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Delete unused files.

tempestpy_adaptions
TimQu 5 years ago
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  1. 363
      src/storm/storage/memorystructure/SparseModelNondeterministicTransitionsBasedMemoryProduct.cpp
  2. 56
      src/storm/storage/memorystructure/SparseModelNondeterministicTransitionsBasedMemoryProduct.h

363
src/storm/storage/memorystructure/SparseModelNondeterministicTransitionsBasedMemoryProduct.cpp
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//
// Created by Florent Delgrange on 2019-05-28.
//
#include "SparseModelNondeterministicTransitionsBasedMemoryProduct.h"
namespace storm {
namespace storage {
template<typename SparseModelType>
SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::SparseModelNondeterministicTransitionsBasedMemoryProduct(SparseModelType const& model, storm::storage::NondeterministicMemoryStructure const& memory, bool forceLabeling)
: model(model), memory(memory), productStates(model.getNumberOfStates()), forceLabeling(forceLabeling)
{}
template<typename SparseModelType>
std::shared_ptr<SparseModelType> SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::build() {
// For simplicity we first build the 'full' product of model and memory (with model.numStates * memory.numStates states).
storm::storage::sparse::ModelComponents<ValueType> components;
components.transitionMatrix = buildTransitions();
components.stateLabeling = buildStateLabeling();
components.choiceLabeling = buildChoiceLabeling(components.transitionMatrix);
// Now delete unreachable states.
storm::storage::BitVector allStates(components.transitionMatrix.getRowGroupCount(), true);
reachableStates = storm::utility::graph::getReachableStates(components.transitionMatrix, components.stateLabeling.getStates("init"), allStates, ~allStates);
storm::storage::BitVector enabledActions(components.transitionMatrix.getRowCount());
for (uint64_t state : reachableStates) {
for (uint64_t row = components.transitionMatrix.getRowGroupIndices()[state]; row < components.transitionMatrix.getRowGroupIndices()[state + 1]; ++ row) {
enabledActions.set(row);
}
}
components.transitionMatrix = components.transitionMatrix.getSubmatrix(true, reachableStates, reachableStates);
components.stateLabeling = components.stateLabeling.getSubLabeling(reachableStates);
components.choiceLabeling = components.choiceLabeling->getSubLabeling(enabledActions);
// build the remaining components
for (auto const& rewModel : model.getRewardModels()) {
components.rewardModels.emplace(rewModel.first, buildRewardModel(rewModel.second, reachableStates, components.transitionMatrix));
}
// build the offset vector, that allows to maintain getter indices
fullProductStatesOffset = std::move(generateOffsetVector(reachableStates));
return std::make_shared<SparseModelType>(std::move(components));
}
template<typename SparseModelType>
storm::storage::SparseMatrix<typename SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::ValueType> SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::buildTransitions() {
storm::storage::SparseMatrix<ValueType> const& origTransitions = model.getTransitionMatrix();
uint64_t numRows = 0;
uint64_t numEntries = 0;
uint64_t numberOfStates = model.getNumberOfStates() * memory.getNumberOfStates() * (1 + model.getNumberOfTransitions());
productStates[0] = 0;
for (uint64_t modelState = 0; modelState < model.getNumberOfStates(); ++ modelState) {
if (modelState < model.getNumberOfStates() - 1) {
productStates[modelState + 1] = productStates[modelState] + memory.getNumberOfStates() * (1 + origTransitions.getRowGroupEntryCount(modelState));
}
for (uint64_t memState = 0; memState < memory.getNumberOfStates(); ++ memState) {
for (uint64_t row = origTransitions.getRowGroupIndices()[modelState];
row < origTransitions.getRowGroupIndices()[modelState + 1];
++ row) {
numRows += 1 + origTransitions.getRow(row).getNumberOfEntries() * memory.getNumberOfOutgoingTransitions(memState);
