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package explicit;
import java.util.ArrayList;
import java.util.BitSet;
import java.util.Vector;
import automata.finite.DeterministicFiniteAutomaton;
import automata.finite.EdgeLabel;
import automata.finite.NondeterministicFiniteAutomaton;
import automata.finite.State;
import explicit.rewards.MCRewards;
import explicit.rewards.MDPRewards;
import explicit.rewards.Rewards;
import parser.ast.ExpressionAccumulation;
import parser.ast.ExpressionRegular;
import prism.PrismException;
import prism.PrismSettings;
/**
* An AccumulationProduct has ProductStates, where the first component is the
* stateId in the original model, and the second component is the index of an
* AccumulationTracker.
*
* @author Sascha Wunderlich
*
* @param <M>
*/
public class AccumulationProductComplexRegular<M extends Model> extends AccumulationProductComplex<M,State>
{
protected DeterministicFiniteAutomaton<String> automaton;
public AccumulationProductComplexRegular(M originalModel) {
super(originalModel);
}
@SuppressWarnings("unchecked")
public static <T extends Model, R extends Rewards> AccumulationProductComplexRegular<T> generate(final Model graph, final ExpressionAccumulation accexp, final Vector<R> rewards, final ProbModelChecker mc, BitSet statesOfInterest) throws PrismException {
switch(graph.getModelType()) {
case DTMC:
return (AccumulationProductComplexRegular<T>)generate((DTMC) graph, accexp, (Vector<MCRewards>) rewards, mc, statesOfInterest);
case MDP:
return (AccumulationProductComplexRegular<T>)generate((MDP) graph, accexp, (Vector<MDPRewards>) rewards, mc, statesOfInterest);
default:
throw new PrismException("Can't handle accumulation product for " + graph.getModelType());
}
}
public static AccumulationProductComplexRegular<DTMC> generate(final DTMC graph, final ExpressionAccumulation accexp, final Vector<MCRewards> rewards, final ProbModelChecker mc, BitSet statesOfInterest) throws PrismException {
final AccumulationProductComplexRegular<DTMC> result = new AccumulationProductComplexRegular<DTMC>(graph);
// Create auxiliary data
result.createAuxData(graph, accexp, rewards, mc);
// Build an operator
class AccumulationDTMCProductOperator implements DTMCProductOperator
{
@Override
public ProductState getInitialState(Integer dtmc_state)
throws PrismException {
int initialAccStateId = result.createInitialStateId();
return new ProductState(dtmc_state, initialAccStateId);
}
@Override
public ProductState getSuccessor(ProductState from_state,
Integer dtmc_to_state) throws PrismException {
// Get the current accumulation state
AccumulationState<State> from_accstate = result.accStates.getById(from_state.getSecondState());
// Get step weights
double[] weights = new double[rewards.size()];
for (int i=0; i < rewards.size(); i++) {
weights[i] = rewards.get(i).getStateReward(from_state.getFirstState());
}
// Update accumulation product state, store it and get its ID.
AccumulationState<State> to_accproduct = result.updateAccumulationState(from_state.getFirstState(), from_accstate, accexp, weights, mc);
int to_accproduct_id = result.accStates.findOrAdd(to_accproduct);
return new ProductState(dtmc_to_state, to_accproduct_id);
}
@Override
public void notify(ProductState state, Integer index)
throws PrismException {
result.generateTrackInfo(state, index, accexp, mc);
}
@Override
public void finish() throws PrismException {
// Do nothing
}
@Override
public DTMC getGraph() {
return graph;
}
}
// Apply the operator
AccumulationDTMCProductOperator op = new AccumulationDTMCProductOperator();
ProductWithProductStates.generate(op, result, statesOfInterest);
return result;
}
public static AccumulationProductComplexRegular<MDP> generate(final MDP graph, final ExpressionAccumulation accexp, final Vector<MDPRewards> rewards, final ProbModelChecker mc, BitSet statesOfInterest) throws PrismException {
// This is basically the same thing as for DTMCs
final AccumulationProductComplexRegular<MDP> result = new AccumulationProductComplexRegular<MDP>(graph);
// Create auxiliary data
result.createAuxData(graph, accexp, rewards, mc);
class AccumulationMDPProductOperator implements MDPProductOperator
{
@Override
public ProductState getInitialState(Integer MDP_state)
throws PrismException {
int initialAccStateId = result.createInitialStateId();
return new ProductState(MDP_state, initialAccStateId);
}
@Override
public ProductState getSuccessor(ProductState from_state,
int choice_i, Integer mdp_to_state) throws PrismException {
// Get the current accumulation state
AccumulationState<State> from_accstate = result.accStates.getById(from_state.getSecondState());
// Get step weights
// THIS IS DIFFERENT FROM ABOVE!
