792 lines
53 KiB
792 lines
53 KiB
#ifndef STORM_ADAPTERS_EXPLICITMODELADAPTER_H
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#define STORM_ADAPTERS_EXPLICITMODELADAPTER_H
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#include <memory>
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#include <unordered_map>
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#include <utility>
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#include <vector>
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#include <queue>
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#include <cstdint>
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#include <boost/functional/hash.hpp>
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#include <boost/container/flat_set.hpp>
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#include <boost/algorithm/string.hpp>
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#include "src/storage/prism/Program.h"
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#include "src/storage/expressions/SimpleValuation.h"
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#include "src/storage/expressions/ExprtkExpressionEvaluator.h"
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#include "src/storage/BitVectorHashMap.h"
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#include "src/utility/PrismUtility.h"
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#include "src/models/AbstractModel.h"
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#include "src/models/Dtmc.h"
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#include "src/models/Ctmc.h"
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#include "src/models/Mdp.h"
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#include "src/models/Ctmdp.h"
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#include "src/models/AtomicPropositionsLabeling.h"
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#include "src/storage/SparseMatrix.h"
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#include "src/settings/SettingsManager.h"
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#include "src/utility/macros.h"
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#include "src/exceptions/WrongFormatException.h"
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namespace storm {
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namespace adapters {
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using namespace storm::utility::prism;
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template<typename ValueType>
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class ExplicitModelAdapter {
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public:
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typedef storm::storage::BitVector StateType;
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// A structure holding information about the reachable state space.
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struct StateInformation {
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StateInformation(uint64_t bitsPerState) : reachableStates(), stateToIndexMap(bitsPerState, 100000) {
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// Intentionally left empty.
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}
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// The number of bits of each state.
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uint64_t bitsPerState;
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// A list of reachable states as indices in the stateToIndexMap.
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std::vector<std::size_t> reachableStates;
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// A list of initial states in terms of their global indices.
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std::vector<uint32_t> initialStateIndices;
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// A mapping from reachable states to their indices.
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storm::storage::BitVectorHashMap<uint32_t> stateToIndexMap;
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};
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// A structure storing information about the used variables of the program.
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struct VariableInformation {
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struct BooleanVariableInformation {
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BooleanVariableInformation(storm::expressions::Variable const& variable, bool initialValue, uint_fast64_t bitOffset) : variable(variable), initialValue(initialValue), bitOffset(bitOffset) {
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// Intentionally left empty.
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}
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storm::expressions::Variable variable;
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bool initialValue;
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uint_fast64_t bitOffset;
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};
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struct IntegerVariableInformation {
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IntegerVariableInformation(storm::expressions::Variable const& variable, int_fast64_t initialValue, int_fast64_t lowerBound, int_fast64_t upperBound, uint_fast64_t bitOffset, uint_fast64_t bitWidth) : variable(variable), initialValue(initialValue), lowerBound(lowerBound), upperBound(upperBound), bitOffset(bitOffset), bitWidth(bitWidth) {
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// Intentionally left empty.
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}
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storm::expressions::Variable variable;
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int_fast64_t initialValue;
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int_fast64_t lowerBound;
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int_fast64_t upperBound;
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uint_fast64_t bitOffset;
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uint_fast64_t bitWidth;
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};
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uint_fast64_t getBitOffset(storm::expressions::Variable const& variable) const {
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auto const& booleanIndex = booleanVariableToIndexMap.find(variable);
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if (booleanIndex != booleanVariableToIndexMap.end()) {
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return booleanVariables[booleanIndex].bitOffset;
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}
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auto const& integerIndex = integerVariableToIndexMap.find(variable);
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if (integerIndex != integerVariableToIndexMap.end()) {
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return integerVariables[integerIndex].bitOffset;
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}
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STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "Cannot look-up bit index of unknown variable.");
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}
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uint_fast64_t getBitWidth(storm::expressions::Variable const& variable) const {
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auto const& integerIndex = integerVariableToIndexMap.find(variable);
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if (integerIndex != integerVariableToIndexMap.end()) {
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return integerVariables[integerIndex].bitWidth;
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}
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STORM_LOG_THROW(false, storm::exceptions::InvalidArgumentException, "Cannot look-up bit width of unknown variable.");
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}
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// The list of boolean variables.
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std::map<storm::expressions::Variable, uint_fast64_t> booleanVariableToIndexMap;
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std::vector<BooleanVariableInformation> booleanVariables;
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// The list of integer variables.
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std::map<storm::expressions::Variable, uint_fast64_t> integerVariableToIndexMap;
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std::vector<IntegerVariableInformation> integerVariables;
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};
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// A structure holding the individual components of a model.
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struct ModelComponents {
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ModelComponents() : transitionMatrix(), stateLabeling(), stateRewards(), transitionRewardMatrix(), choiceLabeling() {
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// Intentionally left empty.
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}
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// The transition matrix.
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storm::storage::SparseMatrix<ValueType> transitionMatrix;
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// The state labeling.
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storm::models::AtomicPropositionsLabeling stateLabeling;
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// The state reward vector.
