/// <summary>
 /// Adds an epsilon-loop with a specified number of intermediate states to a given state.
 /// </summary>
 /// <param name="state">The state.</param>
 /// <param name="loopSize">The number of intermediate states in the loop.</param>
 /// <param name="loopWeight">The weight of the loop.</param>
 private static void AddEpsilonLoop(StringAutomaton.State state, int loopSize, double loopWeight)
 {
     StringAutomaton.State currentState = state;
     for (int i = 0; i <= loopSize; ++i)
     {
         currentState = currentState.AddEpsilonTransition(
             i == 0 ? Weight.FromValue(loopWeight) : Weight.One,
             i == loopSize ? state : null);
     }
 }
Exemple #2
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        /// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="SingleOp"]/message_doc[@name="CharacterAverageConditional(StringDistribution)"]/*'/>
        public static DiscreteChar CharacterAverageConditional(StringDistribution str)
        {
            Argument.CheckIfNotNull(str, "str");

            if (str.IsPointMass)
            {
                return(CharacterAverageConditional(str.Point));
            }

            Vector          resultLogProb = PiecewiseVector.Constant(char.MaxValue + 1, double.NegativeInfinity);
            StringAutomaton probFunc      = str.GetWorkspaceOrPoint();

            StringAutomaton.EpsilonClosure startEpsilonClosure = new Automaton <string, char, DiscreteChar, StringManipulator, StringAutomaton> .EpsilonClosure(probFunc, probFunc.Start);

            for (int stateIndex = 0; stateIndex < startEpsilonClosure.Size; ++stateIndex)
            {
                StringAutomaton.State state = startEpsilonClosure.GetStateByIndex(stateIndex);
                Weight stateLogWeight       = startEpsilonClosure.GetStateWeightByIndex(stateIndex);
                foreach (var transition in state.Transitions)
                {
                    if (!transition.IsEpsilon)
                    {
                        StringAutomaton.State          destState        = probFunc.States[transition.DestinationStateIndex];
                        StringAutomaton.EpsilonClosure destStateClosure = new Automaton <string, char, DiscreteChar, StringManipulator, StringAutomaton> .EpsilonClosure(probFunc, destState);

                        if (!destStateClosure.EndWeight.IsZero)
                        {
                            Weight weight   = Weight.Product(stateLogWeight, transition.Weight, destStateClosure.EndWeight);
                            var    logProbs = transition.ElementDistribution.Value.GetProbs();
                            logProbs.SetToFunction(logProbs, Math.Log);
                            resultLogProb = LogSumExp(resultLogProb, logProbs, weight);
                        }
                    }
                }
            }

            if (resultLogProb.All(double.IsNegativeInfinity))
            {
                throw new AllZeroException("An input distribution assigns zero probability to all single character strings.");
            }

            Vector resultProb    = PiecewiseVector.Zero(char.MaxValue + 1);
            double logNormalizer = resultLogProb.LogSumExp();

            resultProb.SetToFunction(resultLogProb, lp => Math.Exp(lp - logNormalizer));
            return(DiscreteChar.FromVector(resultProb));
        }
Exemple #3
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        /// <summary>EP message to <c>character</c>.</summary>
        /// <param name="str">Incoming message from <c>str</c>.</param>
        /// <returns>The outgoing EP message to the <c>character</c> argument.</returns>
        /// <remarks>
        ///   <para>The outgoing message is a distribution matching the moments of <c>character</c> as the random arguments are varied. The formula is <c>proj[p(character) sum_(str) p(str) factor(character,str)]/p(character)</c>.</para>
        /// </remarks>
        public static DiscreteChar CharacterAverageConditional(StringDistribution str)
        {
            Argument.CheckIfNotNull(str, "str");

            Vector          resultlogProb = PiecewiseVector.Constant(char.MaxValue + 1, double.NegativeInfinity);
            StringAutomaton probFunc      = str.GetProbabilityFunction();

            StringAutomaton.EpsilonClosure startEpsilonClosure = probFunc.Start.GetEpsilonClosure();
            for (int stateIndex = 0; stateIndex < startEpsilonClosure.Size; ++stateIndex)
            {
                StringAutomaton.State state = startEpsilonClosure.GetStateByIndex(stateIndex);
                double stateLogWeight       = startEpsilonClosure.GetStateLogWeightByIndex(stateIndex);
                for (int transitionIndex = 0; transitionIndex < state.Transitions.Count; ++transitionIndex)
                {
                    StringAutomaton.Transition transition = state.Transitions[transitionIndex];
                    if (!transition.IsEpsilon)
                    {
                        StringAutomaton.State          destState        = probFunc.States[transition.DestinationStateIndex];
                        StringAutomaton.EpsilonClosure destStateClosure = destState.GetEpsilonClosure();
                        if (!double.IsNegativeInfinity(destStateClosure.EndLogWeight))
                        {
                            double logWeight = stateLogWeight + transition.LogWeight + destStateClosure.EndLogWeight;
                            resultlogProb = LogSumExp(resultlogProb, transition.ElementDistribution.GetInternalDiscrete().GetLogProbs(), logWeight);
                        }
                    }
                }
            }

            if (resultlogProb.All(double.IsNegativeInfinity))
            {
                throw new AllZeroException("An input distribution assigns zero probability to all single character strings.");
            }

            Vector resultProb = PiecewiseVector.Zero(char.MaxValue + 1);

            resultProb.SetToFunction(resultlogProb, Math.Exp);
            return(DiscreteChar.FromVector(resultProb));
        }