static void MarkovAccompTest()
{
Databank db = new Databank("lib");
var cat = db.Load("Classical");
Composition inputComp = cat.Compositions[6];
MelodySequence inputSeq = inputComp.Tracks[0].GetMainSequence() as MelodySequence;
AccompanyGeneratorMarkov gen = new AccompanyGeneratorMarkov(cat, PatchNames.Orchestral_Strings);
var outMel = gen.Generate(inputSeq, 10);
MusicPlayer player = new MusicPlayer();
Composition comp = new Composition();
Track t = new Track(gen.Instrument, 6);
t.AddSequence(outMel);
comp.Add(t);
comp.Add(inputComp.Tracks[0]);
player.Play(comp);
comp.WriteToMidi("markov_model_accomp.mid");
}
private void Generate()
{
int index = optionsTab.SelectedIndex;
progressGenSlider.Value = 0;
if (index == 0)
{
if (geneticInstrumentBox.SelectedItem == null)
return;
fitnessPlot.ResetAllAxes();
SetupLinePlot(fitnessPlot, "Average Fitness");
(fitnessPlot.Model.Series[0] as LineSeries).Points.Clear();
fitnessPlot.Model.Series[0].Unselect();
fitnessPlot.InvalidatePlot();
//GA
IFitnessFunction fitness = null;
//Options
List<IMetric> activeMetrics = new List<IMetric>();
// if (metricChromaticTone.IsChecked == true)
// activeMetrics.Add(new ChromaticTone());
if (metricChromaticToneDistance.IsChecked == true)
activeMetrics.Add(new ChromaticToneDistance());
if (metricChromaticToneDuration.IsChecked == true)
activeMetrics.Add(new ChromaticToneDuration());
if (metricMelodicBigram.IsChecked == true)
activeMetrics.Add(new MelodicBigram());
if (metricMelodicInterval.IsChecked == true)
activeMetrics.Add(new MelodicInterval());
// if (metricPitch.IsChecked == true)
// activeMetrics.Add(new Pitch());
// if (metricPitchDistance.IsChecked == true)
// activeMetrics.Add(new PitchDistance());
// if (metricRhythm.IsChecked == true)
// activeMetrics.Add(new Rhythm());
if (metricRhythmicBigram.IsChecked == true)
activeMetrics.Add(new RhythmicBigram());
if (metricRhythmicInterval.IsChecked == true)
activeMetrics.Add(new RhythmicInterval());
fitness = GeneticMIDI.FitnessFunctions.MetricSimilarity.GenerateMetricSimilarityMulti(category.Compositions, activeMetrics.ToArray(), GeneticMIDI.FitnessFunctions.SimilarityType.Cosine);
/*
if (fitnessFuncCombo.SelectedIndex == 0)
fitness = new GeneticMIDI.FitnessFunctions.MetricSimilarity(seq, activeMetrics.ToArray(), GeneticMIDI.FitnessFunctions.SimilarityType.Cosine);
if (fitnessFuncCombo.SelectedIndex == 1)
fitness = new GeneticMIDI.FitnessFunctions.MetricSimilarity(seq, activeMetrics.ToArray(), GeneticMIDI.FitnessFunctions.SimilarityType.Euclidian);
if (fitnessFuncCombo.SelectedIndex == 2)
fitness = new GeneticMIDI.FitnessFunctions.MetricSimilarity(seq, activeMetrics.ToArray(), GeneticMIDI.FitnessFunctions.SimilarityType.Pearson);
if (fitnessFuncCombo.SelectedIndex == 3)
fitness = new GeneticMIDI.FitnessFunctions.CrossCorrelation(seq);
if (fitnessFuncCombo.SelectedIndex == 4)
fitness = GeneticMIDI.FitnessFunctions.NCD.FromMelodies(category);*/
Instrument = (PatchNames)geneticInstrumentBox.SelectedItem;
var gen = new GeneticGenerator(fitness, Instrument, category);
gen.OnPercentage += gen_OnPercentage;
gen.MaxGenerations = (int)maxGenerationSlider.Value;
Generator = gen;
new Thread(() =>
{
var notes = gen.Generate();
var mel = notes;
GeneratedSequence = mel;
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Value = 100;
});
}).Start();
}
if (index == 1)
{
if (instrBox.SelectedItem as ListBoxItem == null || (instrBox.SelectedItem as ListBoxItem).Tag == null)
return;
if ((int)((instrBox.SelectedItem as ListBoxItem).Tag) == -1)
{
// Drum Generator
