/// <summary>
/// This algorithm is used for broad band events such as a bird chorus.
/// It selects acoustic content over a band of several kHz and calculates a content score based on a template match to what is in the band.
/// </summary>
/// <param name="oneMinuteOfIndices">Derived from the source recording.</param>
/// <param name="template">A previously prepared template.</param>
/// <param name="templateIndices">The actual dictionary of template arrays.</param>
/// <returns>A similarity score.</returns>
public static double GetBroadbandContent1(Dictionary <string, double[]> oneMinuteOfIndices, TemplateManifest template, Dictionary <string, double[]> templateIndices)
{
// copy over the recording indices required by the template.
var requiredIndices = DataProcessing.GetRequiredIndices(oneMinuteOfIndices, templateIndices.Keys.ToArray());
//reduce indices and convert to vector.
var reductionFactor = template.SpectralReductionFactor;
int freqBinCount = ContentSignatures.FreqBinCount / reductionFactor;
int bottomFreq = template.BandMinHz; //Hertz
int topFreq = template.BandMaxHz; //Hertz
var freqBinBounds = DataProcessing.GetFreqBinBounds(bottomFreq, topFreq, freqBinCount);
var reducedIndices = DataProcessing.ReduceIndicesByFactor(requiredIndices, reductionFactor);
// remove top freq bins and bottom freq bins;
reducedIndices = DataProcessing.ApplyBandPass(reducedIndices, freqBinBounds[0], freqBinBounds[1]);
var oneMinuteVector = DataProcessing.ConvertDictionaryToVector(reducedIndices);
var templateVector = DataProcessing.ConvertDictionaryToVector(templateIndices);
//Get Euclidean distance and normalize the distance
var distance = DataTools.EuclideanDistance(templateVector, oneMinuteVector);
// Normalize the distance
distance /= Math.Sqrt(templateVector.Length);
return(1 - distance);
}
// ###################################################################################
/// <summary>
/// This algorithm is used for broad band events such as a bird chorus.
/// It selects acoustic content over a band of several kHz and calculates a content score based on a template match to what is in the band.
/// </summary>
/// <param name="manifest">A previously prepared template.</param>
/// <param name="templateIndices">The actual dictionary of template arrays.</param>
/// <returns>A similarity score.</returns>
public static Dictionary <string, double[]> CreateBroadbandTemplate1(TemplateManifest manifest, Dictionary <string, double[, ]> templateIndices)
{
// Get the template provenance. Assume array contains only one element.
var provenanceArray = manifest.Provenance;
var provenance = provenanceArray[0];
var startRowId = provenance.StartOffset;
var endRowId = provenance.EndOffset;
var reductionFactor = manifest.SpectralReductionFactor;
var dictionaryOfVector = DataProcessing.AverageIndicesOverMinutes(templateIndices, startRowId, endRowId);
// remove first two freq bins and last four freq bins, i.e. bottomBin = 2 and topBin = 11;
int freqBinCount = ContentSignatures.FreqBinCount / reductionFactor;
int bottomFreq = manifest.BandMinHz; //Hertz
int topFreq = manifest.BandMaxHz; //Hertz
var freqBinBounds = DataProcessing.GetFreqBinBounds(bottomFreq, topFreq, freqBinCount);
var reducedIndices = DataProcessing.ReduceIndicesByFactor(dictionaryOfVector, reductionFactor);
reducedIndices = DataProcessing.ApplyBandPass(reducedIndices, freqBinBounds[0], freqBinBounds[1]);
return(reducedIndices);
}