public WTAMLModel GetDataFromFiles()
{
var result = new WTAMLModel();
result.Neurons = GetNeurons();
result.Iterations = GetIterationData();
return(result);
}
private WTAMLModel GetNewWeight(WTAMLModel data, WinningNeuronModel winningNeuron, List <double> iteration)
{
var weight = data.Neurons.Find(p => p.Id == winningNeuron.Id).InputsWeight.ToList();
for (int i = 0; i < weight.Count(); i++)
{
weight[i] = Math.Round(weight[i] + (0.5 * (iteration[i] - weight[i])), 3);
}
data.Neurons.Find(p => p.Id == winningNeuron.Id).InputsWeight = weight;
return(data);
}
public void Calc(WTAMLModel data)
{
_outputService.InitInformation(data.Neurons);
for (var it = 0; it < data.Iterations.Count; it++)
{
var iteration = data.Iterations[it];
_outputService.WriteIterationData(iteration, it + 1);
WinningNeuronModel winningNeuron = this.winningNeuron(data.Neurons, iteration);
_outputService.WriteWinningNeuron(winningNeuron.Id + 1);
data = GetNewWeight(data, winningNeuron, iteration);
_outputService.WriteNeuronState(data.Neurons);
}
;
}
public void WTA_Generate()
{
WTAMLModel data = _MLDataService.GetMLData(MLDataService.MLRepos.Lab1);
_networkService.Calc(data);
}