| |
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|
| r'''############################################################################### |
| ################################################################################### |
| # |
| # |
| # Tegridy MIDI X Module (TMIDI X / tee-midi eks) |
| # Version 1.0 |
| # |
| # NOTE: TMIDI X Module starts after the partial MIDI.py module @ line 1342 |
| # |
| # Based upon MIDI.py module v.6.7. by Peter Billam / pjb.com.au |
| # |
| # Project Los Angeles |
| # |
| # Tegridy Code 2021 |
| # |
| # https://github.com/Tegridy-Code/Project-Los-Angeles |
| # |
| # |
| ################################################################################### |
| ################################################################################### |
| # Copyright 2021 Project Los Angeles / Tegridy Code |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| ################################################################################### |
| ################################################################################### |
| # |
| # PARTIAL MIDI.py Module v.6.7. by Peter Billam |
| # Please see TMIDI 2.3/tegridy-tools repo for full MIDI.py module code |
| # |
| # Or you can always download the latest full version from: |
| # |
| # https://pjb.com.au/ |
| # https://peterbillam.gitlab.io/miditools/ |
| # |
| # Copyright 2020 Peter Billam |
| # |
| ################################################################################### |
| ###################################################################################''' |
|
|
| import sys, struct, copy |
| Version = '6.7' |
| VersionDate = '20201120' |
|
|
| _previous_warning = '' |
| _previous_times = 0 |
| |
|
|
| def opus2midi(opus=[], text_encoding='ISO-8859-1'): |
| r'''The argument is a list: the first item in the list is the "ticks" |
| parameter, the others are the tracks. Each track is a list |
| of midi-events, and each event is itself a list; see above. |
| opus2midi() returns a bytestring of the MIDI, which can then be |
| written either to a file opened in binary mode (mode='wb'), |
| or to stdout by means of: sys.stdout.buffer.write() |
| |
| my_opus = [ |
| 96, |
| [ # track 0: |
| ['patch_change', 0, 1, 8], # and these are the events... |
| ['note_on', 5, 1, 25, 96], |
| ['note_off', 96, 1, 25, 0], |
| ['note_on', 0, 1, 29, 96], |
| ['note_off', 96, 1, 29, 0], |
| ], # end of track 0 |
| ] |
| my_midi = opus2midi(my_opus) |
| sys.stdout.buffer.write(my_midi) |
| ''' |
| if len(opus) < 2: |
| opus=[1000, [],] |
| tracks = copy.deepcopy(opus) |
| ticks = int(tracks.pop(0)) |
| ntracks = len(tracks) |
| if ntracks == 1: |
| format = 0 |
| else: |
| format = 1 |
|
|
| my_midi = b"MThd\x00\x00\x00\x06"+struct.pack('>HHH',format,ntracks,ticks) |
| for track in tracks: |
| events = _encode(track, text_encoding=text_encoding) |
| my_midi += b'MTrk' + struct.pack('>I',len(events)) + events |
| _clean_up_warnings() |
| return my_midi |
|
|
|
|
| def score2opus(score=None, text_encoding='ISO-8859-1'): |
| r''' |
| The argument is a list: the first item in the list is the "ticks" |
| parameter, the others are the tracks. Each track is a list |
| of score-events, and each event is itself a list. A score-event |
| is similar to an opus-event (see above), except that in a score: |
| 1) the times are expressed as an absolute number of ticks |
| from the track's start time |
| 2) the pairs of 'note_on' and 'note_off' events in an "opus" |
| are abstracted into a single 'note' event in a "score": |
| ['note', start_time, duration, channel, pitch, velocity] |
| score2opus() returns a list specifying the equivalent "opus". |
| |
| my_score = [ |
| 96, |
| [ # track 0: |
| ['patch_change', 0, 1, 8], |
| ['note', 5, 96, 1, 25, 96], |
| ['note', 101, 96, 1, 29, 96] |
| ], # end of track 0 |
| ] |
| my_opus = score2opus(my_score) |
| ''' |
| if len(score) < 2: |
| score=[1000, [],] |
| tracks = copy.deepcopy(score) |
| ticks = int(tracks.pop(0)) |
| opus_tracks = [] |
| for scoretrack in tracks: |
| time2events = dict([]) |
| for scoreevent in scoretrack: |
| if scoreevent[0] == 'note': |
| note_on_event = ['note_on',scoreevent[1], |
| scoreevent[3],scoreevent[4],scoreevent[5]] |
| note_off_event = ['note_off',scoreevent[1]+scoreevent[2], |
| scoreevent[3],scoreevent[4],scoreevent[5]] |
| if time2events.get(note_on_event[1]): |
| time2events[note_on_event[1]].append(note_on_event) |
| else: |
| time2events[note_on_event[1]] = [note_on_event,] |
| if time2events.get(note_off_event[1]): |
| time2events[note_off_event[1]].append(note_off_event) |
| else: |
| time2events[note_off_event[1]] = [note_off_event,] |
| continue |
| if time2events.get(scoreevent[1]): |
| time2events[scoreevent[1]].append(scoreevent) |
| else: |
| time2events[scoreevent[1]] = [scoreevent,] |
|
|
| sorted_times = [] |
| for k in time2events.keys(): |
| sorted_times.append(k) |
| sorted_times.sort() |
|
|
| sorted_events = [] |
| for time in sorted_times: |
| sorted_events.extend(time2events[time]) |
|
|
| abs_time = 0 |
| for event in sorted_events: |
| delta_time = event[1] - abs_time |
| abs_time = event[1] |
| event[1] = delta_time |
| opus_tracks.append(sorted_events) |
| opus_tracks.insert(0,ticks) |
| _clean_up_warnings() |
| return opus_tracks |
|
|
| def score2midi(score=None, text_encoding='ISO-8859-1'): |
| r''' |
| Translates a "score" into MIDI, using score2opus() then opus2midi() |
| ''' |
| return opus2midi(score2opus(score, text_encoding), text_encoding) |
|
|
| |
|
|
| def midi2opus(midi=b'', do_not_check_MIDI_signature=False): |
| r'''Translates MIDI into a "opus". For a description of the |
| "opus" format, see opus2midi() |
| ''' |
| my_midi=bytearray(midi) |
| if len(my_midi) < 4: |
| _clean_up_warnings() |
| return [1000,[],] |
| id = bytes(my_midi[0:4]) |
| if id != b'MThd': |
| _warn("midi2opus: midi starts with "+str(id)+" instead of 'MThd'") |
| _clean_up_warnings() |
| if do_not_check_MIDI_signature == False: |
| return [1000,[],] |
| [length, format, tracks_expected, ticks] = struct.unpack( |
| '>IHHH', bytes(my_midi[4:14])) |
| if length != 6: |
| _warn("midi2opus: midi header length was "+str(length)+" instead of 6") |
| _clean_up_warnings() |
| return [1000,[],] |
| my_opus = [ticks,] |
| my_midi = my_midi[14:] |
| track_num = 1 |
| while len(my_midi) >= 8: |
| track_type = bytes(my_midi[0:4]) |
| if track_type != b'MTrk': |
| |
| pass |
| [track_length] = struct.unpack('>I', my_midi[4:8]) |
| my_midi = my_midi[8:] |
| if track_length > len(my_midi): |
| _warn('midi2opus: track #'+str(track_num)+' length '+str(track_length)+' is too large') |
| _clean_up_warnings() |
| return my_opus |
| my_midi_track = my_midi[0:track_length] |
| my_track = _decode(my_midi_track) |
| my_opus.append(my_track) |
| my_midi = my_midi[track_length:] |
| track_num += 1 |
| _clean_up_warnings() |
| return my_opus |
|
|
| def opus2score(opus=[]): |
| r'''For a description of the "opus" and "score" formats, |
| see opus2midi() and score2opus(). |
| ''' |
| if len(opus) < 2: |
| _clean_up_warnings() |
| return [1000,[],] |
| tracks = copy.deepcopy(opus) |
| ticks = int(tracks.pop(0)) |
| score = [ticks,] |
| for opus_track in tracks: |
| ticks_so_far = 0 |
| score_track = [] |
| chapitch2note_on_events = dict([]) |
| for opus_event in opus_track: |
| ticks_so_far += opus_event[1] |
| if opus_event[0] == 'note_off' or (opus_event[0] == 'note_on' and opus_event[4] == 0): |
| cha = opus_event[2] |
| pitch = opus_event[3] |
| key = cha*128 + pitch |
| if chapitch2note_on_events.get(key): |
| new_event = chapitch2note_on_events[key].pop(0) |
| new_event[2] = ticks_so_far - new_event[1] |
| score_track.append(new_event) |
| elif pitch > 127: |
| pass |
| else: |
| pass |
| elif opus_event[0] == 'note_on': |
| cha = opus_event[2] |
| pitch = opus_event[3] |
| key = cha*128 + pitch |
| new_event = ['note',ticks_so_far,0,cha,pitch, opus_event[4]] |
| if chapitch2note_on_events.get(key): |
| chapitch2note_on_events[key].append(new_event) |
| else: |
| chapitch2note_on_events[key] = [new_event,] |
| else: |
| opus_event[1] = ticks_so_far |
| score_track.append(opus_event) |
| |
| for chapitch in chapitch2note_on_events: |
| note_on_events = chapitch2note_on_events[chapitch] |
| for new_e in note_on_events: |
| new_e[2] = ticks_so_far - new_e[1] |
| score_track.append(new_e) |
| pass |
| score.append(score_track) |
| _clean_up_warnings() |
| return score |
|
|
| def midi2score(midi=b'', do_not_check_MIDI_signature=False): |
| r''' |
| Translates MIDI into a "score", using midi2opus() then opus2score() |
| ''' |
| return opus2score(midi2opus(midi, do_not_check_MIDI_signature)) |
|
|
| def midi2ms_score(midi=b'', do_not_check_MIDI_signature=False): |
| r''' |
| Translates MIDI into a "score" with one beat per second and one |
| tick per millisecond, using midi2opus() then to_millisecs() |
| then opus2score() |
| ''' |
| return opus2score(to_millisecs(midi2opus(midi, do_not_check_MIDI_signature))) |
|
|
| def midi2single_track_ms_score(midi_path_or_bytes, |
| recalculate_channels = False, |
| pass_old_timings_events= False, |
| verbose = False, |
| do_not_check_MIDI_signature=False |
| ): |
| r''' |
| Translates MIDI into a single track "score" with 16 instruments and one beat per second and one |
| tick per millisecond |
| ''' |
|
|
| if type(midi_path_or_bytes) == bytes: |
| midi_data = midi_path_or_bytes |
|
|
| elif type(midi_path_or_bytes) == str: |
| midi_data = open(midi_path_or_bytes, 'rb').read() |
|
|
| score = midi2score(midi_data, do_not_check_MIDI_signature) |
|
|
| if recalculate_channels: |
|
|
| events_matrixes = [] |
|
|
| itrack = 1 |
| events_matrixes_channels = [] |
| while itrack < len(score): |
| events_matrix = [] |
| for event in score[itrack]: |
| if event[0] == 'note' and event[3] != 9: |
| event[3] = (16 * (itrack-1)) + event[3] |
| if event[3] not in events_matrixes_channels: |
| events_matrixes_channels.append(event[3]) |
|
|
| events_matrix.append(event) |
| events_matrixes.append(events_matrix) |
| itrack += 1 |
|
|
| events_matrix1 = [] |
| for e in events_matrixes: |
| events_matrix1.extend(e) |
|
|
| if verbose: |
| if len(events_matrixes_channels) > 16: |
| print('MIDI has', len(events_matrixes_channels), 'instruments!', len(events_matrixes_channels) - 16, 'instrument(s) will be removed!') |
|
|
| for e in events_matrix1: |
| if e[0] == 'note' and e[3] != 9: |
| if e[3] in events_matrixes_channels[:15]: |
| if events_matrixes_channels[:15].index(e[3]) < 9: |
| e[3] = events_matrixes_channels[:15].index(e[3]) |
| else: |
| e[3] = events_matrixes_channels[:15].index(e[3])+1 |
| else: |
| events_matrix1.remove(e) |
| |
| if e[0] in ['patch_change', 'control_change', 'channel_after_touch', 'key_after_touch', 'pitch_wheel_change'] and e[2] != 9: |
| if e[2] in [e % 16 for e in events_matrixes_channels[:15]]: |
| if [e % 16 for e in events_matrixes_channels[:15]].index(e[2]) < 9: |
| e[2] = [e % 16 for e in events_matrixes_channels[:15]].index(e[2]) |
| else: |
| e[2] = [e % 16 for e in events_matrixes_channels[:15]].index(e[2])+1 |
| else: |
| events_matrix1.remove(e) |
| |
| else: |
| events_matrix1 = [] |
| itrack = 1 |
| |
| while itrack < len(score): |
| for event in score[itrack]: |
| events_matrix1.append(event) |
| itrack += 1 |
|
|
| opus = score2opus([score[0], events_matrix1]) |
| ms_score = opus2score(to_millisecs(opus, pass_old_timings_events=pass_old_timings_events)) |
|
|
| return ms_score |
|
|
| |
|
|
| def to_millisecs(old_opus=None, desired_time_in_ms=1, pass_old_timings_events = False): |
| r'''Recallibrates all the times in an "opus" to use one beat |
| per second and one tick per millisecond. This makes it |
| hard to retrieve any information about beats or barlines, |
| but it does make it easy to mix different scores together. |
| ''' |
| if old_opus == None: |
| return [1000 * desired_time_in_ms,[],] |
| try: |
| old_tpq = int(old_opus[0]) |
| except IndexError: |
| _warn('to_millisecs: the opus '+str(type(old_opus))+' has no elements') |
| return [1000 * desired_time_in_ms,[],] |
| new_opus = [1000 * desired_time_in_ms,] |
| |
| ticks2tempo = {} |
| itrack = 1 |
| while itrack < len(old_opus): |
| ticks_so_far = 0 |
| for old_event in old_opus[itrack]: |
| if old_event[0] == 'note': |
| raise TypeError('to_millisecs needs an opus, not a score') |
| ticks_so_far += old_event[1] |
| if old_event[0] == 'set_tempo': |
| ticks2tempo[ticks_so_far] = old_event[2] |
| itrack += 1 |
| |
| tempo_ticks = [] |
| for k in ticks2tempo.keys(): |
| tempo_ticks.append(k) |
| tempo_ticks.sort() |
| |
| |
| itrack = 1 |
| while itrack < len(old_opus): |
| ms_per_old_tick = 400 / old_tpq |
| i_tempo_ticks = 0 |
| ticks_so_far = 0 |
| ms_so_far = 0.0 |
| previous_ms_so_far = 0.0 |
|
|
| if pass_old_timings_events: |
| new_track = [['set_tempo',0,1000000 * desired_time_in_ms],['old_tpq', 0, old_tpq]] |
| else: |
| new_track = [['set_tempo',0,1000000 * desired_time_in_ms],] |
| for old_event in old_opus[itrack]: |
| |
| |
| event_delta_ticks = old_event[1] * desired_time_in_ms |
| if (i_tempo_ticks < len(tempo_ticks) and |
| tempo_ticks[i_tempo_ticks] < (ticks_so_far + old_event[1]) * desired_time_in_ms): |
| delta_ticks = tempo_ticks[i_tempo_ticks] - ticks_so_far |
| ms_so_far += (ms_per_old_tick * delta_ticks * desired_time_in_ms) |
| ticks_so_far = tempo_ticks[i_tempo_ticks] |
| ms_per_old_tick = ticks2tempo[ticks_so_far] / (1000.0*old_tpq * desired_time_in_ms) |
| i_tempo_ticks += 1 |
| event_delta_ticks -= delta_ticks |
| new_event = copy.deepcopy(old_event) |
| ms_so_far += (ms_per_old_tick * old_event[1] * desired_time_in_ms) |
| new_event[1] = round(ms_so_far - previous_ms_so_far) |
|
|
| if pass_old_timings_events: |
| if old_event[0] != 'set_tempo': |
| previous_ms_so_far = ms_so_far |
| new_track.append(new_event) |
| else: |
| new_event[0] = 'old_set_tempo' |
| previous_ms_so_far = ms_so_far |
| new_track.append(new_event) |
| else: |
| if old_event[0] != 'set_tempo': |
| previous_ms_so_far = ms_so_far |
| new_track.append(new_event) |
| ticks_so_far += event_delta_ticks |
| new_opus.append(new_track) |
| itrack += 1 |
| _clean_up_warnings() |
| return new_opus |
|
|
| def event2alsaseq(event=None): |
| r'''Converts an event into the format needed by the alsaseq module, |
| http://pp.com.mx/python/alsaseq |
| The type of track (opus or score) is autodetected. |
| ''' |
| pass |
|
|
| def grep(score=None, channels=None): |
| r'''Returns a "score" containing only the channels specified |
| ''' |
| if score == None: |
| return [1000,[],] |
| ticks = score[0] |
| new_score = [ticks,] |
| if channels == None: |
| return new_score |
| channels = set(channels) |
| global Event2channelindex |
| itrack = 1 |
| while itrack < len(score): |
| new_score.append([]) |
| for event in score[itrack]: |
| channel_index = Event2channelindex.get(event[0], False) |
| if channel_index: |
| if event[channel_index] in channels: |
| new_score[itrack].append(event) |
| else: |
| new_score[itrack].append(event) |
| itrack += 1 |
| return new_score |
|
|
| def play_score(score=None): |
| r'''Converts the "score" to midi, and feeds it into 'aplaymidi -' |
| ''' |
| if score == None: |
| return |
| import subprocess |
| pipe = subprocess.Popen(['aplaymidi','-'], stdin=subprocess.PIPE) |
| if score_type(score) == 'opus': |
| pipe.stdin.write(opus2midi(score)) |
| else: |
| pipe.stdin.write(score2midi(score)) |
| pipe.stdin.close() |
|
|
| def score2stats(opus_or_score=None): |
| r'''Returns a dict of some basic stats about the score, like |
| bank_select (list of tuples (msb,lsb)), |
| channels_by_track (list of lists), channels_total (set), |
| general_midi_mode (list), |
| ntracks, nticks, patch_changes_by_track (list of dicts), |
| num_notes_by_channel (list of numbers), |
| patch_changes_total (set), |
| percussion (dict histogram of channel 9 events), |
| pitches (dict histogram of pitches on channels other than 9), |
| pitch_range_by_track (list, by track, of two-member-tuples), |
