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Conditional Probabilities working. Included two tests. 

Former-commit-id: a89255c4ef
tempestpy_adaptions
dehnert 10 years ago
parent
6bc6753e90
commit
c85df2cd74
2 changed files with 69 additions and 57 deletions
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  1. 102
      src/modelchecker/reachability/SparseDtmcEliminationModelChecker.cpp
  2. 24
      test/functional/modelchecker/SparseDtmcEliminationModelCheckerTest.cpp

102
src/modelchecker/reachability/SparseDtmcEliminationModelChecker.cpp
View File

@ -127,7 +127,7 @@ namespace storm {
STORM_LOG_THROW(model.hasStateRewards() || model.hasTransitionRewards(), storm::exceptions::IllegalArgumentException, "Input model does not have a reward model.");
STORM_LOG_THROW(model.getInitialStates().getNumberOfSetBits() == 1, storm::exceptions::IllegalArgumentException, "Input model is required to have exactly one initial state.");
storm::storage::sparse::state_type initialState = *model.getInitialStates().begin();
// Then, compute the subset of states that has a reachability reward less than infinity.
storm::storage::BitVector trueStates(model.getNumberOfStates(), true);
storm::storage::BitVector infinityStates = storm::utility::graph::performProb1(model.getBackwardTransitions(), trueStates, psiStates);
@ -160,7 +160,7 @@ namespace storm {
// Before starting the model checking process, we assign priorities to states so we can use them to
// impose ordering constraints later.
std::vector<std::size_t> statePriorities = getStatePriorities(submatrix, submatrixTransposed, newInitialStates, oneStepProbabilities);
// Project the state reward vector to all maybe-states.
boost::optional<std::vector<ValueType>> optionalStateRewards(maybeStates.getNumberOfSetBits());
std::vector<ValueType>& stateRewards = optionalStateRewards.get();
@ -170,7 +170,7 @@ namespace storm {
// of the transition probability matrix and the transition reward matrix.
std::vector<ValueType> pointwiseProductRowSumVector = model.getTransitionMatrix().getPointwiseProductRowSumVector(model.getTransitionRewardMatrix());
storm::utility::vector::selectVectorValues(stateRewards, maybeStates, pointwiseProductRowSumVector);
if (model.hasStateRewards()) {
// If a state-based reward model is also available, we need to add this vector
// as well. As the state reward vector contains entries not just for the states
@ -225,6 +225,9 @@ namespace storm {
// From now on, we know the condition does not have a trivial probability in the initial state.
// Compute the 'true' psi states, i.e. those psi states that can be reached without passing through another psi state first.
psiStates = storm::utility::graph::getReachableStates(model.getTransitionMatrix(), model.getInitialStates(), trueStates, psiStates) & psiStates;
// Compute the states that can be reached on a path that has a psi state in it.
storm::storage::BitVector statesWithPsiPredecessor = storm::utility::graph::performProbGreater0(model.getTransitionMatrix(), trueStates, psiStates);
storm::storage::BitVector statesReachingPhi = storm::utility::graph::performProbGreater0(backwardTransitions, trueStates, phiStates);
@ -283,64 +286,56 @@ namespace storm {
// Eliminate the transitions going into the initial state.
eliminateState(flexibleMatrix, oneStepProbabilities, *newInitialStates.begin(), flexibleBackwardTransitions, missingStateRewards, false);
// Now we need to eliminate the chains of phi and psi states.
// Now we need to basically eliminate all chains of not-psi states after phi states and chains of not-phi
// states after psi states.
for (auto const& trans1 : flexibleMatrix.getRow(*newInitialStates.begin())) {
auto initialStateSuccessor = trans1.getColumn();
if (phiStates.get(initialStateSuccessor)) {
bool hasPhiSuccessor = true;
while (hasPhiSuccessor) {
hasPhiSuccessor = false;
// If the state is both a phi and a psi state, we do not need to eliminate chains.
if (psiStates.get(initialStateSuccessor)) {
continue;
}
// At this point, we know that the state satisfies phi and not psi.
// This means, we must compute the probability to reach psi states, which in turn means that we need
// to eliminate all chains of non-psi states between the current state and psi states.
bool hasNonPsiSuccessor = true;
while (hasNonPsiSuccessor) {
hasNonPsiSuccessor = false;
// Only treat the state if it has an outgoing transition other than a self-loop.
auto const currentRow = flexibleMatrix.getRow(initialStateSuccessor);
if (currentRow.size() > 1 || (!currentRow.empty() && currentRow.front().getColumn() != initialStateSuccessor)) {
bool elementToEliminate = false;
for (auto const& element : currentRow) {
if (phiStates.get(element.getColumn())) {
std::cout << "found element to eliminate: " << element.getColumn() << std::endl;
elementToEliminate = true;
break;
// If any of the successors is a phi state, we eliminate it (wrt. all its phi predecessors).
if (!psiStates.get(element.getColumn())) {
eliminateState(flexibleMatrix, oneStepProbabilities, element.getColumn(), flexibleBackwardTransitions, missingStateRewards, false, true, phiStates);
