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); }