| pitch_range_sum (sum over tracks of the pitch_ranges), |
| ''' |
| bank_select_msb = -1 |
| bank_select_lsb = -1 |
| bank_select = [] |
| channels_by_track = [] |
| channels_total = set([]) |
| general_midi_mode = [] |
| num_notes_by_channel = dict([]) |
| patches_used_by_track = [] |
| patches_used_total = set([]) |
| patch_changes_by_track = [] |
| patch_changes_total = set([]) |
| percussion = dict([]) |
| pitches = dict([]) |
| pitch_range_sum = 0 |
| pitch_range_by_track = [] |
| is_a_score = True |
| if opus_or_score == None: |
| return {'bank_select':[], 'channels_by_track':[], 'channels_total':[], |
| 'general_midi_mode':[], 'ntracks':0, 'nticks':0, |
| 'num_notes_by_channel':dict([]), |
| 'patch_changes_by_track':[], 'patch_changes_total':[], |
| 'percussion':{}, 'pitches':{}, 'pitch_range_by_track':[], |
| 'ticks_per_quarter':0, 'pitch_range_sum':0} |
| ticks_per_quarter = opus_or_score[0] |
| i = 1 |
| nticks = 0 |
| while i < len(opus_or_score): |
| highest_pitch = 0 |
| lowest_pitch = 128 |
| channels_this_track = set([]) |
| patch_changes_this_track = dict({}) |
| for event in opus_or_score[i]: |
| if event[0] == 'note': |
| num_notes_by_channel[event[3]] = num_notes_by_channel.get(event[3],0) + 1 |
| if event[3] == 9: |
| percussion[event[4]] = percussion.get(event[4],0) + 1 |
| else: |
| pitches[event[4]] = pitches.get(event[4],0) + 1 |
| if event[4] > highest_pitch: |
| highest_pitch = event[4] |
| if event[4] < lowest_pitch: |
| lowest_pitch = event[4] |
| channels_this_track.add(event[3]) |
| channels_total.add(event[3]) |
| finish_time = event[1] + event[2] |
| if finish_time > nticks: |
| nticks = finish_time |
| elif event[0] == 'note_off' or (event[0] == 'note_on' and event[4] == 0): |
| finish_time = event[1] |
| if finish_time > nticks: |
| nticks = finish_time |
| elif event[0] == 'note_on': |
| is_a_score = False |
| num_notes_by_channel[event[2]] = num_notes_by_channel.get(event[2],0) + 1 |
| if event[2] == 9: |
| percussion[event[3]] = percussion.get(event[3],0) + 1 |
| else: |
| pitches[event[3]] = pitches.get(event[3],0) + 1 |
| if event[3] > highest_pitch: |
| highest_pitch = event[3] |
| if event[3] < lowest_pitch: |
| lowest_pitch = event[3] |
| channels_this_track.add(event[2]) |
| channels_total.add(event[2]) |
| elif event[0] == 'patch_change': |
| patch_changes_this_track[event[2]] = event[3] |
| patch_changes_total.add(event[3]) |
| elif event[0] == 'control_change': |
| if event[3] == 0: |
| bank_select_msb = event[4] |
| elif event[3] == 32: |
| bank_select_lsb = event[4] |
| if bank_select_msb >= 0 and bank_select_lsb >= 0: |
| bank_select.append((bank_select_msb,bank_select_lsb)) |
| bank_select_msb = -1 |
| bank_select_lsb = -1 |
| elif event[0] == 'sysex_f0': |
| if _sysex2midimode.get(event[2], -1) >= 0: |
| general_midi_mode.append(_sysex2midimode.get(event[2])) |
| if is_a_score: |
| if event[1] > nticks: |
| nticks = event[1] |
| else: |
| nticks += event[1] |
| if lowest_pitch == 128: |
| lowest_pitch = 0 |
| channels_by_track.append(channels_this_track) |
| patch_changes_by_track.append(patch_changes_this_track) |
| pitch_range_by_track.append((lowest_pitch,highest_pitch)) |
| pitch_range_sum += (highest_pitch-lowest_pitch) |
| i += 1 |
|
|
| return {'bank_select':bank_select, |
| 'channels_by_track':channels_by_track, |
| 'channels_total':channels_total, |
| 'general_midi_mode':general_midi_mode, |
| 'ntracks':len(opus_or_score)-1, |
| 'nticks':nticks, |
| 'num_notes_by_channel':num_notes_by_channel, |
| 'patch_changes_by_track':patch_changes_by_track, |
| 'patch_changes_total':patch_changes_total, |
| 'percussion':percussion, |
| 'pitches':pitches, |
| 'pitch_range_by_track':pitch_range_by_track, |
| 'pitch_range_sum':pitch_range_sum, |
| 'ticks_per_quarter':ticks_per_quarter} |
|
|
| |
|
|
| _sysex2midimode = { |
| "\x7E\x7F\x09\x01\xF7": 1, |
| "\x7E\x7F\x09\x02\xF7": 0, |
| "\x7E\x7F\x09\x03\xF7": 2, |
| } |
|
|
| |
| MIDI_events = tuple('''note_off note_on key_after_touch |
| control_change patch_change channel_after_touch |
| pitch_wheel_change'''.split()) |
|
|
| Text_events = tuple('''text_event copyright_text_event |
| track_name instrument_name lyric marker cue_point text_event_08 |
| text_event_09 text_event_0a text_event_0b text_event_0c |
| text_event_0d text_event_0e text_event_0f'''.split()) |
|
|
| Nontext_meta_events = tuple('''end_track set_tempo |
| smpte_offset time_signature key_signature sequencer_specific |
| raw_meta_event sysex_f0 sysex_f7 song_position song_select |
| tune_request'''.split()) |
| |
|
|
| |
| Meta_events = Text_events + Nontext_meta_events |
| All_events = MIDI_events + Meta_events |
|
|
| |
| Number2patch = { |
| 0:'Acoustic Grand', |
| 1:'Bright Acoustic', |
| 2:'Electric Grand', |
| 3:'Honky-Tonk', |
| 4:'Electric Piano 1', |
| 5:'Electric Piano 2', |
| 6:'Harpsichord', |
| 7:'Clav', |
| 8:'Celesta', |
| 9:'Glockenspiel', |
| 10:'Music Box', |
| 11:'Vibraphone', |
| 12:'Marimba', |
| 13:'Xylophone', |
| 14:'Tubular Bells', |
| 15:'Dulcimer', |
| 16:'Drawbar Organ', |
| 17:'Percussive Organ', |
| 18:'Rock Organ', |
| 19:'Church Organ', |
| 20:'Reed Organ', |
| 21:'Accordion', |
| 22:'Harmonica', |
| 23:'Tango Accordion', |
| 24:'Acoustic Guitar(nylon)', |
| 25:'Acoustic Guitar(steel)', |
| 26:'Electric Guitar(jazz)', |
| 27:'Electric Guitar(clean)', |
| 28:'Electric Guitar(muted)', |
| 29:'Overdriven Guitar', |
| 30:'Distortion Guitar', |
| 31:'Guitar Harmonics', |
| 32:'Acoustic Bass', |
| 33:'Electric Bass(finger)', |
| 34:'Electric Bass(pick)', |
| 35:'Fretless Bass', |
| 36:'Slap Bass 1', |
| 37:'Slap Bass 2', |
| 38:'Synth Bass 1', |
| 39:'Synth Bass 2', |
| 40:'Violin', |
| 41:'Viola', |
| 42:'Cello', |
| 43:'Contrabass', |
| 44:'Tremolo Strings', |
| 45:'Pizzicato Strings', |
| 46:'Orchestral Harp', |
| 47:'Timpani', |
| 48:'String Ensemble 1', |
| 49:'String Ensemble 2', |
| 50:'SynthStrings 1', |
| 51:'SynthStrings 2', |
| 52:'Choir Aahs', |
| 53:'Voice Oohs', |
| 54:'Synth Voice', |
| 55:'Orchestra Hit', |
| 56:'Trumpet', |
| 57:'Trombone', |
| 58:'Tuba', |
| 59:'Muted Trumpet', |
| 60:'French Horn', |
| 61:'Brass Section', |
| 62:'SynthBrass 1', |
| 63:'SynthBrass 2', |
| 64:'Soprano Sax', |
| 65:'Alto Sax', |
| 66:'Tenor Sax', |
| 67:'Baritone Sax', |
| 68:'Oboe', |
| 69:'English Horn', |
| 70:'Bassoon', |
| 71:'Clarinet', |
| 72:'Piccolo', |
| 73:'Flute', |
| 74:'Recorder', |
| 75:'Pan Flute', |
| 76:'Blown Bottle', |
| 77:'Skakuhachi', |
| 78:'Whistle', |
| 79:'Ocarina', |
| 80:'Lead 1 (square)', |
| 81:'Lead 2 (sawtooth)', |
| 82:'Lead 3 (calliope)', |
| 83:'Lead 4 (chiff)', |
| 84:'Lead 5 (charang)', |
| 85:'Lead 6 (voice)', |
| 86:'Lead 7 (fifths)', |
| 87:'Lead 8 (bass+lead)', |
| 88:'Pad 1 (new age)', |
| 89:'Pad 2 (warm)', |
| 90:'Pad 3 (polysynth)', |
| 91:'Pad 4 (choir)', |
| 92:'Pad 5 (bowed)', |
| 93:'Pad 6 (metallic)', |
| 94:'Pad 7 (halo)', |
| 95:'Pad 8 (sweep)', |
| 96:'FX 1 (rain)', |
| 97:'FX 2 (soundtrack)', |
| 98:'FX 3 (crystal)', |
| 99:'FX 4 (atmosphere)', |
| 100:'FX 5 (brightness)', |
| 101:'FX 6 (goblins)', |
| 102:'FX 7 (echoes)', |
| 103:'FX 8 (sci-fi)', |
| 104:'Sitar', |
| 105:'Banjo', |
| 106:'Shamisen', |
| 107:'Koto', |
| 108:'Kalimba', |
| 109:'Bagpipe', |
| 110:'Fiddle', |
| 111:'Shanai', |
| 112:'Tinkle Bell', |
| 113:'Agogo', |
| 114:'Steel Drums', |
| 115:'Woodblock', |
| 116:'Taiko Drum', |
| 117:'Melodic Tom', |
| 118:'Synth Drum', |
| 119:'Reverse Cymbal', |
| 120:'Guitar Fret Noise', |
| 121:'Breath Noise', |
| 122:'Seashore', |
| 123:'Bird Tweet', |
| 124:'Telephone Ring', |
| 125:'Helicopter', |
| 126:'Applause', |
| 127:'Gunshot', |
| } |
| Notenum2percussion = { |
| 35:'Acoustic Bass Drum', |
| 36:'Bass Drum 1', |
| 37:'Side Stick', |
| 38:'Acoustic Snare', |
| 39:'Hand Clap', |
| 40:'Electric Snare', |
| 41:'Low Floor Tom', |
| 42:'Closed Hi-Hat', |
| 43:'High Floor Tom', |
| 44:'Pedal Hi-Hat', |
| 45:'Low Tom', |
| 46:'Open Hi-Hat', |
| 47:'Low-Mid Tom', |
| 48:'Hi-Mid Tom', |
| 49:'Crash Cymbal 1', |
| 50:'High Tom', |
| 51:'Ride Cymbal 1', |
| 52:'Chinese Cymbal', |
| 53:'Ride Bell', |
| 54:'Tambourine', |
| 55:'Splash Cymbal', |
| 56:'Cowbell', |
| 57:'Crash Cymbal 2', |
| 58:'Vibraslap', |
| 59:'Ride Cymbal 2', |
| 60:'Hi Bongo', |
| 61:'Low Bongo', |
| 62:'Mute Hi Conga', |
| 63:'Open Hi Conga', |
| 64:'Low Conga', |
| 65:'High Timbale', |
| 66:'Low Timbale', |
| 67:'High Agogo', |
| 68:'Low Agogo', |
| 69:'Cabasa', |
| 70:'Maracas', |
| 71:'Short Whistle', |
| 72:'Long Whistle', |
| 73:'Short Guiro', |
| 74:'Long Guiro', |
| 75:'Claves', |
| 76:'Hi Wood Block', |
| 77:'Low Wood Block', |
| 78:'Mute Cuica', |
| 79:'Open Cuica', |
| 80:'Mute Triangle', |
| 81:'Open Triangle', |
| } |
|
|
| Event2channelindex = { 'note':3, 'note_off':2, 'note_on':2, |
| 'key_after_touch':2, 'control_change':2, 'patch_change':2, |
| 'channel_after_touch':2, 'pitch_wheel_change':2 |
| } |
|
|
| |
| |
| |
|
|
| def _twobytes2int(byte_a): |
| r'''decode a 16 bit quantity from two bytes,''' |
| return (byte_a[1] | (byte_a[0] << 8)) |
|
|
| def _int2twobytes(int_16bit): |
| r'''encode a 16 bit quantity into two bytes,''' |
| return bytes([(int_16bit>>8) & 0xFF, int_16bit & 0xFF]) |
|
|
| def _read_14_bit(byte_a): |
| r'''decode a 14 bit quantity from two bytes,''' |
| return (byte_a[0] | (byte_a[1] << 7)) |
|
|
| def _write_14_bit(int_14bit): |
| r'''encode a 14 bit quantity into two bytes,''' |
| return bytes([int_14bit & 0x7F, (int_14bit>>7) & 0x7F]) |
|
|
| def _ber_compressed_int(integer): |
| r'''BER compressed integer (not an ASN.1 BER, see perlpacktut for |
| details). Its bytes represent an unsigned integer in base 128, |
| most significant digit first, with as few digits as possible. |
| Bit eight (the high bit) is set on each byte except the last. |
| ''' |
| ber = bytearray(b'') |
| seven_bits = 0x7F & integer |
| ber.insert(0, seven_bits) |
| integer >>= 7 |
| while integer > 0: |
| seven_bits = 0x7F & integer |
| ber.insert(0, 0x80|seven_bits) |
| integer >>= 7 |
| return ber |
|
|
| def _unshift_ber_int(ba): |
| r'''Given a bytearray, returns a tuple of (the ber-integer at the |
| start, and the remainder of the bytearray). |
| ''' |
| if not len(ba): |
| _warn('_unshift_ber_int: no integer found') |
| return ((0, b"")) |
| byte = ba.pop(0) |
| integer = 0 |
| while True: |
| integer += (byte & 0x7F) |
| if not (byte & 0x80): |
| return ((integer, ba)) |
| if not len(ba): |
| _warn('_unshift_ber_int: no end-of-integer found') |
| return ((0, ba)) |
| byte = ba.pop(0) |
| integer <<= 7 |
|
|
| def _clean_up_warnings(): |
| |
| |
| |
| global _previous_times |
| global _previous_warning |
| if _previous_times > 1: |
| |
| |
| |
| sys.stderr.write(' previous message repeated {0} times\n'.format(_previous_times)) |
| elif _previous_times > 0: |
| sys.stderr.write(' previous message repeated\n') |
| _previous_times = 0 |
| _previous_warning = '' |
|
|
| def _warn(s=''): |
| global _previous_times |
| global _previous_warning |
| if s == _previous_warning: |
| _previous_times = _previous_times + 1 |
| else: |
| _clean_up_warnings() |
| sys.stderr.write(str(s)+"\n") |
| _previous_warning = s |
|
|
| def _some_text_event(which_kind=0x01, text=b'some_text', text_encoding='ISO-8859-1'): |
| if str(type(text)).find("'str'") >= 0: |
| data = bytes(text, encoding=text_encoding) |
| else: |
| data = bytes(text) |
| return b'\xFF'+bytes((which_kind,))+_ber_compressed_int(len(data))+data |
|
|
| def _consistentise_ticks(scores): |
| |
| if len(scores) == 1: |
| return copy.deepcopy(scores) |
| are_consistent = True |
| ticks = scores[0][0] |
| iscore = 1 |
| while iscore < len(scores): |
| if scores[iscore][0] != ticks: |
| are_consistent = False |
| break |
| iscore += 1 |
| if are_consistent: |
| return copy.deepcopy(scores) |
| new_scores = [] |
| iscore = 0 |
| while iscore < len(scores): |
| score = scores[iscore] |
| new_scores.append(opus2score(to_millisecs(score2opus(score)))) |
| iscore += 1 |
| return new_scores |
|
|
|
|
| |
|
|
| def _decode(trackdata=b'', exclude=None, include=None, |
| event_callback=None, exclusive_event_callback=None, no_eot_magic=False): |
| r'''Decodes MIDI track data into an opus-style list of events. |
| The options: |
| 'exclude' is a list of event types which will be ignored SHOULD BE A SET |
| 'include' (and no exclude), makes exclude a list |
| of all possible events, /minus/ what include specifies |
| 'event_callback' is a coderef |
| 'exclusive_event_callback' is a coderef |
| ''' |
| trackdata = bytearray(trackdata) |
| if exclude == None: |
| exclude = [] |
| if include == None: |
| include = [] |
| if include and not exclude: |
| exclude = All_events |
| include = set(include) |
| exclude = set(exclude) |
|
|
| |
| event_code = -1; |
| event_count = 0; |
| events = [] |
|
|
| while(len(trackdata)): |
| |
| eot = False |
| event_count += 1 |
|
|
| E = [] |
| |
|
|
| |
| [time, remainder] = _unshift_ber_int(trackdata) |
|
|
| |
| first_byte = trackdata.pop(0) & 0xFF |
|
|
| if (first_byte < 0xF0): |
| if (first_byte & 0x80): |
| event_code = first_byte |
| else: |
| |
| trackdata.insert(0, first_byte) |
| if (event_code == -1): |
| _warn("Running status not set; Aborting track.") |
| return [] |
|
|
| command = event_code & 0xF0 |
| channel = event_code & 0x0F |
|
|
| if (command == 0xF6): |
| pass |
| elif (command == 0xC0 or command == 0xD0): |
| parameter = trackdata.pop(0) |
| else: |
| parameter = (trackdata.pop(0), trackdata.pop(0)) |
|
|
| |
| |
|
|
| if (command == 0x80): |
| if 'note_off' in exclude: |
| continue |
| E = ['note_off', time, channel, parameter[0], parameter[1]] |
| elif (command == 0x90): |
| if 'note_on' in exclude: |
| continue |
| E = ['note_on', time, channel, parameter[0], parameter[1]] |
| elif (command == 0xA0): |
| if 'key_after_touch' in exclude: |
| continue |
| E = ['key_after_touch',time,channel,parameter[0],parameter[1]] |
| elif (command == 0xB0): |
| if 'control_change' in exclude: |
| continue |
| E = ['control_change',time,channel,parameter[0],parameter[1]] |
| elif (command == 0xC0): |
| if 'patch_change' in exclude: |
| continue |
| E = ['patch_change', time, channel, parameter] |
| elif (command == 0xD0): |
| if 'channel_after_touch' in exclude: |
| continue |
| E = ['channel_after_touch', time, channel, parameter] |
| elif (command == 0xE0): |
| if 'pitch_wheel_change' in exclude: |
| continue |
| E = ['pitch_wheel_change', time, channel, |
| _read_14_bit(parameter)-0x2000] |
| else: |
| _warn("Shouldn't get here; command="+hex(command)) |
|
|
| elif (first_byte == 0xFF): |
| |
| |
| |
| |
| command = trackdata.pop(0) & 0xFF |
| [length, trackdata] = _unshift_ber_int(trackdata) |
| if (command == 0x00): |
| if (length == 2): |
| E = ['set_sequence_number',time,_twobytes2int(trackdata)] |
| else: |
| _warn('set_sequence_number: length must be 2, not '+str(length)) |
| E = ['set_sequence_number', time, 0] |
|
|
| elif command >= 0x01 and command <= 0x0f: |
| |
| |
| |
| |
| text_data = bytes(trackdata[0:length]) |
| |
| if (command == 0x01): |
| E = ['text_event', time, text_data] |
| elif (command == 0x02): |
| E = ['copyright_text_event', time, text_data] |
| elif (command == 0x03): |
| E = ['track_name', time, text_data] |
| elif (command == 0x04): |
| E = ['instrument_name', time, text_data] |
| elif (command == 0x05): |
| E = ['lyric', time, text_data] |
| elif (command == 0x06): |
| E = ['marker', time, text_data] |
| elif (command == 0x07): |
| E = ['cue_point', time, text_data] |
| |
| elif (command == 0x08): |
| E = ['text_event_08', time, text_data] |
| elif (command == 0x09): |
| E = ['text_event_09', time, text_data] |
| elif (command == 0x0a): |
| E = ['text_event_0a', time, text_data] |
| elif (command == 0x0b): |
| E = ['text_event_0b', time, text_data] |
| elif (command == 0x0c): |
| E = ['text_event_0c', time, text_data] |
| elif (command == 0x0d): |
| E = ['text_event_0d', time, text_data] |
| elif (command == 0x0e): |
| E = ['text_event_0e', time, text_data] |
| elif (command == 0x0f): |