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std::vector<ValueType> stateRewards;
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// A matrix storing the reward for particular transitions.
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storm::storage::SparseMatrix<ValueType> transitionRewardMatrix;
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// A vector that stores a labeling for each choice.
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std::vector<boost::container::flat_set<uint_fast64_t>> choiceLabeling;
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};
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/*!
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* Convert the program given at construction time to an abstract model. The type of the model is the one
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* specified in the program. The given reward model name selects the rewards that the model will contain.
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*
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* @param program The program to translate.
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* @param constantDefinitionString A string that contains a comma-separated definition of all undefined
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* constants in the model.
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* @param rewardModel The reward model that is to be built.
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* @return The explicit model that was given by the probabilistic program.
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*/
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static std::unique_ptr<storm::models::AbstractModel<ValueType>> translateProgram(storm::prism::Program program, bool rewards = true, std::string const& rewardModelName = "", std::string const& constantDefinitionString = "") {
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// Start by defining the undefined constants in the model.
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// First, we need to parse the constant definition string.
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std::map<storm::expressions::Variable, storm::expressions::Expression> constantDefinitions = storm::utility::prism::parseConstantDefinitionString(program, constantDefinitionString);
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storm::prism::Program preparedProgram = program.defineUndefinedConstants(constantDefinitions);
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STORM_LOG_THROW(!preparedProgram.hasUndefinedConstants(), storm::exceptions::InvalidArgumentException, "Program still contains undefined constants.");
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// Now that we have defined all the constants in the program, we need to substitute their appearances in
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// all expressions in the program so we can then evaluate them without having to store the values of the
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// constants in the state (i.e., valuation).
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preparedProgram = preparedProgram.substituteConstants();
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storm::prism::RewardModel rewardModel = storm::prism::RewardModel();
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// Select the appropriate reward model.
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if (rewards) {
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// If a specific reward model was selected or one with the empty name exists, select it.
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if (rewardModelName != "" || preparedProgram.hasRewardModel(rewardModelName)) {
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rewardModel = preparedProgram.getRewardModel(rewardModelName);
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} else if (preparedProgram.hasRewardModel()) {
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// Otherwise, we select the first one.
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rewardModel = preparedProgram.getRewardModel(0);
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}
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}
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ModelComponents modelComponents = buildModelComponents(preparedProgram, rewardModel);
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std::unique_ptr<storm::models::AbstractModel<ValueType>> result;
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switch (program.getModelType()) {
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case storm::prism::Program::ModelType::DTMC:
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result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Dtmc<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModel.hasStateRewards() ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModel.hasTransitionRewards() ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
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break;
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case storm::prism::Program::ModelType::CTMC:
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result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Ctmc<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModel.hasStateRewards() ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModel.hasTransitionRewards() ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
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break;
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case storm::prism::Program::ModelType::MDP:
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result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Mdp<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModel.hasStateRewards() ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModel.hasTransitionRewards() ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
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break;
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case storm::prism::Program::ModelType::CTMDP:
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result = std::unique_ptr<storm::models::AbstractModel<ValueType>>(new storm::models::Ctmdp<ValueType>(std::move(modelComponents.transitionMatrix), std::move(modelComponents.stateLabeling), rewardModel.hasStateRewards() ? std::move(modelComponents.stateRewards) : boost::optional<std::vector<ValueType>>(), rewardModel.hasTransitionRewards() ? std::move(modelComponents.transitionRewardMatrix) : boost::optional<storm::storage::SparseMatrix<ValueType>>(), std::move(modelComponents.choiceLabeling)));
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break;
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default:
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LOG4CPLUS_ERROR(logger, "Error while creating model from probabilistic program: cannot handle this model type.");
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throw storm::exceptions::WrongFormatException() << "Error while creating model from probabilistic program: cannot handle this model type.";
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break;
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}
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return result;
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}
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private:
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static void unpackStateIntoEvaluator(storm::storage::BitVector const& currentState, VariableInformation const& variableInformation, storm::expressions::ExprtkExpressionEvaluator& evaluator) {
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for (auto const& booleanVariable : variableInformation.booleanVariables) {
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evaluator.setBooleanValue(booleanVariable.variable, currentState.get(booleanVariable.bitOffset));
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}
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for (auto const& integerVariable : variableInformation.integerVariables) {
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evaluator.setIntegerValue(integerVariable.variable, currentState.getAsInt(integerVariable.bitOffset, integerVariable.bitWidth) + integerVariable.lowerBound);
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}
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}
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/*!
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* Applies an update to the given state and returns the resulting new state object. This methods does not
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* modify the given state but returns a new one.
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*
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* @params state The state to which to apply the update.
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* @params update The update to apply.
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* @return The resulting state.
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*/
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static StateType applyUpdate(VariableInformation const& variableInformation, StateType const& state, storm::prism::Update const& update, storm::expressions::ExprtkExpressionEvaluator const& evaluator) {
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return applyUpdate(variableInformation, state, state, update, evaluator);
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}
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/*!
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* Applies an update to the given state and returns the resulting new state object. The update is evaluated
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* over the variable values of the given base state. This methods does not modify the given state but
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* returns a new one.
