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Enabled check whether initial states are contained in the set of states for which the probability/reward values could be determined via graph algorithms to shorten computation times if possible.

tempestpy_adaptions
dehnert 12 years ago
parent
f44f0ce410
commit
65ebe3dcc3
2 changed files with 85 additions and 53 deletions
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  1. 33
      src/modelchecker/prctl/SparseDtmcPrctlModelChecker.h
  2. 93
      src/modelchecker/prctl/SparseMdpPrctlModelChecker.h

33
src/modelchecker/prctl/SparseDtmcPrctlModelChecker.h
View File

@ -97,11 +97,16 @@ public:
// Check if we already know the result (i.e. probability 0) for all initial states and // Check if we already know the result (i.e. probability 0) for all initial states and
// don't compute anything in this case. // don't compute anything in this case.
if (this->getInitialStates().isSubsetOf(~statesWithProbabilityGreater0)) {
if (this->getInitialStates().isDisjointFrom(statesWithProbabilityGreater0)) {
LOG4CPLUS_INFO(logger, "The probabilities for the initial states were determined in a preprocessing step." LOG4CPLUS_INFO(logger, "The probabilities for the initial states were determined in a preprocessing step."
<< " No exact probabilities were computed."); << " No exact probabilities were computed.");
} else { // Otherwise, we have have to compute the probabilities.
// Now we can eliminate the rows and columns from the original transition probability matrix that have probability 0.
// Set the values for all maybe-states to 0.5 to indicate that their probability values are not 0 (and
// not necessarily 1).
storm::utility::vector::setVectorValues(*result, statesWithProbabilityGreater0, Type(0.5));
} else {
// In this case we have have to compute the probabilities.
// We can eliminate the rows and columns from the original transition probability matrix that have probability 0.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(statesWithProbabilityGreater0); storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(statesWithProbabilityGreater0);
// Compute the new set of target states in the reduced system. // Compute the new set of target states in the reduced system.
@ -117,8 +122,7 @@ public:
// Perform the matrix vector multiplication as often as required by the formula bound. // Perform the matrix vector multiplication as often as required by the formula bound.
this->performMatrixVectorMultiplication(submatrix, subresult, nullptr, formula.getBound()); this->performMatrixVectorMultiplication(submatrix, subresult, nullptr, formula.getBound());
// Create result vector and set its values accordingly.
// Set the values of the resulting vector accordingly.
storm::utility::vector::setVectorValues(*result, statesWithProbabilityGreater0, subresult); storm::utility::vector::setVectorValues(*result, statesWithProbabilityGreater0, subresult);
storm::utility::vector::setVectorValues<Type>(*result, ~statesWithProbabilityGreater0, storm::utility::constGetZero<Type>()); storm::utility::vector::setVectorValues<Type>(*result, ~statesWithProbabilityGreater0, storm::utility::constGetZero<Type>());
} }
@ -260,9 +264,9 @@ public:
// are neither 0 nor 1. // are neither 0 nor 1.
storm::utility::vector::setVectorValues<Type>(*result, maybeStates, Type(0.5)); storm::utility::vector::setVectorValues<Type>(*result, maybeStates, Type(0.5));
} else { } else {
// Otherwise, we have have to compute the probabilities.
// In this case we have have to compute the probabilities.
// First, we can eliminate the rows and columns from the original transition probability matrix.
// We can eliminate the rows and columns from the original transition probability matrix.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates); storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates);
// Converting the matrix from the fixpoint notation to the form needed for the equation // Converting the matrix from the fixpoint notation to the form needed for the equation
// system. That is, we go from x = A*x + b to (I-A)x = b. // system. That is, we go from x = A*x + b to (I-A)x = b.