| E = ['text_event_0f', time, text_data] |
|
|
| |
| elif (command == 0x2F): |
| E = ['end_track', time] |
| |
| |
| elif (command == 0x51): |
| if length != 3: |
| _warn('set_tempo event, but length='+str(length)) |
| E = ['set_tempo', time, |
| struct.unpack(">I", b'\x00'+trackdata[0:3])[0]] |
| elif (command == 0x54): |
| if length != 5: |
| _warn('smpte_offset event, but length='+str(length)) |
| E = ['smpte_offset',time] + list(struct.unpack(">BBBBB",trackdata[0:5])) |
| elif (command == 0x58): |
| if length != 4: |
| _warn('time_signature event, but length='+str(length)) |
| E = ['time_signature', time]+list(trackdata[0:4]) |
| elif (command == 0x59): |
| if length != 2: |
| _warn('key_signature event, but length='+str(length)) |
| E = ['key_signature',time] + list(struct.unpack(">bB",trackdata[0:2])) |
| elif (command == 0x7F): |
| E = ['sequencer_specific',time, bytes(trackdata[0:length])] |
| else: |
| E = ['raw_meta_event', time, command, |
| bytes(trackdata[0:length])] |
| |
| |
| |
|
|
| |
| trackdata = trackdata[length:] |
|
|
| |
| elif (first_byte == 0xF0 or first_byte == 0xF7): |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| [length, trackdata] = _unshift_ber_int(trackdata) |
| if first_byte == 0xF0: |
| |
| |
| E = ['sysex_f0', time, bytes(trackdata[0:length])] |
| else: |
| E = ['sysex_f7', time, bytes(trackdata[0:length])] |
| trackdata = trackdata[length:] |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| elif (first_byte == 0xF2): |
| |
| E = ['song_position', time, _read_14_bit(trackdata[:2])] |
| trackdata = trackdata[2:] |
|
|
| elif (first_byte == 0xF3): |
| |
| E = ['song_select', time, trackdata[0]] |
| trackdata = trackdata[1:] |
| |
|
|
| elif (first_byte == 0xF6): |
| E = ['tune_request', time] |
| |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
|
|
| r''' |
| elif (first_byte > 0xF0) { # Some unknown kinda F-series event #### |
| # Here we only produce a one-byte piece of raw data. |
| # But the encoder for 'raw_data' accepts any length of it. |
| E = [ 'raw_data', |
| time, substr(trackdata,Pointer,1) ] |
| # DTime and the Data (in this case, the one Event-byte) |
| ++Pointer; # itself |
| |
| ''' |
| elif first_byte > 0xF0: |
| |
| |
| E = ['raw_data', time, trackdata[0]] |
| trackdata = trackdata[1:] |
| else: |
| _warn("Aborting track. Command-byte first_byte="+hex(first_byte)) |
| break |
| |
|
|
|
|
| |
| |
| if E and (E[0] == 'end_track'): |
| |
| eot = True |
| if not no_eot_magic: |
| if E[1] > 0: |
| E = ['text_event', E[1], ''] |
| else: |
| E = [] |
| |
| if E and not (E[0] in exclude): |
| |
| |
| |
| |
| events.append(E) |
| if eot: |
| break |
|
|
| |
|
|
| return events |
|
|
|
|
| |
| def _encode(events_lol, unknown_callback=None, never_add_eot=False, |
| no_eot_magic=False, no_running_status=False, text_encoding='ISO-8859-1'): |
| |
| |
| |
| |
| |
|
|
| |
| |
| |
| |
| |
| |
|
|
| data = [] |
|
|
| |
| events = copy.deepcopy(events_lol) |
|
|
| if not never_add_eot: |
| |
| if events: |
| last = events[-1] |
| if not (last[0] == 'end_track'): |
| if (last[0] == 'text_event' and len(last[2]) == 0): |
| |
| if no_eot_magic: |
| |
| |
| events.append(['end_track', 0]) |
| else: |
| |
| last[0] = 'end_track' |
| else: |
| |
| events.append(['end_track', 0]) |
| else: |
| events = [['end_track', 0],] |
|
|
| |
| last_status = -1 |
|
|
| for event_r in (events): |
| E = copy.deepcopy(event_r) |
| |
| if not E: |
| continue |
|
|
| event = E.pop(0) |
| if not len(event): |
| continue |
|
|
| dtime = int(E.pop(0)) |
| |
|
|
| event_data = '' |
|
|
| if ( |
| event == 'note_on' |
| or event == 'note_off' |
| or event == 'control_change' |
| or event == 'key_after_touch' |
| or event == 'patch_change' |
| or event == 'channel_after_touch' |
| or event == 'pitch_wheel_change' ): |
|
|
| |
| if (event == 'note_off'): |
| status = 0x80 | (int(E[0]) & 0x0F) |
| parameters = struct.pack('>BB', int(E[1])&0x7F, int(E[2])&0x7F) |
| elif (event == 'note_on'): |
| status = 0x90 | (int(E[0]) & 0x0F) |
| parameters = struct.pack('>BB', int(E[1])&0x7F, int(E[2])&0x7F) |
| elif (event == 'key_after_touch'): |
| status = 0xA0 | (int(E[0]) & 0x0F) |
| parameters = struct.pack('>BB', int(E[1])&0x7F, int(E[2])&0x7F) |
| elif (event == 'control_change'): |
| status = 0xB0 | (int(E[0]) & 0x0F) |
| parameters = struct.pack('>BB', int(E[1])&0xFF, int(E[2])&0xFF) |
| elif (event == 'patch_change'): |
| status = 0xC0 | (int(E[0]) & 0x0F) |
| parameters = struct.pack('>B', int(E[1]) & 0xFF) |
| elif (event == 'channel_after_touch'): |
| status = 0xD0 | (int(E[0]) & 0x0F) |
| parameters = struct.pack('>B', int(E[1]) & 0xFF) |
| elif (event == 'pitch_wheel_change'): |
| status = 0xE0 | (int(E[0]) & 0x0F) |
| parameters = _write_14_bit(int(E[1]) + 0x2000) |
| else: |
| _warn("BADASS FREAKOUT ERROR 31415!") |
|
|
| |
| |
| |
| |
| |
|
|
| data.append(_ber_compressed_int(dtime)) |
| if (status != last_status) or no_running_status: |
| data.append(struct.pack('>B', status)) |
| data.append(parameters) |
| |
| last_status = status |
| continue |
| else: |
| |
| |
| |
| |
| last_status = -1 |
|
|
| if event == 'raw_meta_event': |
| event_data = _some_text_event(int(E[0]), E[1], text_encoding) |
| elif (event == 'set_sequence_number'): |
| event_data = b'\xFF\x00\x02'+_int2twobytes(E[0]) |
|
|
| |
| |
| elif (event == 'text_event'): |
| event_data = _some_text_event(0x01, E[0], text_encoding) |
| elif (event == 'copyright_text_event'): |
| event_data = _some_text_event(0x02, E[0], text_encoding) |
| elif (event == 'track_name'): |
| event_data = _some_text_event(0x03, E[0], text_encoding) |
| elif (event == 'instrument_name'): |
| event_data = _some_text_event(0x04, E[0], text_encoding) |
| elif (event == 'lyric'): |
| event_data = _some_text_event(0x05, E[0], text_encoding) |
| elif (event == 'marker'): |
| event_data = _some_text_event(0x06, E[0], text_encoding) |
| elif (event == 'cue_point'): |
| event_data = _some_text_event(0x07, E[0], text_encoding) |
| elif (event == 'text_event_08'): |
| event_data = _some_text_event(0x08, E[0], text_encoding) |
| elif (event == 'text_event_09'): |
| event_data = _some_text_event(0x09, E[0], text_encoding) |
| elif (event == 'text_event_0a'): |
| event_data = _some_text_event(0x0A, E[0], text_encoding) |
| elif (event == 'text_event_0b'): |
| event_data = _some_text_event(0x0B, E[0], text_encoding) |
| elif (event == 'text_event_0c'): |
| event_data = _some_text_event(0x0C, E[0], text_encoding) |
| elif (event == 'text_event_0d'): |
| event_data = _some_text_event(0x0D, E[0], text_encoding) |
| elif (event == 'text_event_0e'): |
| event_data = _some_text_event(0x0E, E[0], text_encoding) |
| elif (event == 'text_event_0f'): |
| event_data = _some_text_event(0x0F, E[0], text_encoding) |
| |
|
|
| elif (event == 'end_track'): |
| event_data = b"\xFF\x2F\x00" |
|
|
| elif (event == 'set_tempo'): |
| |
| |
| event_data = b'\xFF\x51\x03'+struct.pack('>I',E[0])[1:] |
| elif (event == 'smpte_offset'): |
| |
| event_data = struct.pack(">BBBbBBBB", 0xFF,0x54,0x05,E[0],E[1],E[2],E[3],E[4]) |
| elif (event == 'time_signature'): |
| |
| event_data = struct.pack(">BBBbBBB", 0xFF, 0x58, 0x04, E[0],E[1],E[2],E[3]) |
| elif (event == 'key_signature'): |
| event_data = struct.pack(">BBBbB", 0xFF, 0x59, 0x02, E[0],E[1]) |
| elif (event == 'sequencer_specific'): |
| |
| event_data = _some_text_event(0x7F, E[0], text_encoding) |
| |
|
|
| |
| elif (event == 'sysex_f0'): |
| |
| |
| event_data = bytearray(b'\xF0')+_ber_compressed_int(len(E[0]))+bytearray(E[0]) |
| elif (event == 'sysex_f7'): |
| |
| event_data = bytearray(b'\xF7')+_ber_compressed_int(len(E[0]))+bytearray(E[0]) |
|
|
| elif (event == 'song_position'): |
| event_data = b"\xF2" + _write_14_bit( E[0] ) |
| elif (event == 'song_select'): |
| event_data = struct.pack('>BB', 0xF3, E[0] ) |
| elif (event == 'tune_request'): |
| event_data = b"\xF6" |
| elif (event == 'raw_data'): |
| _warn("_encode: raw_data event not supported") |
| |
| continue |
| |
|
|
| else: |
| |
| if unknown_callback: |
| |
| pass |
| else: |
| _warn("Unknown event: "+str(event)) |
| |
| |
| continue |
|
|
| |
| if str(type(event_data)).find("'str'") >= 0: |
| event_data = bytearray(event_data.encode('Latin1', 'ignore')) |
| if len(event_data): |
| |
| |
| data.append(_ber_compressed_int(dtime)+event_data) |
|
|
| return b''.join(data) |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
|
|
| import os |
|
|
| import datetime |
|
|
| import copy |
|
|
| from datetime import datetime |
|
|
| import secrets |
|
|
| import random |
|
|
| import pickle |
|
|
| import csv |
|
|
| import tqdm |
|
|
| from itertools import zip_longest |
| from itertools import groupby |
| from collections import Counter |
|
|
| from operator import itemgetter |
|
|
| import sys |
|
|
| from abc import ABC, abstractmethod |
|
|
| from difflib import SequenceMatcher as SM |
|
|
| import statistics |
| import math |
|
|
| import matplotlib.pyplot as plt |
|
|
| |
| |
| |
| |
| |
|
|
| def Tegridy_TXT_to_INT_Converter(input_TXT_string, line_by_line_INT_string=True, max_INT = 0): |
|
|
| '''Tegridy TXT to Intergers Converter |
| |
| Input: Input TXT string in the TMIDI-TXT format |
| |
| Type of output TXT INT string: line-by-line or one long string |
| |
| Maximum absolute integer to process. Maximum is inclusive |
| Default = process all integers. This helps to remove outliers/unwanted ints |
| |
| Output: List of pure intergers |
| String of intergers in the specified format: line-by-line or one long string |
| Number of processed integers |
| Number of skipped integers |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| print('Tegridy TXT to Intergers Converter') |
|
|
| output_INT_list = [] |
|
|
| npi = 0 |
| nsi = 0 |
|
|
| TXT_List = list(input_TXT_string) |
| for char in TXT_List: |
| if max_INT != 0: |
| if abs(ord(char)) <= max_INT: |
| output_INT_list.append(ord(char)) |
| npi += 1 |
| else: |
| nsi += 1 |
| else: |
| output_INT_list.append(ord(char)) |
| npi += 1 |
| |
| if line_by_line_INT_string: |
| output_INT_string = '\n'.join([str(elem) for elem in output_INT_list]) |
| else: |
| output_INT_string = ' '.join([str(elem) for elem in output_INT_list]) |
|
|
| print('Converted TXT to INTs:', npi, ' / ', nsi) |
|
|
| return output_INT_list, output_INT_string, npi, nsi |
|
|
| |
|
|
| def Tegridy_INT_to_TXT_Converter(input_INT_list): |
|
|
| '''Tegridy Intergers to TXT Converter |
| |
| Input: List of intergers in TMIDI-TXT-INT format |
| Output: Decoded TXT string in TMIDI-TXT format |
| Project Los Angeles |
| Tegridy Code 2020''' |
|
|
| output_TXT_string = '' |
|
|
| for i in input_INT_list: |
| output_TXT_string += chr(int(i)) |
| |
| return output_TXT_string |
|
|
| |
|
|
| def Tegridy_INT_String_to_TXT_Converter(input_INT_String, line_by_line_input=True): |
|
|
| '''Tegridy Intergers String to TXT Converter |
| |
| Input: List of intergers in TMIDI-TXT-INT-String format |
| Output: Decoded TXT string in TMIDI-TXT format |
| Project Los Angeles |
| Tegridy Code 2020''' |
| |
| print('Tegridy Intergers String to TXT Converter') |
|
|
| if line_by_line_input: |
| input_string = input_INT_String.split('\n') |
| else: |
| input_string = input_INT_String.split(' ') |
|
|
| output_TXT_string = '' |
|
|
| for i in input_string: |
| try: |
| output_TXT_string += chr(abs(int(i))) |
| except: |
| print('Bad note:', i) |
| continue |
| |
| print('Done!') |
|
|
| return output_TXT_string |
|
|
| |
|
|
| def Tegridy_SONG_to_MIDI_Converter(SONG, |
| output_signature = 'Tegridy TMIDI Module', |
| track_name = 'Composition Track', |
| number_of_ticks_per_quarter = 425, |
| list_of_MIDI_patches = [0, 24, 32, 40, 42, 46, 56, 71, 73, 0, 0, 0, 0, 0, 0, 0], |
| output_file_name = 'TMIDI-Composition', |
| text_encoding='ISO-8859-1', |
| verbose=True): |
|
|
| '''Tegridy SONG to MIDI Converter |
| |
| Input: Input SONG in TMIDI SONG/MIDI.py Score format |
| Output MIDI Track 0 name / MIDI Signature |
| Output MIDI Track 1 name / Composition track name |
| Number of ticks per quarter for the output MIDI |
| List of 16 MIDI patch numbers for output MIDI. Def. is MuseNet compatible patches. |
| Output file name w/o .mid extension. |
| Optional text encoding if you are working with text_events/lyrics. This is especially useful for Karaoke. Please note that anything but ISO-8859-1 is a non-standard way of encoding text_events according to MIDI specs. |
| |
| Output: MIDI File |
| Detailed MIDI stats |
| |
| Project Los Angeles |
| Tegridy Code 2020''' |
| |
| if verbose: |
| print('Converting to MIDI. Please stand-by...') |
| |
| output_header = [number_of_ticks_per_quarter, |
| [['track_name', 0, bytes(output_signature, text_encoding)]]] |
|
|
| patch_list = [['patch_change', 0, 0, list_of_MIDI_patches[0]], |
| ['patch_change', 0, 1, list_of_MIDI_patches[1]], |
| ['patch_change', 0, 2, list_of_MIDI_patches[2]], |
| ['patch_change', 0, 3, list_of_MIDI_patches[3]], |
| ['patch_change', 0, 4, list_of_MIDI_patches[4]], |
| ['patch_change', 0, 5, list_of_MIDI_patches[5]], |
| ['patch_change', 0, 6, list_of_MIDI_patches[6]], |
| ['patch_change', 0, 7, list_of_MIDI_patches[7]], |
| ['patch_change', 0, 8, list_of_MIDI_patches[8]], |
| ['patch_change', 0, 9, list_of_MIDI_patches[9]], |
| ['patch_change', 0, 10, list_of_MIDI_patches[10]], |
| ['patch_change', 0, 11, list_of_MIDI_patches[11]], |
| ['patch_change', 0, 12, list_of_MIDI_patches[12]], |
| ['patch_change', 0, 13, list_of_MIDI_patches[13]], |
| ['patch_change', 0, 14, list_of_MIDI_patches[14]], |
| ['patch_change', 0, 15, list_of_MIDI_patches[15]], |
| ['track_name', 0, bytes(track_name, text_encoding)]] |
|
|
| output = output_header + [patch_list + SONG] |
|
|
| midi_data = score2midi(output, text_encoding) |
| detailed_MIDI_stats = score2stats(output) |
|
|
| with open(output_file_name + '.mid', 'wb') as midi_file: |
| midi_file.write(midi_data) |
| midi_file.close() |
| |
| if verbose: |
| print('Done! Enjoy! :)') |
| |
| return detailed_MIDI_stats |
|
|
| |
|
|
| def Tegridy_ms_SONG_to_MIDI_Converter(ms_SONG, |
| output_signature = 'Tegridy TMIDI Module', |
| track_name = 'Composition Track', |
| list_of_MIDI_patches = [0, 24, 32, 40, 42, 46, 56, 71, 73, 0, 0, 0, 0, 0, 0, 0], |
| output_file_name = 'TMIDI-Composition', |
| text_encoding='ISO-8859-1', |
| timings_multiplier=1, |
| verbose=True |
| ): |
|
|
| '''Tegridy milisecond SONG to MIDI Converter |
| |
| Input: Input ms SONG in TMIDI ms SONG/MIDI.py ms Score format |
| Output MIDI Track 0 name / MIDI Signature |
| Output MIDI Track 1 name / Composition track name |
| List of 16 MIDI patch numbers for output MIDI. Def. is MuseNet compatible patches. |
| Output file name w/o .mid extension. |
| Optional text encoding if you are working with text_events/lyrics. This is especially useful for Karaoke. Please note that anything but ISO-8859-1 is a non-standard way of encoding text_events according to MIDI specs. |
| Optional timings multiplier |
| Optional verbose output |
| |
| Output: MIDI File |
| Detailed MIDI stats |
| |
| Project Los Angeles |
| Tegridy Code 2024''' |
| |
| if verbose: |
| print('Converting to MIDI. Please stand-by...') |
|
|
| output_header = [1000, |
| [['set_tempo', 0, 1000000], |
| ['time_signature', 0, 4, 2, 24, 8], |
| ['track_name', 0, bytes(output_signature, text_encoding)]]] |
|
|
| patch_list = [['patch_change', 0, 0, list_of_MIDI_patches[0]], |
| ['patch_change', 0, 1, list_of_MIDI_patches[1]], |
| ['patch_change', 0, 2, list_of_MIDI_patches[2]], |
| ['patch_change', 0, 3, list_of_MIDI_patches[3]], |
| ['patch_change', 0, 4, list_of_MIDI_patches[4]], |
| ['patch_change', 0, 5, list_of_MIDI_patches[5]], |
| ['patch_change', 0, 6, list_of_MIDI_patches[6]], |
| ['patch_change', 0, 7, list_of_MIDI_patches[7]], |
| ['patch_change', 0, 8, list_of_MIDI_patches[8]], |
| ['patch_change', 0, 9, list_of_MIDI_patches[9]], |
| ['patch_change', 0, 10, list_of_MIDI_patches[10]], |
| ['patch_change', 0, 11, list_of_MIDI_patches[11]], |
| ['patch_change', 0, 12, list_of_MIDI_patches[12]], |