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*
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* @param state The state to which to apply the update.
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* @param baseState The state used for evaluating the update.
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* @param update The update to apply.
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* @return The resulting state.
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*/
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static StateType applyUpdate(VariableInformation const& variableInformation, StateType const& state, StateType const& baseState, storm::prism::Update const& update, storm::expressions::ExprtkExpressionEvaluator const& evaluator) {
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StateType newState(state);
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auto assignmentIt = update.getAssignments().begin();
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auto assignmentIte = update.getAssignments().end();
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// Iterate over all boolean assignments and carry them out.
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auto boolIt = variableInformation.booleanVariables.begin();
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for (; assignmentIt != assignmentIte && assignmentIt->getExpression().hasBooleanType(); ++assignmentIt) {
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while (assignmentIt->getVariable() != boolIt->variable) {
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++boolIt;
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}
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newState.set(boolIt->bitOffset, evaluator.asBool(assignmentIt->getExpression()));
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}
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// Iterate over all integer assignments and carry them out.
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auto integerIt = variableInformation.integerVariables.begin();
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for (; assignmentIt != assignmentIte && assignmentIt->getExpression().hasIntegerType(); ++assignmentIt) {
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while (assignmentIt->getVariable() != integerIt->variable) {
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++integerIt;
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}
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newState.setFromInt(integerIt->bitOffset, integerIt->bitWidth, evaluator.asInt(assignmentIt->getExpression()) - integerIt->lowerBound);
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}
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// Check that we processed all assignments.
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STORM_LOG_ASSERT(assignmentIt == assignmentIte, "Not all assignments were consumed.");
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return newState;
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}
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/*!
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* Retrieves the state id of the given state. If the state has not been encountered yet, it will be added to
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* the lists of all states with a new id. If the state was already known, the object that is pointed to by
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* the given state pointer is deleted and the old state id is returned. Note that the pointer should not be
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* used after invoking this method.
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*
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* @param state A pointer to a state for which to retrieve the index. This must not be used after the call.
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* @param stateInformation The information about the already explored part of the reachable state space.
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* @return A pair indicating whether the state was already discovered before and the state id of the state.
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*/
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static uint32_t getOrAddStateIndex(StateType const& state, StateInformation& stateInformation, std::queue<std::size_t>& stateQueue) {
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uint32_t newIndex = stateInformation.reachableStates.size();
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// Check, if the state was already registered.
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std::pair<uint32_t, std::size_t> actualIndexBucketPair = stateInformation.stateToIndexMap.findOrAddAndGetBucket(state, newIndex);
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if (actualIndexBucketPair.first == newIndex) {
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stateQueue.push(actualIndexBucketPair.second);
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stateInformation.reachableStates.push_back(actualIndexBucketPair.second);
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}
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return actualIndexBucketPair.first;
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}
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/*!
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* Retrieves all commands that are labeled with the given label and enabled in the given state, grouped by
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* modules.
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*
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* This function will iterate over all modules and retrieve all commands that are labeled with the given
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* action and active (i.e. enabled) in the current state. The result is a list of lists of commands in which
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* the inner lists contain all commands of exactly one module. If a module does not have *any* (including
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* disabled) commands, there will not be a list of commands of that module in the result. If, however, the
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* module has a command with a relevant label, but no enabled one, nothing is returned to indicate that there
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* is no legal transition possible.
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*
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* @param The program in which to search for active commands.
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* @param state The current state.
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* @param actionIndex The index of the action label to select.
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* @return A list of lists of active commands or nothing.
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*/
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static boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> getActiveCommandsByActionIndex(storm::prism::Program const& program,storm::expressions::ExprtkExpressionEvaluator const& evaluator, uint_fast64_t const& actionIndex) {
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boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> result((std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>()));
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// Iterate over all modules.
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for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
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storm::prism::Module const& module = program.getModule(i);
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// If the module has no command labeled with the given action, we can skip this module.
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if (!module.hasActionIndex(actionIndex)) {
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continue;
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}
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std::set<uint_fast64_t> const& commandIndices = module.getCommandIndicesByActionIndex(actionIndex);
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// If the module contains the action, but there is no command in the module that is labeled with
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// this action, we don't have any feasible command combinations.
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if (commandIndices.empty()) {
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return boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>>();
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}
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std::vector<std::reference_wrapper<storm::prism::Command const>> commands;
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// Look up commands by their indices and add them if the guard evaluates to true in the given state.
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for (uint_fast64_t commandIndex : commandIndices) {
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storm::prism::Command const& command = module.getCommand(commandIndex);
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if (evaluator.asBool(command.getGuardExpression())) {
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commands.push_back(command);
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}
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}
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// If there was no enabled command although the module has some command with the required action label,
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// we must not return anything.
