/// <summary>
/// THE KEY ANALYSIS METHOD
/// </summary>
/// <param name="recording">
/// The segment Of Source File.
/// </param>
/// <param name="configDict">
/// The config Dict.
/// </param>
/// <param name="value"></param>
/// <returns>
/// The <see cref="LimnodynastesConvexResults"/>.
/// </returns>
internal static LimnodynastesConvexResults Analysis(
Dictionary <string, double[, ]> dictionaryOfHiResSpectralIndices,
AudioRecording recording,
Dictionary <string, string> configDict,
AnalysisSettings analysisSettings,
SegmentSettingsBase segmentSettings)
{
// for Limnodynastes convex, in the D.Stewart CD, there are peaks close to:
//1. 1950 Hz
//2. 1460 hz
//3. 970 hz These are 490 Hz apart.
// for Limnodynastes convex, in the JCU recording, there are peaks close to:
//1. 1780 Hz
//2. 1330 hz
//3. 880 hz These are 450 Hz apart.
// So strategy is to look for three peaks separated by same amount and in the vicinity of the above,
// starting with highest power (the top peak) and working down to lowest power (bottom peak).
var outputDir = segmentSettings.SegmentOutputDirectory;
TimeSpan segmentStartOffset = segmentSettings.SegmentStartOffset;
//KeyValuePair<string, double[,]> kvp = dictionaryOfHiResSpectralIndices.First();
var spg = dictionaryOfHiResSpectralIndices["RHZ"];
int rhzRowCount = spg.GetLength(0);
int rhzColCount = spg.GetLength(1);
int sampleRate = recording.SampleRate;
double herzPerBin = sampleRate / 2 / (double)rhzRowCount;
double scoreThreshold = (double?)double.Parse(configDict["EventThreshold"]) ?? 3.0;
int minimumFrequency = (int?)int.Parse(configDict["MinHz"]) ?? 850;
int dominantFrequency = (int?)int.Parse(configDict["DominantFrequency"]) ?? 1850;
// # The Limnodynastes call has three major peaks. The dominant peak is at 1850 or as set above.
// # The second and third peak are at equal gaps below. DominantFreq-gap and DominantFreq-(2*gap);
// # Set the gap in the Config file. Should typically be in range 880 to 970
int peakGapInHerz = (int?)int.Parse(configDict["PeakGap"]) ?? 470;
int F1AndF2Gap = (int)Math.Round(peakGapInHerz / herzPerBin);
//int F1AndF2Gap = 10; // 10 = number of freq bins
int F1AndF3Gap = 2 * F1AndF2Gap;
//int F1AndF3Gap = 20;
int hzBuffer = 250;
int bottomBin = 5;
int dominantBin = (int)Math.Round(dominantFrequency / herzPerBin);
int binBuffer = (int)Math.Round(hzBuffer / herzPerBin);;
int dominantBinMin = dominantBin - binBuffer;
int dominantBinMax = dominantBin + binBuffer;
// freqBin + rowID = binCount - 1;
// therefore: rowID = binCount - freqBin - 1;
int minRowID = rhzRowCount - dominantBinMax - 1;
int maxRowID = rhzRowCount - dominantBinMin - 1;
int bottomRow = rhzRowCount - bottomBin - 1;
var list = new List <Point>();
// loop through all spectra/columns of the hi-res spectrogram.
for (int c = 1; c < rhzColCount - 1; c++)
{
double maxAmplitude = -double.MaxValue;
int idOfRowWithMaxAmplitude = 0;
for (int r = minRowID; r <= bottomRow; r++)
{
if (spg[r, c] > maxAmplitude)
{
maxAmplitude = spg[r, c];
idOfRowWithMaxAmplitude = r;
}
}
if (idOfRowWithMaxAmplitude < minRowID)
{
continue;
}
if (idOfRowWithMaxAmplitude > maxRowID)
{
continue;
}
// want a spectral peak.
if (spg[idOfRowWithMaxAmplitude, c] < spg[idOfRowWithMaxAmplitude, c - 1])
{
continue;
}
if (spg[idOfRowWithMaxAmplitude, c] < spg[idOfRowWithMaxAmplitude, c + 1])
{
continue;
}
// peak should exceed thresold amplitude
if (spg[idOfRowWithMaxAmplitude, c] < 3.0)
{
continue;
}
// convert row ID to freq bin ID
int freqBinID = rhzRowCount - idOfRowWithMaxAmplitude - 1;
list.Add(new Point(c, freqBinID));
// we now have a list of potential hits for LimCon. This needs to be filtered.