| ['patch_change', 0, 13, list_of_MIDI_patches[13]], |
| ['patch_change', 0, 14, list_of_MIDI_patches[14]], |
| ['patch_change', 0, 15, list_of_MIDI_patches[15]], |
| ['track_name', 0, bytes(track_name, text_encoding)]] |
|
|
| SONG = copy.deepcopy(ms_SONG) |
|
|
| if timings_multiplier != 1: |
| for S in SONG: |
| S[1] = S[1] * timings_multiplier |
| if S[0] == 'note': |
| S[2] = S[2] * timings_multiplier |
|
|
| output = output_header + [patch_list + SONG] |
|
|
| midi_data = score2midi(output, text_encoding) |
| detailed_MIDI_stats = score2stats(output) |
|
|
| with open(output_file_name + '.mid', 'wb') as midi_file: |
| midi_file.write(midi_data) |
| midi_file.close() |
| |
| if verbose: |
| print('Done! Enjoy! :)') |
| |
| return detailed_MIDI_stats |
|
|
| |
|
|
| def hsv_to_rgb(h, s, v): |
| if s == 0.0: |
| return v, v, v |
| i = int(h*6.0) |
| f = (h*6.0) - i |
| p = v*(1.0 - s) |
| q = v*(1.0 - s*f) |
| t = v*(1.0 - s*(1.0-f)) |
| i = i%6 |
| return [(v, t, p), (q, v, p), (p, v, t), (p, q, v), (t, p, v), (v, p, q)][i] |
|
|
| def generate_colors(n): |
| return [hsv_to_rgb(i/n, 1, 1) for i in range(n)] |
|
|
| def add_arrays(a, b): |
| return [sum(pair) for pair in zip(a, b)] |
|
|
| |
|
|
| def plot_ms_SONG(ms_song, |
| preview_length_in_notes=0, |
| block_lines_times_list = None, |
| plot_title='ms Song', |
| max_num_colors=129, |
| drums_color_num=128, |
| plot_size=(11,4), |
| note_height = 0.75, |
| show_grid_lines=False, |
| return_plt = False, |
| timings_multiplier=1, |
| save_plt='', |
| save_only_plt_image=True, |
| save_transparent=False |
| ): |
|
|
| '''Tegridy ms SONG plotter/vizualizer''' |
|
|
| notes = [s for s in ms_song if s[0] == 'note'] |
|
|
| if (len(max(notes, key=len)) != 7) and (len(min(notes, key=len)) != 7): |
| print('The song notes do not have patches information') |
| print('Ploease add patches to the notes in the song') |
|
|
| else: |
|
|
| start_times = [(s[1] * timings_multiplier) / 1000 for s in notes] |
| durations = [(s[2] * timings_multiplier) / 1000 for s in notes] |
| pitches = [s[4] for s in notes] |
| patches = [s[6] for s in notes] |
|
|
| colors = generate_colors(max_num_colors) |
| colors[drums_color_num] = (1, 1, 1) |
|
|
| pbl = (notes[preview_length_in_notes][1] * timings_multiplier) / 1000 |
|
|
| fig, ax = plt.subplots(figsize=plot_size) |
| |
|
|
| |
| for start, duration, pitch, patch in zip(start_times, durations, pitches, patches): |
| rect = plt.Rectangle((start, pitch), duration, note_height, facecolor=colors[patch]) |
| ax.add_patch(rect) |
|
|
| |
| ax.set_xlim([min(start_times), max(add_arrays(start_times, durations))]) |
| ax.set_ylim([min(pitches)-1, max(pitches)+1]) |
|
|
| |
| ax.set_facecolor('black') |
| fig.patch.set_facecolor('white') |
|
|
| if preview_length_in_notes > 0: |
| ax.axvline(x=pbl, c='white') |
|
|
| if block_lines_times_list: |
| for bl in block_lines_times_list: |
| ax.axvline(x=bl, c='white') |
| |
| if show_grid_lines: |
| ax.grid(color='white') |
|
|
| plt.xlabel('Time (s)', c='black') |
| plt.ylabel('MIDI Pitch', c='black') |
|
|
| plt.title(plot_title) |
|
|
| if save_plt != '': |
| if save_only_plt_image: |
| plt.axis('off') |
| plt.title('') |
| plt.savefig(save_plt, transparent=save_transparent, bbox_inches='tight', pad_inches=0, facecolor='black') |
| plt.close() |
| |
| else: |
| plt.savefig(save_plt) |
| plt.close() |
|
|
| if return_plt: |
| return fig |
|
|
| plt.show() |
| plt.close() |
|
|
| |
|
|
| def Tegridy_SONG_to_Full_MIDI_Converter(SONG, |
| output_signature = 'Tegridy TMIDI Module', |
| track_name = 'Composition Track', |
| number_of_ticks_per_quarter = 1000, |
| output_file_name = 'TMIDI-Composition', |
| text_encoding='ISO-8859-1', |
| verbose=True): |
|
|
| '''Tegridy SONG to Full MIDI Converter |
| |
| Input: Input SONG in Full TMIDI SONG/MIDI.py Score format |
| Output MIDI Track 0 name / MIDI Signature |
| Output MIDI Track 1 name / Composition track name |
| Number of ticks per quarter for the output MIDI |
| Output file name w/o .mid extension. |
| Optional text encoding if you are working with text_events/lyrics. This is especially useful for Karaoke. Please note that anything but ISO-8859-1 is a non-standard way of encoding text_events according to MIDI specs. |
| |
| Output: MIDI File |
| Detailed MIDI stats |
| |
| Project Los Angeles |
| Tegridy Code 2023''' |
| |
| if verbose: |
| print('Converting to MIDI. Please stand-by...') |
| |
| output_header = [number_of_ticks_per_quarter, |
| [['set_tempo', 0, 1000000], |
| ['track_name', 0, bytes(output_signature, text_encoding)]]] |
|
|
| song_track = [['track_name', 0, bytes(track_name, text_encoding)]] |
|
|
| output = output_header + [song_track + SONG] |
|
|
| midi_data = score2midi(output, text_encoding) |
| detailed_MIDI_stats = score2stats(output) |
|
|
| with open(output_file_name + '.mid', 'wb') as midi_file: |
| midi_file.write(midi_data) |
| midi_file.close() |
| |
| if verbose: |
| print('Done! Enjoy! :)') |
| |
| return detailed_MIDI_stats |
|
|
| |
|
|
| def Tegridy_File_Time_Stamp(input_file_name='File_Created_on_', ext = ''): |
|
|
| '''Tegridy File Time Stamp |
| |
| Input: Full path and file name without extention |
| File extension |
| |
| Output: File name string with time-stamp and extension (time-stamped file name) |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| print('Time-stamping output file...') |
|
|
| now = '' |
| now_n = str(datetime.now()) |
| now_n = now_n.replace(' ', '_') |
| now_n = now_n.replace(':', '_') |
| now = now_n.replace('.', '_') |
| |
| fname = input_file_name + str(now) + ext |
|
|
| return(fname) |
|
|
| |
|
|
| def Tegridy_Any_Pickle_File_Writer(Data, input_file_name='TMIDI_Pickle_File'): |
|
|
| '''Tegridy Pickle File Writer |
| |
| Input: Data to write (I.e. a list) |
| Full path and file name without extention |
| |
| Output: Named Pickle file |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| print('Tegridy Pickle File Writer') |
|
|
| full_path_to_output_dataset_to = input_file_name + '.pickle' |
|
|
| if os.path.exists(full_path_to_output_dataset_to): |
| os.remove(full_path_to_output_dataset_to) |
| print('Removing old Dataset...') |
| else: |
| print("Creating new Dataset file...") |
|
|
| with open(full_path_to_output_dataset_to, 'wb') as filehandle: |
| |
| pickle.dump(Data, filehandle, protocol=pickle.HIGHEST_PROTOCOL) |
|
|
| print('Dataset was saved as:', full_path_to_output_dataset_to) |
| print('Task complete. Enjoy! :)') |
|
|
| |
|
|
| def Tegridy_Any_Pickle_File_Reader(input_file_name='TMIDI_Pickle_File', ext='.pickle', verbose=True): |
|
|
| '''Tegridy Pickle File Loader |
| |
| Input: Full path and file name with or without extention |
| File extension if different from default .pickle |
| |
| Output: Standard Python 3 unpickled data object |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| if verbose: |
| print('Tegridy Pickle File Loader') |
| print('Loading the pickle file. Please wait...') |
|
|
| if os.path.basename(input_file_name).endswith(ext): |
| fname = input_file_name |
| |
| else: |
| fname = input_file_name + ext |
|
|
| with open(fname, 'rb') as pickle_file: |
| content = pickle.load(pickle_file) |
|
|
| if verbose: |
| print('Done!') |
|
|
| return content |
|
|
| |
|
|
| |
|
|
| |
|
|
| def Optimus_MIDI_TXT_Processor(MIDI_file, |
| line_by_line_output=True, |
| chordify_TXT=False, |
| dataset_MIDI_events_time_denominator=1, |
| output_velocity=True, |
| output_MIDI_channels = False, |
| MIDI_channel=0, |
| MIDI_patch=[0, 1], |
| char_offset = 30000, |
| transpose_by = 0, |
| flip=False, |
| melody_conditioned_encoding=False, |
| melody_pitch_baseline = 0, |
| number_of_notes_to_sample = -1, |
| sampling_offset_from_start = 0, |
| karaoke=False, |
| karaoke_language_encoding='utf-8', |
| song_name='Song', |
| perfect_timings=False, |
| musenet_encoding=False, |
| transform=0, |
| zero_token=False, |
| reset_timings=False): |
|
|
| '''Project Los Angeles |
| Tegridy Code 2021''' |
| |
| |
|
|
| debug = False |
|
|
| ev = 0 |
|
|
| chords_list_final = [] |
| chords_list = [] |
| events_matrix = [] |
| melody = [] |
| melody1 = [] |
|
|
| itrack = 1 |
|
|
| min_note = 0 |
| max_note = 0 |
| ev = 0 |
| patch = 0 |
|
|
| score = [] |
| rec_event = [] |
|
|
| txt = '' |
| txtc = '' |
| chords = [] |
| melody_chords = [] |
|
|
| karaoke_events_matrix = [] |
| karaokez = [] |
|
|
| sample = 0 |
| start_sample = 0 |
|
|
| bass_melody = [] |
|
|
| INTS = [] |
| bints = 0 |
|
|
| |
|
|
| def list_average(num): |
| sum_num = 0 |
| for t in num: |
| sum_num = sum_num + t |
|
|
| avg = sum_num / len(num) |
| return avg |
|
|
| |
|
|
| |
| midi_file = open(MIDI_file, 'rb') |
| if debug: print('Processing File:', file_address) |
| |
| try: |
| opus = midi2opus(midi_file.read()) |
| |
| except: |
| print('Problematic MIDI. Skipping...') |
| print('File name:', MIDI_file) |
| midi_file.close() |
| return txt, melody, chords |
| |
| midi_file.close() |
|
|
| score1 = to_millisecs(opus) |
| score2 = opus2score(score1) |
|
|
| |
| |
| if MIDI_channel == 16: |
| score = score2 |
| |
| if MIDI_channel >= 0 and MIDI_channel <= 15: |
| score = grep(score2, [MIDI_channel]) |
| |
| if MIDI_channel == -1: |
| score = grep(score2, [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15]) |
| |
| |
| while itrack < len(score): |
| for event in score[itrack]: |
| |
| if perfect_timings: |
| if event[0] == 'note': |
| event[1] = round(event[1], -1) |
| event[2] = round(event[2], -1) |
|
|
| if event[0] == 'text_event' or event[0] == 'lyric' or event[0] == 'note': |
| if perfect_timings: |
| event[1] = round(event[1], -1) |
| karaokez.append(event) |
| |
| if event[0] == 'text_event' or event[0] == 'lyric': |
| if perfect_timings: |
| event[1] = round(event[1], -1) |
| try: |
| event[2] = str(event[2].decode(karaoke_language_encoding, 'replace')).replace('/', '').replace(' ', '').replace('\\', '') |
| except: |
| event[2] = str(event[2]).replace('/', '').replace(' ', '').replace('\\', '') |
| continue |
| karaoke_events_matrix.append(event) |
|
|
| if event[0] == 'patch_change': |
| patch = event[3] |
|
|
| if event[0] == 'note' and patch in MIDI_patch: |
| if len(event) == 6: |
| eve = copy.deepcopy(event) |
| |
| eve[1] = int(event[1] / dataset_MIDI_events_time_denominator) |
| eve[2] = int(event[2] / dataset_MIDI_events_time_denominator) |
| |
| eve[4] = int(event[4] + transpose_by) |
| |
| if flip == True: |
| eve[4] = int(127 - (event[4] + transpose_by)) |
| |
| if number_of_notes_to_sample > -1: |
| if sample <= number_of_notes_to_sample: |
| if start_sample >= sampling_offset_from_start: |
| events_matrix.append(eve) |
| sample += 1 |
| ev += 1 |
| else: |
| start_sample += 1 |
|
|
| else: |
| events_matrix.append(eve) |
| ev += 1 |
| start_sample += 1 |
| |
| itrack +=1 |
|
|
| |
|
|
| fn = os.path.basename(MIDI_file) |
| song_name = song_name.replace(' ', '_').replace('=', '_').replace('\'', '-') |
| if song_name == 'Song': |
| sng_name = fn.split('.')[0].replace(' ', '_').replace('=', '_').replace('\'', '-') |
| song_name = sng_name |
|
|
| |
| if zero_token: |
| txt += chr(char_offset) + chr(char_offset) |
| if output_MIDI_channels: |
| txt += chr(char_offset) |
| if output_velocity: |
| txt += chr(char_offset) + chr(char_offset) |
| else: |
| txt += chr(char_offset) |
|
|
| txtc += chr(char_offset) + chr(char_offset) |
| if output_MIDI_channels: |
| txtc += chr(char_offset) |
| if output_velocity: |
| txtc += chr(char_offset) + chr(char_offset) |
| else: |
| txtc += chr(char_offset) |
| |
| txt += '=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes' |
| txtc += '=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes' |
| |
| else: |
| |
| txt += 'SONG=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes' |
| txtc += 'SONG=' + song_name + '_with_' + str(len(events_matrix)-1) + '_notes' |
|
|
| if line_by_line_output: |
| txt += chr(10) |
| txtc += chr(10) |
| else: |
| txt += chr(32) |
| txtc += chr(32) |
|
|
| |
| events_matrix.sort(key=lambda x: x[1]) |
| |
| |
| if reset_timings: |
| ev_matrix = Tegridy_Timings_Converter(events_matrix)[0] |
| else: |
| ev_matrix = events_matrix |
| |
| chords.extend(ev_matrix) |
| |
|
|
| |
| melody_list = [] |
|
|
| |
| values = set(map(lambda x:x[1], ev_matrix)) |
|
|
| groups = [[y for y in ev_matrix if y[1]==x and len(y) == 6] for x in values] |
| |
| |
| for items in groups: |
| |
| items.sort(reverse=True, key=lambda x: x[4]) |
| |
| if melody_conditioned_encoding: items[0][3] = 0 |
| |
| melody_list.append(items[0]) |
| melody_chords.append(items) |
| bass_melody.append(items[-1]) |
| |
| |
| if melody_conditioned_encoding == True: |
| if not karaoke: |
| |
| previous_event = copy.deepcopy(melody_chords[0][0]) |
|
|
| for ev in melody_chords: |
| hp = True |
| ev.sort(reverse=False, key=lambda x: x[4]) |
| for event in ev: |
| |
| |
| start_time = int(abs(event[1] - previous_event[1])) |
| |
| duration = int(previous_event[2]) |
|
|
| if hp == True: |
| if int(previous_event[4]) >= melody_pitch_baseline: |
| channel = int(0) |
| hp = False |
| else: |
| channel = int(previous_event[3]+1) |
| hp = False |
| else: |
| channel = int(previous_event[3]+1) |
| hp = False |
|
|
| pitch = int(previous_event[4]) |
|
|
| velocity = int(previous_event[5]) |
|
|
| |
| try: |
| INTS.append([(start_time)+char_offset, (duration)+char_offset, channel+char_offset, pitch+char_offset, velocity+char_offset]) |
| except: |
| bints += 1 |
|
|
| |
| try: |
| txtc += str(chr(start_time + char_offset)) |
| txtc += str(chr(duration + char_offset)) |
| txtc += str(chr(pitch + char_offset)) |
| if output_velocity: |
| txtc += str(chr(velocity + char_offset)) |
| if output_MIDI_channels: |
| txtc += str(chr(channel + char_offset)) |
|
|
| if line_by_line_output: |
| |
|
|
| txtc += chr(10) |
| else: |
|
|
| txtc += chr(32) |
|
|
| previous_event = copy.deepcopy(event) |
| |
| except: |
| |
| continue |
|
|
| if not line_by_line_output: |
| txtc += chr(10) |
|
|
| txt = txtc |
| chords = melody_chords |
| |
| |
| else: |
| if not karaoke: |
| melody_chords.sort(reverse=False, key=lambda x: x[0][1]) |
| mel_chords = [] |
| for mc in melody_chords: |
| mel_chords.extend(mc) |
|
|
| if transform != 0: |
| chords = Tegridy_Transform(mel_chords, transform) |
| else: |
| chords = mel_chords |
|
|
| |
| previous_event = copy.deepcopy(chords[0]) |
| for event in chords: |
|
|
| |
| start_time = int(abs(event[1] - previous_event[1])) |
| |
| duration = int(previous_event[2]) |
|
|
| channel = int(previous_event[3]) |
|
|
| pitch = int(previous_event[4] + transpose_by) |
| if flip == True: |
| pitch = 127 - int(previous_event[4] + transpose_by) |
|
|
| velocity = int(previous_event[5]) |
|
|
| |
| try: |
| INTS.append([(start_time)+char_offset, (duration)+char_offset, channel+char_offset, pitch+char_offset, velocity+char_offset]) |
| except: |
| bints += 1 |
|
|
| |
| try: |
| txt += str(chr(start_time + char_offset)) |
| txt += str(chr(duration + char_offset)) |
| txt += str(chr(pitch + char_offset)) |
| if output_velocity: |
| txt += str(chr(velocity + char_offset)) |
| if output_MIDI_channels: |
| txt += str(chr(channel + char_offset)) |
|
|
|
|
| if chordify_TXT == True and int(event[1] - previous_event[1]) == 0: |
| txt += '' |
| else: |
| if line_by_line_output: |
| txt += chr(10) |
| else: |
| txt += chr(32) |
| |
| previous_event = copy.deepcopy(event) |
| |
| except: |
| |
| continue |
|
|
| if not line_by_line_output: |
| txt += chr(10) |
|
|
| |
| if karaoke: |
|
|
| melody_chords.sort(reverse=False, key=lambda x: x[0][1]) |
| mel_chords = [] |
| for mc in melody_chords: |
| mel_chords.extend(mc) |
|
|
| if transform != 0: |
| chords = Tegridy_Transform(mel_chords, transform) |
| else: |
| chords = mel_chords |
|
|
| previous_event = copy.deepcopy(chords[0]) |
| for event in chords: |
|
|
| |
| start_time = int(abs(event[1] - previous_event[1])) |
| |
| duration = int(previous_event[2]) |
|
|
| channel = int(previous_event[3]) |
|
|
