/// <summary>
/// Use this method when want to match defined shape in target using cross-correlation.
/// This was the method used by Stewart Gage.
/// First set target and source to same dynamic range.
/// Then NormaliseMatrixValues target and source to unit-length.
/// </summary>
public static Tuple <double[]> Execute_StewartGage(double[,] target, double dynamicRange, SpectrogramStandard sonogram,
List <AcousticEvent> segments, int minHz, int maxHz, double minDuration)
{
Log.WriteLine("SEARCHING FOR EVENTS LIKE TARGET.");
if (segments == null)
{
return(null);
}
int minBin = (int)(minHz / sonogram.FBinWidth);
int maxBin = (int)(maxHz / sonogram.FBinWidth);
int targetLength = target.GetLength(0);
//adjust target's dynamic range to that set by user
target = SNR.SetDynamicRange(target, 0.0, dynamicRange); //set event's dynamic range
double[] v1 = DataTools.Matrix2Array(target);
v1 = DataTools.normalise2UnitLength(v1);
//var image = BaseSonogram.Data2ImageData(target);
//ImageTools.DrawMatrix(image, 1, 1, @"C:\SensorNetworks\Output\FELT_Currawong\target.png");
double[] scores = new double[sonogram.FrameCount];
foreach (AcousticEvent av in segments)
{
Log.WriteLine("SEARCHING SEGMENT.");
int startRow = (int)Math.Round(av.TimeStart * sonogram.FramesPerSecond);
int endRow = (int)Math.Round(av.TimeEnd * sonogram.FramesPerSecond);
if (endRow >= sonogram.FrameCount)
{
endRow = sonogram.FrameCount;
}
int stopRow = endRow - targetLength;
if (stopRow <= startRow)
{
stopRow = startRow + 1; //want minimum of one row
}
int offset = targetLength / 2;
for (int r = startRow; r < stopRow; r++)
{
double[,] matrix = DataTools.Submatrix(sonogram.Data, r, minBin, r + targetLength - 1, maxBin);
matrix = SNR.SetDynamicRange(matrix, 0.0, dynamicRange); //set event's dynamic range
//var image = BaseSonogram.Data2ImageData(matrix);
//ImageTools.DrawMatrix(image, 1, 1, @"C:\SensorNetworks\Output\FELT_CURLEW\compare.png");
double[] v2 = DataTools.Matrix2Array(matrix);
v2 = DataTools.normalise2UnitLength(v2);
scores[r] = DataTools.DotProduct(v1, v2); //the Cross Correlation
} // end of rows in segment
} // foreach (AcousticEvent av in segments)
var tuple = Tuple.Create(scores);
return(tuple);
}
public static double[] AnalyseWaveformAtLocation(double[] signal, double amplitudeThreshold, double scoreThreshold)
{
double[] waveTemplate =
{
-0.000600653, -0.000451427, -0.000193289, -1.91083E-05, 0.000133366, 0.000256465, 0.000387591, 0.000533758, 0.000645976, 0.000670944,
0.000622045, 0.000569337, 0.000553455, 0.000535552, 0.000448935, 0.000286928, 0.000120322, 2.26704E-05, -1.67728E-05, -9.42369E-05,
-0.000289969, -0.000565902, -0.00079103, -0.000883849, -0.000898074, -0.000932191, -0.000985956, -0.00097387, -0.00093, -0.00088,
-0.00088, -0.00087, -0.000883903, -0.000831651, -0.000759236, -0.000668421, -0.00052348, -0.000361632, -0.00028245, -0.000292255,
-0.00025, -8.71854E-05, 0.00011, 0.00014, 0.00010031, 0.00013, 0.00016, 0.000240405, 0.000332283, 0.000357989,
0.000312231, 0.000222307, 0.000138079, 9.49253E-05, 6.74344E-05, -7.81347E-07, -0.000103014, -0.00014973,
};
int templateLength = waveTemplate.Length;
double[] normalTemplate = DataTools.normalise2UnitLength(waveTemplate);
double[] scores = new double[signal.Length];
for (int i = 2; i < signal.Length - templateLength; i++)
{
// look for a local minimum
if (signal[i] > signal[i - 1] || signal[i] > signal[i - 2] || signal[i] > signal[i + 1] || signal[i] > signal[i + 2])
{
continue;
}
double[] subsampleWav = DataTools.Subarray(signal, i, templateLength);
double min, max;
DataTools.MinMax(subsampleWav, out min, out max);
if (max - min < amplitudeThreshold)
{
continue;
}
double[] normalwav = DataTools.normalise2UnitLength(subsampleWav);
// calculate cosine angle as similarity score
double score = DataTools.DotProduct(normalTemplate, normalwav);
if (score > scoreThreshold)
{
for (int j = 0; j < templateLength; j++)
{
if (score > scores[i + j])
{
scores[i + j] = score;
}
}
}
}
//scores = DataTools.NormaliseMatrixValues(scores);
//scores = DataTools.filterMovingAverageOdd(scores, 3);
return(scores);
}
/// <summary>
/// This done using Cosine similarity. Could also use Euclidian distance.