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if (commands.size() == 0) {
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return boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>>();
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}
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result.get().push_back(std::move(commands));
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}
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return result;
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}
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static std::vector<Choice<ValueType>> getUnlabeledTransitions(storm::prism::Program const& program, StateInformation& stateInformation, VariableInformation const& variableInformation, storm::storage::BitVector const& currentState, storm::expressions::ExprtkExpressionEvaluator const& evaluator, std::queue<std::size_t>& stateQueue) {
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std::vector<Choice<ValueType>> result;
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// Iterate over all modules.
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for (uint_fast64_t i = 0; i < program.getNumberOfModules(); ++i) {
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storm::prism::Module const& module = program.getModule(i);
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// Iterate over all commands.
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for (uint_fast64_t j = 0; j < module.getNumberOfCommands(); ++j) {
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storm::prism::Command const& command = module.getCommand(j);
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// Only consider unlabeled commands.
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if (command.isLabeled()) continue;
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// Skip the command, if it is not enabled.
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if (!evaluator.asBool(command.getGuardExpression())) {
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continue;
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}
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result.push_back(Choice<ValueType>());
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Choice<ValueType>& choice = result.back();
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choice.addChoiceLabel(command.getGlobalIndex());
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// Iterate over all updates of the current command.
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double probabilitySum = 0;
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for (uint_fast64_t k = 0; k < command.getNumberOfUpdates(); ++k) {
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storm::prism::Update const& update = command.getUpdate(k);
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// Obtain target state index and add it to the list of known states. If it has not yet been
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// seen, we also add it to the set of states that have yet to be explored.
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uint32_t stateIndex = getOrAddStateIndex(applyUpdate(variableInformation, currentState, update, evaluator), stateInformation, stateQueue);
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// Update the choice by adding the probability/target state to it.
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choice.addProbability(stateIndex, evaluator.asDouble(update.getLikelihoodExpression()));
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}
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// Check that the resulting distribution is in fact a distribution.
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STORM_LOG_THROW(std::abs(1 - probabilitySum) < storm::settings::generalSettings().getPrecision(), storm::exceptions::WrongFormatException, "Probabilities do not sum to one for command '" << command << "'.");
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}
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}
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return result;
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}
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static std::vector<Choice<ValueType>> getLabeledTransitions(storm::prism::Program const& program, StateInformation& stateInformation, VariableInformation const& variableInformation, storm::storage::BitVector const& currentState, storm::expressions::ExprtkExpressionEvaluator const& evaluator, std::queue<std::size_t>& stateQueue) {
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std::vector<Choice<ValueType>> result;
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for (uint_fast64_t actionIndex : program.getActionIndices()) {
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boost::optional<std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>>> optionalActiveCommandLists = getActiveCommandsByActionIndex(program, evaluator, actionIndex);
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// Only process this action label, if there is at least one feasible solution.
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if (optionalActiveCommandLists) {
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std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>> const& activeCommandList = optionalActiveCommandLists.get();
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std::vector<std::vector<std::reference_wrapper<storm::prism::Command const>>::const_iterator> iteratorList(activeCommandList.size());
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// Initialize the list of iterators.
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for (size_t i = 0; i < activeCommandList.size(); ++i) {
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iteratorList[i] = activeCommandList[i].cbegin();
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}
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// As long as there is one feasible combination of commands, keep on expanding it.
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bool done = false;
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while (!done) {
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std::unordered_map<StateType, ValueType>* currentTargetStates = new std::unordered_map<StateType, ValueType>();
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std::unordered_map<StateType, ValueType>* newTargetStates = new std::unordered_map<StateType, ValueType>();
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currentTargetStates->emplace(currentState, storm::utility::one<ValueType>());
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// FIXME: This does not check whether a global variable is written multiple times. While the
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// behaviour for this is undefined anyway, a warning should be issued in that case.
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|
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
|
|
storm::prism::Command const& command = *iteratorList[i];
|
|
|
|
for (uint_fast64_t j = 0; j < command.getNumberOfUpdates(); ++j) {
|
|
storm::prism::Update const& update = command.getUpdate(j);
|
|
|
|
for (auto const& stateProbabilityPair : *currentTargetStates) {
|
|
// Compute the new state under the current update and add it to the set of new target states.
|
|
StateType newTargetState = applyUpdate(variableInformation, stateProbabilityPair.first, currentState, update, evaluator);
|
|
newTargetStates->emplace(newTargetState, stateProbabilityPair.second * evaluator.asDouble(update.getLikelihoodExpression()));
|
|
}
|
|
}
|
|
|
|
// If there is one more command to come, shift the target states one time step back.
|
|
if (i < iteratorList.size() - 1) {
|
|
delete currentTargetStates;
|
|
currentTargetStates = newTargetStates;
|
|
newTargetStates = new std::unordered_map<StateType, ValueType>();
|
|
}
|
|
}
|
|
|
|
// At this point, we applied all commands of the current command combination and newTargetStates
|
|
// contains all target states and their respective probabilities. That means we are now ready to
|
|
// add the choice to the list of transitions.
|
|
result.push_back(Choice<ValueType>(actionIndex));
|
|
|
|
// Now create the actual distribution.
|
|
Choice<ValueType>& choice = result.back();
|
|
|
|
// Add the labels of all commands to this choice.