// Console.WriteLine("Col {0}, Bin {1} ", c, freqBinID);
}
// DEBUG ONLY // ################################ TEMPORARY ################################
// superimpose point on RHZ HiRes spectrogram for debug purposes
bool drawOnHiResSpectrogram = true;
//string filePath = @"G:\SensorNetworks\Output\Frogs\TestOfHiResIndices-2016July\Test\Towsey.HiResIndices\SpectrogramImages\3mile_creek_dam_-_Herveys_Range_1076_248366_20130305_001700_30_0min.CombinedGreyScale.png";
var fileName = Path.GetFileNameWithoutExtension(segmentSettings.SegmentAudioFile.Name);
string filePath = outputDir.FullName + @"\SpectrogramImages\" + fileName + ".CombinedGreyScale.png";
var debugImage = new FileInfo(filePath);
if (!debugImage.Exists)
{
drawOnHiResSpectrogram = false;
}
if (drawOnHiResSpectrogram)
{
// put red dot where max is
Bitmap bmp = new Bitmap(filePath);
foreach (Point point in list)
{
bmp.SetPixel(point.X + 70, 1911 - point.Y, Color.Red);
}
// mark off every tenth frequency bin
for (int r = 0; r < 26; r++)
{
bmp.SetPixel(68, 1911 - (r * 10), Color.Blue);
bmp.SetPixel(69, 1911 - (r * 10), Color.Blue);
}
// mark off upper bound and lower frequency bound
bmp.SetPixel(69, 1911 - dominantBinMin, Color.Lime);
bmp.SetPixel(69, 1911 - dominantBinMax, Color.Lime);
//bmp.SetPixel(69, 1911 - maxRowID, Color.Lime);
string opFilePath = outputDir.FullName + @"\SpectrogramImages\" + fileName + ".CombinedGreyScaleAnnotated.png";
bmp.Save(opFilePath);
}
// END DEBUG ################################ TEMPORARY ################################
// now construct the standard decibel spectrogram WITHOUT noise removal, and look for LimConvex
// get frame parameters for the analysis
double epsilon = Math.Pow(0.5, recording.BitsPerSample - 1);
int frameSize = rhzRowCount * 2;
int frameStep = frameSize; // this default = zero overlap
double frameDurationInSeconds = frameSize / (double)sampleRate;
double frameStepInSeconds = frameStep / (double)sampleRate;
double framesPerSec = 1 / frameStepInSeconds;
//var dspOutput = DSP_Frames.ExtractEnvelopeAndFFTs(recording, frameSize, frameStep);
//// Generate deciBel spectrogram
//double[,] deciBelSpectrogram = MFCCStuff.DecibelSpectra(dspOutput.amplitudeSpectrogram, dspOutput.WindowPower, sampleRate, epsilon);
// i: Init SONOGRAM config
var sonoConfig = new SonogramConfig
{
SourceFName = recording.BaseName,
WindowSize = frameSize,
WindowOverlap = 0.0,
NoiseReductionType = NoiseReductionType.None,
};
// init sonogram
BaseSonogram sonogram = new SpectrogramStandard(sonoConfig, recording.WavReader);
// remove the DC row of the spectrogram
sonogram.Data = MatrixTools.Submatrix(sonogram.Data, 0, 1, sonogram.Data.GetLength(0) - 1, sonogram.Data.GetLength(1) - 1);
//scores.Add(new Plot("Decibels", DataTools.NormaliseMatrixValues(dBArray), ActivityAndCover.DefaultActivityThresholdDb));
//scores.Add(new Plot("Active Frames", DataTools.Bool2Binary(activity.activeFrames), 0.0));
// convert spectral peaks to frequency
//var tuple_DecibelPeaks = SpectrogramTools.HistogramOfSpectralPeaks(deciBelSpectrogram);
//int[] peaksBins = tuple_DecibelPeaks.Item2;
//double[] freqPeaks = new double[peaksBins.Length];
//int binCount = sonogram.Data.GetLength(1);
//for (int i = 1; i < peaksBins.Length; i++) freqPeaks[i] = (lowerBinBound + peaksBins[i]) / (double)nyquistBin;
//scores.Add(new Plot("Max Frequency", freqPeaks, 0.0)); // location of peaks for spectral images
// create new list of LimCon hits in the standard spectrogram.
