def remixing():
in_transcript = reader.load_transcript(file1)
in_transcript2 = reader.load_transcript(file2)
ngram = MultiInstrumentNGram(nsize)
ngram.build_from_transcript(in_transcript)
ngram.build_from_transcript(in_transcript2)
scheduled_tracks = Generator.generate_multi_instrument_tracks(ngram, ticks)
return PatternSchedule(scheduled_tracks=scheduled_tracks, meta=in_transcript.get_transcript_meta())
def run_from_eminem_music():
files = listdir("music/Eminem")
ignored = ["music/Eminem/business.mid", "music/Eminem/forgotaboutdre.mid", "music/Eminem/purple pills.mid"]
# "music/Eminem/Under_The_Influence.mid"]
ngram = MultiInstrumentNGram(nsize)
last_transcript = None
for file in files:
path = "music/Eminem/" + file
if path not in ignored:
print path
transcript = reader.load_transcript(path)
ngram.build_from_transcript(transcript)
last_transcript = transcript
scheduled_tracks = Generator.generate_multi_instrument_tracks(ngram, ticks)
return PatternSchedule(scheduled_tracks=scheduled_tracks, meta=last_transcript.get_transcript_meta())
def generate(input_file, ticks, folder='default', nsize=2, policy='random'):
# properties that should be on the website:
if policy == 'random':
Policies.frame_selection_policy = FrameSelectionPolicy.RANDOM
elif policy == 'highest':
Policies.frame_selection_policy = FrameSelectionPolicy.HIGHEST_COUNT
elif policy == 'prob':
Policies.frame_selection_policy = FrameSelectionPolicy.PROB
elif policy == 'experimental':
Policies.frame_selection_policy = FrameSelectionPolicy.EXPERIMENTAL
else:
Policies.frame_selection_policy = FrameSelectionPolicy.RANDOM
# generation code
name = input_file.split('.')[0]
output_file_name = "%s/output-%s.mid" % (folder, name)
in_transcript = reader.load_transcript("%s/%s" % (folder, input_file))
ngram = MultiInstrumentNGram(nsize)
ngram.build_from_transcript(in_transcript)
scheduled_tracks = generate_multi_instrument_tracks(ngram, ticks)
pattern_schedule = PatternSchedule(scheduled_tracks=scheduled_tracks, meta=in_transcript.get_transcript_meta())
MidiFileWriter(pattern_schedule).save_to_file(output_file_name)
from graphmodel.NGram import MultiInstrumentNGram from graphmodel.appio import reader from graphmodel.appio.scheduler import PatternSchedule from graphmodel.appio.writer import MidiFileWriter # constants from graphmodel.model import Policies nsize = 10 ticks = 10000 Policies.frame_selection_policy = Policies.FrameSelectionPolicy.RANDOM input_midi_file_name = "music/bach.mid" output_midi_file_name = "music/bach-out.mid" # Create a transcript, this encapsulates the midi data into instrument tracks, where each track contains Note objects transcript = reader.load_transcript(input_midi_file_name) # Build the ngram from the track ngram = MultiInstrumentNGram(nsize) ngram.build_from_transcript(transcript) # Generate tracks scheduled_tracks = Generator.generate_multi_instrument_tracks(ngram, ticks) # Create a Pattern Schedule pattern_schedule = PatternSchedule(scheduled_tracks=scheduled_tracks, meta=transcript.get_transcript_meta()) # Convert the Pattern Schedule to an actual Midi Pattern and write it to file MidiFileWriter(pattern_schedule).save_to_file(output_midi_file_name) # Play the generated music
def setUp(self):
file1 = "../music/mary.mid"
self.transcript = reader.load_transcript(file1)
def test_merge_tracks(self):
f = "music/bach.mid"
transcript2 = reader.load_transcript(f)
def reproduce():
transcript = reader.load_transcript("music/Eminem/forgotaboutdre.mid")
ngram = MultiInstrumentNGram(nsize)
ngram.build_from_transcript(transcript)
scheduled_tracks = Generator.generate_multi_instrument_tracks(ngram, ticks)
return PatternSchedule(scheduled_tracks=scheduled_tracks, meta=transcript.get_transcript_meta())