|
|
for (uint_fast64_t i = 0; i < iteratorList.size(); ++i) {
|
|
choice.addChoiceLabel(iteratorList[i]->get().getGlobalIndex());
|
|
}
|
|
|
|
double probabilitySum = 0;
|
|
for (auto const& stateProbabilityPair : *newTargetStates) {
|
|
uint32_t actualIndex = getOrAddStateIndex(stateProbabilityPair.first, stateInformation, stateQueue);
|
|
choice.addProbability(actualIndex, stateProbabilityPair.second);
|
|
}
|
|
|
|
// Check that the resulting distribution is in fact a distribution.
|
|
if (std::abs(1 - probabilitySum) > storm::settings::generalSettings().getPrecision()) {
|
|
LOG4CPLUS_ERROR(logger, "Sum of update probabilities do not some to one for some command.");
|
|
throw storm::exceptions::WrongFormatException() << "Sum of update probabilities do not some to one for some command.";
|
|
}
|
|
|
|
// Dispose of the temporary maps.
|
|
delete currentTargetStates;
|
|
delete newTargetStates;
|
|
|
|
// Now, check whether there is one more command combination to consider.
|
|
bool movedIterator = false;
|
|
for (int_fast64_t j = iteratorList.size() - 1; j >= 0; --j) {
|
|
++iteratorList[j];
|
|
if (iteratorList[j] != activeCommandList[j].end()) {
|
|
movedIterator = true;
|
|
} else {
|
|
// Reset the iterator to the beginning of the list.
|
|
iteratorList[j] = activeCommandList[j].begin();
|
|
}
|
|
}
|
|
|
|
done = !movedIterator;
|
|
}
|
|
}
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
/*!
|
|
* Builds the transition matrix and the transition reward matrix based for the given program.
|
|
*
|
|
* @param program The program for which to build the matrices.
|
|
* @param variableInformation A structure containing information about the variables in the program.
|
|
* @param transitionRewards A list of transition rewards that are to be considered in the transition reward
|
|
* matrix.
|
|
* @param stateInformation A structure containing information about the states of the program.
|
|
* @param deterministicModel A flag indicating whether the model is supposed to be deterministic or not.
|
|
* @param transitionMatrix A reference to an initialized matrix which is filled with all transitions by this
|
|
* function.
|
|
* @param transitionRewardMatrix A reference to an initialized matrix which is filled with all transition
|
|
* rewards by this function.
|
|
* @return A tuple containing a vector with all rows at which the nondeterministic choices of each state begin
|
|
* and a vector containing the labels associated with each choice.
|
|
*/
|
|
static std::vector<boost::container::flat_set<uint_fast64_t>> buildMatrices(storm::prism::Program const& program, VariableInformation const& variableInformation, std::vector<storm::prism::TransitionReward> const& transitionRewards, StateInformation& stateInformation, bool deterministicModel, storm::storage::SparseMatrixBuilder<ValueType>& transitionMatrixBuilder, storm::storage::SparseMatrixBuilder<ValueType>& transitionRewardMatrixBuilder) {
|
|
std::vector<boost::container::flat_set<uint_fast64_t>> choiceLabels;
|
|
|
|
// Initialize a queue and insert the initial state.
|
|
std::queue<std::size_t> stateQueue;
|
|
StateType initialState(stateInformation.bitsPerState);
|
|
|
|
// We need to initialize the values of the variables to their initial value.
|
|
for (auto const& booleanVariable : variableInformation.booleanVariables) {
|
|
initialState.set(booleanVariable.bitOffset, booleanVariable.initialValue);
|
|
}
|
|
for (auto const& integerVariable : variableInformation.integerVariables) {
|
|
initialState.setFromInt(integerVariable.bitOffset, integerVariable.bitWidth, static_cast<uint_fast64_t>(integerVariable.initialValue - integerVariable.lowerBound));
|
|
}
|
|
|
|
// Insert the initial state in the global state to index mapping and state queue.
|
|
getOrAddStateIndex(initialState, stateInformation, stateQueue);
|
|
|
|
// Now explore the current state until there is no more reachable state.
|
|
uint_fast64_t currentRow = 0;
|
|
storm::expressions::ExprtkExpressionEvaluator evaluator(program.getManager());
|
|
while (!stateQueue.empty()) {
|
|
// Get the current state and unpack it.
|
|
std::size_t currentStateBucket = stateQueue.front();
|
|
std::pair<storm::storage::BitVector, uint32_t> stateValuePair = stateInformation.stateToIndexMap.getBucketAndValue(currentStateBucket);
|
|
storm::storage::BitVector const& currentState = stateValuePair.first;
|
|
unpackStateIntoEvaluator(currentState, variableInformation, evaluator);
|
|
|
|
// Retrieve all choices for the current state.
|
|
std::vector<Choice<ValueType>> allUnlabeledChoices = getUnlabeledTransitions(program, stateInformation, variableInformation, currentState, evaluator, stateQueue);
|
|
std::vector<Choice<ValueType>> allLabeledChoices = getLabeledTransitions(program, stateInformation, variableInformation, currentState, evaluator, stateQueue);
|
|
|
|
uint_fast64_t totalNumberOfChoices = allUnlabeledChoices.size() + allLabeledChoices.size();
|
|
|
|
// If the current state does not have a single choice, we equip it with a self-loop if that was
|
|
// requested and issue an error otherwise.
