diff --git a/src/storm/builder/ExplicitModelBuilder.cpp b/src/storm/builder/ExplicitModelBuilder.cpp
index 70b68fbce..3df2f42b7 100644
--- a/src/storm/builder/ExplicitModelBuilder.cpp
+++ b/src/storm/builder/ExplicitModelBuilder.cpp
@@ -154,6 +154,7 @@ namespace storm {
while (!statesToExplore.empty()) {
// Get the first state in the queue.
CompressedState currentState = statesToExplore.front().first;
+ STORM_LOG_DEBUG("Exploring (" << currentRowGroup << ") : " << toString(currentState, this->generator->getVariableInformation()));
StateType currentIndex = statesToExplore.front().second;
statesToExplore.pop_front();
diff --git a/src/storm/modelchecker/helper/infinitehorizon/SparseNondeterministicGameInfiniteHorizonHelper.cpp b/src/storm/modelchecker/helper/infinitehorizon/SparseNondeterministicGameInfiniteHorizonHelper.cpp
index d4f52f65c..34a1a8d93 100644
--- a/src/storm/modelchecker/helper/infinitehorizon/SparseNondeterministicGameInfiniteHorizonHelper.cpp
+++ b/src/storm/modelchecker/helper/infinitehorizon/SparseNondeterministicGameInfiniteHorizonHelper.cpp
@@ -63,7 +63,10 @@ namespace storm {
this->_backwardTransitions = this->_computedBackwardTransitions.get();
}
this->_computedLongRunComponentDecomposition = std::make_unique<storm::storage::GameMaximalEndComponentDecomposition<ValueType>>(this->_transitionMatrix, *this->_backwardTransitions);
+
this->_longRunComponentDecomposition = this->_computedLongRunComponentDecomposition.get();
+ //STORM_LOG_DEBUG("\n" << this->_transitionMatrix);
+ STORM_LOG_DEBUG("GMEC: " << *(this->_longRunComponentDecomposition));
}
}
diff --git a/src/storm/modelchecker/helper/infinitehorizon/internal/LraViHelper.cpp b/src/storm/modelchecker/helper/infinitehorizon/internal/LraViHelper.cpp
index 5e4bfc81a..da16522f1 100644
--- a/src/storm/modelchecker/helper/infinitehorizon/internal/LraViHelper.cpp
+++ b/src/storm/modelchecker/helper/infinitehorizon/internal/LraViHelper.cpp
@@ -24,11 +24,11 @@ namespace storm {
namespace modelchecker {
namespace helper {
namespace internal {
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
LraViHelper<ValueType, ComponentType, TransitionsType>::LraViHelper(ComponentType const& component, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, ValueType const& aperiodicFactor, storm::storage::BitVector const* timedStates, std::vector<ValueType> const* exitRates) : _transitionMatrix(transitionMatrix), _timedStates(timedStates), _hasInstantStates(TransitionsType == LraViTransitionsType::DetTsNondetIs || TransitionsType == LraViTransitionsType::DetTsDetIs), _Tsx1IsCurrent(false) {
setComponent(component);
-
+
// Run through the component and collect some data:
// We create two submodels, one consisting of the timed states of the component and one consisting of the instant states of the component.
// For this, we create a state index map that point from state indices of the input model to indices of the corresponding submodel of that state.
@@ -141,8 +141,9 @@ namespace storm {
_IsTransitions = isTransitionsBuilder.build();
_IsToTsTransitions = isToTsTransitionsBuilder.build();
}
+ STORM_LOG_DEBUG(uniformizationFactor << " - " << _uniformizationRate);
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
void LraViHelper<ValueType, ComponentType, TransitionsType>::setComponent(ComponentType component) {
_component.clear();
@@ -156,7 +157,7 @@ namespace storm {
}
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
ValueType LraViHelper<ValueType, ComponentType, TransitionsType>::performValueIteration(Environment const& env, ValueGetter const& stateValueGetter, ValueGetter const& actionValueGetter, std::vector<ValueType> const* exitRates, storm::solver::OptimizationDirection const* dir, std::vector<uint64_t>* choices) {
initializeNewValues(stateValueGetter, actionValueGetter, exitRates);
@@ -166,7 +167,7 @@ namespace storm {
if (env.solver().lra().isMaximalIterationCountSet()) {
maxIter = env.solver().lra().getMaximalIterationCount();
}
-
+
// start the iterations
ValueType result = storm::utility::zero<ValueType>();
uint64_t iter = 0;
@@ -198,7 +199,7 @@ namespace storm {
// If there will be a next iteration, we have to prepare it.
prepareNextIteration(env);
-
+
}
if (maxIter.is_initialized() && iter == maxIter.get()) {
STORM_LOG_WARN("LRA computation did not converge within " << iter << " iterations.");
@@ -207,15 +208,23 @@ namespace storm {
} else {
STORM_LOG_TRACE("LRA computation converged after " << iter << " iterations.");
}
-
+
if (choices) {
// We will be doing one more iteration step and track scheduler choices this time.
prepareNextIteration(env);
performIterationStep(env, dir, choices);
}
+ std::cout << "result (" << iter << " steps):" << std::endl;
+ for(int i = 0; i < xNew().size() ; i++ ) {
+ std::cout << std::setprecision(4) << i << "\t: " << xNew().at(i) << "\t" << xNew().at(i) * _uniformizationRate << "\t" << std::setprecision(16) << xOld().at(i) *_uniformizationRate << std::endl;
+ //if(i == 50) {std::cout << "only showing top 50 lines"; break; }
+ for(int i = 0; i < xNew().size() ; i++ ) {
+ std::cout << std::setprecision(4) << i << "\t: " << xNew().at(i) << "\t" << xNew().at(i) * _uniformizationRate << "\t" << std::setprecision(16) << xOld().at(i) *_uniformizationRate << std::endl;
+ //if(i == 50) {std::cout << "only showing top 50 lines"; break; }
+ }
return result;
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
void LraViHelper<ValueType, ComponentType, TransitionsType>::initializeNewValues(ValueGetter const& stateValueGetter, ValueGetter const& actionValueGetter, std::vector<ValueType> const* exitRates) {
// clear potential old values and reserve enough space for new values
@@ -225,7 +234,7 @@ namespace storm {
_IsChoiceValues.clear();
_IsChoiceValues.reserve(_IsTransitions.getRowCount());
}
-
+
// Set the new choice-based values
ValueType actionRewardScalingFactor = storm::utility::one<ValueType>() / _uniformizationRate;
for (auto const& element : _component) {
@@ -250,14 +259,14 @@ namespace storm {
// Set-up new iteration vectors for timed states
_Tsx1.assign(_TsTransitions.getRowGroupCount(), storm::utility::zero<ValueType>());
_Tsx2 = _Tsx1;
-
+
if (_hasInstantStates) {
// Set-up vectors for storing intermediate results for instant states.
_Isx.resize(_IsTransitions.getRowGroupCount(), storm::utility::zero<ValueType>());
_Isb = _IsChoiceValues;
}
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
void LraViHelper<ValueType, ComponentType, TransitionsType>::prepareSolversAndMultipliers(const Environment& env, storm::solver::OptimizationDirection const* dir) {
_TsMultiplier = storm::solver::MultiplierFactory<ValueType>().create(env, _TsTransitions);
@@ -315,7 +324,7 @@ namespace storm {
STORM_LOG_THROW(!req.hasEnabledCriticalRequirement(), storm::exceptions::UnmetRequirementException, "The solver requirement " << req.getEnabledRequirementsAsString() << " has not been cleared.");
}
}
-
+
// Set up multipliers for transitions connecting timed and instant states
_TsToIsMultiplier = storm::solver::MultiplierFactory<ValueType>().create(env, _TsToIsTransitions);
_IsToTsMultiplier = storm::solver::MultiplierFactory<ValueType>().create(env, _IsToTsTransitions);
@@ -324,7 +333,7 @@ namespace storm {
_TsMultiplier->setOptimizationDirectionOverride(env.solver().multiplier().getOptimizationDirectionOverride().get());
}
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
void LraViHelper<ValueType, ComponentType, TransitionsType>::setInputModelChoices(std::vector<uint64_t>& choices, std::vector<uint64_t> const& localMecChoices, bool setChoiceZeroToTimedStates, bool setChoiceZeroToInstantStates) const {
// Transform the local choices (within this mec) to choice indices for the input model
@@ -347,7 +356,7 @@ namespace storm {
}
STORM_LOG_ASSERT(localState == localMecChoices.size(), "Did not traverse all component states.");
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
void LraViHelper<ValueType, ComponentType, TransitionsType>::performIterationStep(Environment const& env, storm::solver::OptimizationDirection const* dir, std::vector<uint64_t>* choices) {
STORM_LOG_ASSERT(!((nondetTs() || nondetIs()) && dir == nullptr), "No optimization direction provided for model with nondeterminism");
@@ -355,13 +364,13 @@ namespace storm {
if (!_TsMultiplier) {
prepareSolversAndMultipliers(env, dir);
}
-
+
// Compute new x values for the timed states
// Flip what is new and what is old
_Tsx1IsCurrent = !_Tsx1IsCurrent;
// At this point, xOld() points to what has been computed in the most recent call of performIterationStep (initially, this is the 0-vector).
// The result of this ongoing computation will be stored in xNew()
-
+
// Compute the values obtained by a single uniformization step between timed states only
if (nondetTs() && !gameNondetTs()) {
if (choices == nullptr) {
@@ -425,7 +434,7 @@ namespace storm {
_TsToIsMultiplier->multiply(env, _Isx, &xNew(), xNew());
}
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
typename LraViHelper<ValueType, ComponentType, TransitionsType>::ConvergenceCheckResult LraViHelper<ValueType, ComponentType, TransitionsType>::checkConvergence(bool relative, ValueType precision) const {
STORM_LOG_ASSERT(_TsMultiplier, "tried to check for convergence without doing an iteration first.");
@@ -433,7 +442,7 @@ namespace storm {
// We need to 'revert' this scaling when computing the absolute precision.
// However, for relative precision, the scaling cancels out.
ValueType threshold = relative ? precision : ValueType(precision / _uniformizationRate);
-
+
ConvergenceCheckResult res = { true, storm::utility::one<ValueType>() };
// Now check whether the currently produced results are precise enough
STORM_LOG_ASSERT(threshold > storm::utility::zero<ValueType>(), "Did not expect a non-positive threshold.");
@@ -460,15 +469,15 @@ namespace storm {
break;
}
}
-
+
// Compute the average of the maximal and the minimal difference.
ValueType avgDiff = (maxDiff + minDiff) / (storm::utility::convertNumber<ValueType>(2.0));
-
+
// "Undo" the scaling of the values
res.currentValue = avgDiff * _uniformizationRate;
return res;
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
void LraViHelper<ValueType, ComponentType, TransitionsType>::prepareNextIteration(Environment const& env) {
// To avoid large (and numerically unstable) x-values, we substract a reference value.
@@ -480,39 +489,39 @@ namespace storm {
_IsToTsMultiplier->multiply(env, xNew(), &_IsChoiceValues, _Isb);
}
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
bool LraViHelper<ValueType, ComponentType, TransitionsType>::isTimedState(uint64_t const& inputModelStateIndex) const {
STORM_LOG_ASSERT(!_hasInstantStates || _timedStates != nullptr, "Model has instant states but no partition into timed and instant states is given.");
STORM_LOG_ASSERT(!_hasInstantStates || inputModelStateIndex < _timedStates->size(), "Unable to determine whether state " << inputModelStateIndex << " is timed.");
return !_hasInstantStates || _timedStates->get(inputModelStateIndex);
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
std::vector<ValueType>& LraViHelper<ValueType, ComponentType, TransitionsType>::xNew() {
return _Tsx1IsCurrent ? _Tsx1 : _Tsx2;
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
std::vector<ValueType> const& LraViHelper<ValueType, ComponentType, TransitionsType>::xNew() const {
return _Tsx1IsCurrent ? _Tsx1 : _Tsx2;
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
std::vector<ValueType>& LraViHelper<ValueType, ComponentType, TransitionsType>::xOld() {
return _Tsx1IsCurrent ? _Tsx2 : _Tsx1;
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
std::vector<ValueType> const& LraViHelper<ValueType, ComponentType, TransitionsType>::xOld() const {
return _Tsx1IsCurrent ? _Tsx2 : _Tsx1;
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
bool LraViHelper<ValueType, ComponentType, TransitionsType>::nondetTs() const {
return TransitionsType == LraViTransitionsType::NondetTsNoIs || gameNondetTs();
}
-
+
template <typename ValueType, typename ComponentType, LraViTransitionsType TransitionsType>
bool LraViHelper<ValueType, ComponentType, TransitionsType>::nondetIs() const {
return TransitionsType == LraViTransitionsType::DetTsNondetIs;
@@ -529,11 +538,11 @@ namespace storm {
template class LraViHelper<storm::RationalNumber, storm::storage::MaximalEndComponent, LraViTransitionsType::GameNondetTsNoIs>;
template class LraViHelper<double, storm::storage::MaximalEndComponent, LraViTransitionsType::DetTsNondetIs>;
template class LraViHelper<storm::RationalNumber, storm::storage::MaximalEndComponent, LraViTransitionsType::DetTsNondetIs>;
-
+
template class LraViHelper<double, storm::storage::StronglyConnectedComponent, LraViTransitionsType::DetTsNoIs>;
template class LraViHelper<storm::RationalNumber, storm::storage::StronglyConnectedComponent, LraViTransitionsType::DetTsNoIs>;
-
+
}
}
}
-}
\ No newline at end of file
+}
diff --git a/src/storm/solver/GmmxxMultiplier.cpp b/src/storm/solver/GmmxxMultiplier.cpp
index 32af42f72..0a2843824 100644
--- a/src/storm/solver/GmmxxMultiplier.cpp
+++ b/src/storm/solver/GmmxxMultiplier.cpp
@@ -16,25 +16,26 @@
namespace storm {
namespace solver {
-
+
template<typename ValueType>
GmmxxMultiplier<ValueType>::GmmxxMultiplier(storm::storage::SparseMatrix<ValueType> const& matrix) : Multiplier<ValueType>(matrix) {
// Intentionally left empty.