| pitch = int(previous_event[4] + transpose_by) |
|
|
| velocity = int(previous_event[5]) |
|
|
| |
| txt += str(chr(start_time + char_offset)) |
| txt += str(chr(duration + char_offset)) |
| txt += str(chr(pitch + char_offset)) |
|
|
| txt += str(chr(velocity + char_offset)) |
| txt += str(chr(channel + char_offset)) |
|
|
| if start_time > 0: |
| for k in karaoke_events_matrix: |
| if event[1] == k[1]: |
| txt += str('=') |
| txt += str(k[2]) |
| break |
|
|
| if line_by_line_output: |
| txt += chr(10) |
| else: |
| txt += chr(32) |
| |
| previous_event = copy.deepcopy(event) |
| |
| if not line_by_line_output: |
| txt += chr(10) |
|
|
| |
| |
|
|
| |
| karaokez.sort(reverse=False, key=lambda x: x[1]) |
|
|
| |
| if musenet_encoding and not melody_conditioned_encoding and not karaoke: |
| chords.sort(key=lambda x: (x[1], x[3])) |
| |
| |
| melody_list.sort() |
|
|
| |
| aux1 = [None] |
| aux2 = [None] |
|
|
| return txt, melody_list, chords, bass_melody, karaokez, INTS, aux1, aux2 |
|
|
| |
|
|
| def Optimus_TXT_to_Notes_Converter(Optimus_TXT_String, |
| line_by_line_dataset = True, |
| has_velocities = True, |
| has_MIDI_channels = True, |
| dataset_MIDI_events_time_denominator = 1, |
| char_encoding_offset = 30000, |
| save_only_first_composition = True, |
| simulate_velocity=True, |
| karaoke=False, |
| zero_token=False): |
|
|
| '''Project Los Angeles |
| Tegridy Code 2020''' |
|
|
| print('Tegridy Optimus TXT to Notes Converter') |
| print('Converting TXT to Notes list...Please wait...') |
|
|
| song_name = '' |
|
|
| if line_by_line_dataset: |
| input_string = Optimus_TXT_String.split('\n') |
| else: |
| input_string = Optimus_TXT_String.split(' ') |
|
|
| if line_by_line_dataset: |
| name_string = Optimus_TXT_String.split('\n')[0].split('=') |
| else: |
| name_string = Optimus_TXT_String.split(' ')[0].split('=') |
|
|
| |
| zt = '' |
|
|
| zt += chr(char_encoding_offset) + chr(char_encoding_offset) |
| |
| if has_MIDI_channels: |
| zt += chr(char_encoding_offset) |
| |
| if has_velocities: |
| zt += chr(char_encoding_offset) + chr(char_encoding_offset) |
| |
| else: |
| zt += chr(char_encoding_offset) |
|
|
| if zero_token: |
| if name_string[0] == zt: |
| song_name = name_string[1] |
| |
| else: |
| if name_string[0] == 'SONG': |
| song_name = name_string[1] |
|
|
| output_list = [] |
| st = 0 |
|
|
| for i in range(2, len(input_string)-1): |
|
|
| if save_only_first_composition: |
| if zero_token: |
| if input_string[i].split('=')[0] == zt: |
|
|
| song_name = name_string[1] |
| break |
| |
| else: |
| if input_string[i].split('=')[0] == 'SONG': |
|
|
| song_name = name_string[1] |
| break |
| try: |
| istring = input_string[i] |
|
|
| if has_MIDI_channels == False: |
| step = 4 |
|
|
| if has_MIDI_channels == True: |
| step = 5 |
|
|
| if has_velocities == False: |
| step -= 1 |
|
|
| st += int(ord(istring[0]) - char_encoding_offset) * dataset_MIDI_events_time_denominator |
|
|
| if not karaoke: |
| for s in range(0, len(istring), step): |
| if has_MIDI_channels==True: |
| if step > 3 and len(istring) > 2: |
| out = [] |
| out.append('note') |
|
|
| out.append(st) |
|
|
| out.append(int(ord(istring[s+1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) |
|
|
| if has_velocities: |
| out.append(int(ord(istring[s+4]) - char_encoding_offset)) |
| else: |
| out.append(int(ord(istring[s+3]) - char_encoding_offset)) |
|
|
| out.append(int(ord(istring[s+2]) - char_encoding_offset)) |
|
|
| if simulate_velocity: |
| if s == 0: |
| sim_vel = int(ord(istring[s+2]) - char_encoding_offset) |
| out.append(sim_vel) |
| else: |
| out.append(int(ord(istring[s+3]) - char_encoding_offset)) |
|
|
| if has_MIDI_channels==False: |
| if step > 3 and len(istring) > 2: |
| out = [] |
| out.append('note') |
|
|
| out.append(st) |
| out.append(int(ord(istring[s+1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) |
| out.append(0) |
| out.append(int(ord(istring[s+2]) - char_encoding_offset)) |
|
|
| if simulate_velocity: |
| if s == 0: |
| sim_vel = int(ord(istring[s+2]) - char_encoding_offset) |
| out.append(sim_vel) |
| else: |
| out.append(int(ord(istring[s+3]) - char_encoding_offset)) |
|
|
| if step == 3 and len(istring) > 2: |
| out = [] |
| out.append('note') |
|
|
| out.append(st) |
| out.append(int(ord(istring[s+1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) |
| out.append(0) |
| out.append(int(ord(istring[s+2]) - char_encoding_offset)) |
|
|
| out.append(int(ord(istring[s+2]) - char_encoding_offset)) |
|
|
| output_list.append(out) |
|
|
| if karaoke: |
| try: |
| out = [] |
| out.append('note') |
|
|
| out.append(st) |
| out.append(int(ord(istring[1]) - char_encoding_offset) * dataset_MIDI_events_time_denominator) |
| out.append(int(ord(istring[4]) - char_encoding_offset)) |
| out.append(int(ord(istring[2]) - char_encoding_offset)) |
|
|
| if simulate_velocity: |
| if s == 0: |
| sim_vel = int(ord(istring[2]) - char_encoding_offset) |
| out.append(sim_vel) |
| else: |
| out.append(int(ord(istring[3]) - char_encoding_offset)) |
| output_list.append(out) |
| out = [] |
| if istring.split('=')[1] != '': |
| out.append('lyric') |
| out.append(st) |
| out.append(istring.split('=')[1]) |
| output_list.append(out) |
| except: |
| continue |
|
|
|
|
| except: |
| print('Bad note string:', istring) |
| continue |
|
|
| |
| S = [] |
| for x in output_list: |
| if len(x) == 6 or len(x) == 3: |
| S.append(x) |
|
|
| output_list.clear() |
| output_list = copy.deepcopy(S) |
|
|
|
|
| print('Task complete! Enjoy! :)') |
|
|
| return output_list, song_name |
|
|
| |
|
|
| def Optimus_Data2TXT_Converter(data, |
| dataset_time_denominator=1, |
| transpose_by = 0, |
| char_offset = 33, |
| line_by_line_output = True, |
| output_velocity = False, |
| output_MIDI_channels = False): |
|
|
|
|
| '''Input: data as a flat chords list of flat chords lists |
| |
| Output: TXT string |
| INTs |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| txt = '' |
| TXT = '' |
|
|
| quit = False |
| counter = 0 |
|
|
| INTs = [] |
| INTs_f = [] |
|
|
| for d in tqdm.tqdm(sorted(data)): |
|
|
| if quit == True: |
| break |
|
|
| txt = 'SONG=' + str(counter) |
| counter += 1 |
|
|
| if line_by_line_output: |
| txt += chr(10) |
| else: |
| txt += chr(32) |
| |
| INTs = [] |
|
|
| |
| previous_event = copy.deepcopy(d[0]) |
| for event in sorted(d): |
|
|
| |
| start_time = int(abs(event[1] - previous_event[1]) / dataset_time_denominator) |
| |
| duration = int(previous_event[2] / dataset_time_denominator) |
|
|
| channel = int(previous_event[3]) |
|
|
| pitch = int(previous_event[4] + transpose_by) |
|
|
| velocity = int(previous_event[5]) |
|
|
| INTs.append([start_time, duration, pitch]) |
|
|
| |
| try: |
| txt += str(chr(start_time + char_offset)) |
| txt += str(chr(duration + char_offset)) |
| txt += str(chr(pitch + char_offset)) |
| if output_velocity: |
| txt += str(chr(velocity + char_offset)) |
| if output_MIDI_channels: |
| txt += str(chr(channel + char_offset)) |
| |
| if line_by_line_output: |
| txt += chr(10) |
| else: |
| txt += chr(32) |
| |
| previous_event = copy.deepcopy(event) |
| except KeyboardInterrupt: |
| quit = True |
| break |
| except: |
| print('Problematic MIDI data. Skipping...') |
| continue |
|
|
| if not line_by_line_output: |
| txt += chr(10) |
| |
| TXT += txt |
| INTs_f.extend(INTs) |
|
|
| return TXT, INTs_f |
|
|
| |
|
|
| def Optimus_Squash(chords_list, simulate_velocity=True, mono_compression=False): |
|
|
| '''Input: Flat chords list |
| Simulate velocity or not |
| Mono-compression enabled or disabled |
| |
| Default is almost lossless 25% compression, otherwise, lossy 50% compression (mono-compression) |
| |
| Output: Squashed chords list |
| Resulting compression level |
| |
| Please note that if drums are passed through as is |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| output = [] |
| ptime = 0 |
| vel = 0 |
| boost = 15 |
| stptc = [] |
| ocount = 0 |
| rcount = 0 |
|
|
| for c in chords_list: |
| |
| cc = copy.deepcopy(c) |
| ocount += 1 |
| |
| if [cc[1], cc[3], (cc[4] % 12) + 60] not in stptc: |
| stptc.append([cc[1], cc[3], (cc[4] % 12) + 60]) |
|
|
| if cc[3] != 9: |
| cc[4] = (c[4] % 12) + 60 |
|
|
| if simulate_velocity and c[1] != ptime: |
| vel = c[4] + boost |
| |
| if cc[3] != 9: |
| cc[5] = vel |
|
|
| if mono_compression: |
| if c[1] != ptime: |
| output.append(cc) |
| rcount += 1 |
| else: |
| output.append(cc) |
| rcount += 1 |
| |
| ptime = c[1] |
|
|
| output.sort(key=lambda x: (x[1], x[4])) |
|
|
| comp_level = 100 - int((rcount * 100) / ocount) |
|
|
| return output, comp_level |
|
|
| |
|
|
| def Optimus_Signature(chords_list, calculate_full_signature=False): |
|
|
| '''Optimus Signature |
| |
| ---In the name of the search for a perfect score slice signature--- |
| |
| Input: Flat chords list to evaluate |
| |
| Output: Full Optimus Signature as a list |
| Best/recommended Optimus Signature as a list |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
| |
| |
|
|
| |
| if calculate_full_signature: |
| psd = statistics.stdev([int(y[4]) for y in chords_list]) |
| else: |
| psd = 0 |
|
|
| |
| pmh = statistics.median_high([int(y[4]) for y in chords_list]) |
| pm = statistics.median([int(y[4]) for y in chords_list]) |
| pml = statistics.median_low([int(y[4]) for y in chords_list]) |
| |
| |
| if calculate_full_signature: |
| phm = statistics.harmonic_mean([int(y[4]) for y in chords_list]) |
| else: |
| phm = 0 |
|
|
| |
| dur = statistics.median([int(y[2]) for y in chords_list]) |
|
|
| |
|
|
| vel = statistics.median([int(y[5]) for y in chords_list]) |
|
|
| |
| mtds = statistics.median([int(abs(chords_list[i-1][1]-chords_list[i][1])) for i in range(1, len(chords_list))]) |
| if calculate_full_signature: |
| hmtds = statistics.harmonic_mean([int(abs(chords_list[i-1][1]-chords_list[i][1])) for i in range(1, len(chords_list))]) |
| else: |
| hmtds = 0 |
|
|
| |
| full_Optimus_signature = [round(psd), round(pmh), round(pm), round(pml), round(phm), round(dur), round(vel), round(mtds), round(hmtds)] |
| |
|
|
| best_Optimus_signature = [round(pmh), round(pm), round(pml), round(dur, -1), round(vel, -1), round(mtds, -1)] |
| |
| |
| |
| return full_Optimus_signature, best_Optimus_signature |
| |
|
|
| |
| |
| |
| |
| |
|
|
| def Tegridy_FastSearch(needle, haystack, randomize = False): |
|
|
| ''' |
| |
| Input: Needle iterable |
| Haystack iterable |
| Randomize search range (this prevents determinism) |
| |
| Output: Start index of the needle iterable in a haystack iterable |
| If nothing found, -1 is returned |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| need = copy.deepcopy(needle) |
|
|
| try: |
| if randomize: |
| idx = haystack.index(need, secrets.randbelow(len(haystack)-len(need))) |
| else: |
| idx = haystack.index(need) |
|
|
| except KeyboardInterrupt: |
| return -1 |
|
|
| except: |
| return -1 |
| |
| return idx |
|
|
| |
|
|
| def Tegridy_Chord_Match(chord1, chord2, match_type=2): |
|
|
| '''Tegridy Chord Match |
| |
| Input: Two chords to evaluate |
| Match type: 2 = duration, channel, pitch, velocity |
| 3 = channel, pitch, velocity |
| 4 = pitch, velocity |
| 5 = velocity |
| |
| Output: Match rating (0-100) |
| NOTE: Match rating == -1 means identical source chords |
| NOTE: Match rating == 100 means mutual shortest chord |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| match_rating = 0 |
|
|
| if chord1 == []: |
| return 0 |
| if chord2 == []: |
| return 0 |
|
|
| if chord1 == chord2: |
| return -1 |
|
|
| else: |
| zipped_pairs = list(zip(chord1, chord2)) |
| zipped_diff = abs(len(chord1) - len(chord2)) |
|
|
| short_match = [False] |
| for pair in zipped_pairs: |
| cho1 = ' '.join([str(y) for y in pair[0][match_type:]]) |
| cho2 = ' '.join([str(y) for y in pair[1][match_type:]]) |
| if cho1 == cho2: |
| short_match.append(True) |
| else: |
| short_match.append(False) |
| |
| if True in short_match: |
| return 100 |
|
|
| pairs_ratings = [] |
|
|
| for pair in zipped_pairs: |
| cho1 = ' '.join([str(y) for y in pair[0][match_type:]]) |
| cho2 = ' '.join([str(y) for y in pair[1][match_type:]]) |
| pairs_ratings.append(SM(None, cho1, cho2).ratio()) |
|
|
| match_rating = sum(pairs_ratings) / len(pairs_ratings) * 100 |
|
|
| return match_rating |
|
|
| |
|
|
| def Tegridy_Last_Chord_Finder(chords_list): |
|
|
| '''Tegridy Last Chord Finder |
| |
| Input: Flat chords list |
| |
| Output: Last detected chord of the chords list |
| Last chord start index in the original chords list |
| First chord end index in the original chords list |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| chords = [] |
| cho = [] |
|
|
| ptime = 0 |
|
|
| i = 0 |
|
|
| pc_idx = 0 |
| fc_idx = 0 |
|
|
| chords_list.sort(reverse=False, key=lambda x: x[1]) |
| |
| for cc in chords_list: |
|
|
| if cc[1] == ptime: |
| |
| cho.append(cc) |
|
|
| ptime = cc[1] |
|
|
| else: |
| if pc_idx == 0: |
| fc_idx = chords_list.index(cc) |
| pc_idx = chords_list.index(cc) |
| |
| chords.append(cho) |
| |
| cho = [] |
| |
| cho.append(cc) |
| |
| ptime = cc[1] |
| |
| i += 1 |
| |
| if cho != []: |
| chords.append(cho) |
| i += 1 |
| |
| return chords_list[pc_idx:], pc_idx, fc_idx |
|
|
| |
|
|
| def Tegridy_Chords_Generator(chords_list, shuffle_pairs = True, remove_single_notes=False): |
|
|
| '''Tegridy Score Chords Pairs Generator |
| |
| Input: Flat chords list |
| Shuffle pairs (recommended) |
| |
| Output: List of chords |
| |
| Average time(ms) per chord |
| Average time(ms) per pitch |
| Average chords delta time |
| |
| Average duration |
| Average channel |
| Average pitch |
| Average velocity |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| chords = [] |
| cho = [] |
|
|
| i = 0 |
|
|
| |
| chords_list.sort(reverse=False, key=lambda x: x[1]) |
|
|
| |
| pcho = chords_list[0] |
| for cc in chords_list: |
| if cc[1] == pcho[1]: |
| |
| cho.append(cc) |
| pcho = copy.deepcopy(cc) |
|
|
| else: |
| if not remove_single_notes: |
| chords.append(cho) |
| cho = [] |
| cho.append(cc) |
| pcho = copy.deepcopy(cc) |
| |
| i += 1 |
| else: |
| if len(cho) > 1: |
| chords.append(cho) |
| cho = [] |
| cho.append(cc) |
| pcho = copy.deepcopy(cc) |
| |
| i += 1 |
| |
| |
| t0 = chords[0][0][1] |
| t1 = chords[-1][-1][1] |
| tdel = abs(t1 - t0) |
| avg_ms_per_chord = int(tdel / i) |
| avg_ms_per_pitch = int(tdel / len(chords_list)) |
|
|
| |
| tds = [int(abs(chords_list[i-1][1]-chords_list[i][1]) / 1) for i in range(1, len(chords_list))] |
| if len(tds) != 0: avg_delta_time = int(sum(tds) / len(tds)) |
|
|
| |
| p = int(sum([int(y[4]) for y in chords_list]) / len(chords_list)) |
| d = int(sum([int(y[2]) for y in chords_list]) / len(chords_list)) |
| c = int(sum([int(y[3]) for y in chords_list]) / len(chords_list)) |
| v = int(sum([int(y[5]) for y in chords_list]) / len(chords_list)) |
|
|
| |
| if shuffle_pairs: |
| random.shuffle(chords) |
|
|
| return chords, [avg_ms_per_chord, avg_ms_per_pitch, avg_delta_time], [d, c, p, v] |
|
|
| |
|
|
| def Tegridy_Chords_List_Music_Features(chords_list, st_dur_div = 1, pitch_div = 1, vel_div = 1): |
|
|
| '''Tegridy Chords List Music Features |
| |
| Input: Flat chords list |
| |
| Output: A list of the extracted chords list's music features |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| chords_list1 = [x for x in chords_list if x] |
| chords_list1.sort(reverse=False, key=lambda x: x[1]) |
| |
| |
|
|
| melody_list = [] |
| bass_melody = [] |
| melody_chords = [] |
| mel_avg_tds = [] |
| mel_chrd_avg_tds = [] |
| bass_melody_avg_tds = [] |
|
|
| |
| values = set(map(lambda x:x[1], chords_list1)) |
|
|
| groups = [[y for y in chords_list1 if y[1]==x and len(y) == 6] for x in values] |
|
|
| |
| for items in groups: |
| items.sort(reverse=True, key=lambda x: x[4]) |
| melody_list.append(items[0]) |
| melody_chords.append(items) |
| bass_melody.append(items[-1]) |
|
|
| |
| melody_list.sort(reverse=False, key=lambda x: x[1]) |
| melody_chords.sort(reverse=False, key=lambda x: x[0][1]) |
| bass_melody.sort(reverse=False, key=lambda x: x[1]) |
|
|