|
|
if (totalNumberOfChoices == 0) {
|
|
if (!storm::settings::generalSettings().isDontFixDeadlocksSet()) {
|
|
// Insert empty choice labeling for added self-loop transitions.
|
|
choiceLabels.push_back(boost::container::flat_set<uint_fast64_t>());
|
|
transitionMatrixBuilder.addNextValue(currentRow, stateValuePair.second, storm::utility::one<ValueType>());
|
|
++currentRow;
|
|
} else {
|
|
LOG4CPLUS_ERROR(logger, "Error while creating sparse matrix from probabilistic program: found deadlock state. For fixing these, please provide the appropriate option.");
|
|
throw storm::exceptions::WrongFormatException() << "Error while creating sparse matrix from probabilistic program: found deadlock state. For fixing these, please provide the appropriate option.";
|
|
}
|
|
} else {
|
|
// Then, based on whether the model is deterministic or not, either add the choices individually
|
|
// or compose them to one choice.
|
|
if (deterministicModel) {
|
|
Choice<ValueType> globalChoice;
|
|
std::map<uint32_t, ValueType> stateToRewardMap;
|
|
|
|
// Combine all the choices and scale them with the total number of choices of the current state.
|
|
for (auto const& choice : allUnlabeledChoices) {
|
|
globalChoice.addChoiceLabels(choice.getChoiceLabels());
|
|
for (auto const& stateProbabilityPair : choice) {
|
|
globalChoice.getOrAddEntry(stateProbabilityPair.first) += stateProbabilityPair.second / totalNumberOfChoices;
|
|
|
|
// Now add all rewards that match this choice.
|
|
for (auto const& transitionReward : transitionRewards) {
|
|
if (!transitionReward.isLabeled() && evaluator.asBool(transitionReward.getStatePredicateExpression())) {
|
|
stateToRewardMap[stateProbabilityPair.first] += ValueType(evaluator.asDouble(transitionReward.getRewardValueExpression()));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
for (auto const& choice : allLabeledChoices) {
|
|
globalChoice.addChoiceLabels(choice.getChoiceLabels());
|
|
for (auto const& stateProbabilityPair : choice) {
|
|
globalChoice.getOrAddEntry(stateProbabilityPair.first) += stateProbabilityPair.second / totalNumberOfChoices;
|
|
|
|
// Now add all rewards that match this choice.
|
|
for (auto const& transitionReward : transitionRewards) {
|
|
if (transitionReward.getActionIndex() == choice.getActionIndex() && evaluator.asBool(transitionReward.getStatePredicateExpression())) {
|
|
stateToRewardMap[stateProbabilityPair.first] += ValueType(evaluator.asDouble(transitionReward.getRewardValueExpression()));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
// Now add the resulting distribution as the only choice of the current state.
|
|
choiceLabels.push_back(globalChoice.getChoiceLabels());
|
|
|
|
for (auto const& stateProbabilityPair : globalChoice) {
|
|
transitionMatrixBuilder.addNextValue(currentRow, stateProbabilityPair.first, stateProbabilityPair.second);
|
|
}
|
|
|
|
// Add all transition rewards to the matrix and add dummy entry if there is none.
|
|
if (stateToRewardMap.size() > 0) {
|
|
for (auto const& stateRewardPair : stateToRewardMap) {
|
|
transitionRewardMatrixBuilder.addNextValue(currentRow, stateRewardPair.first, stateRewardPair.second);
|
|
}
|
|
}
|
|
|
|
++currentRow;
|
|
} else {
|
|
// If the model is nondeterministic, we add all choices individually.
|
|
transitionMatrixBuilder.newRowGroup(currentRow);
|
|
transitionRewardMatrixBuilder.newRowGroup(currentRow);
|
|
|
|
// First, process all unlabeled choices.
|
|
for (auto const& choice : allUnlabeledChoices) {
|
|
std::map<uint_fast64_t, ValueType> stateToRewardMap;
|
|
choiceLabels.emplace_back(std::move(choice.getChoiceLabels()));
|
|
|
|
for (auto const& stateProbabilityPair : choice) {
|
|
transitionMatrixBuilder.addNextValue(currentRow, stateProbabilityPair.first, stateProbabilityPair.second);
|
|
|
|
// Now add all rewards that match this choice.
|
|
for (auto const& transitionReward : transitionRewards) {
|
|
if (!transitionReward.isLabeled() && evaluator.asBool(transitionReward.getStatePredicateExpression())) {
|
|
stateToRewardMap[stateProbabilityPair.first] += ValueType(evaluator.asDouble(transitionReward.getRewardValueExpression()));
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
// Add all transition rewards to the matrix and add dummy entry if there is none.