+ //STORM_LOG_DEBUG("\n" << matrix);
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::initialize() const {
if (gmmMatrix.nrows() == 0) {
gmmMatrix = std::move(*storm::adapters::GmmxxAdapter<ValueType>().toGmmxxSparseMatrix(this->matrix));
}
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::clearCache() const {
gmmMatrix = gmm::csr_matrix<ValueType>();
Multiplier<ValueType>::clearCache();
}
-
+
template<typename ValueType>
bool GmmxxMultiplier<ValueType>::parallelize(Environment const& env) const {
#ifdef STORM_HAVE_INTELTBB
@@ -43,7 +44,7 @@ namespace storm {
return false;
#endif
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::multiply(Environment const& env, std::vector<ValueType> const& x, std::vector<ValueType> const* b, std::vector<ValueType>& result) const {
initialize();
@@ -65,7 +66,7 @@ namespace storm {
std::swap(result, *this->cachedVector);
}
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::multiplyGaussSeidel(Environment const& env, std::vector<ValueType>& x, std::vector<ValueType> const* b, bool backwards) const {
initialize();
@@ -84,7 +85,7 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::multiplyAndReduce(Environment const& env, OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& x, std::vector<ValueType> const* b, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
initialize();
@@ -106,13 +107,13 @@ namespace storm {
std::swap(result, *this->cachedVector);
}
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::multiplyAndReduceGaussSeidel(Environment const& env, OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType>& x, std::vector<ValueType> const* b, std::vector<uint_fast64_t>* choices, bool backwards) const {
initialize();
multAddReduceHelper(dir, rowGroupIndices, x, b, x, choices, backwards);
}
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::multiplyRow(uint64_t const& rowIndex, std::vector<ValueType> const& x, ValueType& value) const {
initialize();
@@ -148,14 +149,14 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
template<typename Compare, bool backwards>
void GmmxxMultiplier<ValueType>::multAddReduceHelper(std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& x, std::vector<ValueType> const* b, std::vector<ValueType>& result, std::vector<uint64_t>* choices) const {
Compare compare;
typedef std::vector<ValueType> VectorType;
typedef gmm::csr_matrix<ValueType> MatrixType;
-
+
typename gmm::linalg_traits<VectorType>::const_iterator add_it, add_ite;
if (b) {
add_it = backwards ? gmm::vect_end(*b) - 1 : gmm::vect_begin(*b);
@@ -181,6 +182,7 @@ namespace storm {
uint64_t currentRowGroup = backwards ? rowGroupIndices.size() - 1 : 0;
auto row_group_it = backwards ? rowGroupIndices.end() - 2 : rowGroupIndices.begin();
auto row_group_ite = backwards ? rowGroupIndices.begin() - 1 : rowGroupIndices.end() - 1;
+ //if(choices) STORM_LOG_DEBUG(" ");
while (row_group_it != row_group_ite) {
ValueType currentValue = storm::utility::zero<ValueType>();
@@ -199,7 +201,7 @@ namespace storm {
oldSelectedChoiceValue = currentValue;
}
}
-
+
// move row-based iterators to the next row
if (backwards) {
--itr;
@@ -213,6 +215,10 @@ namespace storm {
// Process the (rowGroupSize-1) remaining rows within the current row Group
uint64_t rowGroupSize = *(row_group_it + 1) - *row_group_it;
+ uint choiceforprintout = 0;
+ //std::cout << currentRowGroup << ": " << currentValue << ", ";
+ //STORM_LOG_DEBUG(std::setprecision(3) << vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x) << " + " << *add_it << "; ");
+ //STORM_LOG_DEBUG(std::setprecision(3) << vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x) << " + " << *add_it << "; ");
for (uint64_t i = 1; i < rowGroupSize; ++i) {
ValueType newValue = b ? *add_it : storm::utility::zero<ValueType>();
newValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
@@ -220,12 +226,13 @@ namespace storm {
if (choices && currentRow == *choice_it + *row_group_it) {
oldSelectedChoiceValue = newValue;
}
-
- if(this->isOverridden(currentRowGroup) ? !compare(newValue, currentValue) : compare(newValue, currentValue)) {
+ //std::cout << newValue << ", ";
+ //STORM_LOG_DEBUG(std::setprecision(3) << vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x) << " + " << *add_it << "; ");
currentValue = newValue;
if (choices) {
selectedChoice = currentRow - *row_group_it;
}
+ choiceforprintout = currentRow - *row_group_it;
}
// move row-based iterators to the next row
if (backwards) {
@@ -238,7 +245,8 @@ namespace storm {
++add_it;
}
}
-
+ //STORM_LOG_DEBUG("\t= " << currentValue << "\tchoice: " << choiceforprintout);
+ //std::cout << std::fixed << std::setprecision(2) << " | v(" << currentRowGroup << ")=" << currentValue << " c: " << choiceforprintout << " |\n" ;
// Finally write value to target vector.
*target_it = currentValue;
if(choices) {
@@ -261,6 +269,7 @@ namespace storm {
++currentRowGroup;
}
}
+ //std::cout << std::endl;
}
template<>
@@ -286,7 +295,7 @@ namespace storm {
multAdd(x, b, result);
#endif
}
-
+
#ifdef STORM_HAVE_INTELTBB
template<typename ValueType, typename Compare>
class TbbMultAddReduceFunctor {
@@ -294,14 +303,14 @@ namespace storm {
TbbMultAddReduceFunctor(std::vector<uint64_t> const& rowGroupIndices, gmm::csr_matrix<ValueType> const& matrix, std::vector<ValueType> const& x, std::vector<ValueType> const* b, std::vector<ValueType>& result, std::vector<uint64_t>* choices) : rowGroupIndices(rowGroupIndices), matrix(matrix), x(x), b(b), result(result), choices(choices) {
// Intentionally left empty.
}
-
+
void operator()(tbb::blocked_range<unsigned long> const& range) const {
typedef std::vector<ValueType> VectorType;
typedef gmm::csr_matrix<ValueType> MatrixType;
auto groupIt = rowGroupIndices.begin() + range.begin();
auto groupIte = rowGroupIndices.begin() + range.end();
-
+
auto itr = mat_row_const_begin(matrix) + *groupIt;
typename std::vector<ValueType>::const_iterator bIt;
if (b) {
@@ -311,40 +320,40 @@ namespace storm {
if (choices) {
choiceIt = choices->begin() + range.begin();
}
-
+
auto resultIt = result.begin() + range.begin();
-
+
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
-
+
uint64_t currentRow = *groupIt;
for (; groupIt != groupIte; ++groupIt, ++resultIt, ++choiceIt) {
ValueType currentValue = storm::utility::zero<ValueType>();
-
+
// Only multiply and reduce if the row group is not empty.
if (*groupIt != *(groupIt + 1)) {
if (b) {
currentValue = *bIt;
++bIt;
}
-
+
currentValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
-
+
if (choices) {
selectedChoice = currentRow - *groupIt;
if (*choiceIt == selectedChoice) {
oldSelectedChoiceValue = currentValue;
}
}
-
+
++itr;
++currentRow;
-
+
for (auto itre = mat_row_const_begin(matrix) + *(groupIt + 1); itr != itre; ++itr, ++bIt, ++currentRow) {
ValueType newValue = b ? *bIt : storm::utility::zero<ValueType>();
newValue += vect_sp(gmm::linalg_traits<MatrixType>::row(itr), x);
-
+
if (compare(newValue, currentValue)) {
currentValue = newValue;
if (choices) {
@@ -353,7 +362,7 @@ namespace storm {
}
}
}
-
+
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && compare(currentValue, oldSelectedChoiceValue)) {
@@ -361,7 +370,7 @@ namespace storm {
}
}
}
-
+
private:
Compare compare;
std::vector<uint64_t> const& rowGroupIndices;
@@ -372,7 +381,7 @@ namespace storm {
std::vector<uint64_t>* choices;
};
#endif
-
+
template<typename ValueType>
void GmmxxMultiplier<ValueType>::multAddReduceParallel(storm::solver::OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& x, std::vector<ValueType> const* b, std::vector<ValueType>& result, std::vector<uint64_t>* choices) const {
#ifdef STORM_HAVE_INTELTBB
@@ -386,18 +395,18 @@ namespace storm {
multAddReduceHelper(dir, rowGroupIndices, x, b, result, choices);
#endif
}
-
+
template<>
void GmmxxMultiplier<storm::RationalFunction>::multAddReduceParallel(storm::solver::OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<storm::RationalFunction> const& x, std::vector<storm::RationalFunction> const* b, std::vector<storm::RationalFunction>& result, std::vector<uint64_t>* choices) const {
STORM_LOG_THROW(false, storm::exceptions::NotSupportedException, "This operation is not supported.");
}
-
+
template class GmmxxMultiplier<double>;
-
+
#ifdef STORM_HAVE_CARL
template class GmmxxMultiplier<storm::RationalNumber>;
template class GmmxxMultiplier<storm::RationalFunction>;
#endif
-
+
}
}
diff --git a/src/storm/storage/Decomposition.cpp b/src/storm/storage/Decomposition.cpp
index efe850083..a45987d69 100644
--- a/src/storm/storage/Decomposition.cpp
+++ b/src/storm/storage/Decomposition.cpp
@@ -8,84 +8,84 @@
namespace storm {
namespace storage {
-
+
template <typename BlockType>
Decomposition<BlockType>::Decomposition() : blocks() {
// Intentionally left empty.
}
-
+
template <typename BlockType>
Decomposition<BlockType>::Decomposition(Decomposition const& other) : blocks(other.blocks) {
// Intentionally left empty.
}
-
+
template <typename BlockType>
Decomposition<BlockType>& Decomposition<BlockType>::operator=(Decomposition const& other) {
this->blocks = other.blocks;
return *this;
}
-
+
template <typename BlockType>
Decomposition<BlockType>::Decomposition(Decomposition&& other) : blocks(std::move(other.blocks)) {
// Intentionally left empty.
}
-
+
template <typename BlockType>
Decomposition<BlockType>& Decomposition<BlockType>::operator=(Decomposition&& other) {
this->blocks = std::move(other.blocks);
return *this;
}
-
+
template <typename BlockType>
std::size_t Decomposition<BlockType>::size() const {
return blocks.size();
}
-
+
template <typename BlockType>
bool Decomposition<BlockType>::empty() const {
return blocks.empty();
}
-
+
template <typename BlockType>
typename Decomposition<BlockType>::iterator Decomposition<BlockType>::begin() {
return blocks.begin();
}
-
+
template <typename BlockType>
typename Decomposition<BlockType>::iterator Decomposition<BlockType>::end() {
return blocks.end();
}
-
+
template <typename BlockType>
typename Decomposition<BlockType>::const_iterator Decomposition<BlockType>::begin() const {
return blocks.begin();
}
-
+
template <typename BlockType>
typename Decomposition<BlockType>::const_iterator Decomposition<BlockType>::end() const {
return blocks.end();
}
-
+
template <typename BlockType>
BlockType const& Decomposition<BlockType>::getBlock(uint_fast64_t index) const {
return blocks.at(index);
}
-
+
template <typename BlockType>
BlockType& Decomposition<BlockType>::getBlock(uint_fast64_t index) {
return blocks.at(index);
}
-
+
template <typename BlockType>
BlockType const& Decomposition<BlockType>::operator[](uint_fast64_t index) const {
return blocks[index];
}
-
+
template <typename BlockType>
BlockType& Decomposition<BlockType>::operator[](uint_fast64_t index) {
return blocks[index];
}
-
+
template <typename BlockType>
template <typename ValueType>
storm::storage::SparseMatrix<ValueType> Decomposition<BlockType>::extractPartitionDependencyGraph(storm::storage::SparseMatrix<ValueType> const& matrix) const {
@@ -97,49 +97,49 @@ namespace storm {
stateToBlockMap[state] = i;
}
}
-
+
// The resulting sparse matrix will have as many rows/columns as there are blocks in the partition.
storm::storage::SparseMatrixBuilder<ValueType> dependencyGraphBuilder(this->size(), this->size());
-
+
for (uint_fast64_t currentBlockIndex = 0; currentBlockIndex < this->size(); ++currentBlockIndex) {
// Get the next block.
block_type const& block = this->getBlock(currentBlockIndex);
-
+
// Now, we determine the blocks which are reachable (in one step) from the current block.
storm::storage::FlatSet<uint_fast64_t> allTargetBlocks;
for (auto state : block) {
for (auto const& transitionEntry : matrix.getRowGroup(state)) {
uint_fast64_t targetBlock = stateToBlockMap[transitionEntry.getColumn()];
-
+
// We only need to consider transitions that are actually leaving the SCC.
if (targetBlock != currentBlockIndex) {
allTargetBlocks.insert(targetBlock);
}
}
}
-
+
// Now we can just enumerate all the target blocks and insert the corresponding transitions.
for (auto const& targetBlock : allTargetBlocks) {
dependencyGraphBuilder.addNextValue(currentBlockIndex, targetBlock, storm::utility::one<ValueType>());
}
}
-
+
return dependencyGraphBuilder.build();
}
-
+
template <typename BlockType>
std::ostream& operator<<(std::ostream& out, Decomposition<BlockType> const& decomposition) {
- out << "[";
+ out << "[ ";
if (decomposition.size() > 0) {
for (uint_fast64_t blockIndex = 0; blockIndex < decomposition.size() - 1; ++blockIndex) {
- out << decomposition.blocks[blockIndex] << ", ";
+ out << decomposition.blocks[blockIndex] << ", " << std::endl;
}
out << decomposition.blocks.back();
}
- out << "]";
+ out << " ]";
return out;
}
-
+
template storm::storage::SparseMatrix<double> Decomposition<StateBlock>::extractPartitionDependencyGraph(storm::storage::SparseMatrix<double> const& matrix) const;
template storm::storage::SparseMatrix<float> Decomposition<StateBlock>::extractPartitionDependencyGraph(storm::storage::SparseMatrix<float> const& matrix) const;
template class Decomposition<StateBlock>;
@@ -149,7 +149,7 @@ namespace storm {
template storm::storage::SparseMatrix<float> Decomposition<StronglyConnectedComponent>::extractPartitionDependencyGraph(storm::storage::SparseMatrix<float> const& matrix) const;
template class Decomposition<StronglyConnectedComponent>;
template std::ostream& operator<<(std::ostream& out, Decomposition<StronglyConnectedComponent> const& decomposition);
-
+
template class Decomposition<MaximalEndComponent>;
template std::ostream& operator<<(std::ostream& out, Decomposition<MaximalEndComponent> const& decomposition);
} // namespace storage
diff --git a/src/storm/storage/MaximalEndComponent.cpp b/src/storm/storage/MaximalEndComponent.cpp
index 68e8eda99..58683a3df 100644
--- a/src/storm/storage/MaximalEndComponent.cpp
+++ b/src/storm/storage/MaximalEndComponent.cpp
@@ -3,125 +3,125 @@
namespace storm {
namespace storage {
-
+
std::ostream& operator<<(std::ostream& out, storm::storage::FlatSet<uint_fast64_t> const& block);
-
+
MaximalEndComponent::MaximalEndComponent() : stateToChoicesMapping() {
// Intentionally left empty.
