public void Reset()
{
af7.Clear();
af8.Clear();
tp9.Clear();
tp10.Clear();
TrainingValues.Clear();
AlphaTrainingValues.Clear();
trainer = null;
training = false;
readingsMean.Clear();
status = EyesStatus.NONE;
ignore = SKIP;
}
private void RunFFT()
{
readingsMean.Clear();
for (int i = 0; i < af7.Count; i++)
{
readingsMean.Add(af7[i] + tp9[i] + tp10[i] + af8[i] / FEATURE_COUNT);
}
CalculateFFT(readingsMean, FFTResults);
CalculateFFT(af7, AF7FFT);
CalculateFFT(af8, AF8FFT);
CalculateFFT(tp9, TP9FFT);
CalculateFFT(tp10, TP10FFT);
if (!Training || (Training && ignore == 0))
{
TrainingValue trainingValue = new TrainingValue((int)Status, FEATURE_COUNT);
trainingValue.Features[0] = PSD(TP9FFT, FREQ_STEP);
trainingValue.Features[1] = PSD(AF7FFT, FREQ_STEP);
trainingValue.Features[2] = PSD(AF8FFT, FREQ_STEP);
trainingValue.Features[3] = PSD(TP10FFT, FREQ_STEP);
if (!Training && trainer != null && trainer.Trained)
{
Status = (EyesStatus)trainer.Predict(trainingValue);
}
if (training || keepTrainingData)
{
TrainingValues.Add(trainingValue);
}
}
else if (Training && ignore != 0)
{
ignore--;
}
}