public static void CollectData(string File)
{
const int samples_to_collect = 20000;
EEG eeg = new EEG(COM);
eeg.Start();
Console.WriteLine("Connected");
List <FatSample> all_samples = new List <FatSample>();
for (int j = 0; j < samples_to_collect; j++)
{
FatSample f = new FatSample(eeg.ReadSample(), eeg.ReadSample());
Console.WriteLine(j);
//Console.WriteLine("INDEX: " + index);
all_samples.Add(f);
//Console.WriteLine(f);
//Console.WriteLine();
}
var filestream = System.IO.File.AppendText(File);
foreach (var i in all_samples)
{
filestream.Write(i.ToSpaceSeparated());
}
filestream.Flush();
filestream.Close();
eeg.Stop();
}
public static FatSample Average(FatSample[] samples)
{
FatSample result = new FatSample();
for (int i = 0; i < 16; i++)
{
for (int j = 0; j < samples.Length; j++)
{
result.Channels[i] += samples[j].Channels[i];
}
result.Channels[i] /= samples.Length;
}
for (int j = 0; j < samples.Length; j++)
{
result.AX += samples[j].AX;
result.AY += samples[j].AY;
result.AZ += samples[j].AZ;
}
result.AX /= samples.Length;
result.AY /= samples.Length;
result.AZ /= samples.Length;
return(result);
}
static void EEGTestWithNN2()
{
Console.WriteLine("Training Neural Network");
var n = NNCollectedData2();
Console.WriteLine($"Percent correct: {n.PercentCorrect()}");
Console.WriteLine("Awaiting Connection");
EEG eeg = new EEG(COM);
eeg.Start();
Console.WriteLine("Connected");
Stopwatch s = new Stopwatch();
s.Start();
while (s.ElapsedMilliseconds < 60000)
{
FatSample[] f = new FatSample[chunk_size];
for (int i = 0; i < f.Length; i++)
{
f[i] = new FatSample(eeg.ReadSample(), eeg.ReadSample());
}
Console.WriteLine(n.Predict(FatSamplesToPackedNNData(f)) == 0 ? "Up" : "Down");
}
}