}
-
+
MaximalEndComponent::MaximalEndComponent(MaximalEndComponent const& other) : stateToChoicesMapping(other.stateToChoicesMapping) {
// Intentionally left empty.
}
-
+
MaximalEndComponent& MaximalEndComponent::operator=(MaximalEndComponent const& other) {
stateToChoicesMapping = other.stateToChoicesMapping;
return *this;
}
-
+
MaximalEndComponent::MaximalEndComponent(MaximalEndComponent&& other) : stateToChoicesMapping(std::move(other.stateToChoicesMapping)) {
// Intentionally left empty.
}
-
+
MaximalEndComponent& MaximalEndComponent::operator=(MaximalEndComponent&& other) {
stateToChoicesMapping = std::move(other.stateToChoicesMapping);
return *this;
}
-
+
void MaximalEndComponent::addState(uint_fast64_t state, set_type const& choices) {
stateToChoicesMapping[state] = choices;
}
-
+
void MaximalEndComponent::addState(uint_fast64_t state, set_type&& choices) {
stateToChoicesMapping.emplace(state, std::move(choices));
}
-
+
std::size_t MaximalEndComponent::size() const {
return stateToChoicesMapping.size();
}
-
+
MaximalEndComponent::set_type const& MaximalEndComponent::getChoicesForState(uint_fast64_t state) const {
auto stateChoicePair = stateToChoicesMapping.find(state);
-
+
if (stateChoicePair == stateToChoicesMapping.end()) {
throw storm::exceptions::InvalidStateException() << "Invalid call to MaximalEndComponent::getChoicesForState: cannot retrieve choices for state not contained in MEC.";
}
-
+
return stateChoicePair->second;
}
-
+
MaximalEndComponent::set_type& MaximalEndComponent::getChoicesForState(uint_fast64_t state) {
auto stateChoicePair = stateToChoicesMapping.find(state);
-
+
if (stateChoicePair == stateToChoicesMapping.end()) {
throw storm::exceptions::InvalidStateException() << "Invalid call to MaximalEndComponent::getChoicesForState: cannot retrieve choices for state not contained in MEC.";
}
-
+
return stateChoicePair->second;
}
-
+
bool MaximalEndComponent::containsState(uint_fast64_t state) const {
auto stateChoicePair = stateToChoicesMapping.find(state);
-
+
if (stateChoicePair == stateToChoicesMapping.end()) {
return false;
}
return true;
}
-
+
void MaximalEndComponent::removeState(uint_fast64_t state) {
auto stateChoicePair = stateToChoicesMapping.find(state);
-
+
if (stateChoicePair == stateToChoicesMapping.end()) {
throw storm::exceptions::InvalidStateException() << "Invalid call to MaximalEndComponent::removeState: cannot remove state not contained in MEC.";
}
-
+
stateToChoicesMapping.erase(stateChoicePair);
}
-
+
bool MaximalEndComponent::containsChoice(uint_fast64_t state, uint_fast64_t choice) const {
auto stateChoicePair = stateToChoicesMapping.find(state);
-
+
if (stateChoicePair == stateToChoicesMapping.end()) {
throw storm::exceptions::InvalidStateException() << "Invalid call to MaximalEndComponent::containsChoice: cannot obtain choices for state not contained in MEC.";
}
-
+
return stateChoicePair->second.find(choice) != stateChoicePair->second.end();
}
-
+
MaximalEndComponent::set_type MaximalEndComponent::getStateSet() const {
set_type states;
states.reserve(stateToChoicesMapping.size());
-
+
for (auto const& stateChoicesPair : stateToChoicesMapping) {
states.insert(stateChoicesPair.first);
}
-
+
return states;
}
-
+
std::ostream& operator<<(std::ostream& out, MaximalEndComponent const& component) {
out << "{";
for (auto const& stateChoicesPair : component.stateToChoicesMapping) {
- out << "{" << stateChoicesPair.first << ", " << stateChoicesPair.second << "}";
+ out << "(" << stateChoicesPair.first << ", " << stateChoicesPair.second << ")";
}
out << "}";
-
+
return out;
}
-
+
MaximalEndComponent::iterator MaximalEndComponent::begin() {
return stateToChoicesMapping.begin();
}
-
+
MaximalEndComponent::iterator MaximalEndComponent::end() {
return stateToChoicesMapping.end();
}
-
+
MaximalEndComponent::const_iterator MaximalEndComponent::begin() const {
return stateToChoicesMapping.begin();
}
-
+
MaximalEndComponent::const_iterator MaximalEndComponent::end() const {
return stateToChoicesMapping.end();
}
diff --git a/src/storm/storage/SparseMatrix.cpp b/src/storm/storage/SparseMatrix.cpp
index 05a526702..d89f7a568 100644
--- a/src/storm/storage/SparseMatrix.cpp
+++ b/src/storm/storage/SparseMatrix.cpp
@@ -21,64 +21,64 @@
namespace storm {
namespace storage {
-
+
template<typename IndexType, typename ValueType>
MatrixEntry<IndexType, ValueType>::MatrixEntry(IndexType column, ValueType value) : entry(column, value) {
// Intentionally left empty.
}
-
+
template<typename IndexType, typename ValueType>
MatrixEntry<IndexType, ValueType>::MatrixEntry(std::pair<IndexType, ValueType>&& pair) : entry(std::move(pair)) {
// Intentionally left empty.
}
-
+
template<typename IndexType, typename ValueType>
IndexType const& MatrixEntry<IndexType, ValueType>::getColumn() const {
return this->entry.first;
}
-
+
template<typename IndexType, typename ValueType>
void MatrixEntry<IndexType, ValueType>::setColumn(IndexType const& column) {
this->entry.first = column;
}
-
+
template<typename IndexType, typename ValueType>
ValueType const& MatrixEntry<IndexType, ValueType>::getValue() const {
return this->entry.second;
}
-
+
template<typename IndexType, typename ValueType>
void MatrixEntry<IndexType, ValueType>::setValue(ValueType const& value) {
this->entry.second = value;
}
-
+
template<typename IndexType, typename ValueType>
std::pair<IndexType, ValueType> const& MatrixEntry<IndexType, ValueType>::getColumnValuePair() const {
return this->entry;
}
-
+
template<typename IndexType, typename ValueType>
MatrixEntry<IndexType, ValueType> MatrixEntry<IndexType, ValueType>::operator*(value_type factor) const {
return MatrixEntry(this->getColumn(), this->getValue() * factor);
}
-
-
+
+
template<typename IndexType, typename ValueType>
bool MatrixEntry<IndexType, ValueType>::operator==(MatrixEntry<IndexType, ValueType> const& other) const {
return this->entry.first == other.entry.first && this->entry.second == other.entry.second;
}
-
+
template<typename IndexType, typename ValueType>
bool MatrixEntry<IndexType, ValueType>::operator!=(MatrixEntry<IndexType, ValueType> const& other) const {
return !(*this == other);
}
-
+
template<typename IndexTypePrime, typename ValueTypePrime>
std::ostream& operator<<(std::ostream& out, MatrixEntry<IndexTypePrime, ValueTypePrime> const& entry) {
out << "(" << entry.getColumn() << ", " << entry.getValue() << ")";
return out;
}
-
+
template<typename ValueType>
SparseMatrixBuilder<ValueType>::SparseMatrixBuilder(index_type rows, index_type columns, index_type entries, bool forceDimensions, bool hasCustomRowGrouping, index_type rowGroups) : initialRowCountSet(rows != 0), initialRowCount(rows), initialColumnCountSet(columns != 0), initialColumnCount(columns), initialEntryCountSet(entries != 0), initialEntryCount(entries), forceInitialDimensions(forceDimensions), hasCustomRowGrouping(hasCustomRowGrouping), initialRowGroupCountSet(rowGroups != 0), initialRowGroupCount(rowGroups), rowGroupIndices(), columnsAndValues(), rowIndications(), currentEntryCount(0), lastRow(0), lastColumn(0), highestColumn(0), currentRowGroupCount(0) {
// Prepare the internal storage.
@@ -96,14 +96,14 @@ namespace storm {
}
rowIndications.push_back(0);
}
-
+
template<typename ValueType>
SparseMatrixBuilder<ValueType>::SparseMatrixBuilder(SparseMatrix<ValueType>&& matrix) : initialRowCountSet(false), initialRowCount(0), initialColumnCountSet(false), initialColumnCount(0), initialEntryCountSet(false), initialEntryCount(0), forceInitialDimensions(false), hasCustomRowGrouping(!matrix.trivialRowGrouping), initialRowGroupCountSet(false), initialRowGroupCount(0), rowGroupIndices(), columnsAndValues(std::move(matrix.columnsAndValues)), rowIndications(std::move(matrix.rowIndications)), currentEntryCount(matrix.entryCount), currentRowGroupCount() {
-
+
lastRow = matrix.rowCount == 0 ? 0 : matrix.rowCount - 1;
lastColumn = columnsAndValues.empty() ? 0 : columnsAndValues.back().getColumn();
highestColumn = matrix.getColumnCount() == 0 ? 0 : matrix.getColumnCount() - 1;
-
+
// If the matrix has a custom row grouping, we move it and remove the last element to make it 'open' again.
if (hasCustomRowGrouping) {
rowGroupIndices = std::move(matrix.rowGroupIndices);
@@ -112,19 +112,19 @@ namespace storm {
}
currentRowGroupCount = rowGroupIndices->empty() ? 0 : rowGroupIndices.get().size() - 1;
}
-
+
// Likewise, we need to 'open' the row indications again.
if (!rowIndications.empty()) {
rowIndications.pop_back();
}
}
-
+
template<typename ValueType>
void SparseMatrixBuilder<ValueType>::addNextValue(index_type row, index_type column, ValueType const& value) {
// Check that we did not move backwards wrt. the row.
STORM_LOG_THROW(row >= lastRow, storm::exceptions::InvalidArgumentException, "Adding an element in row " << row << ", but an element in row " << lastRow << " has already been added.");
STORM_LOG_ASSERT(columnsAndValues.size() == currentEntryCount, "Unexpected size of columnsAndValues vector.");
-
+
// Check if a diagonal entry shall be inserted before
if (pendingDiagonalEntry) {
index_type diagColumn = hasCustomRowGrouping ? currentRowGroupCount - 1 : lastRow;
@@ -143,7 +143,7 @@ namespace storm {
}
}
}
-
+
// If the element is in the same row, but was not inserted in the correct order, we need to fix the row after
// the insertion.
bool fixCurrentRow = row == lastRow && column < lastColumn;
@@ -159,26 +159,26 @@ namespace storm {
rowIndications.resize(row + 1, currentEntryCount);
lastRow = row;
}
-
+
lastColumn = column;
-
+
// Finally, set the element and increase the current size.
columnsAndValues.emplace_back(column, value);
highestColumn = std::max(highestColumn, column);
++currentEntryCount;
-
+
// If we need to fix the row, do so now.
if (fixCurrentRow) {
// First, we sort according to columns.
std::sort(columnsAndValues.begin() + rowIndications.back(), columnsAndValues.end(), [] (storm::storage::MatrixEntry<index_type, ValueType> const& a, storm::storage::MatrixEntry<index_type, ValueType> const& b) {
return a.getColumn() < b.getColumn();
});
-
+
// Then, we eliminate possible duplicate entries.
auto it = std::unique(columnsAndValues.begin() + rowIndications.back(), columnsAndValues.end(), [] (storm::storage::MatrixEntry<index_type, ValueType> const& a, storm::storage::MatrixEntry<index_type, ValueType> const& b) {
return a.getColumn() == b.getColumn();
});
-
+
// Finally, remove the superfluous elements.
std::size_t elementsToRemove = std::distance(it, columnsAndValues.end());
if (elementsToRemove > 0) {
@@ -188,7 +188,7 @@ namespace storm {
}
}
}
-
+
// In case we did not expect this value, we throw an exception.
if (forceInitialDimensions) {
STORM_LOG_THROW(!initialRowCountSet || lastRow < initialRowCount, storm::exceptions::OutOfRangeException, "Cannot insert value at illegal row " << lastRow << ".");
@@ -196,12 +196,12 @@ namespace storm {
STORM_LOG_THROW(!initialEntryCountSet || currentEntryCount <= initialEntryCount, storm::exceptions::OutOfRangeException, "Too many entries in matrix, expected only " << initialEntryCount << ".");
}
}
-
+
template<typename ValueType>
void SparseMatrixBuilder<ValueType>::newRowGroup(index_type startingRow) {
STORM_LOG_THROW(hasCustomRowGrouping, storm::exceptions::InvalidStateException, "Matrix was not created to have a custom row grouping.");
STORM_LOG_THROW(startingRow >= lastRow, storm::exceptions::InvalidStateException, "Illegal row group with negative size.");
-
+
// If there still is a pending diagonal entry, we need to add it now (otherwise, the correct diagonal column will be unclear)
if (pendingDiagonalEntry) {
STORM_LOG_ASSERT(currentRowGroupCount > 0, "Diagonal entry was set before opening the first row group.");
@@ -210,10 +210,10 @@ namespace storm {
pendingDiagonalEntry = boost::none; // clear now, so addNextValue works properly
addNextValue(lastRow, diagColumn, diagValue);
}
-
+
rowGroupIndices.get().push_back(startingRow);
++currentRowGroupCount;
-
+
// Handle the case where the previous row group ends with one or more empty rows
if (lastRow + 1 < startingRow) {
// Close all rows from the most recent one to the starting row.
