatingBox = storm::storage::geometry::Hyperrectangle<storm::RationalNumber>(lb,ub).asPolytope();
EXPECT_TRUE(expectedAchievableValues->minkowskiSum(bloatingBox)->contains(result->asParetoCurveCheckResult<double>().getUnderApproximation()->convertNumberRepresentation<storm::RationalNumber>()));
EXPECT_TRUE(result->asParetoCurveCheckResult<double>().getOverApproximation()->convertNumberRepresentation<storm::RationalNumber>()->minkowskiSum(bloatingBox)->contains(expectedAchievableValues));
}
TEST(SparseMaPcaaModelCheckerTest, jobscheduler_achievability_3Obj) {
std::string programFile = STORM_TEST_RESOURCES_DIR "/ma/jobscheduler.ma";
std::string formulasAsString = "multi(T<=1.31 [ F num_finished=3 ], P>=0.17 [ F<=0.2 num_finished=2 ], P<=0.31 [ F f_j1=1 & f_j3=0 ]) "; //true
formulasAsString += "; multi(T<=1.29 [ F num_finished=3 ], P>=0.18 [ F<=0.2 num_finished=2 ], P<=0.29 [ F f_j1=1 & f_j3=0 ])"; //false
storm::prism::Program program = storm::parseProgram(programFile);
program = storm::utility::prism::preprocess(program, "");
std::vector<std::shared_ptr<storm::logic::Formula const>> formulas = storm::parseFormulasForPrismProgram(formulasAsString, program);
std::shared_ptr<storm::models::sparse::MarkovAutomaton<double>> ma = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::MarkovAutomaton<double>>();
uint_fast64_t const initState = *ma->getInitialStates().begin();
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isExplicitQualitativeCheckResult());
EXPECT_TRUE(result->asExplicitQualitativeCheckResult()[initState]);
std::unique_ptr<storm::modelchecker::CheckResult> result2 = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[1]->asMultiObjectiveFormula());
ASSERT_TRUE(result2->isExplicitQualitativeCheckResult());
EXPECT_FALSE(result2->asExplicitQualitativeCheckResult()[initState]);
}
TEST(SparseMaPcaaModelCheckerTest, jobscheduler_quantitative_3Obj) {
std::string programFile = STORM_TEST_RESOURCES_DIR "/ma/jobscheduler.ma";
std::string formulasAsString = "multi(Tmin=? [ F num_finished=3 ], P>=0.1797900683 [ F<=0.2 num_finished=2 ], P<=0.3 [ F f_j1=1 & f_j3=0 ]) "; //quantitative
formulasAsString += "; multi(T<=1.26 [ F num_finished=3 ], P>=0.2 [ F<=0.2 num_finished=2 ], Pmin=? [ F f_j1=1 & f_j3=0 ])"; //false
storm::prism::Program program = storm::parseProgram(programFile);
program = storm::utility::prism::preprocess(program, "");
std::vector<std::shared_ptr<storm::logic::Formula const>> formulas = storm::parseFormulasForPrismProgram(formulasAsString, program);
std::shared_ptr<storm::models::sparse::MarkovAutomaton<double>> ma = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::MarkovAutomaton<double>>();
uint_fast64_t const initState = *ma->getInitialStates().begin();
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(1.3, result->asExplicitQuantitativeCheckResult<double>()[initState], storm::settings::getModule<storm::settings::modules::MultiObjectiveSettings>().getPrecision());
std::unique_ptr<storm::modelchecker::CheckResult> result2 = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[1]->asMultiObjectiveFormula());
ASSERT_TRUE(result2->isExplicitQualitativeCheckResult());
EXPECT_FALSE(result2->asExplicitQualitativeCheckResult()[initState]);
}
TEST(SparseMaPcaaModelCheckerTest, jobscheduler_pareto_2Obj) {
std::string programFile = STORM_TEST_RESOURCES_DIR "/ma/jobscheduler.ma";
std::string formulasAsString = "multi( Pmax=? [ F<=0.1 num_finished=1], Pmin=? [F<=0.2 num_finished=3]) ";
storm::prism::Program program = storm::parseProgram(programFile);
program = storm::utility::prism::preprocess(program, "");
std::vector<std::shared_ptr<storm::logic::Formula const>> formulas = storm::parseFormulasForPrismProgram(formulasAsString, program);
std::shared_ptr<storm::models::sparse::MarkovAutomaton<double>> ma = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::MarkovAutomaton<double>>();
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*ma, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isParetoCurveCheckResult());
std::vector<double> j12 = {0.2591835573, 0.01990529674};
std::vector<double> j13 = {0.329682099, 0.01970194998};
std::vector<double> j23 = {0.3934717664, 0.01948095743};
// we do our checks with rationals to avoid numerical issues when doing polytope computations...
auto expectedAchievableValues = storm::storage::geometry::Polytope<storm::RationalNumber>::createDownwardClosure(
std::vector<std::vector<storm::RationalNumber>>({storm::utility::vector::convertNumericVector<storm::RationalNumber>(j12),
storm::utility::vector::convertNumericVector<storm::RationalNumber>(j13),
storm::utility::vector::convertNumericVector<storm::RationalNumber>(j23)}));
// due to precision issues, we enlarge one of the polytopes before checking containement
storm::RationalNumber eps = storm::utility::convertNumber<storm::RationalNumber>(storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
std::vector<storm::RationalNumber> lb(2,-eps), ub(2,eps);
auto bloatingBox = storm::storage::geometry::Hyperrectangle<storm::RationalNumber>(lb,ub).asPolytope();
EXPECT_TRUE(expectedAchievableValues->minkowskiSum(bloatingBox)->contains(result->asParetoCurveCheckResult<double>().getUnderApproximation()->convertNumberRepresentation<storm::RationalNumber>()));
EXPECT_TRUE(result->asParetoCurveCheckResult<double>().getOverApproximation()->convertNumberRepresentation<storm::RationalNumber>()->minkowskiSum(bloatingBox)->contains(expectedAchievableValues));
}
#endif /* STORM_HAVE_HYPRO */