double[] weights = new double[rewards.size()];
for (int i=0; i < rewards.size(); i++) {
double currentWeight = rewards.get(i).getStateReward(from_state.getFirstState());
currentWeight += rewards.get(i).getTransitionReward(from_state.getFirstState(), choice_i);
weights[i] = currentWeight;
}
// Update accumulation product state, store it and get its ID.
AccumulationState<State> to_accproduct = result.updateAccumulationState(from_state.getFirstState(), from_accstate, accexp, weights, mc);
int to_accproduct_id = result.accStates.findOrAdd(to_accproduct);
return new ProductState(mdp_to_state, to_accproduct_id);
}
@Override
public void notify(ProductState state, Integer index)
throws PrismException {
result.generateTrackInfo(state, index, accexp, mc);
}
@Override
public void finish() throws PrismException {
// Do nothing
}
@Override
public MDP getGraph() {
return graph;
}
}
AccumulationMDPProductOperator op = new AccumulationMDPProductOperator();
ProductWithProductStates.generate(op, result, statesOfInterest);
return result;
}
@Override
protected boolean isFinalTrack(AccumulationTrack<State> track, ExpressionAccumulation accexp, ProbModelChecker mc) throws PrismException {
boolean isFinal = false;
if ( track != null ) {
isFinal = automaton.isAcceptingState(track.getComponent());
}
return isFinal;
}
@Override
protected State getInitialComponent() {
return automaton.getInitialState();
}
@Override
protected State updateComponent(Integer modelFromStateId, final AccumulationTrack<State> track,
final ExpressionAccumulation accexp, final StateModelChecker mc) {
State currentState = track.getComponent();
// Build EdgeLabel from labels.
// labels is a BitSet with labels L0,...,Ln
ArrayList<String> edgeSymbols = new ArrayList<>();
BitSet edgeValues = new BitSet();
for (int i=0; i < labels.size(); i++) {
// Each bitLabel contains one L
edgeSymbols.add(i, "L"+i);
if(labels.get(i).get(modelFromStateId)) {
edgeValues.set(i);
}
}
EdgeLabel<String> edgeLabel = new EdgeLabel<>(edgeSymbols, edgeValues);
State nextState = automaton.getSuccessor(currentState,edgeLabel);
if(nextState == null) { return null; }
return nextState;
}
/**
* Populates fields:
* - automaton with a trimmed deterministic finite automaton,
* - numberOfTracks with the length of its longest path plus one, and
* - numberOfWeights with the size of the reward vector.
*
* @param graph
* @param accexp
* @param mc
* @throws PrismException
*/
protected void createAuxData(final Model graph, final ExpressionAccumulation accexp, final Vector<? extends Rewards> rewards, final ProbModelChecker mc) throws PrismException {
// Build labels and DFA
AccumulationModelChecker accMc = new AccumulationModelChecker();
ExpressionRegular reg = (ExpressionRegular)accMc.checkMaximalStateFormulas(mc, graph, accexp.getRegularExpression(), labels);
// Create and store the actual DFA
NondeterministicFiniteAutomaton<String> nfa = NondeterministicFiniteAutomaton.fromExpressionRegular(reg);
//System.out.println(nfa.toDot());
automaton = nfa.determinize();
automaton.trim(); // This should remove cycles.
if(mc.getSettings().getBoolean(PrismSettings.ACC_GENERATE_DOTS)) {
nfa.exportToDotFile("DEBUG-automaton-nfa.dot");
automaton.exportToDotFile("DEBUG-automaton-dfa.dot");
}
if (!automaton.isAcyclic()) {
throw new PrismException("Cannot handle cyclic automata!");
}
numberOfTracks = automaton.getLongestPathLength()+1;
numberOfWeights= rewards.size();
for(int i=0; i<numberOfTracks; i++) {
initStates.add(new BitSet());
runStates.add(new BitSet());
goalStates.add(new BitSet());
}
}
}