public MetricSimilarity(MelodySequence seq, IMetric metric, SimilarityType type = SimilarityType.Cosine)
{
this.metrics = new IMetric[]{metric};
this.target = seq.ToArray();
this.type = type;
this.target_metrics = new Dictionary<Pair, float>[] { this.metrics[0].Generate(this.target) };
}
public MetricSimilarity(MelodySequence seq, IMetric[] metrics, SimilarityType type = SimilarityType.Cosine)
{
this.metrics = metrics;
this.target = seq.ToArray();
target_metrics = new Dictionary<Pair, float>[metrics.Length];
this.type = type;
for (int i = 0; i < metrics.Length; i++)
target_metrics[i] = this.metrics[i].Generate(this.target);
}
public CrossCorrelation(MelodySequence seq)
{
this.target = seq.ToArray();
pitches = new double[this.target.Length];
durations = new double[this.target.Length];
for(int i = 0; i < this.target.Length; i++)
{
pitches[i] = this.target[i].Pitch;
durations[i] = this.target[i].Duration;
}
highest_peak = GetSimilarity(pitches, pitches, durations, durations);
}
public void AddMelody(MelodySequence seq)
{
Representation.Note[] notes = seq.ToArray();
chain.Add(notes);
}
public Note[] GenerateMelody(MelodySequence inputSeq)
{
SampleSet set = new SampleSet();
var mainNotes = inputSeq.ToArray();
for (int j = INPUT_NOTES; j < mainNotes.Length && j < 200; j++)
{
Note[] prevNotes = new Note[INPUT_NOTES];
for(int k = 0; k < INPUT_NOTES; k++)
{
prevNotes[INPUT_NOTES - k-1] = mainNotes[j - k];
}
Sample s = GetSample(prevNotes, null);
set.Add(s);
}
List<Note> notes = new List<Note>();
var reverseHashes = Utils.ReverseDictionary(noteHashes);
int mainTime = 0;
int accompTime = 0;
int i = 0;
foreach (Sample sample in set)
{
var res = network.Compute(sample.Inputs);
//Note n = new Note((NoteNames)((int)(res[0] * 12)), 6, (Durations)((int)(res[1] * 64.0)));
Note n = new Note((int)(res[0] * 128), (int)(res[1] * 64.0));
n.Duration *= 2;
n.StandardizeDuration();
if (mainTime >= accompTime)
{
notes.Add(n);
accompTime += (int)n.Duration;
}
if(i++ % 20 == 0)
{
notes.Add(new Note(-1, mainTime - accompTime));
}
mainTime += (int)(sample.Inputs[1] * 64);
}
return notes.ToArray();
}
public HarmonySequence GetHarmonySequence(MelodySequence seq)
{
HarmonySequence sequence = new HarmonySequence();
foreach(Note n in seq.ToArray())
{
if (n.Pitch > 0 && n.Velocity > 0 && n.Duration > (int)Durations.en)
sequence.AddChord(GetChord(n));
else
seq.AddPause(n.Duration);
}
return sequence;
}
public Note[] GenerateMelody(MelodySequence inputSeq)
{
SampleSet set = new SampleSet();
var mainNotes = inputSeq.ToArray();
for (int j = 0; j < mainNotes.Length && j < 200; j++)
{
Sample s = GetSample(mainNotes[j],null);
set.add(s);
}
List<Note> notes = new List<Note>();
var reverseHashes = Utils.ReverseDictionary(noteHashes);
int mainTime = 0;
int accompTime = 0;
foreach (Sample sample in set)
{
var res = ComputeNetworkOutput(sample);
//var maxIndex = GetMaxIndex(res);
Note outputNote = null;
if(res[0] <= 0.05)
outputNote = new Note(-1, (int)(res[1] * 64.0),0);
else
outputNote = new Note((NoteNames)(res[0] * 12), 4, (Durations)(res[1] * 64.0));
outputNote.StandardizeDuration();
notes.Add(outputNote);
/* if (reverseHashes.ContainsKey(maxIndex))
{
outputNote = reverseHashes[maxIndex];
notes.Add(outputNote);
/*accompTime += outputNote.Duration;
if (mainTime > accompTime)
{
notes.Add(new Note(-1, mainTime - accompTime, 0));
accompTime += mainTime - accompTime;
}
mainTime += (int)(sample.getInput()[1] * 64.0);*/
//}
}
return notes.ToArray();
}
public void AddMelodySequence(MelodySequence seq)
{
foreach (Note n in seq.ToArray())
AddNote(n);
}
private MelodySequence FixMelodySequence(MelodySequence seq)
{
var newNotes = new List<Note>();
var notes = seq.ToArray();
if (notes.Length > 1)
newNotes.Add(notes[0]);
for(int i = 1; i < notes.Length; i++)
{
bool add = true;
var note = notes[i];
var prevNote = notes[i - 1];
if (!note.IsRest())
{
if (Math.Abs(note.Pitch - prevNote.Pitch) > 24)
{
add = false;
}
}
if (add)
newNotes.Add(note);
}
return new MelodySequence(newNotes.ToArray());
}
