/// <summary>
/// The values in this class were derived from See5 runs of data taken from ????
/// </summary>
/// <param name="indices"></param>
/// <returns></returns>
public static string ConvertAcousticIndices2Classifcations(RainStruct indices)
{
string classification = header_negative;
if (indices.spikes > 0.2)
{
if (indices.hiFreqCover > 0.24)
{
return(header_rain);
}
else
{
return(header_negative);
}
}
else
{
if (indices.spectralEntropy < 0.6 && indices.bgNoise > -20)
{
return(header_cicada);
}
}
return(classification);
}
} //struct Indices
/// <summary>
///
/// </summary>
/// <param name="signalEnvelope">envelope of the original signal</param>
/// <param name="audioDuration"></param>
/// <param name="frameStepDuration"></param>
/// <param name="spectrogram">the original amplitude spectrum BUT noise reduced</param>
/// <param name="lowFreqBound"></param>
/// <param name="midFreqBound"></param>
/// <param name="binWidth">derived from original nyquist and window/2</param>
/// <returns></returns>
public static Dictionary <string, double> GetIndices(double[] signalEnvelope, TimeSpan audioDuration, TimeSpan frameStepDuration, double[,] spectrogram, int lowFreqBound, int midFreqBound, double binWidth)
{
int chunkDuration = 10; //seconds - assume that signal is not less than one minute duration
double framesPerSecond = 1 / frameStepDuration.TotalSeconds;
int chunkCount = (int)Math.Round(audioDuration.TotalSeconds / chunkDuration);
int framesPerChunk = (int)(chunkDuration * framesPerSecond);
int nyquistBin = spectrogram.GetLength(1);
string[] classifications = new string[chunkCount];
//get acoustic indices and convert to rain indices.
var sb = new StringBuilder();
for (int i = 0; i < chunkCount; i++)
{
int startSecond = i * chunkDuration;
int start = (int)(startSecond * framesPerSecond);
int end = start + framesPerChunk;
if (end >= signalEnvelope.Length)
{
end = signalEnvelope.Length - 1;
}
double[] chunkSignal = DataTools.Subarray(signalEnvelope, start, framesPerChunk);
if (chunkSignal.Length < 50)
{
continue; //an arbitrary minimum length
}
double[,] chunkSpectro = DataTools.Submatrix(spectrogram, start, 1, end, nyquistBin - 1);
RainStruct rainIndices = Get10SecondIndices(chunkSignal, chunkSpectro, lowFreqBound, midFreqBound, frameStepDuration, binWidth);
string classification = ConvertAcousticIndices2Classifcations(rainIndices);
classifications[i] = classification;
//write indices and classification info to console
string separator = ",";
string line = string.Format("{1:d2}{0} {2:d2}{0} {3:f1}{0} {4:f1}{0} {5:f1}{0} {6:f2}{0} {7:f3}{0} {8:f2}{0} {9:f2}{0} {10:f2}{0} {11:f2}{0} {12:f2}{0} {13:f2}{0} {14}", separator,
startSecond, startSecond + chunkDuration,
rainIndices.avSig_dB, rainIndices.bgNoise, rainIndices.snr,
rainIndices.activity, rainIndices.spikes, rainIndices.ACI,
rainIndices.lowFreqCover, rainIndices.midFreqCover, rainIndices.hiFreqCover,
rainIndices.temporalEntropy, rainIndices.spectralEntropy, classification);
//if (verbose)
if (false)
{
LoggedConsole.WriteLine(line);
}
//FOR PREPARING SEE.5 DATA ------- write indices and clsasification info to file
//sb.AppendLine(line);
}
//FOR PREPARING SEE.5 DATA ------ write indices and clsasification info to file
//string opDir = @"C:\SensorNetworks\Output\Rain";
//string opPath = Path.Combine(opDir, recording.BaseName + ".Rain.csv");
//FileTools.WriteTextFile(opPath, sb.ToString());
Dictionary <string, double> dict = ConvertClassifcations2Dictionary(classifications);
return(dict);
} //Analysis()
