//------------------------------------------------------------------------------------------------
//------------------------------------------------------------------------------------------------
//------------------------------------------------------------------------------------------------
/*
* Methods:
*/
#region Belief model methods
/// <summary>
/// Gets the raw mass function from the given sensor measure. No option is applied here as
/// it requires data associated to a specific sensor. (Temporisations and variation are thus
/// applied in <see cref="DiscreteSensorData"/>.
/// </summary>
/// <param name="measure">The sensor measure which the belief is inferred from.</param>
/// <returns>Returns a new mass function given the received sensor measure.</returns>
public DiscreteMassFunction GetEvidence(double?measure)
{
// ----
//Build the new mass function:
// ---
DiscreteMassFunction evidence = new DiscreteMassFunction();
if (measure != null)
{
foreach (DiscreteSensorFocalBelief fb in FocalBeliefs)
{
evidence.AddMass(fb.Element, fb.GetEvidence((double)measure));
}
}
else
{
evidence = DiscreteMassFunction.GetVacuousMassFunction(ElementSize);
}
// ---- /Building ---
return(evidence);
}
//------------------------------------------------------------------------------------------------
/// <summary>
/// Builds a new discrete mass function based on the received measure and the current model. If
/// measure == null, it means that no measure has been received. The effect of options (temporisation,
/// variation) are applied here.
/// </summary>
/// <param name="measure">The sensor measure received.</param>
/// <returns>Returns a new discrete mass function based on the current model and the received
/// measurement (and if options are applied also previous measurements).</returns>
public DiscreteMassFunction GetEvidence(double?measure)
{
// ----
//If variation applies:
// ----
double?newMeasure = 0;
int variationIndex = -1;
for (int i = 0; i < Options.Count; i++)
{
if (Options[i].Flag == DiscreteSensorOption.Option_Flags.OP_VARIATION)
{
variationIndex = i;
}
}
if (variationIndex != -1)
{
double sum = 0;
int nbMeasures = 0;
for (int i = 0; i < Options[i].Param; i++)
{
if (Options[i].Data[i].Measure != null)
{
sum += measure.Value - Options[i].Data[i].Measure.Value;
nbMeasures++;
}
}
if (nbMeasures != 0)
{
newMeasure = sum / nbMeasures;
}
else
{
newMeasure = null;
}
Options[variationIndex].AddMeasure(measure);
}
else
{
newMeasure = measure;
}
// ---- /Variations ----
//Get evidence from the model:
DiscreteMassFunction evidence = _model.GetEvidence(newMeasure);
// ----
//Apply temporization if needed:
// ----
int tempo = -1;
for (int i = 0; i < Options.Count; i++)
{
if (Options[i].Flag == DiscreteSensorOption.Option_Flags.OP_TEMPO_FUSION)
{
tempo = i;
}
}
// ----
//Apply tempo fusion:
// ----
if (tempo != -1)
{
long newTime = _watch.ElapsedMilliseconds;
//First measure:
if (Options[tempo].PreviousTime == -1)
{
Options[tempo].UpdatePreviousTime(newTime);
Options[tempo].PreviousMassFunction.Clear();
foreach (FocalElement <DiscreteElement> e in evidence)
{
Options[tempo].PreviousMassFunction.AddMass(e);
}
}
else
{
//Not first measure:
long elapsedTime = newTime - Options[tempo].PreviousTime;
if (newMeasure != null)
{
if (!(elapsedTime >= Options[tempo].Param))
{
DiscreteMassFunction discounted = Options[tempo].PreviousMassFunction.Discounting((double)elapsedTime / Options[tempo].Param);
evidence = discounted.CombinationDuboisPrade(evidence);
}
Options[tempo].UpdatePreviousTime(newTime);
Options[tempo].PreviousMassFunction.Clear();
foreach (FocalElement <DiscreteElement> e in evidence)
{
Options[tempo].PreviousMassFunction.AddMass(e);
}
}
else
{
if (elapsedTime >= Options[tempo].Param)
{
evidence = DiscreteMassFunction.GetVacuousMassFunction(_model.ElementSize);
}
else
{
evidence = Options[tempo].PreviousMassFunction.Discounting((double)elapsedTime / Options[tempo].Param);
}
}
}
// --- /TempoFusion ----
}
else
{
for (int i = 0; i < Options.Count; i++)
{
if (Options[i].Flag == DiscreteSensorOption.Option_Flags.OP_TEMPO_SPECIFICITY)
{
tempo = i;
}
}
// ----
//Apply tempo specificity:
// ----
if (tempo != -1)
{
long newTime = _watch.ElapsedMilliseconds;
//First measure:
if (Options[tempo].PreviousTime == -1)
{
Options[tempo].UpdatePreviousTime(newTime);
Options[tempo].PreviousMassFunction.Clear();
foreach (FocalElement <DiscreteElement> e in evidence)
{
Options[tempo].PreviousMassFunction.AddMass(e);
}
}
else
{
//Not first measure:
long elapsedTime = newTime - Options[tempo].PreviousTime;
if (newMeasure == null)
{
if (elapsedTime >= Options[tempo].Param)
{
evidence = DiscreteMassFunction.GetVacuousMassFunction(_model.ElementSize);
}
else
{
evidence = Options[tempo].PreviousMassFunction.Discounting((double)elapsedTime / Options[tempo].Param);
}
}
else
{
if (elapsedTime >= Options[tempo].Param)
{
Options[tempo].UpdatePreviousTime(newTime);
// ----
Options[tempo].PreviousMassFunction.Clear();
foreach (FocalElement <DiscreteElement> e in evidence)
{
Options[tempo].PreviousMassFunction.AddMass(e);
}
}
else
{
DiscreteMassFunction discounted = Options[tempo].PreviousMassFunction.Discounting((double)elapsedTime / Options[tempo].Param);
if (discounted.Specificity > evidence.Specificity)
{
evidence = discounted;
}
else
{
Options[tempo].UpdatePreviousTime(newTime);
// ----
Options[tempo].PreviousMassFunction.Clear();
foreach (FocalElement <DiscreteElement> e in evidence)
{
Options[tempo].PreviousMassFunction.AddMass(e);
}
}
}
}
}
}
// ---- /TempoSpec ----
}
return(evidence);
}
