/// <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 = probFunc.Start.GetEpsilonClosure();
for (int stateIndex = 0; stateIndex < startEpsilonClosure.Size; ++stateIndex)
{
StringAutomaton.State state = startEpsilonClosure.GetStateByIndex(stateIndex);
Weight stateLogWeight = startEpsilonClosure.GetStateWeightByIndex(stateIndex);
for (int transitionIndex = 0; transitionIndex < state.TransitionCount; ++transitionIndex)
{
StringAutomaton.Transition transition = state.GetTransition(transitionIndex);
if (!transition.IsEpsilon)
{
StringAutomaton.State destState = probFunc.States[transition.DestinationStateIndex];
StringAutomaton.EpsilonClosure destStateClosure = destState.GetEpsilonClosure();
if (!destStateClosure.EndWeight.IsZero)
{
Weight weight = Weight.Product(stateLogWeight, transition.Weight, destStateClosure.EndWeight);
var logProbs = transition.ElementDistribution.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));
}
/// <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));
}