public void TestAnnotatedSonogramWithPlots()
{
// Make a decibel spectrogram
var actualDecibelSpectrogram = new SpectrogramStandard(this.sonoConfig, this.recording.WavReader);
// prepare normalisation bounds for three plots
double minDecibels = -100.0;
double maxDecibels = -50;
//double decibelThreshold = 12.5 dB above -100 dB;
var normThreshold = 0.25;
//plot 1
int minHz = 2000;
int maxHz = 3000;
var decibelArray = SNR.CalculateFreqBandAvIntensity(actualDecibelSpectrogram.Data, minHz, maxHz, actualDecibelSpectrogram.NyquistFrequency);
var normalisedIntensityArray = DataTools.NormaliseInZeroOne(decibelArray, minDecibels, maxDecibels);
var plot1 = new Plot("Intensity 2-3 kHz", normalisedIntensityArray, normThreshold);
//plot 2
minHz = 3000;
maxHz = 4000;
decibelArray = SNR.CalculateFreqBandAvIntensity(actualDecibelSpectrogram.Data, minHz, maxHz, actualDecibelSpectrogram.NyquistFrequency);
normalisedIntensityArray = DataTools.NormaliseInZeroOne(decibelArray, minDecibels, maxDecibels);
var plot2 = new Plot("Intensity 3-4 kHz", normalisedIntensityArray, normThreshold);
//plot 3
minHz = 4000;
maxHz = 5000;
decibelArray = SNR.CalculateFreqBandAvIntensity(actualDecibelSpectrogram.Data, minHz, maxHz, actualDecibelSpectrogram.NyquistFrequency);
normalisedIntensityArray = DataTools.NormaliseInZeroOne(decibelArray, minDecibels, maxDecibels);
var plot3 = new Plot("Intensity 4-5 kHz", normalisedIntensityArray, normThreshold);
// combine the plots
var plots = new List <Plot> {
plot1, plot2, plot3
};
// create three events
var startOffset = TimeSpan.Zero;
var events = new List <AcousticEvent>
{
new AcousticEvent(startOffset, 10.0, 10.0, 2000, 3000),
new AcousticEvent(startOffset, 25.0, 10.0, 3000, 4000),
new AcousticEvent(startOffset, 40.0, 10.0, 4000, 5000),
};
var image = SpectrogramTools.GetSonogramPlusCharts(actualDecibelSpectrogram, events, plots, null);
// create the image for visual confirmation
image.Save(Path.Combine(this.outputDirectory.FullName, this.recording.BaseName + ".png"));
Assert.AreEqual(1621, image.Width);
Assert.AreEqual(647, image.Height);
}
public void TestGetEventsAroundMaxima()
{
//string abbreviatedSpeciesName = "Pteropus";
string speciesName = "Pteropus species";
int minHz = 800;
int maxHz = 8000;
var minTimeSpan = TimeSpan.FromSeconds(0.15);
var maxTimeSpan = TimeSpan.FromSeconds(0.8);
double decibelThreshold = 9.0;
TimeSpan segmentStartOffset = TimeSpan.Zero;
var decibelArray = SNR.CalculateFreqBandAvIntensity(this.sonogram.Data, minHz, maxHz, this.sonogram.NyquistFrequency);
// prepare plots
double intensityNormalisationMax = 3 * decibelThreshold;
var eventThreshold = decibelThreshold / intensityNormalisationMax;
var normalisedIntensityArray = DataTools.NormaliseInZeroOne(decibelArray, 0, intensityNormalisationMax);
var plot = new Plot(speciesName + " Territory", normalisedIntensityArray, eventThreshold);
var plots = new List <Plot> {
plot
};
//iii: CONVERT decibel SCORES TO ACOUSTIC EVENTS
var acousticEvents = AcousticEvent.GetEventsAroundMaxima(
decibelArray,
segmentStartOffset,
minHz,
maxHz,
decibelThreshold,
minTimeSpan,
maxTimeSpan,
this.sonogram.FramesPerSecond,
this.sonogram.FBinWidth);
Assert.AreEqual(10, acousticEvents.Count);
Assert.AreEqual(new Rectangle(19, 1751, 168, 27), acousticEvents[0].GetEventAsRectangle());
Assert.AreEqual(new Rectangle(19, 1840, 168, 10), acousticEvents[2].GetEventAsRectangle());
Assert.AreEqual(new Rectangle(19, 1961, 168, 31), acousticEvents[5].GetEventAsRectangle());
Assert.AreEqual(new Rectangle(19, 2294, 168, 17), acousticEvents[7].GetEventAsRectangle());
Assert.AreEqual(new Rectangle(19, 2504, 168, 7), acousticEvents[9].GetEventAsRectangle());
//Assert.AreEqual(28.Seconds() + segmentOffset, stats.ResultStartSeconds.Seconds());
}
/// <summary>
/// THis method does the work.