@@ -224,10 +224,10 @@ namespace storm {
lastColumn = 0;
}
}
-
+
template<typename ValueType>
SparseMatrix<ValueType> SparseMatrixBuilder<ValueType>::build(index_type overriddenRowCount, index_type overriddenColumnCount, index_type overriddenRowGroupCount) {
-
+
// If there still is a pending diagonal entry, we need to add it now
if (pendingDiagonalEntry) {
index_type diagColumn = hasCustomRowGrouping ? currentRowGroupCount - 1 : lastRow;
@@ -235,30 +235,30 @@ namespace storm {
pendingDiagonalEntry = boost::none; // clear now, so addNextValue works properly
addNextValue(lastRow, diagColumn, diagValue);
}
-
+
bool hasEntries = currentEntryCount != 0;
-
+
uint_fast64_t rowCount = hasEntries ? lastRow + 1 : 0;
-
+
// If the last row group was empty, we need to add one more to the row count, because otherwise this empty row is not counted.
if (hasCustomRowGrouping) {
if (lastRow < rowGroupIndices->back()) {
++rowCount;
}
}
-
+
if (initialRowCountSet && forceInitialDimensions) {
STORM_LOG_THROW(rowCount <= initialRowCount, storm::exceptions::InvalidStateException, "Expected not more than " << initialRowCount << " rows, but got " << rowCount << ".");
rowCount = std::max(rowCount, initialRowCount);
}
-
+
rowCount = std::max(rowCount, overriddenRowCount);
-
+
// If the current row count was overridden, we may need to add empty rows.
for (index_type i = lastRow + 1; i < rowCount; ++i) {
rowIndications.push_back(currentEntryCount);
}
-
+
// We put a sentinel element at the last position of the row indices array. This eases iteration work,
// as now the indices of row i are always between rowIndications[i] and rowIndications[i + 1], also for
// the first and last row.
@@ -272,12 +272,12 @@ namespace storm {
columnCount = std::max(columnCount, initialColumnCount);
}
columnCount = std::max(columnCount, overriddenColumnCount);
-
+
uint_fast64_t entryCount = currentEntryCount;
if (initialEntryCountSet && forceInitialDimensions) {
STORM_LOG_THROW(entryCount == initialEntryCount, storm::exceptions::InvalidStateException, "Expected " << initialEntryCount << " entries, but got " << entryCount << ".");
}
-
+
// Check whether row groups are missing some entries.
if (hasCustomRowGrouping) {
uint_fast64_t rowGroupCount = currentRowGroupCount;
@@ -286,15 +286,15 @@ namespace storm {
rowGroupCount = std::max(rowGroupCount, initialRowGroupCount);
}
rowGroupCount = std::max(rowGroupCount, overriddenRowGroupCount);
-
+
for (index_type i = currentRowGroupCount; i <= rowGroupCount; ++i) {
rowGroupIndices.get().push_back(rowCount);
}
}
-
+
return SparseMatrix<ValueType>(columnCount, std::move(rowIndications), std::move(columnsAndValues), std::move(rowGroupIndices));
}
-
+
template<typename ValueType>
typename SparseMatrixBuilder<ValueType>::index_type SparseMatrixBuilder<ValueType>::getLastRow() const {
return lastRow;
@@ -313,7 +313,7 @@ namespace storm {
typename SparseMatrixBuilder<ValueType>::index_type SparseMatrixBuilder<ValueType>::getLastColumn() const {
return lastColumn;
}
-
+
// Debug method for printing the current matrix
template<typename ValueType>
void print(std::vector<typename SparseMatrix<ValueType>::index_type> const& rowGroupIndices, std::vector<MatrixEntry<typename SparseMatrix<ValueType>::index_type, typename SparseMatrix<ValueType>::value_type>> const& columnsAndValues, std::vector<typename SparseMatrix<ValueType>::index_type> const& rowIndications) {
@@ -335,11 +335,11 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
void SparseMatrixBuilder<ValueType>::replaceColumns(std::vector<index_type> const& replacements, index_type offset) {
index_type maxColumn = 0;
-
+
for (index_type row = 0; row < rowIndications.size(); ++row) {
bool changed = false;
auto startRow = std::next(columnsAndValues.begin(), rowIndications[row]);
@@ -365,11 +365,11 @@ namespace storm {
}), "Columns not sorted.");
}
}
-
+
highestColumn = maxColumn;
lastColumn = columnsAndValues.empty() ? 0 : columnsAndValues.back().getColumn();
}
-
+
template<typename ValueType>
void SparseMatrixBuilder<ValueType>::addDiagonalEntry(index_type row, ValueType const& value) {
STORM_LOG_THROW(row >= lastRow, storm::exceptions::InvalidArgumentException, "Adding a diagonal element in row " << row << ", but an element in row " << lastRow << " has already been added.");
@@ -399,59 +399,59 @@ namespace storm {
SparseMatrix<ValueType>::rows::rows(iterator begin, index_type entryCount) : beginIterator(begin), entryCount(entryCount) {
// Intentionally left empty.
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::iterator SparseMatrix<ValueType>::rows::begin() {
return beginIterator;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::iterator SparseMatrix<ValueType>::rows::end() {
return beginIterator + entryCount;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::rows::getNumberOfEntries() const {
return this->entryCount;
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::const_rows::const_rows(const_iterator begin, index_type entryCount) : beginIterator(begin), entryCount(entryCount) {
// Intentionally left empty.
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_iterator SparseMatrix<ValueType>::const_rows::begin() const {
return beginIterator;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_iterator SparseMatrix<ValueType>::const_rows::end() const {
return beginIterator + entryCount;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::const_rows::getNumberOfEntries() const {
return this->entryCount;
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::SparseMatrix() : rowCount(0), columnCount(0), entryCount(0), nonzeroEntryCount(0), columnsAndValues(), rowIndications(), rowGroupIndices() {
// Intentionally left empty.
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::SparseMatrix(SparseMatrix<ValueType> const& other) : rowCount(other.rowCount), columnCount(other.columnCount), entryCount(other.entryCount), nonzeroEntryCount(other.nonzeroEntryCount), columnsAndValues(other.columnsAndValues), rowIndications(other.rowIndications), trivialRowGrouping(other.trivialRowGrouping), rowGroupIndices(other.rowGroupIndices) {
// Intentionally left empty.
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::SparseMatrix(SparseMatrix<value_type> const& other, bool insertDiagonalElements) {
storm::storage::BitVector rowConstraint(other.getRowCount(), true);
storm::storage::BitVector columnConstraint(other.getColumnCount(), true);
*this = other.getSubmatrix(false, rowConstraint, columnConstraint, insertDiagonalElements);
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::SparseMatrix(SparseMatrix<ValueType>&& other) : rowCount(other.rowCount), columnCount(other.columnCount), entryCount(other.entryCount), nonzeroEntryCount(other.nonzeroEntryCount), columnsAndValues(std::move(other.columnsAndValues)), rowIndications(std::move(other.rowIndications)), trivialRowGrouping(other.trivialRowGrouping), rowGroupIndices(std::move(other.rowGroupIndices)) {
// Now update the source matrix
@@ -459,12 +459,12 @@ namespace storm {
other.columnCount = 0;
other.entryCount = 0;
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::SparseMatrix(index_type columnCount, std::vector<index_type> const& rowIndications, std::vector<MatrixEntry<index_type, ValueType>> const& columnsAndValues, boost::optional<std::vector<index_type>> const& rowGroupIndices) : rowCount(rowIndications.size() - 1), columnCount(columnCount), entryCount(columnsAndValues.size()), nonzeroEntryCount(0), columnsAndValues(columnsAndValues), rowIndications(rowIndications), trivialRowGrouping(!rowGroupIndices), rowGroupIndices(rowGroupIndices) {
this->updateNonzeroEntryCount();
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>::SparseMatrix(index_type columnCount, std::vector<index_type>&& rowIndications, std::vector<MatrixEntry<index_type, ValueType>>&& columnsAndValues, boost::optional<std::vector<index_type>>&& rowGroupIndices) : columnCount(columnCount), nonzeroEntryCount(0), columnsAndValues(std::move(columnsAndValues)), rowIndications(std::move(rowIndications)), rowGroupIndices(std::move(rowGroupIndices)) {
// Initialize some variables here which depend on other variables
@@ -474,7 +474,7 @@ namespace storm {
this->trivialRowGrouping = !this->rowGroupIndices;
this->updateNonzeroEntryCount();
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>& SparseMatrix<ValueType>::operator=(SparseMatrix<ValueType> const& other) {
// Only perform assignment if source and target are not the same.
@@ -483,7 +483,7 @@ namespace storm {
columnCount = other.columnCount;
entryCount = other.entryCount;
nonzeroEntryCount = other.nonzeroEntryCount;
-
+
columnsAndValues = other.columnsAndValues;
rowIndications = other.rowIndications;
rowGroupIndices = other.rowGroupIndices;
@@ -491,7 +491,7 @@ namespace storm {
}
return *this;
}
-
+
template<typename ValueType>
SparseMatrix<ValueType>& SparseMatrix<ValueType>::operator=(SparseMatrix<ValueType>&& other) {
// Only perform assignment if source and target are not the same.
@@ -500,7 +500,7 @@ namespace storm {
columnCount = other.columnCount;
entryCount = other.entryCount;
nonzeroEntryCount = other.nonzeroEntryCount;
-
+
columnsAndValues = std::move(other.columnsAndValues);
rowIndications = std::move(other.rowIndications);
rowGroupIndices = std::move(other.rowGroupIndices);
@@ -508,15 +508,15 @@ namespace storm {
}
return *this;
}
-
+
template<typename ValueType>
bool SparseMatrix<ValueType>::operator==(SparseMatrix<ValueType> const& other) const {
if (this == &other) {
return true;
}
-
+
bool equalityResult = true;
-
+
equalityResult &= this->getRowCount() == other.getRowCount();
if (!equalityResult) {
return false;
@@ -533,7 +533,7 @@ namespace storm {
if (!equalityResult) {
return false;
}
-
+
// For the actual contents, we need to do a little bit more work, because we want to ignore elements that
// are set to zero, please they may be represented implicitly in the other matrix.
for (index_type row = 0; row < this->getRowCount(); ++row) {
@@ -559,25 +559,25 @@ namespace storm {
return false;
}
}
-
+
return equalityResult;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getRowCount() const {
return rowCount;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getColumnCount() const {
return columnCount;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getEntryCount() const {
return entryCount;
}
-
+
template<typename T>
uint_fast64_t SparseMatrix<T>::getRowGroupEntryCount(uint_fast64_t const group) const {
uint_fast64_t result = 0;
@@ -590,12 +590,12 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getNonzeroEntryCount() const {
return nonzeroEntryCount;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::updateNonzeroEntryCount() const {
this->nonzeroEntryCount = 0;
@@ -605,12 +605,12 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::updateNonzeroEntryCount(std::make_signed<index_type>::type difference) {
this->nonzeroEntryCount += difference;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::updateDimensions() const {
this->nonzeroEntryCount = 0;
@@ -622,7 +622,7 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getRowGroupCount() const {
if (!this->hasTrivialRowGrouping()) {
@@ -631,12 +631,12 @@ namespace storm {
return rowCount;
}
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getRowGroupSize(index_type group) const {
return this->getRowGroupIndices()[group + 1] - this->getRowGroupIndices()[group];
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getSizeOfLargestRowGroup() const {
if (this->hasTrivialRowGrouping()) {
@@ -650,7 +650,7 @@ namespace storm {
}
return res;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getNumRowsInRowGroups(storm::storage::BitVector const& groupConstraint) const {
if (this->hasTrivialRowGrouping()) {
@@ -669,7 +669,7 @@ namespace storm {
return numRows;
}
-
+
template<typename ValueType>
std::vector<typename SparseMatrix<ValueType>::index_type> const& SparseMatrix<ValueType>::getRowGroupIndices() const {
// If there is no current row grouping, we need to create it.
