def test_chords_scale():
major_scale = GenericScale('C', [0, 2, 4, 5, 7, 9, 11])
csd = ChordInScaleDefinition(major_scale)
csd.generate_chord(Note('C', 3))
assert True
def generate_dataset(n_measures,
tempo=Tempo(120),
scale=GenericScale('C', [0, 2, 3, 5, 7, 8, 10]),
sampling_info=SamplingInfo(44100)):
signature = Signature(4, 4)
n_notes_per_measure = 4
bass_instrument = make_bass_instrument(sampling_info)
lead_instrument = make_lead_instrument(sampling_info)
chord_instrument = make_accomp_instrument(sampling_info)
chord_track = generate_chord_track(scale, tempo, signature, n_measures)
y_chord = chord_instrument.generate_track(chord_track)
lead_track = generate_lead_track(scale, tempo, signature, n_measures,
n_notes_per_measure)
y_lead = lead_instrument.generate_track(lead_track)
bass_track = generate_bass_track(scale, tempo, signature, n_measures)
y_bass = bass_instrument.generate_track(bass_track)
mix = mixdown([y_bass, y_chord, y_lead])
return [bass_track, chord_track, lead_track], [y_bass, y_chord,
y_lead], mix
def lead():
lead = generate_dataset(n_measures=4,
tempo=Tempo(120),
scale=GenericScale('C', [0, 2, 3, 5, 7, 8, 10]),
sampling_info=SamplingInfo(44100))[1][2]
lead = np.concatenate((lead, np.zeros(shape=44100)), axis=0)
return lead
def test_in_scale():
major_scale = GenericScale('C', [0, 2, 4, 5, 7, 9, 11])
major_chord = MajorChordDefinition()
chord = major_chord.generate_chord(Note('C', 3))
assert chord.is_in_scale(major_scale)
major_chord = MajorChordDefinition()
chord = major_chord.generate_chord(Note('D', 3))
assert not chord.is_in_scale(major_scale)
def main(length, note_duration):
"""Main function
Args:
length (float): length in seconds
note_duration (float): duration of a single notes in seconds
Returns:
int: program exit-code
"""
sampling_info = SamplingInfo(88200)
score_tracks, audio_tracks, mix = generate_dataset(
n_measures=16,
tempo=Tempo(100),
scale=GenericScale('E', [0, 2, 3, 5, 7, 8, 10]),
sampling_info=sampling_info)
play_array(mix, sampling_info.sample_rate)
return 0
def generate_dataset_for_root(root):
return generate_dataset(n_measures=32,
tempo=Tempo(120),
scale=GenericScale(root, [0, 2, 3, 5, 7, 8, 10]),
sampling_info=sampling_info)