@ -15,7 +15,7 @@ namespace storm {
std : : vector < ValueType > const & exitRates ,
std : : unordered_map < std : : string , RewardModelType > const & rewardModels ,
boost : : optional < std : : vector < LabelSet > > const & optionalChoiceLabeling )
: NondeterministicModel < ValueType , RewardModelType > ( storm : : models : : ModelType : : MarkovAutomaton , transitionMatrix , stateLabeling , rewardModels , optionalChoiceLabeling ) , markovianStates ( markovianStates ) , exitRates ( exitRates ) , closed ( false ) {
: NondeterministicModel < ValueType , RewardModelType > ( storm : : models : : ModelType : : MarkovAutomaton , transitionMatrix , stateLabeling , rewardModels , optionalChoiceLabeling ) , markovianStates ( markovianStates ) , exitRates ( exitRates ) , closed ( this - > checkIsClosed ( ) ) {
this - > turnRatesToProbabilities ( ) ;
}
@ -26,7 +26,7 @@ namespace storm {
std : : vector < ValueType > const & exitRates ,
std : : unordered_map < std : : string , RewardModelType > & & rewardModels ,
boost : : optional < std : : vector < LabelSet > > & & optionalChoiceLabeling )
: NondeterministicModel < ValueType , RewardModelType > ( storm : : models : : ModelType : : MarkovAutomaton , std : : move ( transitionMatrix ) , std : : move ( stateLabeling ) , std : : move ( rewardModels ) , std : : move ( optionalChoiceLabeling ) ) , markovianStates ( markovianStates ) , exitRates ( std : : move ( exitRates ) ) , closed ( false ) {
: NondeterministicModel < ValueType , RewardModelType > ( storm : : models : : ModelType : : MarkovAutomaton , std : : move ( transitionMatrix ) , std : : move ( stateLabeling ) , std : : move ( rewardModels ) , std : : move ( optionalChoiceLabeling ) ) , markovianStates ( markovianStates ) , exitRates ( std : : move ( exitRates ) ) , closed ( this - > checkIsClosed ( ) ) {
this - > turnRatesToProbabilities ( ) ;
}
@ -97,21 +97,19 @@ namespace storm {
// Now copy over all choices that need to be kept.
uint_fast64_t currentChoice = 0 ;
for ( uint_fast64_t state = 0 ; state < this - > getNumberOfStates ( ) ; + + state ) {
// If the state is a hybrid state, closing it will make it a probabilistic state, so we remove the Markovian marking.
if ( this - > isHybridState ( state ) ) {
this - > markovianStates . set ( state , false ) ;
}
// Record the new beginning of choices of this state.
newTransitionMatrixBuilder . newRowGroup ( currentChoice ) ;
// If we are currently treating a hybrid state, we need to skip its first choice.
// If the state is a hybrid state, closing it will make it a probabilistic state, so we remove the Markovian marking.
// Additionally, we need to remember whether we need to skip the first choice of the state when
// we assemble the new transition matrix.
uint_fast64_t offset = 0 ;
if ( this - > isHybridState ( state ) ) {
// Remove the Markovian state marking.
this - > markovianStates . set ( state , false ) ;
offset = 1 ;
}
for ( uint_fast64_t row = this - > getTransitionMatrix ( ) . getRowGroupIndices ( ) [ state ] + ( this - > isHybridState ( state ) ? 1 : 0 ) ; row < this - > getTransitionMatrix ( ) . getRowGroupIndices ( ) [ state + 1 ] ; + + row ) {
for ( uint_fast64_t row = this - > getTransitionMatrix ( ) . getRowGroupIndices ( ) [ state ] + offset ; row < this - > getTransitionMatrix ( ) . getRowGroupIndices ( ) [ state + 1 ] ; + + row ) {
for ( auto const & entry : this - > getTransitionMatrix ( ) . getRow ( row ) ) {
newTransitionMatrixBuilder . addNextValue ( currentChoice , entry . getColumn ( ) , entry . getValue ( ) ) ;
}
@ -216,12 +214,22 @@ namespace storm {
template < typename ValueType , typename RewardModelType >
void MarkovAutomaton < ValueType , RewardModelType > : : turnRatesToProbabilities ( ) {
for ( auto state : this - > markovianStates ) {
for ( auto & transition : this - > getTransitionMatrix ( ) . getRowGroup ( state ) ) {
for ( auto & transition : this - > getTransitionMatrix ( ) . getRow ( this - > getTransitionMatrix ( ) . getRow GroupIndices ( ) [ state ] ) ) {
transition . setValue ( transition . getValue ( ) / this - > exitRates [ state ] ) ;
}
}
}
template < typename ValueType , typename RewardModelType >
bool MarkovAutomaton < ValueType , RewardModelType > : : checkIsClosed ( ) const {
for ( auto state : markovianStates ) {
if ( this - > getTransitionMatrix ( ) . getRowGroupSize ( state ) > 1 ) {
return false ;
}
}
return true ;
}
template class MarkovAutomaton < double > ;
// template class MarkovAutomaton<float>;