double timeSpanOfFrameInSeconds = frameSize / (double)sampleRate;
var newList = new List <int[]>();
int lastFrameID = sonogram.Data.GetLength(0) - 1;
int lastBinID = sonogram.Data.GetLength(1) - 1;
foreach (Point point in list)
{
double secondsFromStartOfSegment = (point.X * 0.1) + 0.05; // convert point.Y to center of time-block.
int framesFromStartOfSegment = (int)Math.Round(secondsFromStartOfSegment / timeSpanOfFrameInSeconds);
// location of max point is uncertain, so search in neighbourhood.
// NOTE: sonogram.data matrix is time*freqBin
double maxValue = -double.MaxValue;
int idOfTMax = framesFromStartOfSegment;
int idOfFMax = point.Y;
for (int deltaT = -4; deltaT <= 4; deltaT++)
{
for (int deltaF = -1; deltaF <= 1; deltaF++)
{
int newT = framesFromStartOfSegment + deltaT;
if (newT < 0)
{
newT = 0;
}
else if (newT > lastFrameID)
{
newT = lastFrameID;
}
double value = sonogram.Data[newT, point.Y + deltaF];
if (value > maxValue)
{
maxValue = value;
idOfTMax = framesFromStartOfSegment + deltaT;
idOfFMax = point.Y + deltaF;
}
}
}
// newList.Add(new Point(frameSpan, point.Y));
int[] array = new int[2];
array[0] = idOfTMax;
array[1] = idOfFMax;
newList.Add(array);
}
// Now obtain more of spectrogram to see if have peaks at two other places characteristic of Limnodynastes convex.
// In the D.Stewart CD, there are peaks close to:
//1. 1950 Hz
//2. 1460 hz
//3. 970 hz These are 490 Hz apart.
// For Limnodynastes convex, in the JCU recording, there are peaks close to:
//1. 1780 Hz
//2. 1330 hz
//3. 880 hz These are 450 Hz apart.
// So strategy is to look for three peaks separated by same amount and in the vicinity of the above,
// starting with highest power (the top peak) and working down to lowest power (bottom peak).
//We have found top/highest peak - now find the other two.
int secondDominantFrequency = 1380;
int secondDominantBin = (int)Math.Round(secondDominantFrequency / herzPerBin);
int thirdDominantFrequency = 900;
int thirdDominantBin = (int)Math.Round(thirdDominantFrequency / herzPerBin);
var acousticEvents = new List <AcousticEvent>();
int Tbuffer = 2;
// First extract a sub-matrix.
foreach (int[] array in newList)
{
// NOTE: sonogram.data matrix is time*freqBin
int Tframe = array[0];
int F1bin = array[1];
double[,] subMatrix = MatrixTools.Submatrix(sonogram.Data, Tframe - Tbuffer, 0, Tframe + Tbuffer, F1bin);
double F1power = subMatrix[Tbuffer, F1bin];
// convert to vector
var spectrum = MatrixTools.GetColumnAverages(subMatrix);
// use the following code to get estimate of background noise
double[,] powerMatrix = MatrixTools.Submatrix(sonogram.Data, Tframe - 3, 10, Tframe + 3, F1bin);
double averagePower = (MatrixTools.GetRowAverages(powerMatrix)).Average();
double score = F1power - averagePower;
// debug - checking what the spectrum looks like.