numEntries += origTransitions.getRow(row).getNumberOfEntries() * (1 + memory.getNumberOfOutgoingTransitions(memState));
}
}
}
storm::storage::SparseMatrixBuilder<ValueType> builder(numRows,
numberOfStates,
numEntries,
true,
true,
numberOfStates);
uint64_t row = 0;
for (uint64_t modelState = 0; modelState < model.getNumberOfStates(); ++ modelState) {
for (uint64_t memState = 0; memState < memory.getNumberOfStates(); ++ memState) {
builder.newRowGroup(row);
uint64_t entryCount = 0;
for (uint64_t origRow = origTransitions.getRowGroupIndices()[modelState]; origRow < origTransitions.getRowGroupIndices()[modelState + 1]; ++origRow) {
for (auto const& entry : origTransitions.getRow(origRow)) {
uint64_t productState = getProductState(modelState, memState);
builder.addNextValue(row, productState + 1 + entryCount, entry.getValue());
++ entryCount;
}
++row;
}
// transition states
for (uint64_t origRow = origTransitions.getRowGroupIndices()[modelState]; origRow < origTransitions.getRowGroupIndices()[modelState + 1]; ++origRow) {
for (auto const& entry : origTransitions.getRow(origRow)) {
builder.newRowGroup(row);
for (auto const& memStatePrime : memory.getTransitions(memState)) {
builder.addNextValue(row, getProductState(entry.getColumn(), memStatePrime), storm::utility::one<ValueType>());
++row;
}
}
}
}
}
return builder.build();
}
template<typename SparseModelType>
storm::models::sparse::StateLabeling SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::buildStateLabeling() const {
storm::storage::SparseMatrix<ValueType> const& origTransitions = model.getTransitionMatrix();
// storm::storage::SparseMatrix<ValueType> backwardTransitions = origTransitions.transpose(true);
uint64_t numberOfStates = model.getNumberOfStates() * memory.getNumberOfStates() * (1 + model.getNumberOfTransitions());
storm::models::sparse::StateLabeling labeling(numberOfStates);
for (auto const& labelName : model.getStateLabeling().getLabels()) {
storm::storage::BitVector newStates(numberOfStates, false);
// The init label is only assigned to Product states with the initial memory state
if (labelName == "init") {
for (auto const& modelState : model.getStateLabeling().getStates(labelName)) {
uint64_t nextProductState = getProductState(modelState, memory.getInitialState() + 1); //memory.getInitialState() < memory.getNumberOfStates() - 1 ? getProductState(modelState, memory.getInitialState() + 1) : getProductState(modelState + 1, 0);
// by assuming that all states between (s, m) and (s, m + 1) are labeled with s
for (uint64_t productState = getProductState(modelState, memory.getInitialState()); productState < nextProductState; ++ productState) {
newStates.set(productState);
}
}
} else {
for (auto const& modelState : model.getStateLabeling().getStates(labelName)) {
// by assuming that all states between (s, 0) and (s + 1, 0) are labeled with labels of s
for (uint64_t productState = getProductState(modelState, 0); productState < getProductState(modelState, memory.getNumberOfStates()); ++ productState) {
newStates.set(productState);
}
}
}
labeling.addLabel(labelName, std::move(newStates));
}
auto addLabel = [&] (std::string const& labelName, uint64_t state) -> void {
if (not labeling.containsLabel(labelName)) {
labeling.addLabel(labelName);
}
labeling.addLabelToState(labelName, state);
};
for (uint64_t modelState = 0; modelState < model.getNumberOfStates(); ++ modelState) {
if (forceLabeling) {
for (uint64_t memoryState = 0; memoryState < memory.getNumberOfStates(); ++ memoryState) {
if (labeling.getLabelsOfState(getProductState(modelState, memoryState)).empty()) {
std::ostringstream stream;
stream << "s" << modelState;
std::string labelName = stream.str();
addLabel(labelName, getProductState(modelState, memoryState));
}
{
std::ostringstream stream;
stream << "m" << memoryState;
std::string labelName = stream.str();
addLabel(labelName, getProductState(modelState, memoryState));
}
}
}
uint64_t entryCount = 0;
