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@ -453,6 +453,22 @@ namespace storm { |
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return result; |
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} |
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template<typename ValueType, typename RewardModelType> |
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storm::storage::BitVector SparseDtmcPrctlHelper<ValueType, RewardModelType>::BaierTransformedModel::getNewRelevantStates() const { |
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storm::storage::BitVector newRelevantStates(transitionMatrix.get().getRowCount()); |
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for (uint64_t i = 0; i < this->beforeStates.getNumberOfSetBits(); ++i) { |
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newRelevantStates.set(i); |
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} |
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return newRelevantStates; |
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} |
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template<typename ValueType, typename RewardModelType> |
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storm::storage::BitVector SparseDtmcPrctlHelper<ValueType, RewardModelType>::BaierTransformedModel::getNewRelevantStates(storm::storage::BitVector const& oldRelevantStates) const { |
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storm::storage::BitVector result = oldRelevantStates % this->beforeStates; |
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result.resize(transitionMatrix.get().getRowCount()); |
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return result; |
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} |
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template<typename ValueType, typename RewardModelType> |
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std::vector<ValueType> SparseDtmcPrctlHelper<ValueType, RewardModelType>::computeConditionalProbabilities(Environment const& env, storm::solver::SolveGoal<ValueType>&& goal, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, storm::storage::BitVector const& targetStates, storm::storage::BitVector const& conditionStates, bool qualitative, storm::solver::LinearEquationSolverFactory<ValueType> const& linearEquationSolverFactory) { |
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@ -472,6 +488,13 @@ namespace storm { |
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// Now compute reachability probabilities in the transformed model.
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storm::storage::SparseMatrix<ValueType> const& newTransitionMatrix = transformedModel.transitionMatrix.get(); |
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storm::storage::BitVector newRelevantValues; |
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if (goal.hasRelevantValues()) { |
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newRelevantValues = transformedModel.getNewRelevantStates(goal.relevantValues()); |
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} else { |
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newRelevantValues = transformedModel.getNewRelevantStates(); |
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} |
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goal.setRelevantValues(std::move(newRelevantValues)); |
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std::vector<ValueType> conditionalProbabilities = computeUntilProbabilities(env, std::move(goal), newTransitionMatrix, newTransitionMatrix.transpose(), storm::storage::BitVector(newTransitionMatrix.getRowCount(), true), transformedModel.targetStates.get(), qualitative, linearEquationSolverFactory); |
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storm::utility::vector::setVectorValues(result, transformedModel.beforeStates, conditionalProbabilities); |
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@ -498,6 +521,13 @@ namespace storm { |
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// Now compute reachability probabilities in the transformed model.
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storm::storage::SparseMatrix<ValueType> const& newTransitionMatrix = transformedModel.transitionMatrix.get(); |
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storm::storage::BitVector newRelevantValues; |
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if (goal.hasRelevantValues()) { |
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newRelevantValues = transformedModel.getNewRelevantStates(goal.relevantValues()); |
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} else { |
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newRelevantValues = transformedModel.getNewRelevantStates(); |
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} |
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goal.setRelevantValues(std::move(newRelevantValues)); |
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std::vector<ValueType> conditionalRewards = computeReachabilityRewards(env, std::move(goal), newTransitionMatrix, newTransitionMatrix.transpose(), transformedModel.stateRewards.get(), transformedModel.targetStates.get(), qualitative, linearEquationSolverFactory); |
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storm::utility::vector::setVectorValues(result, transformedModel.beforeStates, conditionalRewards); |
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} |
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