@ -388,14 +392,14 @@ public:
storm::storage::BitVector trueStates(this->getModel().getNumberOfStates(), true); storm::storage::BitVector trueStates(this->getModel().getNumberOfStates(), true);
storm::storage::BitVector infinityStates = storm::utility::graph::performProb1(this->getModel(), trueStates, *targetStates); storm::storage::BitVector infinityStates = storm::utility::graph::performProb1(this->getModel(), trueStates, *targetStates);
infinityStates.complement(); infinityStates.complement();
LOG4CPLUS_INFO(logger, "Found " << infinityStates.getNumberOfSetBits() << " 'infinity' states.");
storm::storage::BitVector maybeStates = ~(*targetStates) & ~infinityStates;
LOG4CPLUS_INFO(logger, "Found " << infinityStates.getNumberOfSetBits() << " 'infinity' states.");
LOG4CPLUS_INFO(logger, "Found " << targetStates->getNumberOfSetBits() << " 'target' states.");
LOG4CPLUS_INFO(logger, "Found " << maybeStates.getNumberOfSetBits() << " 'maybe' states.");
// Create resulting vector. // Create resulting vector.
std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates()); std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates());
// Check whether there are states for which we have to compute the result.
storm::storage::BitVector maybeStates = ~(*targetStates) & ~infinityStates;
// Check whether we need to compute exact rewards for some states. // Check whether we need to compute exact rewards for some states.
if (this->getInitialStates().isDisjointFrom(maybeStates)) { if (this->getInitialStates().isDisjointFrom(maybeStates)) {
LOG4CPLUS_INFO(logger, "The rewards for the initial states were determined in a preprocessing step." LOG4CPLUS_INFO(logger, "The rewards for the initial states were determined in a preprocessing step."
@ -405,7 +409,6 @@ public:
storm::utility::vector::setVectorValues<Type>(*result, maybeStates, storm::utility::constGetOne<Type>()); storm::utility::vector::setVectorValues<Type>(*result, maybeStates, storm::utility::constGetOne<Type>());
} else { } else {
// In this case we have to compute the reward values for the remaining states. // In this case we have to compute the reward values for the remaining states.
const int maybeStatesSetBitCount = maybeStates.getNumberOfSetBits();
// Now we can eliminate the rows and columns from the original transition probability matrix. // Now we can eliminate the rows and columns from the original transition probability matrix.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates); storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates);
@ -415,10 +418,10 @@ public:
// Initialize the x vector with 1 for each element. This is the initial guess for // Initialize the x vector with 1 for each element. This is the initial guess for
// the iterative solvers. // the iterative solvers.
std::vector<Type> x(maybeStatesSetBitCount, storm::utility::constGetOne<Type>());
std::vector<Type> x(submatrix.getColCount(), storm::utility::constGetOne<Type>());
// Prepare the right-hand side of the equation system. // Prepare the right-hand side of the equation system.
std::vector<Type> b(maybeStatesSetBitCount);
std::vector<Type> b(submatrix.getRowCount());
if (this->getModel().hasTransitionRewards()) { if (this->getModel().hasTransitionRewards()) {
// If a transition-based reward model is available, we initialize the right-hand // If a transition-based reward model is available, we initialize the right-hand
// side to the vector resulting from summing the rows of the pointwise product // side to the vector resulting from summing the rows of the pointwise product
@ -431,7 +434,7 @@ public:
// as well. As the state reward vector contains entries not just for the states // as well. As the state reward vector contains entries not just for the states
// that we still consider (i.e. maybeStates), we need to extract these values // that we still consider (i.e. maybeStates), we need to extract these values
// first. // first.
std::vector<Type> subStateRewards(maybeStatesSetBitCount);
std::vector<Type> subStateRewards(b.size());
storm::utility::vector::selectVectorValues(subStateRewards, maybeStates, this->getModel().getStateRewardVector()); storm::utility::vector::selectVectorValues(subStateRewards, maybeStates, this->getModel().getStateRewardVector());
storm::utility::vector::addVectorsInPlace(b, subStateRewards); storm::utility::vector::addVectorsInPlace(b, subStateRewards);
} }

93
src/modelchecker/prctl/SparseMdpPrctlModelChecker.h
View File

@ -94,37 +94,49 @@ public:
// First, we need to compute the states that satisfy the sub-formulas of the until-formula. // First, we need to compute the states that satisfy the sub-formulas of the until-formula.