for (uint64_t row = origTransitions.getRowGroupIndices()[modelState]; row < origTransitions.getRowGroupIndices()[modelState + 1]; ++ row) {
for (auto const& entry : origTransitions.getRow(row)) {
uint64_t const& successor = entry.getColumn();
for (uint64_t memoryState = 0; memoryState < memory.getNumberOfStates(); ++ memoryState) {
uint64_t productState = getProductState(modelState, memoryState) + 1 + entryCount;
// origin state
if ( model.getStateLabeling().getLabelsOfState(modelState).empty() or
(model.getStateLabeling().getLabelsOfState(modelState).size() == 1 and model.getStateLabeling().getStateHasLabel("init", modelState)
and not labeling.getStateHasLabel("init", productState)) ){
if (forceLabeling) {
std::ostringstream stream;
stream << "s" << modelState;
std::string labelName = stream.str();
addLabel(labelName, productState);
}
} else {
for (auto const& labelName : model.getStateLabeling().getLabelsOfState(modelState)) {
if (labelName != "init") {
addLabel(labelName, productState);
}
}
}
// memory labeling
if (forceLabeling) {
std::ostringstream stream;
stream << "m" << memoryState;
std::string labelName = stream.str();
addLabel(labelName, productState);
}
// action labeling
if (forceLabeling and (not model.getOptionalChoiceLabeling()
or model.getChoiceLabeling().getLabelsOfChoice(row).empty())) {
std::ostringstream stream;
stream << "a" << row;
std::string labelName = stream.str();
addLabel(labelName, productState);
} else if (model.getOptionalChoiceLabeling()) {
for (auto const &labelName : model.getChoiceLabeling().getLabelsOfChoice(row)) {
addLabel(labelName, productState);
}
}
// arrival state
if ( model.getStateLabeling().getLabelsOfState(successor).empty() or
(model.getStateLabeling().getLabelsOfState(successor).size() == 1 and model.getStateLabeling().getStateHasLabel("init", successor)
and not labeling.getStateHasLabel("init", productState)) ){
if (forceLabeling) {
std::ostringstream stream;
stream << "s" << successor;
std::string labelName = stream.str();
addLabel(labelName, productState);
}
} else {
for (auto const& labelName : model.getStateLabeling().getLabelsOfState(successor)) {
if (labelName != "init") {
addLabel(labelName, productState);
}
}
}
}
++ entryCount;
}
}
}
return labeling;
}
template<typename SparseModelType>
storm::models::sparse::ChoiceLabeling SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::buildChoiceLabeling(storm::storage::SparseMatrix<ValueType> const& transitions) const {
storm::storage::SparseMatrix<ValueType> const& origTransitions = model.getTransitionMatrix();
storm::models::sparse::ChoiceLabeling labeling(transitions.getRowCount());
auto addLabel = [&] (std::string const& labelName, uint64_t row) -> void {
if (not labeling.containsLabel(labelName)) {
labeling.addLabel(labelName);
}
labeling.addLabelToChoice(labelName, row);
};
uint64_t row = 0;
for (uint64_t modelState = 0; modelState < model.getNumberOfStates(); ++ modelState) {
for (uint64_t memState = 0; memState < memory.getNumberOfStates(); ++ memState) {
for (uint64_t origRow = origTransitions.getRowGroupIndices()[modelState]; origRow < origTransitions.getRowGroupIndices()[modelState + 1]; ++origRow) {
if (forceLabeling and (not model.getOptionalChoiceLabeling()
or model.getChoiceLabeling().getLabelsOfChoice(origRow).empty())) {
std::ostringstream stream;
stream << "a" << origRow;
std::string labelName = stream.str();
addLabel(labelName, row);
} else if (model.getOptionalChoiceLabeling()) {
for (auto const &labelName : model.getChoiceLabeling().getLabelsOfChoice(origRow)) {
addLabel(labelName, row);
}
}
++row;
}
// transition states
for (uint64_t origRow = origTransitions.getRowGroupIndices()[modelState]; origRow < origTransitions.getRowGroupIndices()[modelState + 1]; ++origRow) {
for (auto const& entry : origTransitions.getRow(origRow)) {
for (auto const& memStatePrime : memory.getTransitions(memState)) {
if (forceLabeling) {
std::ostringstream stream;
stream << "m" << memStatePrime;
std::string labelName = stream.str();
addLabel(labelName, row);
}
++row;