//for (int i = 0; i < 18; i++)
// spectrum[i] = -100.0;
//DataTools.writeBarGraph(spectrum);
// locate the peaks in lower frequency bands, F2 and F3
bool[] peaks = DataTools.GetPeaks(spectrum);
int F2bin = 0;
double F2power = -200.0; // dB
for (int i = -3; i <= 2; i++)
{
int bin = F1bin - F1AndF2Gap + i;
if ((peaks[bin]) && (F2power < subMatrix[1, bin]))
{
F2bin = bin;
F2power = subMatrix[1, bin];
}
}
if (F2bin == 0)
{
continue;
}
if (F2power == -200.0)
{
continue;
}
score += (F2power - averagePower);
int F3bin = 0;
double F3power = -200.0;
for (int i = -5; i <= 2; i++)
{
int bin = F1bin - F1AndF3Gap + i;
if ((peaks[bin]) && (F3power < subMatrix[1, bin]))
{
F3bin = bin;
F3power = subMatrix[1, bin];
}
}
if (F3bin == 0)
{
continue;
}
if (F3power == -200.0)
{
continue;
}
score += (F3power - averagePower);
score /= 3;
// ignore events where SNR < decibel threshold
if (score < scoreThreshold)
{
continue;
}
// ignore events with wrong power distribution. A good LimnoConvex call has strongest F1 power
if ((F3power > F1power) || (F2power > F1power))
{
continue;
}
//freq Bin ID must be converted back to Matrix row ID
// freqBin + rowID = binCount - 1;
// therefore: rowID = binCount - freqBin - 1;
minRowID = rhzRowCount - F1bin - 2;
maxRowID = rhzRowCount - F3bin - 1;
int F1RowID = rhzRowCount - F1bin - 1;
int F2RowID = rhzRowCount - F2bin - 1;
int F3RowID = rhzRowCount - F3bin - 1;
int maxfreq = dominantFrequency + hzBuffer;
int topBin = (int)Math.Round(maxfreq / herzPerBin);
int frameCount = 4;
double duration = frameCount * frameStepInSeconds;
double startTimeWrtSegment = (Tframe - 2) * frameStepInSeconds;
// Got to here so start initialising an acoustic event
var ae = new AcousticEvent(segmentStartOffset, startTimeWrtSegment, duration, minimumFrequency, maxfreq);
ae.SetTimeAndFreqScales(framesPerSec, herzPerBin);
//var ae = new AcousticEvent(oblong, recording.Nyquist, binCount, frameDurationInSeconds, frameStepInSeconds, frameCount);
//ae.StartOffset = TimeSpan.FromSeconds(Tframe * frameStepInSeconds);
var pointF1 = new Point(2, topBin - F1bin);
var pointF2 = new Point(2, topBin - F2bin);
var pointF3 = new Point(2, topBin - F3bin);
ae.Points = new List <Point>();
ae.Points.Add(pointF1);
ae.Points.Add(pointF2);
ae.Points.Add(pointF3);
//tried using HitElements but did not do what I wanted later on.
