private static List <double> CalcEntropy(double[][] imfsF3, double[][] imfsC4, int N, int m, double r)
{
List <double> features = new List <double>();
foreach (var imfF3 in imfsF3)
{
features.Add(SampleEntropy.CalcSampleEntropy(imfF3, N /*(int)(imfF3.Length* percSamples)*/ /*EEGEmoProc2ChSettings.Instance.N.Value*/,
m, r,
EEGEmoProc2ChSettings.Instance.shift.Value));
}
foreach (var imfC4 in imfsC4)
{
features.Add(SampleEntropy.CalcSampleEntropy(imfC4, N /*(int)(imfC4.Length * percSamples)*//*EEGEmoProc2ChSettings.Instance.N.Value*/,
m, r,
EEGEmoProc2ChSettings.Instance.shift.Value));
}
for (int i = 0; i < features.Count; i++)
{
if (features[i].Equals(0))
{
features[i] = _xrand.Next(5) / 100;
}
}
string internalDirectory = _dataAccessFacade.GetGeneralSettings().GetModalDirectory("Emotion");
var file_entropy = File.AppendText(Path.Combine(internalDirectory, "entropy.json"));
file_entropy.WriteLine(features.ToJsonString());
file_entropy.Flush();
file_entropy.Close();
Console.WriteLine(features.ToJsonString());
return(features);
}
private List <double> CalcEntropy(double[][] imfsF3, double[][] imfsC4, int N, int m, double r)
{
List <double> features = new List <double>();
foreach (var imfF3 in imfsF3)
{
features.Add(SampleEntropy.CalcSampleEntropy(imfF3, N, m, r,
EEGEmoProc2ChSettings.Instance.shift.Value));
}
foreach (var imfC4 in imfsC4)
{
features.Add(SampleEntropy.CalcSampleEntropy(imfC4, N, m, r,
EEGEmoProc2ChSettings.Instance.shift.Value));
}
return(features);
}