storm::storage::BitVector* leftStates = formula.getLeft().check(*this); storm::storage::BitVector* leftStates = formula.getLeft().check(*this);
storm::storage::BitVector* rightStates = formula.getRight().check(*this); storm::storage::BitVector* rightStates = formula.getRight().check(*this);
std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates());
// Determine the states that have 0 probability of reaching the target states. // Determine the states that have 0 probability of reaching the target states.
storm::storage::BitVector maybeStates;
storm::storage::BitVector statesWithProbabilityGreater0;
if (this->minimumOperatorStack.top()) { if (this->minimumOperatorStack.top()) {
maybeStates = storm::utility::graph::performProbGreater0A(this->getModel(), this->getModel().getBackwardTransitions(), *leftStates, *rightStates, true, formula.getBound());
statesWithProbabilityGreater0 = storm::utility::graph::performProbGreater0A(this->getModel(), this->getModel().getBackwardTransitions(), *leftStates, *rightStates, true, formula.getBound());
} else { } else {
maybeStates = storm::utility::graph::performProbGreater0E(this->getModel(), this->getModel().getBackwardTransitions(), *leftStates, *rightStates, true, formula.getBound());
statesWithProbabilityGreater0 = storm::utility::graph::performProbGreater0E(this->getModel(), this->getModel().getBackwardTransitions(), *leftStates, *rightStates, true, formula.getBound());
} }
// Now we can eliminate the rows and columns from the original transition probability matrix that have probability 0.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates, this->getModel().getNondeterministicChoiceIndices());
// Check if we already know the result (i.e. probability 0) for all initial states and
// don't compute anything in this case.
if (this->getInitialStates().isDisjointFrom(statesWithProbabilityGreater0)) {
LOG4CPLUS_INFO(logger, "The probabilities for the initial states were determined in a preprocessing step."
<< " No exact probabilities were computed.");
// Set the values for all maybe-states to 0.5 to indicate that their probability values are not 0 (and
// not necessarily 1).
storm::utility::vector::setVectorValues(*result, statesWithProbabilityGreater0, Type(0.5));
} else {
// In this case we have have to compute the probabilities.
// Get the "new" nondeterministic choice indices for the submatrix.
std::vector<uint_fast64_t> subNondeterministicChoiceIndices = this->computeNondeterministicChoiceIndicesForConstraint(maybeStates);
// We can eliminate the rows and columns from the original transition probability matrix that have probability 0.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(statesWithProbabilityGreater0, this->getModel().getNondeterministicChoiceIndices());
// Compute the new set of target states in the reduced system.
storm::storage::BitVector rightStatesInReducedSystem = maybeStates % *rightStates;
// Get the "new" nondeterministic choice indices for the submatrix.
std::vector<uint_fast64_t> subNondeterministicChoiceIndices = this->computeNondeterministicChoiceIndicesForConstraint(statesWithProbabilityGreater0);
// Make all rows absorbing that satisfy the second sub-formula.
submatrix.makeRowsAbsorbing(rightStatesInReducedSystem, subNondeterministicChoiceIndices);
// Compute the new set of target states in the reduced system.
storm::storage::BitVector rightStatesInReducedSystem = statesWithProbabilityGreater0 % *rightStates;
// Create the vector with which to multiply.
std::vector<Type> subresult(maybeStates.getNumberOfSetBits());
storm::utility::vector::setVectorValues(subresult, rightStatesInReducedSystem, storm::utility::constGetOne<Type>());
// Make all rows absorbing that satisfy the second sub-formula.