@@ -679,7 +679,7 @@ namespace storm {
}
return rowGroupIndices.get();
}
-
+
template<typename ValueType>
std::vector<typename SparseMatrix<ValueType>::index_type> SparseMatrix<ValueType>::swapRowGroupIndices(std::vector<index_type>&& newRowGrouping) {
std::vector<index_type> result;
@@ -689,7 +689,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::setRowGroupIndices(std::vector<index_type> const& newRowGroupIndices) {
trivialRowGrouping = false;
@@ -700,7 +700,7 @@ namespace storm {
bool SparseMatrix<ValueType>::hasTrivialRowGrouping() const {
return trivialRowGrouping;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::makeRowGroupingTrivial() {
if (trivialRowGrouping) {
@@ -710,7 +710,7 @@ namespace storm {
rowGroupIndices = boost::none;
}
}
-
+
template<typename ValueType>
storm::storage::BitVector SparseMatrix<ValueType>::getRowFilter(storm::storage::BitVector const& groupConstraint) const {
storm::storage::BitVector res(this->getRowCount(), false);
@@ -722,7 +722,7 @@ namespace storm {
}
return res;
}
-
+
template<typename ValueType>
storm::storage::BitVector SparseMatrix<ValueType>::getRowFilter(storm::storage::BitVector const& groupConstraint, storm::storage::BitVector const& columnConstraint) const {
storm::storage::BitVector result(this->getRowCount(), false);
@@ -743,7 +743,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
storm::storage::BitVector SparseMatrix<ValueType>::getRowGroupFilter(storm::storage::BitVector const& rowConstraint, bool setIfForAllRowsInGroup) const {
STORM_LOG_ASSERT(!this->hasTrivialRowGrouping(), "Tried to get a row group filter but this matrix does not have row groups");
@@ -766,14 +766,14 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::makeRowsAbsorbing(storm::storage::BitVector const& rows) {
for (auto row : rows) {
makeRowDirac(row, row);
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::makeRowGroupsAbsorbing(storm::storage::BitVector const& rowGroupConstraint) {
if (!this->hasTrivialRowGrouping()) {
@@ -788,19 +788,19 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::makeRowDirac(index_type row, index_type column) {
iterator columnValuePtr = this->begin(row);
iterator columnValuePtrEnd = this->end(row);
-
+
// If the row has no elements in it, we cannot make it absorbing, because we would need to move all elements
// in the vector of nonzeros otherwise.
if (columnValuePtr >= columnValuePtrEnd) {
throw storm::exceptions::InvalidStateException() << "Illegal call to SparseMatrix::makeRowDirac: cannot make row " << row << " absorbing, because there is no entry in this row.";
}
iterator lastColumnValuePtr = this->end(row) - 1;
-
+
// If there is at least one entry in this row, we can set it to one, modify its column value to the
// one given by the parameter and set all subsequent elements of this row to zero.
// However, we want to preserve that column indices within a row are ascending, so we pick an entry that is close to the desired column index
@@ -824,7 +824,7 @@ namespace storm {
columnValuePtr->setValue(storm::utility::zero<ValueType>());
}
}
-
+
template<typename ValueType>
bool SparseMatrix<ValueType>::compareRows(index_type i1, index_type i2) const {
const_iterator end1 = this->end(i1);
@@ -841,7 +841,7 @@ namespace storm {
}
return false;
}
-
+
template<typename ValueType>
BitVector SparseMatrix<ValueType>::duplicateRowsInRowgroups() const {
BitVector bv(this->getRowCount());
@@ -856,31 +856,31 @@ namespace storm {
}
return bv;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::swapRows(index_type const& row1, index_type const& row2) {
if (row1 == row2) {
return;
}
-
+
// Get the index of the row that has more / less entries than the other.
index_type largerRow = getRow(row1).getNumberOfEntries() > getRow(row2).getNumberOfEntries() ? row1 : row2;
index_type smallerRow = largerRow == row1 ? row2 : row1;
index_type rowSizeDifference = getRow(largerRow).getNumberOfEntries() - getRow(smallerRow).getNumberOfEntries();
-
+
// Save contents of larger row.
auto copyRow = getRow(largerRow);
std::vector<MatrixEntry<index_type, value_type>> largerRowContents(copyRow.begin(), copyRow.end());
-
+
if (largerRow < smallerRow) {
auto writeIt = getRows(largerRow, smallerRow + 1).begin();
-
+
// Write smaller row to its new position.
for (auto& smallerRowEntry : getRow(smallerRow)) {
*writeIt = std::move(smallerRowEntry);
++writeIt;
}
-
+
// Write the intermediate rows into their correct position.
if (!storm::utility::isZero(rowSizeDifference)) {
for (auto& intermediateRowEntry : getRows(largerRow + 1, smallerRow)) {
@@ -891,15 +891,15 @@ namespace storm {
// skip the intermediate rows
writeIt = getRow(smallerRow).begin();
}
-
+
// Write the larger row to its new position.
for (auto& largerRowEntry : largerRowContents) {
*writeIt = std::move(largerRowEntry);
++writeIt;
}
-
+
STORM_LOG_ASSERT(writeIt == getRow(smallerRow).end(), "Unexpected position of write iterator.");
-
+
// Update the row indications to account for the shift of indices at where the rows now start.
if (!storm::utility::isZero(rowSizeDifference)) {
for (index_type row = largerRow + 1; row <= smallerRow; ++row) {
@@ -908,14 +908,14 @@ namespace storm {
}
} else {
auto writeIt = getRows(smallerRow, largerRow + 1).end() - 1;
-
+
// Write smaller row to its new position
auto copyRow = getRow(smallerRow);
for (auto smallerRowEntryIt = copyRow.end() - 1; smallerRowEntryIt != copyRow.begin() - 1; --smallerRowEntryIt) {
*writeIt = std::move(*smallerRowEntryIt);
--writeIt;
}
-
+
// Write the intermediate rows into their correct position.
if (!storm::utility::isZero(rowSizeDifference)) {
for (auto intermediateRowEntryIt = getRows(smallerRow + 1, largerRow).end() - 1; intermediateRowEntryIt != getRows(smallerRow + 1, largerRow).begin() - 1; --intermediateRowEntryIt) {
@@ -926,15 +926,15 @@ namespace storm {
// skip the intermediate rows
writeIt = getRow(smallerRow).end() - 1;
}
-
+
// Write the larger row to its new position.
for (auto largerRowEntryIt = largerRowContents.rbegin(); largerRowEntryIt != largerRowContents.rend(); ++largerRowEntryIt) {
*writeIt = std::move(*largerRowEntryIt);
--writeIt;
}
-
+
STORM_LOG_ASSERT(writeIt == getRow(smallerRow).begin() - 1, "Unexpected position of write iterator.");
-
+
// Update row indications.
// Update the row indications to account for the shift of indices at where the rows now start.
if (!storm::utility::isZero(rowSizeDifference)) {
@@ -944,11 +944,11 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
std::vector<ValueType> SparseMatrix<ValueType>::getRowSumVector() const {
std::vector<ValueType> result(this->getRowCount());
-
+
index_type row = 0;
for (auto resultIt = result.begin(), resultIte = result.end(); resultIt != resultIte; ++resultIt, ++row) {
*resultIt = getRowSum(row);
@@ -956,7 +956,7 @@ namespace storm {
return result;
}
-
+
template<typename ValueType>
ValueType SparseMatrix<ValueType>::getConstrainedRowSum(index_type row, storm::storage::BitVector const& constraint) const {
ValueType result = storm::utility::zero<ValueType>();
@@ -967,7 +967,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
std::vector<ValueType> SparseMatrix<ValueType>::getConstrainedRowSumVector(storm::storage::BitVector const& rowConstraint, storm::storage::BitVector const& columnConstraint) const {
std::vector<ValueType> result(rowConstraint.getNumberOfSetBits());
@@ -977,7 +977,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
std::vector<ValueType> SparseMatrix<ValueType>::getConstrainedRowGroupSumVector(storm::storage::BitVector const& rowGroupConstraint, storm::storage::BitVector const& columnConstraint) const {
std::vector<ValueType> result;
@@ -995,7 +995,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::getSubmatrix(bool useGroups, storm::storage::BitVector const& rowConstraint, storm::storage::BitVector const& columnConstraint, bool insertDiagonalElements, storm::storage::BitVector const& makeZeroColumns) const {
if (useGroups) {
@@ -1008,14 +1008,14 @@ namespace storm {
*it = i;
}
auto res = getSubmatrix(rowConstraint, columnConstraint, fakeRowGroupIndices, insertDiagonalElements, makeZeroColumns);
-
+
// Create a new row grouping that reflects the new sizes of the row groups if the current matrix has a
// non trivial row-grouping.
if (!this->hasTrivialRowGrouping()) {
std::vector<uint_fast64_t> newRowGroupIndices;
newRowGroupIndices.push_back(0);
auto selectedRowIt = rowConstraint.begin();
-
+
// For this, we need to count how many rows were preserved in every group.
for (uint_fast64_t group = 0; group < this->getRowGroupCount(); ++group) {
uint_fast64_t newRowCount = 0;
@@ -1027,20 +1027,20 @@ namespace storm {
newRowGroupIndices.push_back(newRowGroupIndices.back() + newRowCount);
}
}
-
+
res.trivialRowGrouping = false;
res.rowGroupIndices = newRowGroupIndices;
}
-
+
return res;
}
}
-
+
template<typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::getSubmatrix(storm::storage::BitVector const& rowGroupConstraint, storm::storage::BitVector const& columnConstraint, std::vector<index_type> const& rowGroupIndices, bool insertDiagonalEntries, storm::storage::BitVector const& makeZeroColumns) const {
STORM_LOG_THROW(!rowGroupConstraint.empty() && !columnConstraint.empty(), storm::exceptions::InvalidArgumentException, "Cannot build empty submatrix.");
uint_fast64_t submatrixColumnCount = columnConstraint.getNumberOfSetBits();
-
+
// Start by creating a temporary vector that stores for each index whose bit is set to true the number of
// bits that were set before that particular index.
std::vector<index_type> columnBitsSetBeforeIndex = columnConstraint.getNumberOfSetBitsBeforeIndices();
@@ -1049,7 +1049,7 @@ namespace storm {
tmp = std::make_unique<std::vector<index_type>>(rowGroupConstraint.getNumberOfSetBitsBeforeIndices());
}
std::vector<index_type> const& rowBitsSetBeforeIndex = tmp ? *tmp : columnBitsSetBeforeIndex;
-
+
// Then, we need to determine the number of entries and the number of rows of the submatrix.
index_type subEntries = 0;
index_type subRows = 0;
@@ -1058,17 +1058,17 @@ namespace storm {
subRows += rowGroupIndices[index + 1] - rowGroupIndices[index];
for (index_type i = rowGroupIndices[index]; i < rowGroupIndices[index + 1]; ++i) {
bool foundDiagonalElement = false;
-
+
for (const_iterator it = this->begin(i), ite = this->end(i); it != ite; ++it) {
if (columnConstraint.get(it->getColumn()) && (makeZeroColumns.size() == 0 || !makeZeroColumns.get(it->getColumn())) ) {
++subEntries;
-
+
if (columnBitsSetBeforeIndex[it->getColumn()] == rowBitsSetBeforeIndex[index]) {
foundDiagonalElement = true;
}
}
}
-
+
// If requested, we need to reserve one entry more for inserting the diagonal zero entry.
if (insertDiagonalEntries && !foundDiagonalElement && rowGroupCount < submatrixColumnCount) {
++subEntries;
@@ -1076,10 +1076,10 @@ namespace storm {
}
++rowGroupCount;
}
-
+
// Create and initialize resulting matrix.
SparseMatrixBuilder<ValueType> matrixBuilder(subRows, submatrixColumnCount, subEntries, true, !this->hasTrivialRowGrouping());
-
+
// Copy over selected entries.
rowGroupCount = 0;
index_type rowCount = 0;
@@ -1090,7 +1090,7 @@ namespace storm {
}
for (index_type i = rowGroupIndices[index]; i < rowGroupIndices[index + 1]; ++i) {
bool insertedDiagonalElement = false;
-
+
for (const_iterator it = this->begin(i), ite = this->end(i); it != ite; ++it) {
if (columnConstraint.get(it->getColumn()) && (makeZeroColumns.size() == 0 || !makeZeroColumns.get(it->getColumn()))) {
if (columnBitsSetBeforeIndex[it->getColumn()] == rowBitsSetBeforeIndex[index]) {
@@ -1110,20 +1110,20 @@ namespace storm {
}
++rowGroupCount;
}
-
+
return matrixBuilder.build();
}
-
+
template<typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::restrictRows(storm::storage::BitVector const& rowsToKeep, bool allowEmptyRowGroups) const {
STORM_LOG_ASSERT(rowsToKeep.size() == this->getRowCount(), "Dimensions mismatch.");
-
+
// Count the number of entries of the resulting matrix
uint_fast64_t entryCount = 0;
for (auto const& row : rowsToKeep) {
entryCount += this->getRow(row).getNumberOfEntries();
}
-
+
// Get the smallest row group index such that all row groups with at least this index are empty.
uint_fast64_t firstTrailingEmptyRowGroup = this->getRowGroupCount();
for (auto groupIndexIt = this->getRowGroupIndices().rbegin() + 1; groupIndexIt != this->getRowGroupIndices().rend(); ++groupIndexIt) {
@@ -1133,7 +1133,7 @@ namespace storm {
--firstTrailingEmptyRowGroup;
}
STORM_LOG_THROW(allowEmptyRowGroups || firstTrailingEmptyRowGroup == this->getRowGroupCount(), storm::exceptions::InvalidArgumentException, "Empty rows are not allowed, but row group " << firstTrailingEmptyRowGroup << " is empty.");
-
+
// build the matrix. The row grouping will always be considered as nontrivial.