/// </summary>
/// <param name="audioRecording">the recording.</param>
/// <param name="configuration">the config file.</param>
/// <param name="profileName">name of call/event type to be found.</param>
/// <param name="segmentStartOffset">where one segment is located in the total recording.</param>
/// <returns>a list of events.</returns>
private static RecognizerResults WingBeats(AudioRecording audioRecording, Config configuration, string profileName, TimeSpan segmentStartOffset)
{
ConfigFile.TryGetProfile(configuration, profileName, out var profile);
// get the common properties
string speciesName = configuration[AnalysisKeys.SpeciesName] ?? "Pteropus species";
string abbreviatedSpeciesName = configuration[AnalysisKeys.AbbreviatedSpeciesName] ?? "Pteropus";
// The following parameters worked well on a ten minute recording containing 14-16 calls.
// Note: if you lower the dB threshold, you need to increase maxDurationSeconds
int minHz = profile.GetIntOrNull(AnalysisKeys.MinHz) ?? 100;
int maxHz = profile.GetIntOrNull(AnalysisKeys.MaxHz) ?? 3000;
double minDurationSeconds = profile.GetDoubleOrNull(AnalysisKeys.MinDuration) ?? 1.0;
double maxDurationSeconds = profile.GetDoubleOrNull(AnalysisKeys.MaxDuration) ?? 10.0;
double decibelThreshold = profile.GetDoubleOrNull("DecibelThreshold") ?? 6.0;
double dctDuration = profile.GetDoubleOrNull("DctDuration") ?? 1.0;
double dctThreshold = profile.GetDoubleOrNull("DctThreshold") ?? 0.5;
double minOscFreq = profile.GetDoubleOrNull("MinOscilFreq") ?? 4.0;
double maxOscFreq = profile.GetDoubleOrNull("MaxOscilFreq") ?? 6.0;
double eventThreshold = profile.GetDoubleOrNull("EventThreshold") ?? 0.3;
//######################
//2. Don't use samples in this recognizer.
//var samples = audioRecording.WavReader.Samples;
//Instead, convert each segment to a spectrogram.
var sonogram = GetSonogram(configuration, audioRecording);
var decibelArray = SNR.CalculateFreqBandAvIntensity(sonogram.Data, minHz, maxHz, sonogram.NyquistFrequency);
// Look for wing beats using oscillation detector
/*
* int scoreSmoothingWindow = 11; // sets a default that was good for Cane toad
* Oscillations2019.Execute(
* (SpectrogramStandard)sonogram,
* minHz,
* maxHz,
* decibelThreshold,
* dctDuration,
* (int)Math.Floor(minOscFreq),
* (int)Math.Floor(maxOscFreq),
* dctThreshold,
* eventThreshold,
* minDurationSeconds,
* maxDurationSeconds,
* scoreSmoothingWindow,
* out var scores,
* out var acousticEvents,
* //out var hits,
* segmentStartOffset);
*/
Oscillations2012.Execute(
(SpectrogramStandard)sonogram,
minHz,
maxHz,
//decibelThreshold,
dctDuration,
(int)Math.Floor(minOscFreq),
(int)Math.Floor(maxOscFreq),
dctThreshold,
eventThreshold,
minDurationSeconds,
maxDurationSeconds,
out var scores,
out var acousticEvents,
out var hits,
segmentStartOffset);
// prepare plots
double intensityNormalisationMax = 3 * decibelThreshold;
var normThreshold = decibelThreshold / intensityNormalisationMax;
var normalisedIntensityArray = DataTools.NormaliseInZeroOne(decibelArray, 0, intensityNormalisationMax);
var plot1 = new Plot(speciesName + " Wing-beat band", normalisedIntensityArray, normThreshold);
var plot2 = new Plot(speciesName + " Wing-beat Osc Score", scores, eventThreshold);
var plots = new List <Plot> {
plot1, plot2
};
// ######################################################################
// add additional information about the recording and sonogram properties from which the event is derived.
