/// <inheritdoc/>
public void Update(double activation, double normalizedActivation, bool spike)
{
PredictorActivationLinWAvgSettings cfg = (PredictorActivationLinWAvgSettings)Cfg;
if (cfg.Window == PredictorActivationLinWAvgSettings.NAWindowNum)
{
++_continuousWeight;
_continuousAvg.AddSample(activation, _continuousWeight);
}
return;
}
/// <summary>
/// Computes the composite output of the cluster.
/// </summary>
private double[] ComputeCompositeOutput(List <Tuple <int, double[]> > memberNetOutputs)
{
if (Output == TNRNet.OutputType.Real)
{
//Real output
double[] output = new double[NumOfOutputs];
for (int outIdx = 0; outIdx < NumOfOutputs; outIdx++)
{
//Compute weighted average of members single output
WeightedAvg wAvg = new WeightedAvg();
for (int i = 0; i < memberNetOutputs.Count; i++)
{
//Add sub-result to weighted average
wAvg.AddSample(memberNetOutputs[i].Item2[outIdx], _memberNetWeights[i]);
}
//Store averaged output
output[outIdx] = wAvg.Result;
}
//Return averaged outputs
return(output);
}
else
{
//Probabilistic or SingleBool output
int numOfOutputProbabilities = memberNetOutputs[0].Item2.Length;
double[] outProbabilities = new double[numOfOutputProbabilities];
for (int pIdx = 0; pIdx < numOfOutputProbabilities; pIdx++)
{
double[] memberPs = new double[NumOfMembers];
for (int i = 0; i < NumOfMembers; i++)
{
memberPs[i] = PMixer.ProbabilityRange.Rescale(memberNetOutputs[i].Item2[pIdx], OutputDataRange);
}
//Compute members mixed probability
outProbabilities[pIdx] = PMixer.MixP(memberPs, _memberNetWeights);
}
if (numOfOutputProbabilities > 1)
{
outProbabilities.ScaleToNewSum(1d);
}
//Rescale probabilities to output range
for (int pIdx = 0; pIdx < numOfOutputProbabilities; pIdx++)
{
outProbabilities[pIdx] = OutputDataRange.Rescale(outProbabilities[pIdx], PMixer.ProbabilityRange);
}
return(outProbabilities);
}
}
