/// <summary>
/// Do your analysis. This method is called once per segment (typically one-minute segments).
/// </summary>
/// <param name="recording"></param>
/// <param name="configuration"></param>
/// <param name="segmentStartOffset"></param>
/// <param name="getSpectralIndexes"></param>
/// <param name="outputDirectory"></param>
/// <param name="imageWidth"></param>
/// <returns></returns>
public override RecognizerResults Recognize(AudioRecording recording, Config configuration, TimeSpan segmentStartOffset, Lazy <IndexCalculateResult[]> getSpectralIndexes, DirectoryInfo outputDirectory, int?imageWidth)
{
var recognizerConfig = new LitoriaCaeruleaConfig();
recognizerConfig.ReadConfigFile(configuration);
// common properties
string speciesName = configuration[AnalysisKeys.SpeciesName] ?? "<no name>";
string abbreviatedSpeciesName = configuration[AnalysisKeys.AbbreviatedSpeciesName] ?? "<no.sp>";
// BETTER TO SET THESE. IGNORE USER!
// This framesize is large because the oscillation we wish to detect is due to repeated croaks
// having an interval of about 0.6 seconds. The overlap is also required to give smooth oscillation.
const int frameSize = 2048;
const double windowOverlap = 0.5;
// i: MAKE SONOGRAM
var sonoConfig = new SonogramConfig
{
SourceFName = recording.BaseName,
WindowSize = frameSize,
WindowOverlap = windowOverlap,
// use the default HAMMING window
//WindowFunction = WindowFunctions.HANNING.ToString(),
//WindowFunction = WindowFunctions.NONE.ToString(),
// if do not use noise reduction can get a more sensitive recogniser.
//NoiseReductionType = NoiseReductionType.None
NoiseReductionType = NoiseReductionType.Standard,
NoiseReductionParameter = 0.0,
};
TimeSpan recordingDuration = recording.WavReader.Time;
int sr = recording.SampleRate;
double freqBinWidth = sr / (double)sonoConfig.WindowSize;
double framesPerSecond = sr / (sonoConfig.WindowSize * (1 - windowOverlap));
//int dominantFreqBin = (int)Math.Round(recognizerConfig.DominantFreq / freqBinWidth) + 1;
int minBin = (int)Math.Round(recognizerConfig.MinHz / freqBinWidth) + 1;
int maxBin = (int)Math.Round(recognizerConfig.MaxHz / freqBinWidth) + 1;
var decibelThreshold = 9.0;
BaseSonogram sonogram = new SpectrogramStandard(sonoConfig, recording.WavReader);
// ######################################################################
// ii: DO THE ANALYSIS AND RECOVER SCORES OR WHATEVER
int rowCount = sonogram.Data.GetLength(0);
// get the freq band as set by min and max Herz
var frogBand = MatrixTools.Submatrix(sonogram.Data, 0, minBin, rowCount - 1, maxBin);
// Now look for spectral maxima. For L.caerulea, the max should lie around 1100Hz +/-150 Hz.
// Skip over spectra where maximum is not in correct location.
int buffer = 150;
var croakScoreArray = new double[rowCount];
var hzAtTopOfTopBand = recognizerConfig.DominantFreq + buffer;
var hzAtBotOfTopBand = recognizerConfig.DominantFreq - buffer;
var binAtTopOfTopBand = (int)Math.Round((hzAtTopOfTopBand - recognizerConfig.MinHz) / freqBinWidth);
var binAtBotOfTopBand = (int)Math.Round((hzAtBotOfTopBand - recognizerConfig.MinHz) / freqBinWidth);
// scan the frog band and get the decibel value of those spectra which have their maximum within the correct subband.
