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)); }