public void ShouldBeAbleToGenerateMultipleTimesDifferentSignatures()
{
double howSimilarAreVectors = 0.4;
int topWavelets = 200, vectorLength = 8192;
var similarityUtility = new SimilarityUtility();
double similarity = 0;
int simulationRuns = 20000, aggreeOn = 0;
for (int i = 0; i < simulationRuns; ++i)
{
var arrays = this.GenerateVectors(howSimilarAreVectors, topWavelets, vectorLength);
Assert.AreEqual(topWavelets, arrays.Item1.TrueCounts());
Assert.AreEqual(topWavelets, arrays.Item2.TrueCounts());
aggreeOn += arrays.Item1.AgreeOn(arrays.Item2);
similarity += similarityUtility.CalculateJaccardSimilarity(arrays.Item1.ToBools(), arrays.Item2.ToBools());
}
double averageSimilarityOnTrueBits = (double)aggreeOn / simulationRuns;
Assert.AreEqual(
averageSimilarityOnTrueBits,
howSimilarAreVectors * topWavelets,
1.0,
"Actual Average Similarity on True bits: " + averageSimilarityOnTrueBits);
// values that match are counted one time, values that don't count twice (1 0 | 1 0) - don't match on 2 bits, even though they are generated from 1 wavelet
double jaccardSimilarity = (howSimilarAreVectors * topWavelets) / ((2 * topWavelets) - (howSimilarAreVectors * topWavelets));
Assert.AreEqual(jaccardSimilarity, similarity / simulationRuns, 0.1, "Jaccard Similarity is not as requested: " + (similarity / simulationRuns));
}
public void CalculateJaccardSimilarityCorrect()
{
bool[] first = new[] { true, true, false, true, false, true, false, false, true, true };
bool[] second = new[] { false, true, false, true, false, true, false, false, true, true };
var result = SimilarityUtility.CalculateJaccardSimilarity(first, second);
Assert.AreEqual(5f / 6, result);
}
public void CalculateHammingSimilarityCorrect()
{
byte[] first = new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
byte[] second = new byte[] { 1, 2, 3, 8, 5, 9, 7, 8, 11, 13 };
var result = SimilarityUtility.CalculateHammingSimilarity(first, second);
Assert.AreEqual(6, result);
}
private void GetFingerprintSimilarity(IFingerprintCommand databaseSong, IFingerprintCommand querySong, SimilarityResult results)
{
double sum = 0;
List <bool[]> fingerprintsDatabaseSong = databaseSong.Fingerprint()
.Result
.Select(fingerprint => fingerprint)
.ToList();
List <bool[]> fingerprintsQuerySong = querySong.Fingerprint()
.Result
.Select(fingerprint => fingerprint)
.ToList();
double max = double.MinValue;
double min = double.MaxValue;
int comparisonsCount = 0;
for (int i = 0; i < fingerprintsDatabaseSong.Count; i++)
{
for (int j = 0; j < fingerprintsQuerySong.Count; j++)
{
double value = SimilarityUtility.CalculateJaccardSimilarity(fingerprintsDatabaseSong[i], fingerprintsQuerySong[j]);
if (value > max)
{
max = value;
}
if (value < min)
{
min = value;
}
sum += value;
comparisonsCount++;
}
}
results.SumJaqSimilarityBetweenDatabaseAndQuerySong += sum;
results.AverageJaqSimilarityBetweenDatabaseAndQuerySong += sum / comparisonsCount;
if (max > results.MaxJaqSimilarityBetweenDatabaseAndQuerySong)
{
results.MaxJaqSimilarityBetweenDatabaseAndQuerySong = max;
}
if (min < results.MinJaqSimilarityBetweenDatabaseAndQuerySong)
{
results.MinJaqSimilarityBetweenDatabaseAndQuerySong = min;
}
results.NumberOfAnalizedFingerprints = comparisonsCount;
}
public QueryResult Query(IModelService modelService, IEnumerable <HashData> hashes, IQueryConfiguration queryConfiguration)
{
var hammingSimilarities = new Dictionary <IModelReference, int>();
foreach (var hash in hashes)
{
var subFingerprints = GetSubFingerprints(modelService, hash, queryConfiguration);
foreach (var subFingerprint in subFingerprints)
{
int similarity = SimilarityUtility.CalculateHammingSimilarity(hash.SubFingerprint, subFingerprint.Signature);
if (hammingSimilarities.ContainsKey(subFingerprint.TrackReference))
{
hammingSimilarities[subFingerprint.TrackReference] += similarity;
}
else
{
hammingSimilarities.Add(subFingerprint.TrackReference, similarity);
}
}
}
if (hammingSimilarities.Any())
{
var topMatches = hammingSimilarities.OrderByDescending(pair => pair.Value).Take(queryConfiguration.MaximumNumberOfTracksToReturnAsResult);
var resultSet = topMatches.Select(match => new ResultEntry {
Track = modelService.ReadTrackByReference(match.Key), Similarity = match.Value
}).ToList();
return(new QueryResult
{
ResultEntries = resultSet,
IsSuccessful = true,
AnalyzedCandidatesCount = hammingSimilarities.Count
});
}
return(new QueryResult
{
ResultEntries = Enumerable.Empty <ResultEntry>().ToList(),
IsSuccessful = false,
AnalyzedCandidatesCount = 0
});
}