for (int x = 0; x < rowCount; x++)
{
//extract spectrum
var spectrum = MatrixTools.GetRow(frogBand, x);
int maxIndex = DataTools.GetMaxIndex(spectrum);
if (spectrum[maxIndex] < decibelThreshold)
{
continue;
}
if (maxIndex < binAtTopOfTopBand && maxIndex > binAtBotOfTopBand)
{
croakScoreArray[x] = spectrum[maxIndex];
}
}
// Perpare a normalised plot for later display with spectrogram
double[] normalisedScores;
double normalisedThreshold;
DataTools.Normalise(croakScoreArray, decibelThreshold, out normalisedScores, out normalisedThreshold);
var text1 = string.Format($"Croak scores (threshold={decibelThreshold})");
var croakPlot1 = new Plot(text1, normalisedScores, normalisedThreshold);
// extract potential croak events from the array of croak candidate
var croakEvents = AcousticEvent.ConvertScoreArray2Events(
croakScoreArray,
recognizerConfig.MinHz,
recognizerConfig.MaxHz,
sonogram.FramesPerSecond,
freqBinWidth,
recognizerConfig.EventThreshold,
recognizerConfig.MinCroakDuration,
recognizerConfig.MaxCroakDuration,
segmentStartOffset);
// add necesary info into the candidate events
var prunedEvents = new List <AcousticEvent>();
foreach (var ae in croakEvents)
{
// add additional info
ae.SpeciesName = speciesName;
ae.SegmentStartSeconds = segmentStartOffset.TotalSeconds;
ae.SegmentDurationSeconds = recordingDuration.TotalSeconds;
ae.Name = recognizerConfig.AbbreviatedSpeciesName;
prunedEvents.Add(ae);
}
// With those events that survive the above Array2Events process, we now extract a new array croak scores
croakScoreArray = AcousticEvent.ExtractScoreArrayFromEvents(prunedEvents, rowCount, recognizerConfig.AbbreviatedSpeciesName);
DataTools.Normalise(croakScoreArray, decibelThreshold, out normalisedScores, out normalisedThreshold);
var text2 = string.Format($"Croak events (threshold={decibelThreshold})");
var croakPlot2 = new Plot(text2, normalisedScores, normalisedThreshold);
// Look for oscillations in the difference array
// duration of DCT in seconds
//croakScoreArray = DataTools.filterMovingAverageOdd(croakScoreArray, 5);
double dctDuration = recognizerConfig.DctDuration;
// minimum acceptable value of a DCT coefficient
double dctThreshold = recognizerConfig.DctThreshold;
double minOscRate = 1 / recognizerConfig.MaxPeriod;
double maxOscRate = 1 / recognizerConfig.MinPeriod;
var dctScores = Oscillations2012.DetectOscillations(croakScoreArray, framesPerSecond, dctDuration, minOscRate, maxOscRate, dctThreshold);
// ######################################################################
// ii: DO THE ANALYSIS AND RECOVER SCORES OR WHATEVER
var events = AcousticEvent.ConvertScoreArray2Events(
dctScores,
recognizerConfig.MinHz,
recognizerConfig.MaxHz,
sonogram.FramesPerSecond,
freqBinWidth,
recognizerConfig.EventThreshold,
recognizerConfig.MinDuration,
recognizerConfig.MaxDuration,
segmentStartOffset);
double[,] hits = null;
prunedEvents = new List <AcousticEvent>();
foreach (var ae in events)
{
// add additional info
ae.SpeciesName = speciesName;
ae.SegmentStartSeconds = segmentStartOffset.TotalSeconds;
ae.SegmentDurationSeconds = recordingDuration.TotalSeconds;
ae.Name = recognizerConfig.AbbreviatedSpeciesName;
prunedEvents.Add(ae);
}
// do a recognizer test.
if (MainEntry.InDEBUG)
{
//TestTools.RecognizerScoresTest(scores, new FileInfo(recording.FilePath));
//AcousticEvent.TestToCompareEvents(prunedEvents, new FileInfo(recording.FilePath));
}
var scoresPlot = new Plot(this.DisplayName, dctScores, recognizerConfig.EventThreshold);
if (true)
{
// display a variety of debug score arrays
// calculate amplitude at location
double[] amplitudeArray = MatrixTools.SumRows(frogBand);
DataTools.Normalise(amplitudeArray, decibelThreshold, out normalisedScores, out normalisedThreshold);
var amplPlot = new Plot("Band amplitude", normalisedScores, normalisedThreshold);
var debugPlots = new List <Plot> {
scoresPlot, croakPlot2, croakPlot1, amplPlot
};
// NOTE: This DrawDebugImage() method can be over-written in this class.
var debugImage = DrawDebugImage(sonogram, prunedEvents, debugPlots, hits);
var debugPath = FilenameHelpers.AnalysisResultPath(outputDirectory, recording.BaseName, this.SpeciesName, "png", "DebugSpectrogram");
debugImage.Save(debugPath);
}
return(new RecognizerResults()
{
Sonogram = sonogram,
Hits = hits,
Plots = scoresPlot.AsList(),
Events = prunedEvents,
//Events = events
});
}