submatrix.makeRowsAbsorbing(rightStatesInReducedSystem, subNondeterministicChoiceIndices);
this->performMatrixVectorMultiplication(submatrix, subresult, subNondeterministicChoiceIndices, nullptr, formula.getBound());
// Create the vector with which to multiply.
std::vector<Type> subresult(statesWithProbabilityGreater0.getNumberOfSetBits());
storm::utility::vector::setVectorValues(subresult, rightStatesInReducedSystem, storm::utility::constGetOne<Type>());
// Create the resulting vector.
std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates());
storm::utility::vector::setVectorValues(*result, maybeStates, subresult);
storm::utility::vector::setVectorValues(*result, ~maybeStates, storm::utility::constGetZero<Type>());
this->performMatrixVectorMultiplication(submatrix, subresult, subNondeterministicChoiceIndices, nullptr, formula.getBound());
// Set the values of the resulting vector accordingly.
storm::utility::vector::setVectorValues(*result, statesWithProbabilityGreater0, subresult);
storm::utility::vector::setVectorValues(*result, ~statesWithProbabilityGreater0, storm::utility::constGetZero<Type>());
}
// Delete intermediate results and return result. // Delete intermediate results and return result.
delete leftStates; delete leftStates;
@ -246,17 +258,28 @@ public:
delete leftStates; delete leftStates;
delete rightStates; delete rightStates;
storm::storage::BitVector maybeStates = ~(statesWithProbability0 | statesWithProbability1);
LOG4CPLUS_INFO(logger, "Found " << statesWithProbability0.getNumberOfSetBits() << " 'no' states."); LOG4CPLUS_INFO(logger, "Found " << statesWithProbability0.getNumberOfSetBits() << " 'no' states.");
LOG4CPLUS_INFO(logger, "Found " << statesWithProbability1.getNumberOfSetBits() << " 'yes' states."); LOG4CPLUS_INFO(logger, "Found " << statesWithProbability1.getNumberOfSetBits() << " 'yes' states.");
storm::storage::BitVector maybeStates = ~(statesWithProbability0 | statesWithProbability1);
LOG4CPLUS_INFO(logger, "Found " << maybeStates.getNumberOfSetBits() << " 'maybe' states."); LOG4CPLUS_INFO(logger, "Found " << maybeStates.getNumberOfSetBits() << " 'maybe' states.");
// Create resulting vector. // Create resulting vector.
std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates()); std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates());
// Only try to solve system if there are states for which the probability is unknown.
uint_fast64_t maybeStatesSetBitCount = maybeStates.getNumberOfSetBits();
if (maybeStatesSetBitCount > 0) {
// Check whether we need to compute exact probabilities for some states.
if (this->getInitialStates().isDisjointFrom(maybeStates) || qualitative) {
if (qualitative) {
LOG4CPLUS_INFO(logger, "The formula was checked qualitatively. No exact probabilities were computed.");
} else {
LOG4CPLUS_INFO(logger, "The probabilities for the initial states were determined in a preprocessing step."
<< " No exact probabilities were computed.");
}
// Set the values for all maybe-states to 0.5 to indicate that their probability values
// are neither 0 nor 1.
storm::utility::vector::setVectorValues<Type>(*result, maybeStates, Type(0.5));
} else {
// In this case we have have to compute the probabilities.
// First, we can eliminate the rows and columns from the original transition probability matrix for states // First, we can eliminate the rows and columns from the original transition probability matrix for states
// whose probabilities are already known. // whose probabilities are already known.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates, this->getModel().getNondeterministicChoiceIndices()); storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates, this->getModel().getNondeterministicChoiceIndices());
@ -265,7 +288,7 @@ public:
std::vector<uint_fast64_t> subNondeterministicChoiceIndices = this->computeNondeterministicChoiceIndicesForConstraint(maybeStates); std::vector<uint_fast64_t> subNondeterministicChoiceIndices = this->computeNondeterministicChoiceIndicesForConstraint(maybeStates);
// Create vector for results for maybe states. // Create vector for results for maybe states.
std::vector<Type> x(maybeStatesSetBitCount);
std::vector<Type> x(maybeStates.getNumberOfSetBits());
// Prepare the right-hand side of the equation system. For entry i this corresponds to // Prepare the right-hand side of the equation system. For entry i this corresponds to
// the accumulated probability of going from state i to some 'yes' state. // the accumulated probability of going from state i to some 'yes' state.