| |
| |
| |
| mel_avg_pitch = int(sum([y[4] for y in melody_list]) / len(melody_list) / pitch_div) |
| mel_avg_dur = int(sum([int(y[2] / st_dur_div) for y in melody_list]) / len(melody_list)) |
| mel_avg_vel = int(sum([int(y[5] / vel_div) for y in melody_list]) / len(melody_list)) |
| mel_avg_chan = int(sum([int(y[3]) for y in melody_list]) / len(melody_list)) |
| |
| mel_tds = [int(abs(melody_list[i-1][1]-melody_list[i][1])) for i in range(1, len(melody_list))] |
| if len(mel_tds) != 0: mel_avg_tds = int(sum(mel_tds) / len(mel_tds) / st_dur_div) |
| |
| melody_features = [mel_avg_tds, mel_avg_dur, mel_avg_chan, mel_avg_pitch, mel_avg_vel] |
|
|
| |
| mel_chrd_avg_pitch = int(sum([y[4] for y in chords_list1]) / len(chords_list1) / pitch_div) |
| mel_chrd_avg_dur = int(sum([int(y[2] / st_dur_div) for y in chords_list1]) / len(chords_list1)) |
| mel_chrd_avg_vel = int(sum([int(y[5] / vel_div) for y in chords_list1]) / len(chords_list1)) |
| mel_chrd_avg_chan = int(sum([int(y[3]) for y in chords_list1]) / len(chords_list1)) |
| |
| mel_chrd_tds = [int(abs(chords_list1[i-1][1]-chords_list1[i][1])) for i in range(1, len(chords_list1))] |
| if len(mel_tds) != 0: mel_chrd_avg_tds = int(sum(mel_chrd_tds) / len(mel_chrd_tds) / st_dur_div) |
| |
| chords_list_features = [mel_chrd_avg_tds, mel_chrd_avg_dur, mel_chrd_avg_chan, mel_chrd_avg_pitch, mel_chrd_avg_vel] |
|
|
| |
| bass_melody_avg_pitch = int(sum([y[4] for y in bass_melody]) / len(bass_melody) / pitch_div) |
| bass_melody_avg_dur = int(sum([int(y[2] / st_dur_div) for y in bass_melody]) / len(bass_melody)) |
| bass_melody_avg_vel = int(sum([int(y[5] / vel_div) for y in bass_melody]) / len(bass_melody)) |
| bass_melody_avg_chan = int(sum([int(y[3]) for y in bass_melody]) / len(bass_melody)) |
| |
| bass_melody_tds = [int(abs(bass_melody[i-1][1]-bass_melody[i][1])) for i in range(1, len(bass_melody))] |
| if len(bass_melody_tds) != 0: bass_melody_avg_tds = int(sum(bass_melody_tds) / len(bass_melody_tds) / st_dur_div) |
| |
| bass_melody_features = [bass_melody_avg_tds, bass_melody_avg_dur, bass_melody_avg_chan, bass_melody_avg_pitch, bass_melody_avg_vel] |
| |
| |
| music_features = [] |
|
|
| music_features.extend([len(chords_list1)]) |
| |
| music_features.extend(melody_features) |
| music_features.extend(chords_list_features) |
| music_features.extend(bass_melody_features) |
| music_features.extend([sum([y[4] for y in chords_list1])]) |
|
|
| return music_features |
|
|
| |
|
|
| def Tegridy_Transform(chords_list, to_pitch=60, to_velocity=-1): |
|
|
| '''Tegridy Transform |
| |
| Input: Flat chords list |
| Desired average pitch (-1 == no change) |
| Desired average velocity (-1 == no change) |
| |
| Output: Transformed flat chords list |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| transformed_chords_list = [] |
|
|
| chords_list.sort(reverse=False, key=lambda x: x[1]) |
|
|
| chords_list_features = Optimus_Signature(chords_list)[1] |
|
|
| pitch_diff = int((chords_list_features[0] + chords_list_features[1] + chords_list_features[2]) / 3) - to_pitch |
| velocity_diff = chords_list_features[4] - to_velocity |
|
|
| for c in chords_list: |
| cc = copy.deepcopy(c) |
| if c[3] != 9: |
| if to_pitch != -1: |
| cc[4] = c[4] - pitch_diff |
| |
| if to_velocity != -1: |
| cc[5] = c[5] - velocity_diff |
| |
| transformed_chords_list.append(cc) |
|
|
| return transformed_chords_list |
|
|
| |
|
|
| def Tegridy_MIDI_Zip_Notes_Summarizer(chords_list, match_type = 4): |
|
|
| '''Tegridy MIDI Zip Notes Summarizer |
| |
| Input: Flat chords list / SONG |
| Match type according to 'note' event of MIDI.py |
| |
| Output: Summarized chords list |
| Number of summarized notes |
| Number of dicarted notes |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| i = 0 |
| j = 0 |
| out1 = [] |
| pout = [] |
| |
|
|
| for o in chords_list: |
|
|
| |
|
|
| if o[match_type:] not in pout: |
| pout.append(o[match_type:]) |
| |
| out1.append(o) |
| j += 1 |
| |
| else: |
| i += 1 |
|
|
| return out1, i |
|
|
| |
|
|
| def Tegridy_Score_Chords_Pairs_Generator(chords_list, shuffle_pairs = True, remove_single_notes=False): |
|
|
| '''Tegridy Score Chords Pairs Generator |
| |
| Input: Flat chords list |
| Shuffle pairs (recommended) |
| |
| Output: Score chords pairs list |
| Number of created pairs |
| Number of detected chords |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| chords = [] |
| cho = [] |
|
|
| i = 0 |
| j = 0 |
|
|
| chords_list.sort(reverse=False, key=lambda x: x[1]) |
| pcho = chords_list[0] |
| for cc in chords_list: |
| if cc[1] == pcho[1]: |
| |
| cho.append(cc) |
| pcho = copy.deepcopy(cc) |
|
|
| else: |
| if not remove_single_notes: |
| chords.append(cho) |
| cho = [] |
| cho.append(cc) |
| pcho = copy.deepcopy(cc) |
| |
| i += 1 |
| else: |
| if len(cho) > 1: |
| chords.append(cho) |
| cho = [] |
| cho.append(cc) |
| pcho = copy.deepcopy(cc) |
| |
| i += 1 |
| |
| chords_pairs = [] |
| for i in range(len(chords)-1): |
| chords_pairs.append([chords[i], chords[i+1]]) |
| j += 1 |
| if shuffle_pairs: random.shuffle(chords_pairs) |
|
|
| return chords_pairs, j, i |
|
|
| |
|
|
| def Tegridy_Sliced_Score_Pairs_Generator(chords_list, number_of_miliseconds_per_slice=2000, shuffle_pairs = False): |
|
|
| '''Tegridy Sliced Score Pairs Generator |
| |
| Input: Flat chords list |
| Number of miliseconds per slice |
| |
| Output: Sliced score pairs list |
| Number of created slices |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| chords = [] |
| cho = [] |
|
|
| time = number_of_miliseconds_per_slice |
|
|
| i = 0 |
|
|
| chords_list1 = [x for x in chords_list if x] |
| chords_list1.sort(reverse=False, key=lambda x: x[1]) |
| pcho = chords_list1[0] |
| for cc in chords_list1[1:]: |
|
|
| if cc[1] <= time: |
| |
| cho.append(cc) |
|
|
| else: |
| if cho != [] and pcho != []: chords.append([pcho, cho]) |
| pcho = copy.deepcopy(cho) |
| cho = [] |
| cho.append(cc) |
| time += number_of_miliseconds_per_slice |
| i += 1 |
| |
| if cho != [] and pcho != []: |
| chords.append([pcho, cho]) |
| pcho = copy.deepcopy(cho) |
| i += 1 |
| |
| if shuffle_pairs: random.shuffle(chords) |
|
|
| return chords, i |
|
|
| |
|
|
| def Tegridy_Timings_Converter(chords_list, |
| max_delta_time = 1000, |
| fixed_start_time = 250, |
| start_time = 0, |
| start_time_multiplier = 1, |
| durations_multiplier = 1): |
|
|
| '''Tegridy Timings Converter |
| |
| Input: Flat chords list |
| Max delta time allowed between notes |
| Fixed start note time for excessive gaps |
| |
| Output: Converted flat chords list |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| song = chords_list |
|
|
| song1 = [] |
|
|
| p = song[0] |
|
|
| p[1] = start_time |
|
|
| time = start_time |
|
|
| delta = [0] |
|
|
| for i in range(len(song)): |
| if song[i][0] == 'note': |
| ss = copy.deepcopy(song[i]) |
| if song[i][1] != p[1]: |
| |
| if abs(song[i][1] - p[1]) > max_delta_time: |
| time += fixed_start_time |
| else: |
| time += abs(song[i][1] - p[1]) |
| delta.append(abs(song[i][1] - p[1])) |
|
|
| ss[1] = int(round(time * start_time_multiplier, -1)) |
| ss[2] = int(round(song[i][2] * durations_multiplier, -1)) |
| song1.append(ss) |
| |
| p = copy.deepcopy(song[i]) |
| else: |
| |
| ss[1] = int(round(time * start_time_multiplier, -1)) |
| ss[2] = int(round(song[i][2] * durations_multiplier, -1)) |
| song1.append(ss) |
| |
| p = copy.deepcopy(song[i]) |
| |
| else: |
| ss = copy.deepcopy(song[i]) |
| ss[1] = time |
| song1.append(ss) |
| |
| average_delta_st = int(sum(delta) / len(delta)) |
| average_duration = int(sum([y[2] for y in song1 if y[0] == 'note']) / len([y[2] for y in song1 if y[0] == 'note'])) |
|
|
| song1.sort(reverse=False, key=lambda x: x[1]) |
|
|
| return song1, time, average_delta_st, average_duration |
|
|
| |
|
|
| def Tegridy_Score_Slicer(chords_list, number_of_miliseconds_per_slice=2000, overlap_notes = 0, overlap_chords=False): |
|
|
| '''Tegridy Score Slicer |
| |
| Input: Flat chords list |
| Number of miliseconds per slice |
| |
| Output: Sliced chords list |
| Number of created slices |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| chords = [] |
| cho = [] |
|
|
| time = number_of_miliseconds_per_slice |
| ptime = 0 |
|
|
| i = 0 |
|
|
| pc_idx = 0 |
|
|
| chords_list.sort(reverse=False, key=lambda x: x[1]) |
| |
| for cc in chords_list: |
|
|
| if cc[1] <= time: |
| |
| cho.append(cc) |
|
|
| if ptime != cc[1]: |
| pc_idx = cho.index(cc) |
|
|
| ptime = cc[1] |
|
|
|
|
| else: |
|
|
| if overlap_chords: |
| chords.append(cho) |
| cho.extend(chords[-1][pc_idx:]) |
| |
| else: |
| chords.append(cho[:pc_idx]) |
| |
| cho = [] |
| |
| cho.append(cc) |
| |
| time += number_of_miliseconds_per_slice |
| ptime = cc[1] |
| |
| i += 1 |
| |
| if cho != []: |
| chords.append(cho) |
| i += 1 |
| |
| return [x for x in chords if x], i |
|
|
| |
|
|
| def Tegridy_TXT_Tokenizer(input_TXT_string, line_by_line_TXT_string=True): |
|
|
| '''Tegridy TXT Tokenizer |
| |
| Input: TXT String |
| |
| Output: Tokenized TXT string + forward and reverse dics |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| print('Tegridy TXT Tokenizer') |
|
|
| if line_by_line_TXT_string: |
| T = input_TXT_string.split() |
| else: |
| T = input_TXT_string.split(' ') |
|
|
| DIC = dict(zip(T, range(len(T)))) |
| RDIC = dict(zip(range(len(T)), T)) |
|
|
| TXTT = '' |
|
|
| for t in T: |
| try: |
| TXTT += chr(DIC[t]) |
| except: |
| print('Error. Could not finish.') |
| return TXTT, DIC, RDIC |
| |
| print('Done!') |
| |
| return TXTT, DIC, RDIC |
|
|
| |
|
|
| def Tegridy_TXT_DeTokenizer(input_Tokenized_TXT_string, RDIC): |
|
|
| '''Tegridy TXT Tokenizer |
| |
| Input: Tokenized TXT String |
| |
| |
| Output: DeTokenized TXT string |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| print('Tegridy TXT DeTokenizer') |
|
|
| Q = list(input_Tokenized_TXT_string) |
| c = 0 |
| RTXT = '' |
| for q in Q: |
| try: |
| RTXT += RDIC[ord(q)] + chr(10) |
| except: |
| c+=1 |
|
|
| print('Number of errors:', c) |
|
|
| print('Done!') |
|
|
| return RTXT |
|
|
| |
|
|
| def Tegridy_List_Slicer(input_list, slices_length_in_notes=20): |
|
|
| '''Input: List to slice |
| Desired slices length in notes |
| |
| Output: Sliced list of lists |
| |
| Project Los Angeles |
| Tegridy Code 2021''' |
|
|
| for i in range(0, len(input_list), slices_length_in_notes): |
| yield input_list[i:i + slices_length_in_notes] |
| |
| |
| |
| def Tegridy_Split_List(list_to_split, split_value=0): |
| |
| |
| |
| |
| |
| size = len(list_to_split) |
| idx_list = [idx + 1 for idx, val in |
| enumerate(list_to_split) if val == split_value] |
|
|
|
|
| res = [list_to_split[i: j] for i, j in |
| zip([0] + idx_list, idx_list + |
| ([size] if idx_list[-1] != size else []))] |
| |
| |
| |
| |
| return res |
|
|
| |
|
|
| |
|
|
| def tones_chord_to_bits(chord, reverse=True): |
|
|
| bits = [0] * 12 |
|
|
| for num in chord: |
| bits[num] = 1 |
| |
| if reverse: |
| bits.reverse() |
| return bits |
| |
| else: |
| return bits |
|
|
| def bits_to_tones_chord(bits): |
| return [i for i, bit in enumerate(bits) if bit == 1] |
|
|
| def shift_bits(bits, n): |
| return bits[-n:] + bits[:-n] |
|
|
| def bits_to_int(bits, shift_bits_value=0): |
| bits = shift_bits(bits, shift_bits_value) |
| result = 0 |
| for bit in bits: |
| result = (result << 1) | bit |
| |
| return result |
|
|
| def int_to_bits(n): |
| bits = [0] * 12 |
| for i in range(12): |
| bits[11 - i] = n % 2 |
| n //= 2 |
| |
| return bits |
|
|
| def bad_chord(chord): |
| bad = any(b - a == 1 for a, b in zip(chord, chord[1:])) |
| if (0 in chord) and (11 in chord): |
| bad = True |
| |
| return bad |
|
|
| def pitches_chord_to_int(pitches_chord, tones_transpose_value=0): |
|
|
| pitches_chord = [x for x in pitches_chord if 0 < x < 128] |
|
|
| if not (-12 < tones_transpose_value < 12): |
| tones_transpose_value = 0 |
|
|
| tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))]))) |
| bits = tones_chord_to_bits(tones_chord) |
| integer = bits_to_int(bits, shift_bits_value=tones_transpose_value) |
|
|
| return integer |
|
|
| def int_to_pitches_chord(integer, chord_base_pitch=60): |
| if 0 < integer < 4096: |
| bits = int_to_bits(integer) |
| tones_chord = bits_to_tones_chord(bits) |
| if not bad_chord(tones_chord): |
| pitches_chord = [t+chord_base_pitch for t in tones_chord] |
| return [pitches_chord, tones_chord] |
| |
| else: |
| return 0 |
| |
| else: |
| return -1 |
|
|
| |
|
|
| def bad_chord(chord): |
| bad = any(b - a == 1 for a, b in zip(chord, chord[1:])) |
| if (0 in chord) and (11 in chord): |
| bad = True |
| |
| return bad |
|
|
| def validate_pitches_chord(pitches_chord, return_sorted = True): |
|
|
| pitches_chord = sorted(list(set([x for x in pitches_chord if 0 < x < 128]))) |
|
|
| tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))]))) |
|
|
| if not bad_chord(tones_chord): |
| if return_sorted: |
| pitches_chord.sort(reverse=True) |
| return pitches_chord |
| |
| else: |
| if 0 in tones_chord and 11 in tones_chord: |
| tones_chord.remove(0) |
|
|
| fixed_tones = [[a, b] for a, b in zip(tones_chord, tones_chord[1:]) if b-a != 1] |
|
|
| fixed_tones_chord = [] |
| for f in fixed_tones: |
| fixed_tones_chord.extend(f) |
| fixed_tones_chord = list(set(fixed_tones_chord)) |
| |
| fixed_pitches_chord = [] |
|
|
| for p in pitches_chord: |
| if (p % 12) in fixed_tones_chord: |
| fixed_pitches_chord.append(p) |
|
|
| if return_sorted: |
| fixed_pitches_chord.sort(reverse=True) |
|
|
| return fixed_pitches_chord |
|
|
| def validate_pitches(chord, channel_to_check = 0, return_sorted = True): |
|
|
| pitches_chord = sorted(list(set([x[4] for x in chord if 0 < x[4] < 128 and x[3] == channel_to_check]))) |
|
|
| if pitches_chord: |
|
|
| tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))]))) |
|
|
| if not bad_chord(tones_chord): |
| if return_sorted: |
| chord.sort(key = lambda x: x[4], reverse=True) |
| return chord |
| |
| else: |
| if 0 in tones_chord and 11 in tones_chord: |
| tones_chord.remove(0) |
|
|
| fixed_tones = [[a, b] for a, b in zip(tones_chord, tones_chord[1:]) if b-a != 1] |
|
|
| fixed_tones_chord = [] |
| for f in fixed_tones: |
| fixed_tones_chord.extend(f) |
| fixed_tones_chord = list(set(fixed_tones_chord)) |
| |
| fixed_chord = [] |
|
|
| for c in chord: |
| if c[3] == channel_to_check: |
| if (c[4] % 12) in fixed_tones_chord: |
| fixed_chord.append(c) |
| else: |
| fixed_chord.append(c) |
|
|
| if return_sorted: |
| fixed_chord.sort(key = lambda x: x[4], reverse=True) |
| |
| return fixed_chord |
|
|
| else: |
| chord.sort(key = lambda x: x[4], reverse=True) |
| return chord |
|
|
| def adjust_score_velocities(score, max_velocity): |
|
|
| min_velocity = min([c[5] for c in score]) |
| max_velocity_all_channels = max([c[5] for c in score]) |
| min_velocity_ratio = min_velocity / max_velocity_all_channels |
|
|
| max_channel_velocity = max([c[5] for c in score]) |
| if max_channel_velocity < min_velocity: |
| factor = max_velocity / min_velocity |
| else: |
| factor = max_velocity / max_channel_velocity |
| for i in range(len(score)): |
| score[i][5] = int(score[i][5] * factor) |
|
|
| def chordify_score(score, |
| return_choridfied_score=True, |
| return_detected_score_information=False |
| ): |
|
|
| if score: |
| |
| num_tracks = 1 |
| single_track_score = [] |
| score_num_ticks = 0 |
|
|
| if type(score[0]) == int and len(score) > 1: |
|
|
| score_type = 'MIDI_PY' |
| score_num_ticks = score[0] |
|
|
| while num_tracks < len(score): |
| for event in score[num_tracks]: |
| single_track_score.append(event) |
| num_tracks += 1 |
| |
| else: |
| score_type = 'CUSTOM' |
| single_track_score = score |
|
|
| if single_track_score and single_track_score[0]: |
| |
| try: |
|
|
| if type(single_track_score[0][0]) == str or single_track_score[0][0] == 'note': |
| single_track_score.sort(key = lambda x: x[1]) |
| score_timings = [s[1] for s in single_track_score] |
| else: |
| score_timings = [s[0] for s in single_track_score] |
|
|
| is_score_time_absolute = lambda sct: all(x <= y for x, y in zip(sct, sct[1:])) |