//ae.HitElements = new HashSet<Point>();
//ae.HitElements = new SortedSet<Point>();
//ae.HitElements.Add(pointF1);
//ae.HitElements.Add(pointF2);
//ae.HitElements.Add(pointF3);
ae.Score = score;
//ae.MinFreq = Math.Round((topBin - F3bin - 5) * herzPerBin);
//ae.MaxFreq = Math.Round(topBin * herzPerBin);
acousticEvents.Add(ae);
}
// now add in extra common info to the acoustic events
acousticEvents.ForEach(ae =>
{
ae.SpeciesName = configDict[AnalysisKeys.SpeciesName];
ae.SegmentStartSeconds = segmentStartOffset.TotalSeconds;
ae.SegmentDurationSeconds = recording.Duration.TotalSeconds;
ae.Name = abbreviatedName;
ae.BorderColour = Color.Red;
ae.FileName = recording.BaseName;
});
double[] scores = new double[rhzColCount]; // predefinition of score array
double nomalisationConstant = scoreThreshold * 4; // four times the score threshold
double compressionFactor = rhzColCount / (double)sonogram.Data.GetLength(0);
foreach (AcousticEvent ae in acousticEvents)
{
ae.ScoreNormalised = ae.Score / nomalisationConstant;
if (ae.ScoreNormalised > 1.0)
{
ae.ScoreNormalised = 1.0;
}
int frameID = (int)Math.Round(ae.EventStartSeconds / frameDurationInSeconds);
int hiresFrameID = (int)Math.Floor(frameID * compressionFactor);
scores[hiresFrameID] = ae.ScoreNormalised;
}
var plot = new Plot(AnalysisName, scores, scoreThreshold);
// DEBUG ONLY ################################ TEMPORARY ################################
// Draw a standard spectrogram and mark of hites etc.
bool createStandardDebugSpectrogram = true;
var imageDir = new DirectoryInfo(outputDir.FullName + @"\SpectrogramImages");
if (!imageDir.Exists)
{
imageDir.Create();
}
if (createStandardDebugSpectrogram)
{
var fileName2 = Path.GetFileNameWithoutExtension(segmentSettings.SegmentAudioFile.Name);
string filePath2 = Path.Combine(imageDir.FullName, fileName + ".Spectrogram.png");
Bitmap sonoBmp = (Bitmap)sonogram.GetImage();
int height = sonoBmp.Height;
foreach (AcousticEvent ae in acousticEvents)
{
ae.DrawEvent(sonoBmp);
//g.DrawRectangle(pen, ob.ColumnLeft, ob.RowTop, ob.ColWidth-1, ob.RowWidth);
//ae.DrawPoint(sonoBmp, ae.HitElements.[0], Color.OrangeRed);
//ae.DrawPoint(sonoBmp, ae.HitElements[1], Color.Yellow);
//ae.DrawPoint(sonoBmp, ae.HitElements[2], Color.Green);
ae.DrawPoint(sonoBmp, ae.Points[0], Color.OrangeRed);
ae.DrawPoint(sonoBmp, ae.Points[1], Color.Yellow);
ae.DrawPoint(sonoBmp, ae.Points[2], Color.LimeGreen);
}
// draw the original hits on the standard sonogram
foreach (int[] array in newList)
{
sonoBmp.SetPixel(array[0], height - array[1], Color.Cyan);
}
// mark off every tenth frequency bin on the standard sonogram
for (int r = 0; r < 20; r++)
{
sonoBmp.SetPixel(0, height - (r * 10) - 1, Color.Blue);
sonoBmp.SetPixel(1, height - (r * 10) - 1, Color.Blue);
}
// mark off upper bound and lower frequency bound
sonoBmp.SetPixel(0, height - dominantBinMin, Color.Lime);
sonoBmp.SetPixel(0, height - dominantBinMax, Color.Lime);
sonoBmp.Save(filePath2);
}
// END DEBUG ################################ TEMPORARY ################################
return(new LimnodynastesConvexResults
{
Sonogram = sonogram,
Hits = null,
Plot = plot,
Events = acousticEvents,
RecordingDuration = recording.Duration,
});
} // Analysis()
/// <summary>
///
/// </summary>
/// <param name="segmentOfSourceFile"></param>
/// <param name="configDict"></param>
/// <param name="analysisSettings"></param>
/// <param name="segmentSettings"></param>
/// <param name="segmentStartOffset"></param>
/// <returns></returns>
internal static LimnodynastesConvexResults Analysis(FileInfo segmentOfSourceFile, Dictionary <string, string> configDict, AnalysisSettings analysisSettings, SegmentSettingsBase segmentSettings)
{
Dictionary <string, double[, ]> dictionaryOfHiResSpectralIndices = null;
var recording = new AudioRecording(segmentOfSourceFile.FullName);
return(Analysis(dictionaryOfHiResSpectralIndices, recording, configDict, analysisSettings, segmentSettings));
}