@ -385,27 +408,33 @@ public:
infinityStates = storm::utility::graph::performProb1E(this->getModel(), this->getModel().getBackwardTransitions(), trueStates, *targetStates); infinityStates = storm::utility::graph::performProb1E(this->getModel(), this->getModel().getBackwardTransitions(), trueStates, *targetStates);
} }
infinityStates.complement(); infinityStates.complement();
storm::storage::BitVector maybeStates = ~(*targetStates) & ~infinityStates;
LOG4CPLUS_INFO(logger, "Found " << infinityStates.getNumberOfSetBits() << " 'infinity' states."); LOG4CPLUS_INFO(logger, "Found " << infinityStates.getNumberOfSetBits() << " 'infinity' states.");
LOG4CPLUS_INFO(logger, "Found " << targetStates->getNumberOfSetBits() << " 'target' states."); LOG4CPLUS_INFO(logger, "Found " << targetStates->getNumberOfSetBits() << " 'target' states.");
storm::storage::BitVector maybeStates = ~(*targetStates) & ~infinityStates;
LOG4CPLUS_INFO(logger, "Found " << maybeStates.getNumberOfSetBits() << " 'maybe' states."); LOG4CPLUS_INFO(logger, "Found " << maybeStates.getNumberOfSetBits() << " 'maybe' states.");
// Create resulting vector. // Create resulting vector.
std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates()); std::vector<Type>* result = new std::vector<Type>(this->getModel().getNumberOfStates());
// Check whether there are states for which we have to compute the result.
const int maybeStatesSetBitCount = maybeStates.getNumberOfSetBits();
if (maybeStatesSetBitCount > 0) {
// First, we can eliminate the rows and columns from the original transition probability matrix for states
// whose probabilities are already known.
// Check whether we need to compute exact rewards for some states.
if (this->getInitialStates().isDisjointFrom(maybeStates)) {
LOG4CPLUS_INFO(logger, "The rewards for the initial states were determined in a preprocessing step."
<< " No exact rewards were computed.");
// Set the values for all maybe-states to 1 to indicate that their reward values
// are neither 0 nor infinity.
storm::utility::vector::setVectorValues<Type>(*result, maybeStates, storm::utility::constGetOne<Type>());
} else {
// In this case we have to compute the reward values for the remaining states.
// We can eliminate the rows and columns from the original transition probability matrix for states
// whose reward values are already known.
storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates, this->getModel().getNondeterministicChoiceIndices()); storm::storage::SparseMatrix<Type> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(maybeStates, this->getModel().getNondeterministicChoiceIndices());
// Get the "new" nondeterministic choice indices for the submatrix. // Get the "new" nondeterministic choice indices for the submatrix.
std::vector<uint_fast64_t> subNondeterministicChoiceIndices = this->computeNondeterministicChoiceIndicesForConstraint(maybeStates); std::vector<uint_fast64_t> subNondeterministicChoiceIndices = this->computeNondeterministicChoiceIndicesForConstraint(maybeStates);
// Create vector for results for maybe states. // Create vector for results for maybe states.
std::vector<Type> x(maybeStatesSetBitCount);
std::vector<Type> x(submatrix.getRowCount());
// Prepare the right-hand side of the equation system. For entry i this corresponds to // Prepare the right-hand side of the equation system. For entry i this corresponds to
// the accumulated probability of going from state i to some 'yes' state. // the accumulated probability of going from state i to some 'yes' state.

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