|
|
| score_timings_type = '' |
|
|
| if is_score_time_absolute(score_timings): |
| score_timings_type = 'ABS' |
|
|
| chords = [] |
| cho = [] |
|
|
| if score_type == 'MIDI_PY': |
| pe = single_track_score[0] |
| else: |
| pe = single_track_score[0] |
|
|
| for e in single_track_score: |
| |
| if score_type == 'MIDI_PY': |
| time = e[1] |
| ptime = pe[1] |
| else: |
| time = e[0] |
| ptime = pe[0] |
|
|
| if time == ptime: |
| cho.append(e) |
| |
| else: |
| if len(cho) > 0: |
| chords.append(cho) |
| cho = [] |
| cho.append(e) |
|
|
| pe = e |
|
|
| if len(cho) > 0: |
| chords.append(cho) |
|
|
| else: |
| score_timings_type = 'REL' |
| |
| chords = [] |
| cho = [] |
|
|
| for e in single_track_score: |
| |
| if score_type == 'MIDI_PY': |
| time = e[1] |
| else: |
| time = e[0] |
|
|
| if time == 0: |
| cho.append(e) |
| |
| else: |
| if len(cho) > 0: |
| chords.append(cho) |
| cho = [] |
| cho.append(e) |
|
|
| if len(cho) > 0: |
| chords.append(cho) |
|
|
| requested_data = [] |
|
|
| if return_detected_score_information: |
| |
| detected_score_information = [] |
|
|
| detected_score_information.append(['Score type', score_type]) |
| detected_score_information.append(['Score timings type', score_timings_type]) |
| detected_score_information.append(['Score tpq', score_num_ticks]) |
| detected_score_information.append(['Score number of tracks', num_tracks]) |
| |
| requested_data.append(detected_score_information) |
|
|
| if return_choridfied_score and return_detected_score_information: |
| requested_data.append(chords) |
|
|
| if return_choridfied_score and not return_detected_score_information: |
| requested_data.extend(chords) |
|
|
| return requested_data |
|
|
| except Exception as e: |
| print('Error!') |
| print('Check score for consistency and compatibility!') |
| print('Exception detected:', e) |
|
|
| else: |
| return None |
|
|
| else: |
| return None |
|
|
| def fix_monophonic_score_durations(monophonic_score): |
| |
| fixed_score = [] |
|
|
| if monophonic_score[0][0] == 'note': |
|
|
| for i in range(len(monophonic_score)-1): |
| note = monophonic_score[i] |
|
|
| nmt = monophonic_score[i+1][1] |
|
|
| if note[1]+note[2] >= nmt: |
| note_dur = nmt-note[1]-1 |
| else: |
| note_dur = note[2] |
|
|
| new_note = [note[0], note[1], note_dur] + note[3:] |
|
|
| fixed_score.append(new_note) |
|
|
| fixed_score.append(monophonic_score[-1]) |
|
|
| elif type(monophonic_score[0][0]) == int: |
|
|
| for i in range(len(monophonic_score)-1): |
| note = monophonic_score[i] |
|
|
| nmt = monophonic_score[i+1][0] |
|
|
| if note[0]+note[1] >= nmt: |
| note_dur = nmt-note[0]-1 |
| else: |
| note_dur = note[1] |
|
|
| new_note = [note[0], note_dur] + note[2:] |
|
|
| fixed_score.append(new_note) |
|
|
| fixed_score.append(monophonic_score[-1]) |
|
|
| return fixed_score |
|
|
| |
|
|
| from itertools import product |
|
|
| ALL_CHORDS = [[0], [7], [5], [9], [2], [4], [11], [10], [8], [6], [3], [1], [0, 9], [2, 5], |
| [4, 7], [7, 10], [2, 11], [0, 3], [6, 9], [1, 4], [8, 11], [5, 8], [1, 10], |
| [3, 6], [0, 4], [5, 9], [7, 11], [0, 7], [0, 5], [2, 10], [2, 7], [2, 9], |
| [2, 6], [4, 11], [4, 9], [3, 7], [5, 10], [1, 9], [0, 8], [6, 11], [3, 11], |
| [4, 8], [3, 10], [3, 8], [1, 5], [1, 8], [1, 6], [6, 10], [3, 9], [4, 10], |
| [1, 7], [0, 6], [2, 8], [5, 11], [5, 7], [0, 10], [0, 2], [9, 11], [7, 9], |
| [2, 4], [4, 6], [3, 5], [8, 10], [6, 8], [1, 3], [1, 11], [2, 7, 11], |
| [0, 4, 7], [0, 5, 9], [2, 6, 9], [2, 5, 10], [1, 4, 9], [4, 8, 11], [3, 7, 10], |
| [0, 3, 8], [3, 6, 11], [1, 5, 8], [1, 6, 10], [0, 4, 9], [2, 5, 9], [4, 7, 11], |
| [2, 7, 10], [2, 6, 11], [0, 3, 7], [0, 5, 8], [1, 4, 8], [1, 6, 9], [3, 8, 11], |
| [1, 5, 10], [3, 6, 10], [2, 5, 11], [4, 7, 10], [3, 6, 9], [0, 6, 9], |
| [0, 3, 9], [2, 8, 11], [2, 5, 8], [1, 7, 10], [1, 4, 7], [0, 3, 6], [1, 4, 10], |
| [5, 8, 11], [2, 5, 7], [0, 7, 10], [0, 2, 9], [0, 3, 5], [6, 9, 11], [4, 7, 9], |
| [2, 4, 11], [5, 8, 10], [1, 3, 10], [1, 4, 6], [3, 6, 8], [1, 8, 11], |
| [5, 7, 11], [0, 4, 10], [3, 5, 9], [0, 2, 6], [1, 7, 9], [0, 7, 9], [5, 7, 10], |
| [2, 8, 10], [3, 9, 11], [0, 2, 5], [2, 4, 8], [2, 4, 7], [0, 2, 7], [2, 7, 9], |
| [4, 9, 11], [4, 6, 9], [1, 3, 7], [2, 4, 9], [0, 5, 7], [0, 3, 10], [2, 9, 11], |
| [0, 5, 10], [0, 6, 8], [4, 6, 10], [4, 6, 11], [1, 4, 11], [6, 8, 11], |
| [1, 5, 11], [1, 6, 11], [1, 8, 10], [1, 6, 8], [3, 5, 8], [3, 8, 10], |
| [1, 3, 8], [3, 5, 10], [1, 3, 6], [2, 5, 7, 10], [0, 3, 7, 10], [1, 4, 8, 11], |
| [2, 4, 7, 11], [0, 4, 7, 9], [0, 2, 5, 9], [2, 6, 9, 11], [1, 5, 8, 10], |
| [0, 3, 5, 8], [3, 6, 8, 11], [1, 3, 6, 10], [1, 4, 6, 9], [1, 5, 9], [0, 4, 8], |
| [2, 6, 10], [3, 7, 11], [0, 3, 6, 9], [2, 5, 8, 11], [1, 4, 7, 10], |
| [2, 5, 7, 11], [0, 2, 6, 9], [0, 4, 7, 10], [2, 4, 8, 11], [0, 3, 5, 9], |
| [1, 4, 7, 9], [3, 6, 9, 11], [2, 5, 8, 10], [1, 4, 6, 10], [0, 3, 6, 8], |
| [1, 3, 7, 10], [1, 5, 8, 11], [2, 4, 10], [5, 9, 11], [1, 5, 7], [0, 2, 8], |
| [0, 4, 6], [1, 7, 11], [3, 7, 9], [1, 3, 9], [7, 9, 11], [5, 7, 9], [0, 6, 10], |
| [0, 2, 10], [2, 6, 8], [0, 2, 4], [4, 8, 10], [1, 9, 11], [2, 4, 6], |
| [3, 5, 11], [3, 5, 7], [0, 8, 10], [4, 6, 8], [1, 3, 11], [6, 8, 10], |
| [1, 3, 5], [0, 2, 5, 10], [0, 5, 7, 9], [0, 3, 8, 10], [0, 2, 4, 7], |
| [4, 6, 8, 11], [3, 5, 7, 10], [2, 7, 9, 11], [2, 4, 6, 9], [1, 6, 8, 10], |
| [1, 4, 9, 11], [1, 3, 5, 8], [1, 3, 6, 11], [2, 5, 9, 11], [2, 4, 7, 10], |
| [0, 2, 5, 8], [1, 5, 7, 10], [0, 4, 6, 9], [1, 3, 6, 9], [0, 3, 6, 10], |
| [2, 6, 8, 11], [0, 2, 7, 9], [1, 4, 8, 10], [0, 3, 7, 9], [3, 5, 8, 11], |
| [0, 5, 7, 10], [0, 2, 5, 7], [1, 4, 7, 11], [2, 4, 7, 9], [0, 3, 5, 10], |
| [4, 6, 9, 11], [1, 4, 6, 11], [2, 4, 9, 11], [1, 6, 8, 11], [1, 3, 6, 8], |
| [1, 3, 8, 10], [3, 5, 8, 10], [4, 7, 9, 11], [0, 2, 7, 10], [2, 5, 7, 9], |
| [0, 2, 4, 9], [1, 6, 9, 11], [2, 4, 6, 11], [0, 3, 5, 7], [0, 5, 8, 10], |
| [1, 4, 6, 8], [1, 3, 5, 10], [1, 3, 8, 11], [3, 6, 8, 10], [0, 2, 5, 7, 10], |
| [0, 2, 4, 7, 9], [0, 2, 5, 7, 9], [1, 3, 7, 9], [1, 4, 6, 9, 11], |
| [1, 3, 6, 8, 11], [3, 5, 9, 11], [1, 3, 6, 8, 10], [1, 4, 6, 8, 11], |
| [1, 3, 5, 8, 10], [2, 4, 6, 9, 11], [2, 4, 8, 10], [2, 4, 7, 9, 11], |
| [0, 3, 5, 7, 10], [1, 5, 7, 11], [0, 2, 6, 8], [0, 3, 5, 8, 10], [0, 4, 6, 10], |
| [1, 3, 5, 9], [1, 5, 7, 9], [2, 6, 8, 10], [3, 7, 9, 11], [0, 2, 4, 8], |
| [0, 4, 6, 8], [0, 4, 8, 10], [2, 4, 6, 10], [1, 3, 7, 11], [0, 2, 6, 10], |
| [1, 5, 9, 11], [3, 5, 7, 11], [1, 7, 9, 11], [0, 2, 4, 6], [1, 3, 9, 11], |
| [0, 2, 4, 10], [5, 7, 9, 11], [2, 4, 6, 8], [0, 2, 8, 10], [3, 5, 7, 9], |
| [1, 3, 5, 7], [4, 6, 8, 10], [0, 6, 8, 10], [1, 3, 5, 11], [0, 3, 6, 8, 10], |
| [0, 2, 4, 6, 9], [1, 4, 7, 9, 11], [2, 4, 6, 8, 11], [1, 3, 6, 9, 11], |
| [1, 3, 5, 8, 11], [0, 2, 5, 8, 10], [1, 4, 6, 8, 10], [0, 3, 5, 7, 9], |
| [2, 5, 7, 9, 11], [1, 3, 5, 7, 10], [0, 2, 4, 7, 10], [1, 3, 5, 7, 9], |
| [1, 3, 5, 9, 11], [1, 5, 7, 9, 11], [1, 3, 7, 9, 11], [3, 5, 7, 9, 11], |
| [2, 4, 6, 8, 10], [0, 4, 6, 8, 10], [0, 2, 6, 8, 10], [1, 3, 5, 7, 11], |
| [0, 2, 4, 8, 10], [0, 2, 4, 6, 8], [0, 2, 4, 6, 10], [0, 2, 4, 6, 8, 10], |
| [1, 3, 5, 7, 9, 11]] |
|
|
| def find_exact_match_variable_length(list_of_lists, target_list, uncertain_indices): |
| |
| possible_values = {idx: set() for idx in uncertain_indices} |
| for sublist in list_of_lists: |
| for idx in uncertain_indices: |
| if idx < len(sublist): |
| possible_values[idx].add(sublist[idx]) |
| |
| |
| uncertain_combinations = product(*(possible_values[idx] for idx in uncertain_indices)) |
| |
| for combination in uncertain_combinations: |
| |
| test_list = target_list[:] |
| for idx, value in zip(uncertain_indices, combination): |
| test_list[idx] = value |
| |
| |
| |
| for sublist in list_of_lists: |
| if len(sublist) >= len(test_list) and sublist[:len(test_list)] == test_list: |
| return sublist |
| |
| return None |
|
|
|
|
| def advanced_validate_chord_pitches(chord, channel_to_check = 0, return_sorted = True): |
|
|
| pitches_chord = sorted(list(set([x[4] for x in chord if 0 < x[4] < 128 and x[3] == channel_to_check]))) |
|
|
| if pitches_chord: |
|
|
| tones_chord = sorted(list(set([c % 12 for c in sorted(list(set(pitches_chord)))]))) |
|
|
| if not bad_chord(tones_chord): |
| if return_sorted: |
| chord.sort(key = lambda x: x[4], reverse=True) |
| return chord |
|
|
| else: |
| bad_chord_indices = list(set([i for s in [[tones_chord.index(a), tones_chord.index(b)] for a, b in zip(tones_chord, tones_chord[1:]) if b-a == 1] for i in s])) |
| |
| good_tones_chord = find_exact_match_variable_length(ALL_CHORDS, tones_chord, bad_chord_indices) |
| |
| if good_tones_chord is not None: |
| |
| fixed_chord = [] |
|
|
| for c in chord: |
| if c[3] == channel_to_check: |
| if (c[4] % 12) in good_tones_chord: |
| fixed_chord.append(c) |
| else: |
| fixed_chord.append(c) |
|
|
| if return_sorted: |
| fixed_chord.sort(key = lambda x: x[4], reverse=True) |
|
|
| else: |
|
|
| if 0 in tones_chord and 11 in tones_chord: |
| tones_chord.remove(0) |
|
|
| fixed_tones = [[a, b] for a, b in zip(tones_chord, tones_chord[1:]) if b-a != 1] |
|
|
| fixed_tones_chord = [] |
| for f in fixed_tones: |
| fixed_tones_chord.extend(f) |
| fixed_tones_chord = list(set(fixed_tones_chord)) |
| |
| fixed_chord = [] |
|
|
| for c in chord: |
| if c[3] == channel_to_check: |
| if (c[4] % 12) in fixed_tones_chord: |
| fixed_chord.append(c) |
| else: |
| fixed_chord.append(c) |
|
|
| if return_sorted: |
| fixed_chord.sort(key = lambda x: x[4], reverse=True) |
| |
| return fixed_chord |
|
|
| else: |
| chord.sort(key = lambda x: x[4], reverse=True) |
| return chord |
|
|
| |
|
|
| def analyze_score_pitches(score, channels_to_analyze=[0]): |
|
|
| analysis = {} |
|
|
| score_notes = [s for s in score if s[3] in channels_to_analyze] |
|
|
| cscore = chordify_score(score_notes) |
|
|
| chords_tones = [] |
|
|
| all_tones = [] |
|
|
| all_chords_good = True |
|
|
| bad_chords = [] |
|
|
| for c in cscore: |
| tones = sorted(list(set([t[4] % 12 for t in c]))) |
| chords_tones.append(tones) |
| all_tones.extend(tones) |
|
|
| if tones not in ALL_CHORDS: |
| all_chords_good = False |
| bad_chords.append(tones) |
|
|
| analysis['Number of notes'] = len(score_notes) |
| analysis['Number of chords'] = len(cscore) |
| analysis['Score tones'] = sorted(list(set(all_tones))) |
| analysis['Shortest chord'] = sorted(min(chords_tones, key=len)) |
| analysis['Longest chord'] = sorted(max(chords_tones, key=len)) |
| analysis['All chords good'] = all_chords_good |
| analysis['Bad chords'] = bad_chords |
|
|
| return analysis |
|
|
| |
|
|
| ALL_CHORDS_GROUPED = [[[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]], |
| [[0, 2], [0, 3], [0, 4], [0, 5], [0, 6], [0, 7], [0, 8], [0, 9], [0, 10], |
| [1, 3], [1, 4], [1, 5], [1, 6], [1, 7], [1, 8], [1, 9], [1, 10], [1, 11], |
| [2, 4], [2, 5], [2, 6], [2, 7], [2, 8], [2, 9], [2, 10], [2, 11], [3, 5], |
| [3, 6], [3, 7], [3, 8], [3, 9], [3, 10], [3, 11], [4, 6], [4, 7], [4, 8], |
| [4, 9], [4, 10], [4, 11], [5, 7], [5, 8], [5, 9], [5, 10], [5, 11], [6, 8], |
| [6, 9], [6, 10], [6, 11], [7, 9], [7, 10], [7, 11], [8, 10], [8, 11], |
| [9, 11]], |
| [[0, 2, 4], [0, 2, 5], [0, 3, 5], [0, 2, 6], [0, 3, 6], [0, 4, 6], [0, 2, 7], |
| [0, 3, 7], [0, 4, 7], [0, 5, 7], [0, 2, 8], [0, 3, 8], [0, 4, 8], [0, 5, 8], |
| [0, 6, 8], [0, 2, 9], [0, 3, 9], [0, 4, 9], [0, 5, 9], [0, 6, 9], [0, 7, 9], |
| [0, 2, 10], [0, 3, 10], [0, 4, 10], [0, 5, 10], [0, 6, 10], [0, 7, 10], |
| [0, 8, 10], [1, 3, 5], [1, 3, 6], [1, 4, 6], [1, 3, 7], [1, 4, 7], [1, 5, 7], |
| [1, 3, 8], [1, 4, 8], [1, 5, 8], [1, 6, 8], [1, 3, 9], [1, 4, 9], [1, 5, 9], |
| [1, 6, 9], [1, 7, 9], [1, 3, 10], [1, 4, 10], [1, 5, 10], [1, 6, 10], |
| [1, 7, 10], [1, 8, 10], [1, 3, 11], [1, 4, 11], [1, 5, 11], [1, 6, 11], |
| [1, 7, 11], [1, 8, 11], [1, 9, 11], [2, 4, 6], [2, 4, 7], [2, 5, 7], |
| [2, 4, 8], [2, 5, 8], [2, 6, 8], [2, 4, 9], [2, 5, 9], [2, 6, 9], [2, 7, 9], |
| [2, 4, 10], [2, 5, 10], [2, 6, 10], [2, 7, 10], [2, 8, 10], [2, 4, 11], |
| [2, 5, 11], [2, 6, 11], [2, 7, 11], [2, 8, 11], [2, 9, 11], [3, 5, 7], |
| [3, 5, 8], [3, 6, 8], [3, 5, 9], [3, 6, 9], [3, 7, 9], [3, 5, 10], [3, 6, 10], |
| [3, 7, 10], [3, 8, 10], [3, 5, 11], [3, 6, 11], [3, 7, 11], [3, 8, 11], |
| [3, 9, 11], [4, 6, 8], [4, 6, 9], [4, 7, 9], [4, 6, 10], [4, 7, 10], |
| [4, 8, 10], [4, 6, 11], [4, 7, 11], [4, 8, 11], [4, 9, 11], [5, 7, 9], |
| [5, 7, 10], [5, 8, 10], [5, 7, 11], [5, 8, 11], [5, 9, 11], [6, 8, 10], |
| [6, 8, 11], [6, 9, 11], [7, 9, 11]], |
| [[0, 2, 4, 6], [0, 2, 4, 7], [0, 2, 5, 7], [0, 3, 5, 7], [0, 2, 4, 8], |
| [0, 2, 5, 8], [0, 2, 6, 8], [0, 3, 5, 8], [0, 3, 6, 8], [0, 4, 6, 8], |
| [0, 2, 4, 9], [0, 2, 5, 9], [0, 2, 6, 9], [0, 2, 7, 9], [0, 3, 5, 9], |
| [0, 3, 6, 9], [0, 3, 7, 9], [0, 4, 6, 9], [0, 4, 7, 9], [0, 5, 7, 9], |
| [0, 2, 4, 10], [0, 2, 5, 10], [0, 2, 6, 10], [0, 2, 7, 10], [0, 2, 8, 10], |
| [0, 3, 5, 10], [0, 3, 6, 10], [0, 3, 7, 10], [0, 3, 8, 10], [0, 4, 6, 10], |
| [0, 4, 7, 10], [0, 4, 8, 10], [0, 5, 7, 10], [0, 5, 8, 10], [0, 6, 8, 10], |
| [1, 3, 5, 7], [1, 3, 5, 8], [1, 3, 6, 8], [1, 4, 6, 8], [1, 3, 5, 9], |
| [1, 3, 6, 9], [1, 3, 7, 9], [1, 4, 6, 9], [1, 4, 7, 9], [1, 5, 7, 9], |
| [1, 3, 5, 10], [1, 3, 6, 10], [1, 3, 7, 10], [1, 3, 8, 10], [1, 4, 6, 10], |
| [1, 4, 7, 10], [1, 4, 8, 10], [1, 5, 7, 10], [1, 5, 8, 10], [1, 6, 8, 10], |
| [1, 3, 5, 11], [1, 3, 6, 11], [1, 3, 7, 11], [1, 3, 8, 11], [1, 3, 9, 11], |
| [1, 4, 6, 11], [1, 4, 7, 11], [1, 4, 8, 11], [1, 4, 9, 11], [1, 5, 7, 11], |
| [1, 5, 8, 11], [1, 5, 9, 11], [1, 6, 8, 11], [1, 6, 9, 11], [1, 7, 9, 11], |
| [2, 4, 6, 8], [2, 4, 6, 9], [2, 4, 7, 9], [2, 5, 7, 9], [2, 4, 6, 10], |
| [2, 4, 7, 10], [2, 4, 8, 10], [2, 5, 7, 10], [2, 5, 8, 10], [2, 6, 8, 10], |
| [2, 4, 6, 11], [2, 4, 7, 11], [2, 4, 8, 11], [2, 4, 9, 11], [2, 5, 7, 11], |
| [2, 5, 8, 11], [2, 5, 9, 11], [2, 6, 8, 11], [2, 6, 9, 11], [2, 7, 9, 11], |
| [3, 5, 7, 9], [3, 5, 7, 10], [3, 5, 8, 10], [3, 6, 8, 10], [3, 5, 7, 11], |
| [3, 5, 8, 11], [3, 5, 9, 11], [3, 6, 8, 11], [3, 6, 9, 11], [3, 7, 9, 11], |
| [4, 6, 8, 10], [4, 6, 8, 11], [4, 6, 9, 11], [4, 7, 9, 11], [5, 7, 9, 11]], |
| [[0, 2, 4, 6, 8], [0, 2, 4, 6, 9], [0, 2, 4, 7, 9], [0, 2, 5, 7, 9], |
| [0, 3, 5, 7, 9], [0, 2, 4, 6, 10], [0, 2, 4, 7, 10], [0, 2, 4, 8, 10], |
| [0, 2, 5, 7, 10], [0, 2, 5, 8, 10], [0, 2, 6, 8, 10], [0, 3, 5, 7, 10], |
| [0, 3, 5, 8, 10], [0, 3, 6, 8, 10], [0, 4, 6, 8, 10], [1, 3, 5, 7, 9], |
| [1, 3, 5, 7, 10], [1, 3, 5, 8, 10], [1, 3, 6, 8, 10], [1, 4, 6, 8, 10], |
| [1, 3, 5, 7, 11], [1, 3, 5, 8, 11], [1, 3, 5, 9, 11], [1, 3, 6, 8, 11], |
| [1, 3, 6, 9, 11], [1, 3, 7, 9, 11], [1, 4, 6, 8, 11], [1, 4, 6, 9, 11], |
| [1, 4, 7, 9, 11], [1, 5, 7, 9, 11], [2, 4, 6, 8, 10], [2, 4, 6, 8, 11], |
| [2, 4, 6, 9, 11], [2, 4, 7, 9, 11], [2, 5, 7, 9, 11], [3, 5, 7, 9, 11]], |
| [[0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11]]] |
|
|
| def group_sublists_by_length(lst): |
| unique_lengths = sorted(list(set(map(len, lst))), reverse=True) |
| return [[x for x in lst if len(x) == i] for i in unique_lengths] |
|
|
| def pitches_to_tones_chord(pitches): |
| return sorted(set([p % 12 for p in pitches])) |
|
|
| def tones_chord_to_pitches(tones_chord, base_pitch=60): |
| return [t+base_pitch for t in tones_chord if 0 <= t < 12] |
|
|
| |
|
|
| def advanced_score_processor(raw_score, |
| patches_to_analyze=list(range(129)), |
| return_score_analysis=False, |
| return_enhanced_score=False, |
| return_enhanced_score_notes=False, |
| return_enhanced_monophonic_melody=False, |
| return_chordified_enhanced_score=False, |
| return_chordified_enhanced_score_with_lyrics=False, |
| return_score_tones_chords=False, |
| return_text_and_lyric_events=False |
| ): |
|
|
| '''TMIDIX Advanced Score Processor''' |
|
|
| |
|
|
| if raw_score and type(raw_score) == list: |
|
|
| num_ticks = 0 |
| num_tracks = 1 |
|
|
| basic_single_track_score = [] |
|
|
| if type(raw_score[0]) != int: |
| if len(raw_score[0]) < 5 and type(raw_score[0][0]) != str: |