SparseMatrixBuilder<ValueType> builder(rowsToKeep.getNumberOfSetBits(), this->getColumnCount(), entryCount, true, true, this->getRowGroupCount());
uint_fast64_t newRow = 0;
@@ -1150,12 +1150,12 @@ namespace storm {
}
STORM_LOG_THROW(allowEmptyRowGroups || !rowGroupEmpty, storm::exceptions::InvalidArgumentException, "Empty rows are not allowed, but row group " << rowGroup << " is empty.");
}
-
+
// The all remaining row groups will be empty. Note that it is not allowed to call builder.addNewGroup(...) if there are no more rows afterwards.
SparseMatrix<ValueType> res = builder.build();
return res;
}
-
+
template<typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::filterEntries(storm::storage::BitVector const& rowFilter) const {
// Count the number of entries in the resulting matrix.
@@ -1163,7 +1163,7 @@ namespace storm {
for (auto const& row : rowFilter) {
entryCount += getRow(row).getNumberOfEntries();
}
-
+
// Build the resulting matrix.
SparseMatrixBuilder<ValueType> builder(getRowCount(), getColumnCount(), entryCount);
for (auto const& row : rowFilter) {
@@ -1172,14 +1172,14 @@ namespace storm {
}
}
SparseMatrix<ValueType> result = builder.build();
-
+
// Add a row grouping if necessary.
if (!hasTrivialRowGrouping()) {
result.setRowGroupIndices(getRowGroupIndices());
}
return result;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::dropZeroEntries() {
updateNonzeroEntryCount();
@@ -1200,7 +1200,7 @@ namespace storm {
*this = std::move(result);
}
}
-
+
template<typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::selectRowsFromRowGroups(std::vector<index_type> const& rowGroupToRowIndexMapping, bool insertDiagonalEntries) const {
// First, we need to count how many non-zero entries the resulting matrix will have and reserve space for
@@ -1209,7 +1209,7 @@ namespace storm {
for (index_type rowGroupIndex = 0, rowGroupIndexEnd = rowGroupToRowIndexMapping.size(); rowGroupIndex < rowGroupIndexEnd; ++rowGroupIndex) {
// Determine which row we need to select from the current row group.
index_type rowToCopy = this->getRowGroupIndices()[rowGroupIndex] + rowGroupToRowIndexMapping[rowGroupIndex];
-
+
// Iterate through that row and count the number of slots we have to reserve for copying.
bool foundDiagonalElement = false;
for (const_iterator it = this->begin(rowToCopy), ite = this->end(rowToCopy); it != ite; ++it) {
@@ -1222,15 +1222,15 @@ namespace storm {
++subEntries;
}
}
-
+
// Now create the matrix to be returned with the appropriate size.
SparseMatrixBuilder<ValueType> matrixBuilder(rowGroupIndices.get().size() - 1, columnCount, subEntries);
-
+
// Copy over the selected lines from the source matrix.
for (index_type rowGroupIndex = 0, rowGroupIndexEnd = rowGroupToRowIndexMapping.size(); rowGroupIndex < rowGroupIndexEnd; ++rowGroupIndex) {
// Determine which row we need to select from the current row group.
index_type rowToCopy = this->getRowGroupIndices()[rowGroupIndex] + rowGroupToRowIndexMapping[rowGroupIndex];
-
+
// Iterate through that row and copy the entries. This also inserts a zero element on the diagonal if
// there is no entry yet.
bool insertedDiagonalElement = false;
@@ -1247,7 +1247,7 @@ namespace storm {
matrixBuilder.addNextValue(rowGroupIndex, rowGroupIndex, storm::utility::zero<ValueType>());
}
}
-
+
// Finalize created matrix and return result.
return matrixBuilder.build();
}
@@ -1317,7 +1317,7 @@ namespace storm {
}
return result;
}
-
+
template <typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::transpose(bool joinGroups, bool keepZeros) const {
index_type rowCount = this->getColumnCount();
@@ -1329,10 +1329,10 @@ namespace storm {
this->updateNonzeroEntryCount();
entryCount = this->getNonzeroEntryCount();
}
-
+
std::vector<index_type> rowIndications(rowCount + 1);
std::vector<MatrixEntry<index_type, ValueType>> columnsAndValues(entryCount);
-
+
// First, we need to count how many entries each column has.
for (index_type group = 0; group < columnCount; ++group) {
for (auto const& transition : joinGroups ? this->getRowGroup(group) : this->getRow(group)) {
@@ -1341,17 +1341,17 @@ namespace storm {
}
}
}
-
+
// Now compute the accumulated offsets.
for (index_type i = 1; i < rowCount + 1; ++i) {
rowIndications[i] = rowIndications[i - 1] + rowIndications[i];
}
-
+
// Create an array that stores the index for the next value to be added for
// each row in the transposed matrix. Initially this corresponds to the previously
// computed accumulated offsets.
std::vector<index_type> nextIndices = rowIndications;
-
+
// Now we are ready to actually fill in the values of the transposed matrix.
for (index_type group = 0; group < columnCount; ++group) {
for (auto const& transition : joinGroups ? this->getRowGroup(group) : this->getRow(group)) {
@@ -1361,17 +1361,17 @@ namespace storm {
}
}
}
-
+
storm::storage::SparseMatrix<ValueType> transposedMatrix(columnCount, std::move(rowIndications), std::move(columnsAndValues), boost::none);
-
+
return transposedMatrix;
}
-
+
template <typename ValueType>
SparseMatrix<ValueType> SparseMatrix<ValueType>::transposeSelectedRowsFromRowGroups(std::vector<uint_fast64_t> const& rowGroupChoices, bool keepZeros) const {
index_type rowCount = this->getColumnCount();
index_type columnCount = this->getRowGroupCount();
-
+
// Get the overall entry count as well as the number of entries of each column
index_type entryCount = 0;
std::vector<index_type> rowIndications(columnCount + 1);
@@ -1384,19 +1384,19 @@ namespace storm {
}
}
}
-
+
// Now compute the accumulated offsets.
for (index_type i = 1; i < rowCount + 1; ++i) {
rowIndications[i] = rowIndications[i - 1] + rowIndications[i];
}
-
+
std::vector<MatrixEntry<index_type, ValueType>> columnsAndValues(entryCount);
-
+
// Create an array that stores the index for the next value to be added for
// each row in the transposed matrix. Initially this corresponds to the previously
// computed accumulated offsets.
std::vector<index_type> nextIndices = rowIndications;
-
+
// Now we are ready to actually fill in the values of the transposed matrix.
rowGroupChoiceIt = rowGroupChoices.begin();
for (index_type rowGroup = 0; rowGroup < columnCount; ++rowGroup, ++rowGroupChoiceIt) {
@@ -1407,16 +1407,16 @@ namespace storm {
}
}
}
-
+
return storm::storage::SparseMatrix<ValueType>(std::move(columnCount), std::move(rowIndications), std::move(columnsAndValues), boost::none);
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::convertToEquationSystem() {
invertDiagonal();
negateAllNonDiagonalEntries();
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::invertDiagonal() {
// Now iterate over all row groups and set the diagonal elements to the inverted value.
@@ -1439,14 +1439,14 @@ namespace storm {
foundDiagonalElement = true;
}
}
-
+
// Throw an exception if a row did not have an element on the diagonal.
if (!foundDiagonalElement) {
throw storm::exceptions::InvalidArgumentException() << "Illegal call to SparseMatrix::invertDiagonal: matrix is missing diagonal entries.";
}
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::negateAllNonDiagonalEntries() {
// Iterate over all row groups and negate all the elements that are not on the diagonal.
@@ -1458,7 +1458,7 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::deleteDiagonalEntries() {
// Iterate over all rows and negate all the elements that are not on the diagonal.
@@ -1471,15 +1471,15 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
typename std::pair<storm::storage::SparseMatrix<ValueType>, std::vector<ValueType>> SparseMatrix<ValueType>::getJacobiDecomposition() const {
STORM_LOG_THROW(this->getRowCount() == this->getColumnCount(), storm::exceptions::InvalidArgumentException, "Canno compute Jacobi decomposition of non-square matrix.");
-
+
// Prepare the resulting data structures.
SparseMatrixBuilder<ValueType> luBuilder(this->getRowCount(), this->getColumnCount());
std::vector<ValueType> invertedDiagonal(rowCount);
-
+
// Copy entries to the appropriate matrices.
for (index_type rowNumber = 0; rowNumber < rowCount; ++rowNumber) {
for (const_iterator it = this->begin(rowNumber), ite = this->end(rowNumber); it != ite; ++it) {
@@ -1490,22 +1490,22 @@ namespace storm {
}
}
}
-
+
return std::make_pair(luBuilder.build(), std::move(invertedDiagonal));
}
-
+
#ifdef STORM_HAVE_CARL
template<>
typename std::pair<storm::storage::SparseMatrix<Interval>, std::vector<Interval>> SparseMatrix<Interval>::getJacobiDecomposition() const {
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "This operation is not supported.");
}
-
+
template<>
typename std::pair<storm::storage::SparseMatrix<RationalFunction>, std::vector<RationalFunction>> SparseMatrix<RationalFunction>::getJacobiDecomposition() const {
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "This operation is not supported.");
}
#endif
-
+
template<typename ValueType>
template<typename OtherValueType, typename ResultValueType>
ResultValueType SparseMatrix<ValueType>::getPointwiseProductRowSum(storm::storage::SparseMatrix<OtherValueType> const& otherMatrix, index_type const& row) const {
@@ -1513,7 +1513,7 @@ namespace storm {
typename storm::storage::SparseMatrix<ValueType>::const_iterator ite1 = this->end(row);
typename storm::storage::SparseMatrix<OtherValueType>::const_iterator it2 = otherMatrix.begin(row);
typename storm::storage::SparseMatrix<OtherValueType>::const_iterator ite2 = otherMatrix.end(row);
-
+
ResultValueType result = storm::utility::zero<ResultValueType>();
for (;it1 != ite1 && it2 != ite2; ++it1) {
if (it1->getColumn() < it2->getColumn()) {
@@ -1529,7 +1529,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
template<typename OtherValueType, typename ResultValueType>
std::vector<ResultValueType> SparseMatrix<ValueType>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<OtherValueType> const& otherMatrix) const {
@@ -1540,7 +1540,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyWithVector(std::vector<ValueType> const& vector, std::vector<ValueType>& result, std::vector<value_type> const* summand) const {
// If the vector and the result are aliases and this is not set to be allowed, we need and temporary vector.
@@ -1553,14 +1553,14 @@ namespace storm {
} else {
target = &result;
}
-
+
this->multiplyWithVectorForward(vector, *target, summand);
-
+
if (target == &temporary) {
std::swap(result, *target);
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyWithVectorForward(std::vector<ValueType> const& vector, std::vector<ValueType>& result, std::vector<value_type> const* summand) const {
const_iterator it = this->begin();
@@ -1572,7 +1572,7 @@ namespace storm {
if (summand) {
summandIterator = summand->begin();
}
-
+
for (; resultIterator != resultIteratorEnd; ++rowIterator, ++resultIterator, ++summandIterator) {
ValueType newValue;
if (summand) {
@@ -1580,15 +1580,15 @@ namespace storm {
} else {
newValue = storm::utility::zero<ValueType>();
}
-
+
for (ite = this->begin() + *(rowIterator + 1); it != ite; ++it) {
newValue += it->getValue() * vector[it->getColumn()];
}
-
+
*resultIterator = newValue;
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyWithVectorBackward(std::vector<ValueType> const& vector, std::vector<ValueType>& result, std::vector<value_type> const* summand) const {
const_iterator it = this->end() - 1;
@@ -1600,7 +1600,7 @@ namespace storm {
if (summand) {
summandIterator = summand->end() - 1;
}
-
+
for (; resultIterator != resultIteratorEnd; --rowIterator, --resultIterator, --summandIterator) {
ValueType newValue;
if (summand) {
@@ -1608,15 +1608,15 @@ namespace storm {
} else {
newValue = storm::utility::zero<ValueType>();
}
-
+
for (ite = this->begin() + *rowIterator - 1; it != ite; --it) {
newValue += (it->getValue() * vector[it->getColumn()]);
}
-
+
*resultIterator = newValue;
}
}
-
+
#ifdef STORM_HAVE_INTELTBB
template <typename ValueType>
class TbbMultAddFunctor {
@@ -1624,11 +1624,11 @@ namespace storm {
typedef typename storm::storage::SparseMatrix<ValueType>::index_type index_type;
typedef typename storm::storage::SparseMatrix<ValueType>::value_type value_type;
typedef typename storm::storage::SparseMatrix<ValueType>::const_iterator const_iterator;
-
+
TbbMultAddFunctor(std::vector<MatrixEntry<index_type, value_type>> const& columnsAndEntries, std::vector<uint64_t> const& rowIndications, std::vector<ValueType> const& x, std::vector<ValueType>& result, std::vector<value_type> const* summand) : columnsAndEntries(columnsAndEntries), rowIndications(rowIndications), x(x), result(result), summand(summand) {
// Intentionally left empty.
