public void DisplayItems()
{
if (InvokeRequired)
{
Invoke((MethodInvoker)(DisplayItems));
return;
}
ShownItems = new Audios(Core.GetAudios());//temp !!!!!
pnAudios.Build(ShownItems);
lbItemCount.Text = "Items: " + ShownItems.Count;
Invalidate(true);
}
public EstimationResult EstimateAlgorithm(ISearchAlgorithm algorithm, object parameters = null)
{
if (algorithm == null)
{
throw new ArgumentNullException("algorithm");
}
Dictionary <SHA1Hash, Dictionary <SHA1Hash, int> > AutoScores = new Dictionary <SHA1Hash, Dictionary <SHA1Hash, int> >();
List <Audio> Audios = Core.GetAudios().ToList();
List <Audio> ReferenceList = Audios.ToList();
foreach (Audio ReferenceAudio in ReferenceList)
{
IList <Audio> Series = Audios.Search(ReferenceAudio, algorithm, parameters)
.Where(audio => HashMap.Contains(audio.GetHash()))
.ToList();
SHA1Hash ReferenceHash = ReferenceAudio.GetHash();
AutoScores.Add(ReferenceHash, new Dictionary <SHA1Hash, int>());
int Rank = 0;
foreach (Audio TargetAudio in Series)
{
AutoScores[ReferenceHash].Add(TargetAudio.GetHash(), TransformRankToScore(Rank++, Series.Count));
}
}
List <double> Errors = new List <double>();
List <double> ManualScoresList = new List <double>();
List <double> ReducedAutoScoresList = new List <double>();
foreach (SHA1Hash Reference in ManualScores.Keys)
{
foreach (SHA1Hash Target in ManualScores[Reference].Keys)
{
if (AutoScores.ContainsKey(Reference) && AutoScores[Reference].ContainsKey(Target))
{
int ReferenceScore = ManualScores[Reference][Target];
int AutoScore = AutoScores[Reference][Target];
int Error = ReferenceScore - AutoScore;
Errors.Add(Error);
ManualScoresList.Add(ReferenceScore);
ReducedAutoScoresList.Add(AutoScore);
}
}
}
double Mean = Errors.Mean();
double StandardDeviation = Errors.StandardDeviation();
double Covariance = ManualScoresList.Covariance(ReducedAutoScoresList);
double PearsonCoeff = Correlation.Pearson(ManualScoresList, ReducedAutoScoresList);
EstimationResult Result = new EstimationResult()
{
AlgorithmName = algorithm.DisplayName,
Parameters = Convert.ToString(parameters),
Mean = Mean,
StandardDeviation = StandardDeviation,
Covariance = Covariance,
PearsonCoeff = PearsonCoeff,
Scores = AutoScores
};
return(Result);
}