|
|
if (stateToRewardMap.size() > 0) {
|
|
for (auto const& stateRewardPair : stateToRewardMap) {
|
|
transitionRewardMatrixBuilder.addNextValue(currentRow, stateRewardPair.first, stateRewardPair.second);
|
|
}
|
|
}
|
|
|
|
++currentRow;
|
|
}
|
|
|
|
// Then, process all labeled choices.
|
|
for (auto const& choice : allLabeledChoices) {
|
|
std::map<uint_fast64_t, ValueType> stateToRewardMap;
|
|
choiceLabels.emplace_back(std::move(choice.getChoiceLabels()));
|
|
|
|
for (auto const& stateProbabilityPair : choice) {
|
|
transitionMatrixBuilder.addNextValue(currentRow, stateProbabilityPair.first, stateProbabilityPair.second);
|
|
|
|
// Now add all rewards that match this choice.
|
|
for (auto const& transitionReward : transitionRewards) {
|
|
if (transitionReward.getActionIndex() == choice.getActionIndex() && evaluator.asBool(transitionReward.getStatePredicateExpression())) {
|
|
stateToRewardMap[stateProbabilityPair.first] += ValueType(evaluator.asDouble(transitionReward.getRewardValueExpression()));
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
// Add all transition rewards to the matrix and add dummy entry if there is none.
|
|
if (stateToRewardMap.size() > 0) {
|
|
for (auto const& stateRewardPair : stateToRewardMap) {
|
|
transitionRewardMatrixBuilder.addNextValue(currentRow, stateRewardPair.first, stateRewardPair.second);
|
|
}
|
|
}
|
|
|
|
++currentRow;
|
|
}
|
|
}
|
|
}
|
|
|
|
stateQueue.pop();
|
|
}
|
|
|
|
return choiceLabels;
|
|
}
|
|
|
|
/*!
|
|
* Explores the state space of the given program and returns the components of the model as a result.
|
|
*
|
|
* @param program The program whose state space to explore.
|
|
* @param rewardModel The reward model that is to be considered.
|
|
* @return A structure containing the components of the resulting model.
|
|
*/
|
|
static ModelComponents buildModelComponents(storm::prism::Program const& program, storm::prism::RewardModel const& rewardModel) {
|
|
ModelComponents modelComponents;
|
|
|
|
uint_fast64_t bitOffset = 0;
|
|
VariableInformation variableInformation;
|
|
for (auto const& booleanVariable : program.getGlobalBooleanVariables()) {
|
|
variableInformation.booleanVariables.emplace_back(booleanVariable.getExpressionVariable(), booleanVariable.getInitialValueExpression().evaluateAsBool(), bitOffset);
|
|
++bitOffset;
|
|
variableInformation.booleanVariableToIndexMap[booleanVariable.getExpressionVariable()] = variableInformation.booleanVariables.size() - 1;
|
|
}
|
|
for (auto const& integerVariable : program.getGlobalIntegerVariables()) {
|
|
int_fast64_t lowerBound = integerVariable.getLowerBoundExpression().evaluateAsInt();
|
|
int_fast64_t upperBound = integerVariable.getUpperBoundExpression().evaluateAsInt();
|
|
uint_fast64_t bitwidth = static_cast<uint_fast64_t>(std::ceil(std::log2(upperBound - lowerBound)));
|
|
variableInformation.integerVariables.emplace_back(integerVariable.getExpressionVariable(), integerVariable.getInitialValueExpression().evaluateAsInt(), lowerBound, upperBound, bitOffset, bitwidth);
|
|
bitOffset += bitwidth;
|
|
variableInformation.integerVariableToIndexMap[integerVariable.getExpressionVariable()] = variableInformation.integerVariables.size() - 1;
|
|
}
|
|
for (auto const& module : program.getModules()) {
|
|
for (auto const& booleanVariable : module.getBooleanVariables()) {
|
|
variableInformation.booleanVariables.emplace_back(booleanVariable.getExpressionVariable(), booleanVariable.getInitialValueExpression().evaluateAsBool(), bitOffset);
|
|
++bitOffset;
|
|
variableInformation.booleanVariableToIndexMap[booleanVariable.getExpressionVariable()] = variableInformation.booleanVariables.size() - 1;
|
|
}
|
|
for (auto const& integerVariable : module.getIntegerVariables()) {
|
|
int_fast64_t lowerBound = integerVariable.getLowerBoundExpression().evaluateAsInt();
|
|
int_fast64_t upperBound = integerVariable.getUpperBoundExpression().evaluateAsInt();
|
|
uint_fast64_t bitwidth = static_cast<uint_fast64_t>(std::ceil(std::log2(upperBound - lowerBound)));
|
|
variableInformation.integerVariables.emplace_back(integerVariable.getExpressionVariable(), integerVariable.getInitialValueExpression().evaluateAsInt(), lowerBound, upperBound, bitOffset, bitwidth);
|
|
bitOffset += bitwidth;
|
|
variableInformation.integerVariableToIndexMap[integerVariable.getExpressionVariable()] = variableInformation.integerVariables.size() - 1;
|
|
}
|
|
}
|
|
|
|
// Create the structure for storing the reachable state space.
