public override AnalysisResult2 Analyze <T>(AnalysisSettings analysisSettings, SegmentSettings <T> segmentSettings)
{
Contract.Requires(segmentSettings.SegmentStartOffset == segmentSettings.Segment.StartOffsetSeconds.Seconds());
var recording = new AudioRecording(segmentSettings.SegmentAudioFile);
var segment = (RemoteSegmentWithData)segmentSettings.Segment;
// sometimes events will share the same audio block so we have to analyze each event
// within this segment of audio
IReadOnlyCollection <object> importedEvents = segment.Data;
Log.Debug($"Calculating event statistics for {importedEvents.Count} items in {segmentSettings.SegmentAudioFile}");
EventStatistics[] results = new EventStatistics[importedEvents.Count];
int index = 0;
foreach (var importedEventObject in importedEvents)
{
var importedEvent = (ImportedEvent)importedEventObject;
var temporalRange = new Range <TimeSpan>(
importedEvent.EventStartSeconds.Value.Seconds(),
importedEvent.EventEndSeconds.Value.Seconds());
var spectralRange = new Range <double>(
importedEvent.LowFrequencyHertz.Value,
importedEvent.HighFrequencyHertz.Value);
Log.Debug(
$"Calculating event statistics for {importedEvent.AudioEventId},{temporalRange}," +
$"{spectralRange} in {segmentSettings.SegmentAudioFile}, Duration: {recording.Duration}");
// Repeat sanity check here. Previous duration sanity check only checks the header of the audio file,
// but that still allows for a fragmented audio file to have been downloaded, shorter than it should be
var expectedDuration = segment.Offsets.Size().Seconds();
var durationDelta = expectedDuration - recording.Duration;
if (durationDelta > 1.0.Seconds())
{
Log.Warn(
$"Media ({segmentSettings.SegmentAudioFile}) did not have expected duration."
+ $" Expected: {expectedDuration}, Actual: {recording.Duration}");
}
var configuration = (EventStatisticsConfiguration)analysisSettings.Configuration;
var statistics = EventStatisticsCalculate.AnalyzeAudioEvent(
recording,
temporalRange,
spectralRange,
configuration,
segmentSettings.SegmentStartOffset);
if (statistics.Error)
{
Log.Warn($"Event statistics failed for {importedEvent.AudioEventId},{temporalRange}," +
$"{spectralRange} in {segmentSettings.SegmentAudioFile}, Duration: {recording.Duration}");
}
// lastly add some metadata to make the results useful
statistics.Order = importedEvent.Order;
statistics.AudioRecordingId = segment.Source.Id;
statistics.AudioRecordingRecordedDate = segment.SourceMetadata.RecordedDate;
statistics.AudioEventId = importedEvent.AudioEventId;
results[index] = statistics;
index++;
}
var result = new AnalysisResult2(analysisSettings, segmentSettings, recording.Duration);
result.Events = results;
return(result);
}
public void TestCalculateEventStatistics()
{
int sampleRate = 22050;
double duration = 28;
int[] harmonics1 = { 500 };
int[] harmonics2 = { 500, 1000, 2000, 4000, 8000 };
var signal1 = DspFilters.GenerateTestSignal(sampleRate, duration, harmonics1, WaveType.Sine);
var signal2 = DspFilters.GenerateTestSignal(sampleRate, 4, harmonics2, WaveType.Sine);
var signal3 = DspFilters.GenerateTestSignal(sampleRate, duration, harmonics1, WaveType.Sine);
var signal = DataTools.ConcatenateVectors(signal1, signal2, signal3);
var wr = new WavReader(signal, 1, 16, sampleRate);
var recording = new AudioRecording(wr);
// this value is fake, but we set it to ensure output values are calculated correctly w.r.t. segment start
var segmentOffset = 547.123.Seconds();
var start = TimeSpan.FromSeconds(28) + segmentOffset;
var end = TimeSpan.FromSeconds(32) + segmentOffset;
double lowFreq = 1500.0;
double topFreq = 8500.0;
var statsConfig = new EventStatisticsConfiguration()
{
FrameSize = 512,
FrameStep = 512,
};
EventStatistics stats =
EventStatisticsCalculate.AnalyzeAudioEvent(
recording,
(start, end).AsRange(),
(lowFreq, topFreq).AsRange(),
statsConfig,
segmentOffset);
LoggedConsole.WriteLine($"Stats: Temporal entropy = {stats.TemporalEnergyDistribution:f4}");
LoggedConsole.WriteLine($"Stats: Spectral entropy = {stats.SpectralEnergyDistribution:f4}");
LoggedConsole.WriteLine($"Stats: Spectral centroid= {stats.SpectralCentroid}");
LoggedConsole.WriteLine($"Stats: DominantFrequency= {stats.DominantFrequency}");
Assert.AreEqual(0.0, stats.TemporalEnergyDistribution, 1E-4);
Assert.AreEqual(0.6062, stats.SpectralEnergyDistribution, 1E-4);
Assert.AreEqual(6687, stats.SpectralCentroid);
Assert.AreEqual(8003, stats.DominantFrequency);
Assert.AreEqual(1500, stats.LowFrequencyHertz);
Assert.AreEqual(8500, stats.HighFrequencyHertz);
Assert.AreEqual(28.Seconds() + segmentOffset, stats.EventStartSeconds.Seconds());
Assert.AreEqual(32.Seconds() + segmentOffset, stats.EventEndSeconds.Seconds());
Assert.AreEqual(28.Seconds() + segmentOffset, stats.ResultStartSeconds.Seconds());
/*
* // Assume linear scale.
* int nyquist = sampleRate / 2;
* var freqScale = new FrequencyScale(nyquist: nyquist, frameSize: statsConfig.FrameSize, hertzLinearGridInterval: 1000);
*
* var sonoConfig = new SonogramConfig
* {
* WindowSize = statsConfig.FrameSize,
* WindowStep = statsConfig.FrameSize,
* WindowOverlap = 0.0,
* SourceFName = "SineSignal3",
* NoiseReductionType = NoiseReductionType.Standard,
* NoiseReductionParameter = 0.12,
* };
* var sonogram = new AmplitudeSonogram(sonoConfig, recording.WavReader);
* var image = sonogram.GetImage();
* string title = $"Spectrogram of Harmonics: SR={sampleRate} Window={freqScale.WindowSize}";
* image = sonogram.GetImageFullyAnnotated(image, title, freqScale.GridLineLocations);
* string path = @"C:\SensorNetworks\Output\Sonograms\UnitTestSonograms\SineSignal3.png";
* image.Save(path);
*
* // get spectrum from row 1300
* var normalisedIndex = DataTools.normalise(MatrixTools.GetRow(sonogram.Data, 1300));
* var image2 = GraphsAndCharts.DrawGraph("SPECTRUM", normalisedIndex, 100);
* string path2 = @"C:\SensorNetworks\Output\Sonograms\UnitTestSonograms\Spectrum3.png";
* image2.Save(path2);
*/
}