/// </summary>
/// <param name=""></param>
/// <param name=""></param>
public static void CalculateSimilarityScores(Arguments arguments, Output output)
{
int speciesCount = arguments.SpeciesCount;
int instanceCount = arguments.InstanceCount;
output.SimilarityScores = new double[instanceCount, speciesCount];
// loop through all instances
for (int r = 0; r < instanceCount; r++)
{
double[] instance = MatrixTools.GetRow(output.InstanceFeatureMatrix, r);
for (int s = 0; s < speciesCount; s++)
{
double[] species = MatrixTools.GetRow(output.SpeciesFeatureMatrix, s);
double similarity = DataTools.DotProduct(instance, species);
output.SimilarityScores[r, s] = similarity;
}
} // end for loop r over all instances
}
public static Tuple <double[]> Execute_MFCC_XCOR(double[,] target, double dynamicRange, SpectrogramStandard sonogram,
List <AcousticEvent> segments, int minHz, int maxHz, double minDuration)
{
Log.WriteLine("SEARCHING FOR EVENTS LIKE TARGET.");
if (segments == null)
{
return(null);
}
int minBin = (int)(minHz / sonogram.FBinWidth);
int maxBin = (int)(maxHz / sonogram.FBinWidth);
int targetLength = target.GetLength(0);
//set up the matrix of cosine coefficients
int coeffCount = 12; //only use first 12 coefficients.
int binCount = target.GetLength(1); //number of filters in filter bank
double[,] cosines = MFCCStuff.Cosines(binCount, coeffCount + 1); //set up the cosine coefficients
//adjust target's dynamic range to that set by user
target = SNR.SetDynamicRange(target, 3.0, dynamicRange); //set event's dynamic range
target = MFCCStuff.Cepstra(target, coeffCount, cosines);
double[] v1 = DataTools.Matrix2Array(target);
v1 = DataTools.normalise2UnitLength(v1);
string imagePath2 = @"C:\SensorNetworks\Output\FELT_Currawong\target.png";
var result1 = BaseSonogram.Data2ImageData(target);
var image = result1.Item1;
ImageTools.DrawMatrix(image, 1, 1, imagePath2);
double[] scores = new double[sonogram.FrameCount];
foreach (AcousticEvent av in segments)
{
Log.WriteLine("SEARCHING SEGMENT.");
int startRow = (int)Math.Round(av.TimeStart * sonogram.FramesPerSecond);
int endRow = (int)Math.Round(av.TimeEnd * sonogram.FramesPerSecond);
if (endRow >= sonogram.FrameCount)
{
endRow = sonogram.FrameCount - 1;
}
endRow -= targetLength;
if (endRow <= startRow)
{
endRow = startRow + 1; //want minimum of one row
}
for (int r = startRow; r < endRow; r++)
{
double[,] matrix = DataTools.Submatrix(sonogram.Data, r, minBin, r + targetLength - 1, maxBin);
matrix = SNR.SetDynamicRange(matrix, 3.0, dynamicRange); //set event's dynamic range
//string imagePath2 = @"C:\SensorNetworks\Output\FELT_Gecko\compare.png";
//var image = BaseSonogram.Data2ImageData(matrix);
//ImageTools.DrawMatrix(image, 1, 1, imagePath2);
matrix = MFCCStuff.Cepstra(matrix, coeffCount, cosines);
double[] v2 = DataTools.Matrix2Array(matrix);
v2 = DataTools.normalise2UnitLength(v2);
double crossCor = DataTools.DotProduct(v1, v2);
scores[r] = crossCor;
} //end of rows in segment
} //foreach (AcousticEvent av in segments)
var tuple = Tuple.Create(scores);
return(tuple);
}