public long?GetRneuronIdFromInputs(RlmGetRneuronIdFromInputs data)
{
RlmNetworkWebAPI network = LoadNetworkFromCache(data);
RlmSessionCaseHistory hist = network.SessionCaseHistory;
return(hist.GetRneuronIdFromInputs(data.InputValuesPair));
}
private IEnumerable <RlmLearnedCase> GetCasesLearningEvents(IEnumerable <IRLVIOValues> inputValues, IEnumerable <IRLVIOValues> outputValues, double scale)
{
IEnumerable <RlmLearnedCase> retVal = null;
var inputValuesPair = TransformIOValues(inputValues);
long?rneuronId = rlmHistory.GetRneuronIdFromInputs(inputValuesPair);
long?solutionId = null;
if (!rneuronId.HasValue)
{
DataNotAvailableEvent?.Invoke(new Exception("Input values did not find a matching rneuron"));
}
else
{
var outputValuesPair = TransformIOValues(outputValues);
solutionId = rlmHistory.GetSolutionIdFromOutputs(outputValuesPair);
if (!solutionId.HasValue)
{
DataNotAvailableEvent?.Invoke(new Exception("Output values did not find a matching solution"));
}
}
if (rneuronId.HasValue && solutionId.HasValue)
{
currentRneuronId = rneuronId.Value;
currentSolutionId = solutionId.Value;
retVal = GetCasesLearningEvents(rneuronId.Value, solutionId.Value, scale);
if (retVal.Count() == 0)
{
DataNotAvailableEvent?.Invoke(new Exception("Cases not yet available for this rneuron and solution combination."));
}
}
return(retVal);
}
public long?GetRneuronIdFromInputs(RlmGetRneuronIdFromInputs data)
{
RlmSessionCaseHistory hist = new RlmSessionCaseHistory(data.RlmName);
return(hist.GetRneuronIdFromInputs(data.InputValuesPair));
}