hasNonPsiSuccessor = true;
}
}
if (elementToEliminate) {
std::cout << "before elimination" << std::endl;
for (auto const& element : currentRow) {
std::cout << element.getColumn() << " -> " << element.getValue() << " ";
}
std::cout << std::endl;
for (auto const& element : currentRow) {
// If any of the successors is a phi state, we eliminate it (wrt. all its phi predecessors).
if (phiStates.get(element.getColumn())) {
eliminateState(flexibleMatrix, oneStepProbabilities, element.getColumn(), flexibleBackwardTransitions, missingStateRewards, false, true, phiStates);
hasPhiSuccessor = true;
}
}
std::cout << "after elimination" << std::endl;
for (auto const& element : currentRow) {
std::cout << element.getColumn() << " -> " << element.getValue() << " ";
}
std::cout << std::endl;
}
STORM_LOG_ASSERT(!flexibleMatrix.getRow(initialStateSuccessor).empty(), "(1) New transitions expected to be non-empty.");
}
}
} else {
STORM_LOG_ASSERT(psiStates.get(initialStateSuccessor), "Expected psi state.");
bool hasPsiSuccessor = true;
// At this point, we know that the state satisfies psi and not phi.
// This means, we must compute the probability to reach phi states, which in turn means that we need
// to eliminate all chains of non-phi states between the current state and phi states.
while (hasPsiSuccessor) {
hasPsiSuccessor = false;
bool hasNonPhiSuccessor = true;
while (hasNonPhiSuccessor) {
hasNonPhiSuccessor = false;
// Only treat the state if it has an outgoing transition other than a self-loop.
auto const currentRow = flexibleMatrix.getRow(initialStateSuccessor);
if (currentRow.size() > 1 || (!currentRow.empty() && currentRow.front().getColumn() != initialStateSuccessor)) {
for (auto const& element : currentRow) {
// If any of the successors is a psi state, we eliminate it (wrt. all its psi predecessors).
if (psiStates.get(element.getColumn())) {
if (!phiStates.get(element.getColumn())) {
eliminateState(flexibleMatrix, oneStepProbabilities, element.getColumn(), flexibleBackwardTransitions, missingStateRewards, false, true, psiStates);
hasPsiSuccessor = true;
hasNonPhiSuccessor = true;
}
}
}
@ -351,31 +346,30 @@ namespace storm {
ValueType numerator = storm::utility::zero<ValueType>();
ValueType denominator = storm::utility::zero<ValueType>();
flexibleMatrix.print();
for (auto const& trans1 : flexibleMatrix.getRow(*newInitialStates.begin())) {
auto initialStateSuccessor = trans1.getColumn();
if (phiStates.get(initialStateSuccessor)) {
ValueType additiveTerm = storm::utility::zero<ValueType>();
for (auto const& trans2 : flexibleMatrix.getRow(initialStateSuccessor)) {
std::cout << "(1) " << trans2.getColumn() << " -> " << trans2.getValue() << std::endl;
STORM_LOG_ASSERT(psiStates.get(trans2.getColumn()), "Expected " << trans2.getColumn() << " to be a psi state.");
additiveTerm += trans2.getValue();
if (psiStates.get(initialStateSuccessor)) {
numerator += trans1.getValue();
denominator += trans1.getValue();
} else {
ValueType additiveTerm = storm::utility::zero<ValueType>();
for (auto const& trans2 : flexibleMatrix.getRow(initialStateSuccessor)) {
STORM_LOG_ASSERT(psiStates.get(trans2.getColumn()), "Expected " << trans2.getColumn() << " to be a psi state.");
additiveTerm += trans2.getValue();
}
additiveTerm *= trans1.getValue();
numerator += additiveTerm;
denominator += additiveTerm;
}
std::cout << "(1) trans1.getValue: " << trans1.getValue() << " and additive term " << additiveTerm << std::endl;
additiveTerm *= trans1.getValue();
numerator += additiveTerm;
denominator += additiveTerm;
} else {
STORM_LOG_ASSERT(psiStates.get(initialStateSuccessor), "Expected psi state.");
denominator += trans1.getValue();
ValueType additiveTerm = storm::utility::zero<ValueType>();
for (auto const& trans2 : flexibleMatrix.getRow(initialStateSuccessor)) {
std::cout << "(2) " << trans2.getColumn() << " -> " << trans2.getValue() << std::endl;
STORM_LOG_ASSERT(phiStates.get(trans2.getColumn()), "Expected " << trans2.getColumn() << " to be a phi state.");
additiveTerm += trans2.getValue();
}
std::cout << "(2) trans1.getValue: " << trans1.getValue() << " and additive term " << additiveTerm << std::endl;
numerator += trans1.getValue() * additiveTerm;
}
}
@ -732,12 +726,6 @@ namespace storm {
predecessorForwardTransitionCount += predecessorForwardTransitions.size();
typename FlexibleSparseMatrix::row_type::iterator multiplyElement = std::find_if(predecessorForwardTransitions.begin(), predecessorForwardTransitions.end(), [&](storm::storage::MatrixEntry<typename FlexibleSparseMatrix::index_type, typename FlexibleSparseMatrix::value_type> const& a) { return a.getColumn() == state; });
if (multiplyElement == predecessorForwardTransitions.end()) {
for (auto const& entry : predecessorForwardTransitions) {
std::cout << entry << " ";
}
std::cout << std::endl;
}
// Make sure we have found the probability and set it to zero.
STORM_LOG_THROW(multiplyElement != predecessorForwardTransitions.end(), storm::exceptions::InvalidStateException, "No probability for successor found.");
ValueType multiplyFactor = multiplyElement->getValue();