}
}
}
}
}
return labeling;
}
template<typename SparseModelType>
storm::models::sparse::StandardRewardModel<typename SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::ValueType> SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::buildRewardModel(storm::models::sparse::StandardRewardModel<ValueType> const& rewardModel, storm::storage::BitVector const& reachableStates, storm::storage::SparseMatrix<ValueType> const& resultTransitionMatrix) const {
boost::optional<std::vector<ValueType>> stateRewards, actionRewards;
if (rewardModel.hasStateRewards()) {
stateRewards = std::vector<ValueType>();
stateRewards->reserve(resultTransitionMatrix.getRowGroupCount());
for (uint64_t modelState = 0; modelState < model.getNumberOfStates(); ++ modelState) {
for (uint64_t memState = 0; memState < memory.getNumberOfStates(); ++ memState) {
if (reachableStates.get(getProductState(modelState, memState))) {
stateRewards->push_back(rewardModel.getStateReward(modelState));
}
}
}
}
if (rewardModel.hasStateActionRewards()) {
actionRewards = std::vector<ValueType>();
actionRewards->reserve(resultTransitionMatrix.getRowCount());
for (uint64_t modelState = 0; modelState < model.getNumberOfStates(); ++ modelState) {
uint64_t numberOfModelOutgoingTransitions = model.getTransitionMatrix().getRowGroupEntryCount(modelState);
for (uint64_t memState = 0; memState < memory.getNumberOfStates(); ++ memState) {
uint64_t numberOfMemoryOutgoingTransitions = memory.getNumberOfOutgoingTransitions(memState);
if (reachableStates.get(getProductState(modelState, memState))) {
for (uint64_t origRow = model.getTransitionMatrix().getRowGroupIndices()[modelState]; origRow < model.getTransitionMatrix().getRowGroupIndices()[modelState + 1]; ++ origRow) {
ValueType const& actionReward = rewardModel.getStateActionReward(origRow);
// push the reward of choosing a in (s, m)
actionRewards->push_back(actionReward);
}
// note that all outgoing model states are reachable by definition
actionRewards->insert(actionRewards->end(), numberOfModelOutgoingTransitions * numberOfMemoryOutgoingTransitions, storm::utility::zero<ValueType>());
}
}
}
}
STORM_LOG_THROW(!rewardModel.hasTransitionRewards(), storm::exceptions::NotSupportedException, "Transition rewards are currently not supported.");
return storm::models::sparse::StandardRewardModel<ValueType>(std::move(stateRewards), std::move(actionRewards));
}
template<typename SparseModelType>
std::vector<uint64_t> SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::generateOffsetVector(storm::storage::BitVector const& reachableStates) {
uint64_t numberOfStates = model.getNumberOfStates() * memory.getNumberOfStates() * (1 + model.getNumberOfTransitions());
STORM_LOG_ASSERT(reachableStates.size() == numberOfStates, "vector reachableStates has wrong size");
uint64_t state = 0;
uint64_t offset = 0;
std::vector<uint64_t> offsetVector(numberOfStates);
while (state < numberOfStates) {
if (reachableStates[state]) {
offsetVector[state] = offset;
++ state;
}
else {
uint64_t nextState = reachableStates.getNextSetIndex(state);
offset += nextState - state;
for (; state < nextState; ++ state) {
offsetVector[state] = offset;
}
}
}
return std::move(offsetVector);
}
template<typename SparseModelType>
uint64_t SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::getProductState(uint64_t modelState, uint64_t memoryState) const {
uint64_t index = productStates[modelState] + memoryState * (1 + model.getTransitionMatrix().getRowGroupEntryCount(modelState));
return index - (fullProductStatesOffset.empty() ? 0 : fullProductStatesOffset[index]);
}
template<typename SparseModelType>
bool SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::isProductStateReachable(uint64_t modelState, uint64_t memoryState) const {
STORM_LOG_ASSERT(not fullProductStatesOffset.empty(), "The product is not yet built");
uint64_t index = productStates[modelState] + memoryState * (1 + model.getTransitionMatrix().getRowGroupEntryCount(modelState));
return reachableStates[index];