}
-
+
void operator()(tbb::blocked_range<index_type> const& range) const {
index_type startRow = range.begin();
index_type endRow = range.end();
@@ -1641,18 +1641,18 @@ namespace storm {
if (summand) {
summandIterator = summand->begin() + startRow;
}
-
+
for (; resultIterator != resultIteratorEnd; ++rowIterator, ++resultIterator, ++summandIterator) {
ValueType newValue = summand ? *summandIterator : storm::utility::zero<ValueType>();
-
+
for (ite = columnsAndEntries.begin() + *(rowIterator + 1); it != ite; ++it) {
newValue += it->getValue() * x[it->getColumn()];
}
-
+
*resultIterator = newValue;
}
}
-
+
private:
std::vector<MatrixEntry<index_type, value_type>> const& columnsAndEntries;
std::vector<uint64_t> const& rowIndications;
@@ -1660,7 +1660,7 @@ namespace storm {
std::vector<ValueType>& result;
std::vector<value_type> const* summand;
};
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyWithVectorParallel(std::vector<ValueType> const& vector, std::vector<ValueType>& result, std::vector<value_type> const* summand) const {
if (&vector == &result) {
@@ -1673,7 +1673,7 @@ namespace storm {
}
}
#endif
-
+
template<typename ValueType>
ValueType SparseMatrix<ValueType>::multiplyRowWithVector(index_type row, std::vector<ValueType> const& vector) const {
ValueType result = storm::utility::zero<ValueType>();
@@ -1683,7 +1683,7 @@ namespace storm {
}
return result;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::performSuccessiveOverRelaxationStep(ValueType omega, std::vector<ValueType>& x, std::vector<ValueType> const& b) const {
const_iterator it = this->end() - 1;
@@ -1692,13 +1692,13 @@ namespace storm {
typename std::vector<ValueType>::const_iterator bIt = b.end() - 1;
typename std::vector<ValueType>::iterator resultIterator = x.end() - 1;
typename std::vector<ValueType>::iterator resultIteratorEnd = x.begin() - 1;
-
+
index_type currentRow = getRowCount();
for (; resultIterator != resultIteratorEnd; --rowIterator, --resultIterator, --bIt) {
--currentRow;
ValueType tmpValue = storm::utility::zero<ValueType>();
ValueType diagonalElement = storm::utility::zero<ValueType>();
-
+
for (ite = this->begin() + *rowIterator - 1; it != ite; --it) {
if (it->getColumn() != currentRow) {
tmpValue += it->getValue() * x[it->getColumn()];
@@ -1710,14 +1710,14 @@ namespace storm {
*resultIterator = ((storm::utility::one<ValueType>() - omega) * *resultIterator) + (omega / diagonalElement) * (*bIt - tmpValue);
}
}
-
+
#ifdef STORM_HAVE_CARL
template<>
void SparseMatrix<Interval>::performSuccessiveOverRelaxationStep(Interval, std::vector<Interval>&, std::vector<Interval> const&) const {
STORM_LOG_THROW(false, storm::exceptions::NotSupportedException, "This operation is not supported.");
}
#endif
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::performWalkerChaeStep(std::vector<ValueType> const& x, std::vector<ValueType> const& columnSums, std::vector<ValueType> const& b, std::vector<ValueType> const& ax, std::vector<ValueType>& result) const {
const_iterator it = this->begin();
@@ -1735,7 +1735,7 @@ namespace storm {
result[it->getColumn()] += it->getValue() * (b[row] / ax[row]);
}
}
-
+
auto xIterator = x.begin();
auto sumsIterator = columnSums.begin();
for (auto& entry : result) {
@@ -1751,7 +1751,7 @@ namespace storm {
STORM_LOG_THROW(false, storm::exceptions::NotSupportedException, "This operation is not supported.");
}
#endif
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduceForward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
if (dir == OptimizationDirection::Minimize) {
@@ -1776,36 +1776,36 @@ namespace storm {
if (choices) {
choiceIt = choices->begin();
}
-
+
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
-
+
uint64_t currentRow = 0;
for (auto resultIt = result.begin(), resultIte = result.end(); resultIt != resultIte; ++resultIt, ++choiceIt, ++rowGroupIt) {
ValueType currentValue = storm::utility::zero<ValueType>();
-
+
// Only multiply and reduce if there is at least one row in the group.
if (*rowGroupIt < *(rowGroupIt + 1)) {
if (summand) {
currentValue = *summandIt;
++summandIt;
}
-
+
for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
-
+
if (choices) {
selectedChoice = 0;
if (*choiceIt == 0) {
oldSelectedChoiceValue = currentValue;
}
}
-
+
++rowIt;
++currentRow;
-
+
for (; currentRow < *(rowGroupIt + 1); ++rowIt, ++currentRow) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
@@ -1815,7 +1815,7 @@ namespace storm {
if (choices && currentRow == *choiceIt + *rowGroupIt) {
oldSelectedChoiceValue = newValue;
}
-
+
if (compare(newValue, currentValue)) {
currentValue = newValue;
if (choices) {
@@ -1826,7 +1826,7 @@ namespace storm {
++summandIt;
}
}
-
+
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && compare(currentValue, oldSelectedChoiceValue)) {
@@ -1835,14 +1835,14 @@ namespace storm {
}
}
}
-
+
#ifdef STORM_HAVE_CARL
template<>
void SparseMatrix<storm::RationalFunction>::multiplyAndReduceForward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<storm::RationalFunction> const& vector, std::vector<storm::RationalFunction> const* b, std::vector<storm::RationalFunction>& result, std::vector<uint_fast64_t>* choices) const {
STORM_LOG_THROW(false, storm::exceptions::NotSupportedException, "This operation is not supported.");
}
#endif
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduceBackward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
if (dir == storm::OptimizationDirection::Minimize) {
@@ -1851,7 +1851,7 @@ namespace storm {
multiplyAndReduceBackward<storm::utility::ElementGreater<ValueType>>(rowGroupIndices, vector, summand, result, choices);
}
}
-
+
template<typename ValueType>
template<typename Compare>
void SparseMatrix<ValueType>::multiplyAndReduceBackward(std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
@@ -1867,22 +1867,22 @@ namespace storm {
if (choices) {
choiceIt = choices->end() - 1;
}
-
+
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
-
+
uint64_t currentRow = this->getRowCount() - 1;
for (auto resultIt = result.end() - 1, resultIte = result.begin() - 1; resultIt != resultIte; --resultIt, --choiceIt, --rowGroupIt) {
ValueType currentValue = storm::utility::zero<ValueType>();
-
+
// Only multiply and reduce if there is at least one row in the group.
if (*rowGroupIt < *(rowGroupIt + 1)) {
if (summand) {
currentValue = *summandIt;
--summandIt;
}
-
+
for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) {
currentValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
@@ -1894,17 +1894,17 @@ namespace storm {
}
--rowIt;
--currentRow;
-
+
for (uint64_t i = *rowGroupIt + 1, end = *(rowGroupIt + 1); i < end; --rowIt, --currentRow, ++i, --summandIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = this->begin() + *rowIt - 1; elementIt != elementIte; --elementIt) {
newValue += elementIt->getValue() * vector[elementIt->getColumn()];
}
-
+
if (choices && currentRow == *choiceIt + *rowGroupIt) {
oldSelectedChoiceValue = newValue;
}
-
+
if (compare(newValue, currentValue)) {
currentValue = newValue;
if (choices) {
@@ -1912,7 +1912,7 @@ namespace storm {
}
}
}
-
+
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && compare(currentValue, oldSelectedChoiceValue)) {
@@ -1921,14 +1921,14 @@ namespace storm {
}
}
}
-
+
#ifdef STORM_HAVE_CARL
template<>
void SparseMatrix<storm::RationalFunction>::multiplyAndReduceBackward(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<storm::RationalFunction> const& vector, std::vector<storm::RationalFunction> const* b, std::vector<storm::RationalFunction>& result, std::vector<uint_fast64_t>* choices) const {
STORM_LOG_THROW(false, storm::exceptions::NotSupportedException, "This operation is not supported.");
}
#endif
-
+
#ifdef STORM_HAVE_INTELTBB
template <typename ValueType, typename Compare>
class TbbMultAddReduceFunctor {
@@ -1936,16 +1936,16 @@ namespace storm {
typedef typename storm::storage::SparseMatrix<ValueType>::index_type index_type;
typedef typename storm::storage::SparseMatrix<ValueType>::value_type value_type;
typedef typename storm::storage::SparseMatrix<ValueType>::const_iterator const_iterator;
-
+
TbbMultAddReduceFunctor(std::vector<uint64_t> const& rowGroupIndices, std::vector<MatrixEntry<index_type, value_type>> const& columnsAndEntries, std::vector<uint64_t> const& rowIndications, std::vector<ValueType> const& x, std::vector<ValueType>& result, std::vector<value_type> const* summand, std::vector<uint_fast64_t>* choices) : rowGroupIndices(rowGroupIndices), columnsAndEntries(columnsAndEntries), rowIndications(rowIndications), x(x), result(result), summand(summand), choices(choices) {
// Intentionally left empty.
}
-
+
void operator()(tbb::blocked_range<index_type> const& range) const {
auto groupIt = rowGroupIndices.begin() + range.begin();
auto groupIte = rowGroupIndices.begin() + range.end();
-
+
auto rowIt = rowIndications.begin() + *groupIt;
auto elementIt = columnsAndEntries.begin() + *rowIt;
typename std::vector<ValueType>::const_iterator summandIt;
@@ -1956,9 +1956,9 @@ namespace storm {
if (choices) {
choiceIt = choices->begin() + range.begin();
}
-
+
auto resultIt = result.begin() + range.begin();
-
+
// Variables for correctly tracking choices (only update if new choice is strictly better).
ValueType oldSelectedChoiceValue;
uint64_t selectedChoice;
@@ -1966,7 +1966,7 @@ namespace storm {
uint64_t currentRow = *groupIt;
for (; groupIt != groupIte; ++groupIt, ++resultIt, ++choiceIt) {
ValueType currentValue = storm::utility::zero<ValueType>();
-
+
// Only multiply and reduce if there is at least one row in the group.
if (*groupIt < *(groupIt + 1)) {
if (summand) {
@@ -1977,23 +1977,23 @@ namespace storm {
for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
currentValue += elementIt->getValue() * x[elementIt->getColumn()];
}
-
+
if (choices) {
selectedChoice = 0;
if (*choiceIt == 0) {
oldSelectedChoiceValue = currentValue;
}
}
-
+
++rowIt;
++currentRow;
-
+
for (; currentRow < *(groupIt + 1); ++rowIt, ++currentRow, ++summandIt) {
ValueType newValue = summand ? *summandIt : storm::utility::zero<ValueType>();
for (auto elementIte = columnsAndEntries.begin() + *(rowIt + 1); elementIt != elementIte; ++elementIt) {
newValue += elementIt->getValue() * x[elementIt->getColumn()];
}
-
+
if (choices && currentRow == *choiceIt + *groupIt) {
oldSelectedChoiceValue = newValue;
}
@@ -2005,7 +2005,7 @@ namespace storm {
}
}
}
-
+
// Finally write value to target vector.
*resultIt = currentValue;
if (choices && compare(currentValue, oldSelectedChoiceValue)) {
@@ -2014,7 +2014,7 @@ namespace storm {
}
}
}
-
+
private:
Compare compare;
std::vector<uint64_t> const& rowGroupIndices;
@@ -2025,7 +2025,7 @@ namespace storm {
std::vector<value_type> const* summand;
std::vector<uint_fast64_t>* choices;
};
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduceParallel(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
if (dir == storm::OptimizationDirection::Minimize) {
@@ -2034,7 +2034,7 @@ namespace storm {
tbb::parallel_for(tbb::blocked_range<index_type>(0, rowGroupIndices.size() - 1, 100), TbbMultAddReduceFunctor<ValueType, storm::utility::ElementGreater<ValueType>>(rowGroupIndices, columnsAndValues, rowIndications, vector, result, summand, choices));
}
}
-
+
#ifdef STORM_HAVE_CARL
template<>
void SparseMatrix<storm::RationalFunction>::multiplyAndReduceParallel(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<storm::RationalFunction> const& vector, std::vector<storm::RationalFunction> const* summand, std::vector<storm::RationalFunction>& result, std::vector<uint_fast64_t>* choices) const {
@@ -2042,10 +2042,10 @@ namespace storm {
}
#endif
#endif
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyAndReduce(OptimizationDirection const& dir, std::vector<uint64_t> const& rowGroupIndices, std::vector<ValueType> const& vector, std::vector<ValueType> const* summand, std::vector<ValueType>& result, std::vector<uint_fast64_t>* choices) const {
-
+
// If the vector and the result are aliases, we need and temporary vector.