acousticEvents.ForEach(ae =>
{
ae.FileName = audioRecording.BaseName;
ae.SpeciesName = speciesName;
ae.Name = abbreviatedSpeciesName + profileName;
ae.Profile = profileName;
ae.SegmentDurationSeconds = audioRecording.Duration.TotalSeconds;
ae.SegmentStartSeconds = segmentStartOffset.TotalSeconds;
var frameOffset = sonogram.FrameStep;
var frameDuration = sonogram.FrameDuration;
ae.SetTimeAndFreqScales(frameOffset, frameDuration, sonogram.FBinWidth);
//UNCOMMENT following lines to get spectral profiles of the Wingbeat events.
/* double[,] spectrogramData = sonogram.Data;
* int maxBin = (int)Math.Round(8000 / sonogram.FBinWidth);
* double startSecond = ae.EventStartSeconds - ae.SegmentStartSeconds;
* int startFrame = (int)Math.Round(startSecond / sonogram.FrameStep);
* int frameLength = (int)Math.Round(ae.EventDurationSeconds / sonogram.FrameStep);
* int endFrame = startFrame + frameLength;
*
* // get only the frames from centre of the acoustic event
* var subMatrix = DataTools.Submatrix(spectrogramData, startFrame + 10, 0, endFrame - 10, maxBin);
* var spectrum = MatrixTools.GetColumnAverages(subMatrix);
* var normalisedSpectrum = DataTools.normalise(spectrum);
* normalisedSpectrum = DataTools.filterMovingAverageOdd(normalisedSpectrum, 11);
* var maxId = DataTools.GetMaxIndex(normalisedSpectrum);
* var hzMax = (int)Math.Ceiling(maxId * sonogram.FBinWidth);
* string name = "BeatSpectrum " + (ae.SegmentStartSeconds / 60) + "m" + (int)Math.Floor(startSecond) + "s hzMax" + hzMax;
* var bmp2 = GraphsAndCharts.DrawGraph(name, normalisedSpectrum, 100);
*
* //Set required path
* bmp2.Save(Path.Combine(@"C:\PATH", name + ".png"));
*/
});
return(new RecognizerResults()
{
Events = acousticEvents,
Hits = null,
ScoreTrack = null,
Plots = plots,
Sonogram = sonogram,
});
}
/// <summary>
/// THis method does the work.
/// </summary>
/// <param name="audioRecording">the recording.</param>
/// <param name="configuration">the config file.</param>
/// <param name="profileName">name of the call/event type.</param>
/// <param name="segmentStartOffset">where one segment is located in the total recording.</param>
/// <returns>a list of events.</returns>
private static RecognizerResults TerritorialCall(AudioRecording audioRecording, Config configuration, string profileName, TimeSpan segmentStartOffset)
{
ConfigFile.TryGetProfile(configuration, profileName, out var profile);
// get the common properties
string speciesName = configuration[AnalysisKeys.SpeciesName] ?? "Pteropus species";
string abbreviatedSpeciesName = configuration[AnalysisKeys.AbbreviatedSpeciesName] ?? "Pteropus";
// The following parameters worked well on a ten minute recording containing 14-16 calls.