10
src/test/modelchecker/SparseMdpPcaaModelCheckerTest.cpp
View File

@ -26,8 +26,6 @@ TEST(SparseMdpPcaaModelCheckerTest, consensus) {
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::Mdp<double>>();
uint_fast64_t const initState = *mdp->getInitialStates().begin();;
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<double>> checker(*mdp);
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*mdp, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(0.10833260970000025, result->asExplicitQuantitativeCheckResult<double>()[initState], storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
@ -54,8 +52,6 @@ TEST(SparseMdpPcaaModelCheckerTest, zeroconf) {
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::Mdp<double>>();
uint_fast64_t const initState = *mdp->getInitialStates().begin();
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<double>> checker(*mdp);
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*mdp, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(0.0003075787401574803, result->asExplicitQuantitativeCheckResult<double>()[initState], storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
@ -73,8 +69,6 @@ TEST(SparseMdpPcaaModelCheckerTest, team3with3objectives) {
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::Mdp<double>>();
uint_fast64_t const initState = *mdp->getInitialStates().begin();
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<double>> checker(*mdp);
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*mdp, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(0.7448979591841851, result->asExplicitQuantitativeCheckResult<double>()[initState], storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());
@ -92,8 +86,6 @@ TEST(SparseMdpPcaaModelCheckerTest, scheduler) {
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::Mdp<double>>();
uint_fast64_t const initState = *mdp->getInitialStates().begin();
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<double>> checker(*mdp);
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*mdp, formulas[0]->asMultiObjectiveFormula());
EXPECT_TRUE(result->asExplicitQualitativeCheckResult()[initState]);
}
@ -110,8 +102,6 @@ TEST(SparseMdpPcaaModelCheckerTest, dpm) {
std::shared_ptr<storm::models::sparse::Mdp<double>> mdp = storm::buildSparseModel<double>(program, formulas)->as<storm::models::sparse::Mdp<double>>();
uint_fast64_t const initState = *mdp->getInitialStates().begin();
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<double>> checker(*mdp);
std::unique_ptr<storm::modelchecker::CheckResult> result = storm::modelchecker::multiobjective::performPcaa(*mdp, formulas[0]->asMultiObjectiveFormula());
ASSERT_TRUE(result->isExplicitQuantitativeCheckResult());
EXPECT_NEAR(121.61288, result->asExplicitQuantitativeCheckResult<double>()[initState], storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision());

Write Preview
Loading…
Cancel
Save