}
template<typename SparseModelType>
uint64_t SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::getModelState(uint64_t productState) const {
uint64_t productStateWithOffset = productState + (fullProductStatesOffset.empty() ? 0 : fullProductStatesOffset[productState]);
// binary search in the vector containing the product states indices
auto search = std::upper_bound(productStates.begin(), productStates.end(), productStateWithOffset);
return search - productStates.begin() - 1;
}
template<typename SparseModelType>
uint64_t SparseModelNondeterministicTransitionsBasedMemoryProduct<SparseModelType>::getMemoryState(uint64_t productState) const {
uint64_t productStateWithOffset = productState + (fullProductStatesOffset.empty() ? 0 : fullProductStatesOffset[productState]);
// binary search in the vector containing the product states indices
uint64_t modelState = std::upper_bound(productStates.begin(), productStates.end(), productStateWithOffset) - productStates.begin() - 1;
uint64_t offset = productStateWithOffset - productStates[modelState];
return offset / (1 + model.getTransitionMatrix().getRowGroupEntryCount(modelState));
}
template class SparseModelNondeterministicTransitionsBasedMemoryProduct<storm::models::sparse::Mdp<double>>;
template class SparseModelNondeterministicTransitionsBasedMemoryProduct<storm::models::sparse::Mdp<storm::RationalNumber>>;
}
}

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src/storm/storage/memorystructure/SparseModelNondeterministicTransitionsBasedMemoryProduct.h
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//
// Created by Florent Delgrange on 2019-05-28.
//
#ifndef STORM_SPARSEMODELNONDETERMINISTICTRANSITIONSBASEDMEMORYPRODUCT_H
#define STORM_SPARSEMODELNONDETERMINISTICTRANSITIONSBASEDMEMORYPRODUCT_H
#include <storm/models/sparse/StateLabeling.h>
#include <storm/storage/SparseMatrix.h>
#include <storm/models/sparse/StandardRewardModel.h>
#include <storm/storage/memorystructure/NondeterministicMemoryStructure.h>
#include <storm/storage/sparse/ModelComponents.h>
#include <storm/utility/graph.h>
#include <storm/exceptions/NotSupportedException.h>
#include <storm/models/sparse/Mdp.h>
namespace storm {
namespace storage {
template<typename SparseModelType>
class SparseModelNondeterministicTransitionsBasedMemoryProduct {
public:
typedef typename SparseModelType::ValueType ValueType;
SparseModelNondeterministicTransitionsBasedMemoryProduct(SparseModelType const& model, storm::storage::NondeterministicMemoryStructure const& memory, bool forceLabeling = false);
std::shared_ptr<SparseModelType> build();
uint64_t getProductState(uint64_t modelState, uint64_t memoryState) const;
uint64_t getModelState(uint64_t productState) const;
uint64_t getMemoryState(uint64_t productState) const;
bool isProductStateReachable(uint64_t modelState, uint64_t memoryState) const;
private:
storm::storage::SparseMatrix<ValueType> buildTransitions();
storm::models::sparse::StateLabeling buildStateLabeling() const;
storm::models::sparse::ChoiceLabeling buildChoiceLabeling(storm::storage::SparseMatrix<ValueType> const& transitions) const;
storm::models::sparse::StandardRewardModel<ValueType> buildRewardModel(storm::models::sparse::StandardRewardModel<ValueType> const& rewardModel, storm::storage::BitVector const& reachableStates, storm::storage::SparseMatrix<ValueType> const& resultTransitionMatrix) const;
std::vector<uint64_t> generateOffsetVector(storm::storage::BitVector const& reachableStates);
SparseModelType const& model;
storm::storage::NondeterministicMemoryStructure const& memory;
std::vector<uint64_t> productStates; // has a size equals to the number of states of the original model
std::vector<uint64_t> fullProductStatesOffset; // has a size equal to the number of states of the full product
storm::storage::BitVector reachableStates;
bool forceLabeling;
};
}
}
#endif //STORM_SPARSEMODELNONDETERMINISTICTRANSITIONSBASEDMEMORYPRODUCT_H
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