|
|
uint64_t bitsPerState = ((bitOffset / 64) + 1) * 64;
|
|
StateInformation stateInformation(bitsPerState);
|
|
|
|
// Determine whether we have to combine different choices to one or whether this model can have more than
|
|
// one choice per state.
|
|
bool deterministicModel = program.getModelType() == storm::prism::Program::ModelType::DTMC || program.getModelType() == storm::prism::Program::ModelType::CTMC;
|
|
|
|
// Build the transition and reward matrices.
|
|
storm::storage::SparseMatrixBuilder<ValueType> transitionMatrixBuilder(0, 0, 0, false, !deterministicModel, 0);
|
|
storm::storage::SparseMatrixBuilder<ValueType> transitionRewardMatrixBuilder(0, 0, 0, false, !deterministicModel, 0);
|
|
modelComponents.choiceLabeling = buildMatrices(program, variableInformation, rewardModel.getTransitionRewards(), stateInformation, deterministicModel, transitionMatrixBuilder, transitionRewardMatrixBuilder);
|
|
|
|
// Finalize the resulting matrices.
|
|
modelComponents.transitionMatrix = transitionMatrixBuilder.build();
|
|
modelComponents.transitionRewardMatrix = transitionRewardMatrixBuilder.build(modelComponents.transitionMatrix.getRowCount(), modelComponents.transitionMatrix.getColumnCount(), modelComponents.transitionMatrix.getRowGroupCount());
|
|
|
|
// Now build the state labeling.
|
|
modelComponents.stateLabeling = buildStateLabeling(program, variableInformation, stateInformation);
|
|
|
|
// Finally, construct the state rewards.
|
|
modelComponents.stateRewards = buildStateRewards(program, variableInformation, rewardModel.getStateRewards(), stateInformation);
|
|
|
|
return modelComponents;
|
|
}
|
|
|
|
/*!
|
|
* Builds the state labeling for the given program.
|
|
*
|
|
* @param program The program for which to build the state labeling.
|
|
* @param variableInformation Information about the variables in the program.
|
|
* @param stateInformation Information about the state space of the program.
|
|
* @return The state labeling of the given program.
|
|
*/
|
|
static storm::models::AtomicPropositionsLabeling buildStateLabeling(storm::prism::Program const& program, VariableInformation const& variableInformation, StateInformation const& stateInformation) {
|
|
storm::expressions::ExprtkExpressionEvaluator evaluator(program.getManager());
|
|
|
|
std::vector<storm::prism::Label> const& labels = program.getLabels();
|
|
|
|
storm::models::AtomicPropositionsLabeling result(stateInformation.reachableStates.size(), labels.size() + 1);
|
|
|
|
// Initialize labeling.
|
|
for (auto const& label : labels) {
|
|
result.addAtomicProposition(label.getName());
|
|
}
|
|
for (uint_fast64_t index = 0; index < stateInformation.reachableStates.size(); index++) {
|
|
for (auto const& label : labels) {
|
|
unpackStateIntoEvaluator(stateInformation.stateToIndexMap.getValue(stateInformation.reachableStates[index]), variableInformation, evaluator);
|
|
|
|
// Add label to state, if the corresponding expression is true.
|
|
if (evaluator.asBool(label.getStatePredicateExpression())) {
|
|
result.addAtomicPropositionToState(label.getName(), index);
|
|
}
|
|
}
|
|
}
|
|
|
|
// Also label the initial state with the special label "init".
|
|
result.addAtomicProposition("init");
|
|
for (auto const& index : stateInformation.initialStateIndices) {
|
|
result.addAtomicPropositionToState("init", index);
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
/*!
|
|
* Builds the state rewards for the given state space.
|
|
*
|
|
* @param rewards A vector of state rewards to consider.
|
|
* @param stateInformation Information about the state space.
|
|
* @return A vector containing the state rewards for the state space.
|
|
*/
|
|
static std::vector<ValueType> buildStateRewards(storm::prism::Program const& program, VariableInformation const& variableInformation, std::vector<storm::prism::StateReward> const& rewards, StateInformation const& stateInformation) {
|
|
storm::expressions::ExprtkExpressionEvaluator evaluator(program.getManager());
|
|
|
|
std::vector<ValueType> result(stateInformation.reachableStates.size());
|
|
for (uint_fast64_t index = 0; index < stateInformation.reachableStates.size(); index++) {
|
|
result[index] = ValueType(0);
|
|
for (auto const& reward : rewards) {
|
|
unpackStateIntoEvaluator(stateInformation.stateToIndexMap.getValue(stateInformation.reachableStates[index]), variableInformation, evaluator);
|
|
|
|
// Add this reward to the state if the state is included in the state reward.
|
|
if (evaluator.asBool(reward.getStatePredicateExpression())) {
|
|
result[index] += ValueType(evaluator.asDouble(reward.getRewardValueExpression()));
|
|
}
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
};
|
|
|
|
} // namespace adapters
|
|
} // namespace storm
|
|
|
|
#endif /* STORM_ADAPTERS_EXPLICITMODELADAPTER_H */
|