24
test/functional/modelchecker/SparseDtmcEliminationModelCheckerTest.cpp
View File

@ -89,6 +89,30 @@ TEST(SparseDtmcEliminationModelCheckerTest, Crowds) {
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult3 = result->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(0.32153724292835045, quantitativeResult3[0], storm::settings::gmmxxEquationSolverSettings().getPrecision());
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("observe0Greater1");
eventuallyFormula = std::make_shared<storm::logic::EventuallyFormula>(labelFormula);
auto labelFormula2 = std::make_shared<storm::logic::AtomicLabelFormula>("observeIGreater1");
auto eventuallyFormula2 = std::make_shared<storm::logic::EventuallyFormula>(labelFormula2);
auto conditionalFormula = std::make_shared<storm::logic::ConditionalPathFormula>(eventuallyFormula, eventuallyFormula2);
result = checker.check(*conditionalFormula);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult4 = result->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(0.15330064292476167, quantitativeResult4[0], storm::settings::gmmxxEquationSolverSettings().getPrecision());
labelFormula = std::make_shared<storm::logic::AtomicLabelFormula>("observeOnlyTrueSender");
eventuallyFormula = std::make_shared<storm::logic::EventuallyFormula>(labelFormula);
labelFormula2 = std::make_shared<storm::logic::AtomicLabelFormula>("observe0Greater1");
eventuallyFormula2 = std::make_shared<storm::logic::EventuallyFormula>(labelFormula2);
conditionalFormula = std::make_shared<storm::logic::ConditionalPathFormula>(eventuallyFormula, eventuallyFormula2);
result = checker.check(*conditionalFormula);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeResult5 = result->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(0.96592521978041668, quantitativeResult5[0], storm::settings::gmmxxEquationSolverSettings().getPrecision());
}
TEST(SparseDtmcEliminationModelCheckerTest, SynchronousLeader) {

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