// Note: if you lower the dB threshold, you need to increase maxDurationSeconds
int minHz = profile.GetIntOrNull(AnalysisKeys.MinHz) ?? 800;
int maxHz = profile.GetIntOrNull(AnalysisKeys.MaxHz) ?? 8000;
double minDurationSeconds = profile.GetDoubleOrNull(AnalysisKeys.MinDuration) ?? 0.15;
double maxDurationSeconds = profile.GetDoubleOrNull(AnalysisKeys.MaxDuration) ?? 0.5;
double decibelThreshold = profile.GetDoubleOrNull(AnalysisKeys.DecibelThreshold) ?? 9.0;
var minTimeSpan = TimeSpan.FromSeconds(minDurationSeconds);
var maxTimeSpan = TimeSpan.FromSeconds(maxDurationSeconds);
//######################
//2. Convert each segment to a spectrogram.
var sonogram = GetSonogram(configuration, audioRecording);
var decibelArray = SNR.CalculateFreqBandAvIntensity(sonogram.Data, minHz, maxHz, sonogram.NyquistFrequency);
// prepare plots
double intensityNormalisationMax = 3 * decibelThreshold;
var eventThreshold = decibelThreshold / intensityNormalisationMax;
var normalisedIntensityArray = DataTools.NormaliseInZeroOne(decibelArray, 0, intensityNormalisationMax);
var plot = new Plot(speciesName + " Territory", normalisedIntensityArray, eventThreshold);
var plots = new List <Plot> {
plot
};
//iii: CONVERT decibel SCORES TO ACOUSTIC EVENTS
var acousticEvents = AcousticEvent.GetEventsAroundMaxima(
decibelArray,
segmentStartOffset,
minHz,
maxHz,
decibelThreshold,
minTimeSpan,
maxTimeSpan,
sonogram.FramesPerSecond,
sonogram.FBinWidth);
//iV add additional info to the acoustic events
acousticEvents.ForEach(ae =>
{
ae.FileName = audioRecording.BaseName;
ae.SpeciesName = speciesName;
ae.Name = abbreviatedSpeciesName + profileName;
ae.Profile = profileName;
ae.SegmentDurationSeconds = audioRecording.Duration.TotalSeconds;
ae.SegmentStartSeconds = segmentStartOffset.TotalSeconds;
});
acousticEvents = FilterEventsForSpectralProfile(acousticEvents, sonogram);
return(new RecognizerResults()
{
Events = acousticEvents,
Hits = null,
ScoreTrack = null,
Plots = plots,
Sonogram = sonogram,
});
}
public static void Execute(
SpectrogramStandard sonogram,
int minHz,
int maxHz,
double decibelThreshold,
double dctDuration,
int minOscFreq,
int maxOscFreq,
double dctThreshold,
double scoreThreshold,
double minDuration,
double maxDuration,
int smoothingWindow,
out double[] dctScores,
out List <OscillationEvent> events,
TimeSpan segmentStartOffset)
{
// smooth the frames to make oscillations more regular.
sonogram.Data = MatrixTools.SmoothRows(sonogram.Data, 5);
// extract array of decibel values, frame averaged over required frequency band
var decibelArray = SNR.CalculateFreqBandAvIntensity(sonogram.Data, minHz, maxHz, sonogram.NyquistFrequency);
// if first value is negative dB, this means noise removal was not done.
// Do noise removal now
//if (decibelArray[0] < 0.0)
//{
// NoiseRemovalModal.CalculateNoiseUsingLamelsAlgorithm(decibelArray, out double _, out double _, out double noiseMode, out double _);
// decibelArray = SNR.SubtractAndTruncate2Zero(decibelArray, noiseMode);
//}
//DETECT OSCILLATIONS
var framesPerSecond = sonogram.FramesPerSecond;
DetectOscillations(
decibelArray,
framesPerSecond,
decibelThreshold,
dctDuration,
minOscFreq,
maxOscFreq,
dctThreshold,
out dctScores,
out var oscFreq);
// smooth the scores - window=11 has been the DEFAULT. Now letting user set this.
dctScores = DataTools.filterMovingAverage(dctScores, smoothingWindow);
//double midOscFreq = minOscFreq + ((maxOscFreq - minOscFreq) / 2);
events = Oscillations2012.ConvertOscillationScores2Events(
dctScores,
oscFreq,
minHz,
maxHz,
sonogram.FramesPerSecond,
sonogram.FBinWidth,
scoreThreshold,
minDuration,
maxDuration,
sonogram.Configuration.SourceFName,
segmentStartOffset);
}