DrumGenerator gen = new DrumGenerator();
Generator = gen;
Instrument = PatchNames.Helicopter;
new Thread(() =>
{
StartSpinner();
gen.Initialize(new Databank(GeneticMIDI.Constants.LOCAL_LIBRARY_PATH));
GeneratedSequence = gen.Generate();
StopSpinner();
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Value = 100;
});
}).Start();
}
else
{
PatchNames instrument = (PatchNames)((instrBox.SelectedItem as ListBoxItem).Tag);
Instrument = instrument;
InstrumentalGenerator gen = Generator as InstrumentalGenerator;
if (gen == null)
return;
gen.SetInstrument(Instrument);
new Thread(() =>
{
if (gen.IsInitialized)
{
StartSpinner();
GeneratedSequence = gen.GenerateInstrument(instrument);
StopSpinner();
}
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Value = 100;
});
}).Start();
}
}
if(index == 2)
{
if (accompInstruBox.Items.Count == 0 || accompTrackBox.Items.Count == 0)
return;
Instrument = (PatchNames)(accompInstruBox.SelectedItem);
Track track = (accompTrackBox.SelectedItem as ListBoxItem).Tag as Track;
var melSeq = track.GetMainSequence() as MelodySequence;
Random rnd = new Random();
if(accompMethoBox.SelectedIndex == 0)
{
AccompanyGeneratorMarkov gen = new AccompanyGeneratorMarkov(category, Instrument);
Generator = gen;
new Thread(() =>
{
StartSpinner();
GeneratedSequence = gen.Generate(melSeq,rnd.Next());
StopSpinner();
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Value = 100;
});
}).Start();
}
else if (accompMethoBox.SelectedIndex == 1)
{
AccompanimentGeneratorANNFF gen = new AccompanimentGeneratorANNFF(category, Instrument);
Generator = gen;
gen.SetSequence(melSeq);
new Thread(() =>
{
StartSpinner();
gen.Load();
GeneratedSequence = gen.Generate();
StopSpinner();
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Value = 100;
});
}).Start();
}
}
if(index == 3)
{
//stochasticLogPlot.Model.Series.Clear();
stochasticLogPlot.ResetAllAxes();
SetupLinePlot(stochasticLogPlot, "Log Likelihood");
(stochasticLogPlot.Model.Series[0] as LineSeries).Points.Clear();
stochasticLogPlot.Model.Series[0].Unselect();
stochasticLogPlot.InvalidatePlot();
if (loadInstrument.SelectedItem == null)
return;
Instrument = (PatchNames)(loadInstrument.SelectedItem);
SamplingWithReplacement swr = new SamplingWithReplacement(category, Instrument);
swr.OnProgressChange += swr_OnProgressChange;
swr.MaxIterations = (int)loadGenerationsSlider.Value;
Generator = swr;
new Thread(() =>
{
StartSpinner();
GeneratedSequence = swr.Generate();
StopSpinner();
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Maximum = 100;
progressGenSlider.Value = 100;
});
}).Start();
}
if(index == 4)
{
if (randomInstrument.SelectedItem == null)
return;
Instrument = (PatchNames)randomInstrument.SelectedItem;
int centralNotePitch = (int)randomOctave.Value * 12;
int noteShift = (int)randomPitchVar.Value;
int minNote = centralNotePitch - noteShift;
int maxNote = centralNotePitch + noteShift;
if (minNote <= 0)
minNote = 1;
if (maxNote >= 127)
maxNote = 126;
int durMin = (int)Math.Pow(randomDurationRange.LowerValue, 2);
int durMax = (int)Math.Pow(randomDurationRange.UpperValue, 2);
int length = (int)randomLength.Value;
ScaleType scale = randomScale.SelectedItem as ScaleType;
var gen = new ReflectingBrownNoteGenerator(new NoteRangeRestrictor(minNote, maxNote, durMin, durMax, scale), new Random(), -2, 2, -1, 1, Instrument);
Generator = gen;
gen.MaxNotes = length;
new Thread(() =>
{
StartSpinner();
GeneratedSequence = gen.Generate();
StopSpinner();
progressGenSlider.Dispatcher.Invoke(() =>
{
progressGenSlider.Value = 100;
});
}).Start();
Console.ReadLine();
}
}