std::vector<ValueType>* target;
std::vector<ValueType> temporary;
@@ -2056,21 +2056,21 @@ namespace storm {
} else {
target = &result;
}
-
+
this->multiplyAndReduceForward(dir, rowGroupIndices, vector, summand, *target, choices);
if (target == &temporary) {
std::swap(temporary, result);
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::multiplyVectorWithMatrix(std::vector<value_type> const& vector, std::vector<value_type>& result) const {
const_iterator it = this->begin();
const_iterator ite;
std::vector<index_type>::const_iterator rowIterator = rowIndications.begin();
std::vector<index_type>::const_iterator rowIteratorEnd = rowIndications.end();
-
+
uint_fast64_t currentRow = 0;
for (; rowIterator != rowIteratorEnd - 1; ++rowIterator) {
for (ite = this->begin() + *(rowIterator + 1); it != ite; ++it) {
@@ -2079,7 +2079,7 @@ namespace storm {
++currentRow;
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::scaleRowsInPlace(std::vector<ValueType> const& factors) {
STORM_LOG_ASSERT(factors.size() == this->getRowCount(), "Can not scale rows: Number of rows and number of scaling factors do not match.");
@@ -2091,7 +2091,7 @@ namespace storm {
++row;
}
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::divideRowsInPlace(std::vector<ValueType> const& divisors) {
STORM_LOG_ASSERT(divisors.size() == this->getRowCount(), "Can not divide rows: Number of rows and number of divisors do not match.");
@@ -2104,34 +2104,34 @@ namespace storm {
++row;
}
}
-
+
#ifdef STORM_HAVE_CARL
template<>
void SparseMatrix<Interval>::divideRowsInPlace(std::vector<Interval> const&) {
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "This operation is not supported.");
}
#endif
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_rows SparseMatrix<ValueType>::getRows(index_type startRow, index_type endRow) const {
return const_rows(this->columnsAndValues.begin() + this->rowIndications[startRow], this->rowIndications[endRow] - this->rowIndications[startRow]);
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::rows SparseMatrix<ValueType>::getRows(index_type startRow, index_type endRow) {
return rows(this->columnsAndValues.begin() + this->rowIndications[startRow], this->rowIndications[endRow] - this->rowIndications[startRow]);
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_rows SparseMatrix<ValueType>::getRow(index_type row) const {
return getRows(row, row + 1);
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::rows SparseMatrix<ValueType>::getRow(index_type row) {
return getRows(row, row + 1);
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_rows SparseMatrix<ValueType>::getRow(index_type rowGroup, index_type offset) const {
STORM_LOG_ASSERT(rowGroup < this->getRowGroupCount(), "Row group is out-of-bounds.");
@@ -2142,7 +2142,7 @@ namespace storm {
return getRow(this->getRowGroupIndices()[rowGroup] + offset);
}
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::rows SparseMatrix<ValueType>::getRow(index_type rowGroup, index_type offset) {
STORM_LOG_ASSERT(rowGroup < this->getRowGroupCount(), "Row group is out-of-bounds.");
@@ -2154,8 +2154,8 @@ namespace storm {
return getRow(rowGroup + offset);
}
}
-
-
+
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_rows SparseMatrix<ValueType>::getRowGroup(index_type rowGroup) const {
STORM_LOG_ASSERT(rowGroup < this->getRowGroupCount(), "Row group is out-of-bounds.");
@@ -2165,7 +2165,7 @@ namespace storm {
return getRows(rowGroup, rowGroup + 1);
}
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::rows SparseMatrix<ValueType>::getRowGroup(index_type rowGroup) {
STORM_LOG_ASSERT(rowGroup < this->getRowGroupCount(), "Row group is out-of-bounds.");
@@ -2175,32 +2175,32 @@ namespace storm {
return getRows(rowGroup, rowGroup + 1);
}
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_iterator SparseMatrix<ValueType>::begin(index_type row) const {
return this->columnsAndValues.begin() + this->rowIndications[row];
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::iterator SparseMatrix<ValueType>::begin(index_type row) {
return this->columnsAndValues.begin() + this->rowIndications[row];
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_iterator SparseMatrix<ValueType>::end(index_type row) const {
return this->columnsAndValues.begin() + this->rowIndications[row + 1];
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::iterator SparseMatrix<ValueType>::end(index_type row) {
return this->columnsAndValues.begin() + this->rowIndications[row + 1];
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::const_iterator SparseMatrix<ValueType>::end() const {
return this->columnsAndValues.begin() + this->rowIndications[rowCount];
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::iterator SparseMatrix<ValueType>::end() {
return this->columnsAndValues.begin() + this->rowIndications[rowCount];
@@ -2214,7 +2214,7 @@ namespace storm {
}
return sum;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getNonconstantEntryCount() const {
index_type nonConstEntries = 0;
@@ -2225,7 +2225,7 @@ namespace storm {
}
return nonConstEntries;
}
-
+
template<typename ValueType>
typename SparseMatrix<ValueType>::index_type SparseMatrix<ValueType>::getNonconstantRowGroupCount() const {
index_type nonConstRowGroups = 0;
@@ -2239,7 +2239,7 @@ namespace storm {
}
return nonConstRowGroups;
}
-
+
template<typename ValueType>
bool SparseMatrix<ValueType>::isProbabilistic() const {
storm::utility::ConstantsComparator<ValueType> comparator;
@@ -2258,7 +2258,7 @@ namespace storm {
}
return true;
}
-
+
template<typename ValueType>
template<typename OtherValueType>
bool SparseMatrix<ValueType>::isSubmatrixOf(SparseMatrix<OtherValueType> const& matrix) const {
@@ -2269,7 +2269,7 @@ namespace storm {
if (!this->hasTrivialRowGrouping() && matrix.hasTrivialRowGrouping()) return false;
if (!this->hasTrivialRowGrouping() && !matrix.hasTrivialRowGrouping() && this->getRowGroupIndices() != matrix.getRowGroupIndices()) return false;
if (this->getRowGroupIndices() != matrix.getRowGroupIndices()) return false;
-
+
// Check the subset property for all rows individually.
for (index_type row = 0; row < this->getRowCount(); ++row) {
auto it2 = matrix.begin(row);
@@ -2286,7 +2286,7 @@ namespace storm {
}
return true;
}
-
+
template<typename ValueType>
bool SparseMatrix<ValueType>::isIdentityMatrix() const {
if (this->getRowCount() != this->getColumnCount()) {
@@ -2326,7 +2326,7 @@ namespace storm {
return result;
}
-
+
template<typename ValueType>
std::ostream& operator<<(std::ostream& out, SparseMatrix<ValueType> const& matrix) {
// Print column numbers in header.
@@ -2335,22 +2335,22 @@ namespace storm {
out << i << "\t";
}
out << std::endl;
-
+
// Iterate over all row groups.
for (typename SparseMatrix<ValueType>::index_type group = 0; group < matrix.getRowGroupCount(); ++group) {
out << "\t---- group " << group << "/" << (matrix.getRowGroupCount() - 1) << " ---- " << std::endl;
typename SparseMatrix<ValueType>::index_type start = matrix.hasTrivialRowGrouping() ? group : matrix.getRowGroupIndices()[group];
typename SparseMatrix<ValueType>::index_type end = matrix.hasTrivialRowGrouping() ? group + 1 : matrix.getRowGroupIndices()[group + 1];
-
+
for (typename SparseMatrix<ValueType>::index_type i = start; i < end; ++i) {
typename SparseMatrix<ValueType>::index_type nextIndex = matrix.rowIndications[i];
-
+
// Print the actual row.
out << i << "\t(\t";
typename SparseMatrix<ValueType>::index_type currentRealIndex = 0;
while (currentRealIndex < matrix.columnCount) {
if (nextIndex < matrix.rowIndications[i + 1] && currentRealIndex == matrix.columnsAndValues[nextIndex].getColumn()) {
- out << matrix.columnsAndValues[nextIndex].getValue() << "\t";
+ out << std::setprecision(3) << matrix.columnsAndValues[nextIndex].getValue() << "\t";
++nextIndex;
} else {
out << "0\t";
@@ -2360,17 +2360,17 @@ namespace storm {
out << "\t)\t" << i << std::endl;
}
}
-
+
// Print column numbers in footer.
out << "\t\t";
for (typename SparseMatrix<ValueType>::index_type i = 0; i < matrix.getColumnCount(); ++i) {
out << i << "\t";
}
out << std::endl;
-
+
return out;
}
-
+
template<typename ValueType>
void SparseMatrix<ValueType>::printAsMatlabMatrix(std::ostream& out) const {
// Iterate over all row groups.
@@ -2378,7 +2378,7 @@ namespace storm {
STORM_LOG_ASSERT(this->getRowGroupSize(group) == 1, "Incorrect row group size.");
for (typename SparseMatrix<ValueType>::index_type i = this->getRowGroupIndices()[group]; i < this->getRowGroupIndices()[group + 1]; ++i) {
typename SparseMatrix<ValueType>::index_type nextIndex = this->rowIndications[i];
-
+
// Print the actual row.
out << i << "\t(";
typename SparseMatrix<ValueType>::index_type currentRealIndex = 0;
@@ -2395,11 +2395,11 @@ namespace storm {
}
}
}
-
+
template<typename ValueType>
std::size_t SparseMatrix<ValueType>::hash() const {
std::size_t result = 0;
-
+
boost::hash_combine(result, this->getRowCount());
boost::hash_combine(result, this->getColumnCount());
boost::hash_combine(result, this->getEntryCount());
@@ -2408,11 +2408,11 @@ namespace storm {
if (!this->hasTrivialRowGrouping()) {
boost::hash_combine(result, boost::hash_range(rowGroupIndices.get().begin(), rowGroupIndices.get().end()));
}
-
+
return result;
}
-
-
+
+
#ifdef STORM_HAVE_CARL
std::set<storm::RationalFunctionVariable> getVariables(SparseMatrix<storm::RationalFunction> const& matrix)
{
@@ -2422,9 +2422,9 @@ namespace storm {
}
return result;
}
-
+
#endif
-
+
// Explicitly instantiate the entry, builder and the matrix.
// double
template class MatrixEntry<typename SparseMatrix<double>::index_type, double>;
@@ -2435,10 +2435,10 @@ namespace storm {
template double SparseMatrix<double>::getPointwiseProductRowSum(storm::storage::SparseMatrix<double> const& otherMatrix, typename SparseMatrix<double>::index_type const& row) const;
template std::vector<double> SparseMatrix<double>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<double> const& otherMatrix) const;
template bool SparseMatrix<double>::isSubmatrixOf(SparseMatrix<double> const& matrix) const;
-
+
template class MatrixEntry<uint32_t, double>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<uint32_t, double> const& entry);
-
+
// float
template class MatrixEntry<typename SparseMatrix<float>::index_type, float>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<typename SparseMatrix<float>::index_type, float> const& entry);
@@ -2448,7 +2448,7 @@ namespace storm {
template float SparseMatrix<float>::getPointwiseProductRowSum(storm::storage::SparseMatrix<float> const& otherMatrix, typename SparseMatrix<float>::index_type const& row) const;
template std::vector<float> SparseMatrix<float>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<float> const& otherMatrix) const;
template bool SparseMatrix<float>::isSubmatrixOf(SparseMatrix<float> const& matrix) const;
-
+
// int
template class MatrixEntry<typename SparseMatrix<int>::index_type, int>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<typename SparseMatrix<int>::index_type, int> const& entry);
@@ -2456,7 +2456,7 @@ namespace storm {
template class SparseMatrix<int>;
template std::ostream& operator<<(std::ostream& out, SparseMatrix<int> const& matrix);
template bool SparseMatrix<int>::isSubmatrixOf(SparseMatrix<int> const& matrix) const;
-
+
// state_type
template class MatrixEntry<typename SparseMatrix<storm::storage::sparse::state_type>::index_type, storm::storage::sparse::state_type>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<typename SparseMatrix<storm::storage::sparse::state_type>::index_type, storm::storage::sparse::state_type> const& entry);
@@ -2464,10 +2464,10 @@ namespace storm {
template class SparseMatrix<storm::storage::sparse::state_type>;
template std::ostream& operator<<(std::ostream& out, SparseMatrix<storm::storage::sparse::state_type> const& matrix);
template bool SparseMatrix<int>::isSubmatrixOf(SparseMatrix<storm::storage::sparse::state_type> const& matrix) const;
-
+
#ifdef STORM_HAVE_CARL
// Rational Numbers
-
+
#if defined(STORM_HAVE_CLN)
template class MatrixEntry<typename SparseMatrix<ClnRationalNumber>::index_type, ClnRationalNumber>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<uint_fast64_t, ClnRationalNumber> const& entry);
@@ -2478,7 +2478,7 @@ namespace storm {
template std::vector<storm::ClnRationalNumber> SparseMatrix<ClnRationalNumber>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<storm::ClnRationalNumber> const& otherMatrix) const;
template bool SparseMatrix<storm::ClnRationalNumber>::isSubmatrixOf(SparseMatrix<storm::ClnRationalNumber> const& matrix) const;
#endif
-
+
#if defined(STORM_HAVE_GMP)
template class MatrixEntry<typename SparseMatrix<GmpRationalNumber>::index_type, GmpRationalNumber>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<uint_fast64_t, GmpRationalNumber> const& entry);
@@ -2489,7 +2489,7 @@ namespace storm {
template std::vector<storm::GmpRationalNumber> SparseMatrix<GmpRationalNumber>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<storm::GmpRationalNumber> const& otherMatrix) const;
template bool SparseMatrix<storm::GmpRationalNumber>::isSubmatrixOf(SparseMatrix<storm::GmpRationalNumber> const& matrix) const;
#endif
-
+
// Rational Function
template class MatrixEntry<typename SparseMatrix<RationalFunction>::index_type, RationalFunction>;
template std::ostream& operator<<(std::ostream& out, MatrixEntry<uint_fast64_t, RationalFunction> const& entry);
@@ -2505,7 +2505,7 @@ namespace storm {
template std::vector<storm::RationalFunction> SparseMatrix<float>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<storm::RationalFunction> const& otherMatrix) const;
template std::vector<storm::RationalFunction> SparseMatrix<int>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<storm::RationalFunction> const& otherMatrix) const;
template bool SparseMatrix<storm::RationalFunction>::isSubmatrixOf(SparseMatrix<storm::RationalFunction> const& matrix) const;
-
+
// Intervals
template std::vector<storm::Interval> SparseMatrix<double>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<storm::Interval> const& otherMatrix) const;
template class MatrixEntry<typename SparseMatrix<Interval>::index_type, Interval>;
@@ -2515,13 +2515,10 @@ namespace storm {
template std::ostream& operator<<(std::ostream& out, SparseMatrix<Interval> const& matrix);
template std::vector<storm::Interval> SparseMatrix<Interval>::getPointwiseProductRowSumVector(storm::storage::SparseMatrix<storm::Interval> const& otherMatrix) const;
template bool SparseMatrix<storm::Interval>::isSubmatrixOf(SparseMatrix<storm::Interval> const& matrix) const;
-
+
template bool SparseMatrix<storm::Interval>::isSubmatrixOf(SparseMatrix<double> const& matrix) const;
#endif
-
-
- } // namespace storage
-} // namespace storm
-
+ } // namespace storage
+} // namespace storm