| return ['Check score for errors and compatibility!'] |
|
|
| else: |
| basic_single_track_score = copy.deepcopy(raw_score) |
| |
| else: |
| num_ticks = raw_score[0] |
| while num_tracks < len(raw_score): |
| for event in raw_score[num_tracks]: |
| ev = copy.deepcopy(event) |
| basic_single_track_score.append(ev) |
| num_tracks += 1 |
|
|
| basic_single_track_score.sort(key=lambda x: x[4] if x[0] == 'note' else 128, reverse=True) |
| basic_single_track_score.sort(key=lambda x: x[1]) |
|
|
| enhanced_single_track_score = [] |
| patches = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] |
| all_score_patches = [] |
| num_patch_changes = 0 |
|
|
| for event in basic_single_track_score: |
| if event[0] == 'patch_change': |
| patches[event[2]] = event[3] |
| enhanced_single_track_score.append(event) |
| num_patch_changes += 1 |
|
|
| if event[0] == 'note': |
| if event[3] != 9: |
| event.extend([patches[event[3]]]) |
| all_score_patches.extend([patches[event[3]]]) |
| else: |
| event.extend([128]) |
| all_score_patches.extend([128]) |
|
|
| if enhanced_single_track_score: |
| if (event[1] == enhanced_single_track_score[-1][1]): |
| if ([event[3], event[4]] != enhanced_single_track_score[-1][3:5]): |
| enhanced_single_track_score.append(event) |
| else: |
| enhanced_single_track_score.append(event) |
|
|
| else: |
| enhanced_single_track_score.append(event) |
|
|
| if event[0] not in ['note', 'patch_change']: |
| enhanced_single_track_score.append(event) |
|
|
| enhanced_single_track_score.sort(key=lambda x: x[6] if x[0] == 'note' else -1) |
| enhanced_single_track_score.sort(key=lambda x: x[4] if x[0] == 'note' else 128, reverse=True) |
| enhanced_single_track_score.sort(key=lambda x: x[1]) |
|
|
| |
|
|
| cscore = [] |
| cescore = [] |
| chords_tones = [] |
| tones_chords = [] |
| all_tones = [] |
| all_chords_good = True |
| bad_chords = [] |
| bad_chords_count = 0 |
| score_notes = [] |
| score_pitches = [] |
| score_patches = [] |
| num_text_events = 0 |
| num_lyric_events = 0 |
| num_other_events = 0 |
| text_and_lyric_events = [] |
| text_and_lyric_events_latin = None |
|
|
| analysis = {} |
|
|
| score_notes = [s for s in enhanced_single_track_score if s[0] == 'note' and s[6] in patches_to_analyze] |
| score_patches = [sn[6] for sn in score_notes] |
|
|
| if return_text_and_lyric_events: |
| text_and_lyric_events = [e for e in enhanced_single_track_score if e[0] in ['text_event', 'lyric']] |
| |
| if text_and_lyric_events: |
| text_and_lyric_events_latin = True |
| for e in text_and_lyric_events: |
| try: |
| tle = str(e[2].decode()) |
| except: |
| tle = str(e[2]) |
|
|
| for c in tle: |
| if not 0 <= ord(c) < 128: |
| text_and_lyric_events_latin = False |
|
|
| if (return_chordified_enhanced_score or return_score_analysis) and any(elem in patches_to_analyze for elem in score_patches): |
|
|
| cescore = chordify_score([num_ticks, enhanced_single_track_score]) |
|
|
| if return_score_analysis: |
|
|
| cscore = chordify_score(score_notes) |
| |
| score_pitches = [sn[4] for sn in score_notes] |
| |
| text_events = [e for e in enhanced_single_track_score if e[0] == 'text_event'] |
| num_text_events = len(text_events) |
|
|
| lyric_events = [e for e in enhanced_single_track_score if e[0] == 'lyric'] |
| num_lyric_events = len(lyric_events) |
|
|
| other_events = [e for e in enhanced_single_track_score if e[0] not in ['note', 'patch_change', 'text_event', 'lyric']] |
| num_other_events = len(other_events) |
| |
| for c in cscore: |
| tones = sorted(set([t[4] % 12 for t in c if t[3] != 9])) |
|
|
| if tones: |
| chords_tones.append(tones) |
| all_tones.extend(tones) |
|
|
| if tones not in ALL_CHORDS: |
| all_chords_good = False |
| bad_chords.append(tones) |
| bad_chords_count += 1 |
| |
| analysis['Number of ticks per quarter note'] = num_ticks |
| analysis['Number of tracks'] = num_tracks |
| analysis['Number of all events'] = len(enhanced_single_track_score) |
| analysis['Number of patch change events'] = num_patch_changes |
| analysis['Number of text events'] = num_text_events |
| analysis['Number of lyric events'] = num_lyric_events |
| analysis['All text and lyric events Latin'] = text_and_lyric_events_latin |
| analysis['Number of other events'] = num_other_events |
| analysis['Number of score notes'] = len(score_notes) |
| analysis['Number of score chords'] = len(cscore) |
| analysis['Score patches'] = sorted(set(score_patches)) |
| analysis['Score pitches'] = sorted(set(score_pitches)) |
| analysis['Score tones'] = sorted(set(all_tones)) |
| if chords_tones: |
| analysis['Shortest chord'] = sorted(min(chords_tones, key=len)) |
| analysis['Longest chord'] = sorted(max(chords_tones, key=len)) |
| analysis['All chords good'] = all_chords_good |
| analysis['Number of bad chords'] = bad_chords_count |
| analysis['Bad chords'] = sorted([list(c) for c in set(tuple(bc) for bc in bad_chords)]) |
|
|
| else: |
| analysis['Error'] = 'Provided score does not have specified patches to analyse' |
| analysis['Provided patches to analyse'] = sorted(patches_to_analyze) |
| analysis['Patches present in the score'] = sorted(set(all_score_patches)) |
|
|
| if return_enhanced_monophonic_melody: |
|
|
| score_notes_copy = copy.deepcopy(score_notes) |
| chordified_score_notes = chordify_score(score_notes_copy) |
|
|
| melody = [c[0] for c in chordified_score_notes] |
|
|
| fixed_melody = [] |
|
|
| for i in range(len(melody)-1): |
| note = melody[i] |
| nmt = melody[i+1][1] |
|
|
| if note[1]+note[2] >= nmt: |
| note_dur = nmt-note[1]-1 |
| else: |
| note_dur = note[2] |
|
|
| melody[i][2] = note_dur |
|
|
| fixed_melody.append(melody[i]) |
| fixed_melody.append(melody[-1]) |
|
|
| if return_score_tones_chords: |
| cscore = chordify_score(score_notes) |
| for c in cscore: |
| tones_chord = sorted(set([t[4] % 12 for t in c if t[3] != 9])) |
| if tones_chord: |
| tones_chords.append(tones_chord) |
|
|
| if return_chordified_enhanced_score_with_lyrics: |
| score_with_lyrics = [e for e in enhanced_single_track_score if e[0] in ['note', 'text_event', 'lyric']] |
| chordified_enhanced_score_with_lyrics = chordify_score(score_with_lyrics) |
| |
| |
|
|
| requested_data = [] |
|
|
| if return_score_analysis and analysis: |
| requested_data.append([[k, v] for k, v in analysis.items()]) |
|
|
| if return_enhanced_score and enhanced_single_track_score: |
| requested_data.append([num_ticks, enhanced_single_track_score]) |
|
|
| if return_enhanced_score_notes and score_notes: |
| requested_data.append(score_notes) |
|
|
| if return_enhanced_monophonic_melody and fixed_melody: |
| requested_data.append(fixed_melody) |
| |
| if return_chordified_enhanced_score and cescore: |
| requested_data.append(cescore) |
|
|
| if return_chordified_enhanced_score_with_lyrics and chordified_enhanced_score_with_lyrics: |
| requested_data.append(chordified_enhanced_score_with_lyrics) |
|
|
| if return_score_tones_chords and tones_chords: |
| requested_data.append(tones_chords) |
|
|
| if return_text_and_lyric_events and text_and_lyric_events: |
| requested_data.append(text_and_lyric_events) |
|
|
| return requested_data |
| |
| else: |
| return ['Check score for errors and compatibility!'] |
|
|
| |
|
|
| import random |
| import copy |
|
|
| |
|
|
| def replace_bad_tones_chord(bad_tones_chord): |
| bad_chord_p = [0] * 12 |
| for b in bad_tones_chord: |
| bad_chord_p[b] = 1 |
|
|
| match_ratios = [] |
| good_chords = [] |
| for c in ALL_CHORDS: |
| good_chord_p = [0] * 12 |
| for cc in c: |
| good_chord_p[cc] = 1 |
|
|
| good_chords.append(good_chord_p) |
| match_ratios.append(sum(i == j for i, j in zip(good_chord_p, bad_chord_p)) / len(good_chord_p)) |
|
|
| best_good_chord = good_chords[match_ratios.index(max(match_ratios))] |
|
|
| replaced_chord = [] |
| for i in range(len(best_good_chord)): |
| if best_good_chord[i] == 1: |
| replaced_chord.append(i) |
|
|
| return [replaced_chord, max(match_ratios)] |
|
|
| |
|
|
| def check_and_fix_chord(chord, |
| channel_index=3, |
| pitch_index=4 |
| ): |
|
|
| tones_chord = sorted(set([t[pitch_index] % 12 for t in chord if t[channel_index] != 9])) |
|
|
| notes_events = [t for t in chord if t[channel_index] != 9] |
| notes_events.sort(key=lambda x: x[pitch_index], reverse=True) |
|
|
| drums_events = [t for t in chord if t[channel_index] == 9] |
|
|
| checked_and_fixed_chord = [] |
|
|
| if tones_chord: |
| |
| new_tones_chord = advanced_check_and_fix_tones_chord(tones_chord, high_pitch=notes_events[0][pitch_index]) |
|
|
| if new_tones_chord != tones_chord: |
|
|
| if len(notes_events) > 1: |
| checked_and_fixed_chord.extend([notes_events[0]]) |
| for cc in notes_events[1:]: |
| if cc[channel_index] != 9: |
| if (cc[pitch_index] % 12) in new_tones_chord: |
| checked_and_fixed_chord.extend([cc]) |
| checked_and_fixed_chord.extend(drums_events) |
| else: |
| checked_and_fixed_chord.extend([notes_events[0]]) |
| else: |
| checked_and_fixed_chord.extend(chord) |
| else: |
| checked_and_fixed_chord.extend(chord) |
|
|
| checked_and_fixed_chord.sort(key=lambda x: x[pitch_index], reverse=True) |
|
|
| return checked_and_fixed_chord |
|
|
| |
|
|
| def find_similar_tones_chord(tones_chord, |
| max_match_threshold=1, |
| randomize_chords_matches=False, |
| custom_chords_list=[]): |
| chord_p = [0] * 12 |
| for b in tones_chord: |
| chord_p[b] = 1 |
|
|
| match_ratios = [] |
| good_chords = [] |
|
|
| if custom_chords_list: |
| CHORDS = copy.deepcopy([list(x) for x in set(tuple(t) for t in custom_chords_list)]) |
| else: |
| CHORDS = copy.deepcopy(ALL_CHORDS) |
|
|
| if randomize_chords_matches: |
| random.shuffle(CHORDS) |
|
|
| for c in CHORDS: |
| good_chord_p = [0] * 12 |
| for cc in c: |
| good_chord_p[cc] = 1 |
|
|
| good_chords.append(good_chord_p) |
| match_ratio = sum(i == j for i, j in zip(good_chord_p, chord_p)) / len(good_chord_p) |
| if match_ratio < max_match_threshold: |
| match_ratios.append(match_ratio) |
| else: |
| match_ratios.append(0) |
|
|
| best_good_chord = good_chords[match_ratios.index(max(match_ratios))] |
|
|
| similar_chord = [] |
| for i in range(len(best_good_chord)): |
| if best_good_chord[i] == 1: |
| similar_chord.append(i) |
|
|
| return [similar_chord, max(match_ratios)] |
|
|
| |
|
|
| def generate_tones_chords_progression(number_of_chords_to_generate=100, |
| start_tones_chord=[], |
| custom_chords_list=[]): |
|
|
| if start_tones_chord: |
| start_chord = start_tones_chord |
| else: |
| start_chord = random.choice(ALL_CHORDS) |
|
|
| chord = [] |
|
|
| chords_progression = [start_chord] |
|
|
| for i in range(number_of_chords_to_generate): |
| if not chord: |
| chord = start_chord |
|
|
| if custom_chords_list: |
| chord = find_similar_tones_chord(chord, randomize_chords_matches=True, custom_chords_list=custom_chords_list)[0] |
| else: |
| chord = find_similar_tones_chord(chord, randomize_chords_matches=True)[0] |
| |
| chords_progression.append(chord) |
|
|
| return chords_progression |
|
|
| |
|
|
| def ascii_texts_search(texts = ['text1', 'text2', 'text3'], |
| search_query = 'Once upon a time...', |
| deterministic_matching = False |
| ): |
|
|
| texts_copy = texts |
|
|
| if not deterministic_matching: |
| texts_copy = copy.deepcopy(texts) |
| random.shuffle(texts_copy) |
|
|
| clean_texts = [] |
|
|
| for t in texts_copy: |
| text_words_list = [at.split(chr(32)) for at in t.split(chr(10))] |
| |
| clean_text_words_list = [] |
| for twl in text_words_list: |
| for w in twl: |
| clean_text_words_list.append(''.join(filter(str.isalpha, w.lower()))) |
| |
| clean_texts.append(clean_text_words_list) |
|
|
| text_search_query = [at.split(chr(32)) for at in search_query.split(chr(10))] |
| clean_text_search_query = [] |
| for w in text_search_query: |
| for ww in w: |
| clean_text_search_query.append(''.join(filter(str.isalpha, ww.lower()))) |
|
|
| if clean_texts[0] and clean_text_search_query: |
| texts_match_ratios = [] |
| words_match_indexes = [] |
| for t in clean_texts: |
| word_match_count = 0 |
| wmis = [] |
|
|
| for c in clean_text_search_query: |
| if c in t: |
| word_match_count += 1 |
| wmis.append(t.index(c)) |
| else: |
| wmis.append(-1) |
|
|
| words_match_indexes.append(wmis) |
| words_match_indexes_consequtive = all(abs(b) - abs(a) == 1 for a, b in zip(wmis, wmis[1:])) |
| words_match_indexes_consequtive_ratio = sum([abs(b) - abs(a) == 1 for a, b in zip(wmis, wmis[1:])]) / len(wmis) |
|
|
| if words_match_indexes_consequtive: |
| texts_match_ratios.append(word_match_count / len(clean_text_search_query)) |
| else: |
| texts_match_ratios.append(((word_match_count / len(clean_text_search_query)) + words_match_indexes_consequtive_ratio) / 2) |
|
|
| if texts_match_ratios: |
| max_text_match_ratio = max(texts_match_ratios) |
| max_match_ratio_text = texts_copy[texts_match_ratios.index(max_text_match_ratio)] |
| max_text_words_match_indexes = words_match_indexes[texts_match_ratios.index(max_text_match_ratio)] |
|
|
| return [max_match_ratio_text, max_text_match_ratio, max_text_words_match_indexes] |
| |
| else: |
| return None |
|
|
| |
|
|
| def ascii_text_words_counter(ascii_text): |
|
|
| text_words_list = [at.split(chr(32)) for at in ascii_text.split(chr(10))] |
|
|
| clean_text_words_list = [] |
| for twl in text_words_list: |
| for w in twl: |
| wo = '' |
| for ww in w.lower(): |
| if 96 < ord(ww) < 123: |
| wo += ww |
| if wo != '': |
| clean_text_words_list.append(wo) |
|
|
| words = {} |
| for i in clean_text_words_list: |
| words[i] = words.get(i, 0) + 1 |
|
|
| words_sorted = dict(sorted(words.items(), key=lambda item: item[1], reverse=True)) |
|
|
| return len(clean_text_words_list), words_sorted, clean_text_words_list |
| |
| |
|
|
| def check_and_fix_tones_chord(tones_chord): |
|
|
| lst = tones_chord |
|
|
| if len(lst) == 2: |
| if lst[1] - lst[0] == 1: |
| return [lst[-1]] |
| else: |
| if 0 in lst and 11 in lst: |
| lst.remove(0) |
| return lst |
|
|
| non_consecutive = [lst[0]] |
|
|
| if len(lst) > 2: |
| for i in range(1, len(lst) - 1): |
| if lst[i-1] + 1 != lst[i] and lst[i] + 1 != lst[i+1]: |
| non_consecutive.append(lst[i]) |
| non_consecutive.append(lst[-1]) |
|
|
| if 0 in non_consecutive and 11 in non_consecutive: |
| non_consecutive.remove(0) |
|
|
| return non_consecutive |
|
|
| |
|
|
| def find_closest_tone(tones, tone): |
| return min(tones, key=lambda x:abs(x-tone)) |
|
|
| def advanced_check_and_fix_tones_chord(tones_chord, high_pitch=0): |
|
|
| lst = tones_chord |
|
|
| if 0 < high_pitch < 128: |
| ht = high_pitch % 12 |
| else: |
| ht = 12 |
|
|
| cht = find_closest_tone(lst, ht) |
|
|
| if len(lst) == 2: |
| if lst[1] - lst[0] == 1: |
| return [cht] |
| else: |
| if 0 in lst and 11 in lst: |
| if find_closest_tone([0, 11], cht) == 11: |
| lst.remove(0) |
| else: |
| lst.remove(11) |
| return lst |
|
|
| non_consecutive = [] |
|
|
| if len(lst) > 2: |
| for i in range(0, len(lst) - 1): |
| if lst[i] + 1 != lst[i+1]: |
| non_consecutive.append(lst[i]) |
| if lst[-1] - lst[-2] > 1: |
| non_consecutive.append(lst[-1]) |
|
|
| if cht not in non_consecutive: |
| non_consecutive.append(cht) |
| non_consecutive.sort() |
| if any(abs(non_consecutive[i+1] - non_consecutive[i]) == 1 for i in range(len(non_consecutive) - 1)): |
| final_list = [x for x in non_consecutive if x == cht or abs(x - cht) > 1] |
| else: |
| final_list = non_consecutive |
|
|
| else: |
| final_list = non_consecutive |
|
|
| if 0 in final_list and 11 in final_list: |
| if find_closest_tone([0, 11], cht) == 11: |
| final_list.remove(0) |
| else: |
| final_list.remove(11) |
|
|
| if cht in final_list or ht in final_list: |
| return final_list |
| else: |
| return ['Error'] |
|
|
| |
|
|
| def create_similarity_matrix(list_of_values, matrix_length=0): |
|
|
| counts = Counter(list_of_values).items() |
|
|
| if matrix_length > 0: |
| sim_matrix = [0] * max(matrix_length, len(list_of_values)) |
| else: |
| sim_matrix = [0] * len(counts) |
|
|
| for c in counts: |
| sim_matrix[c[0]] = c[1] |
|
|
| similarity_matrix = [[0] * len(sim_matrix) for _ in range(len(sim_matrix))] |
|
|
| for i in range(len(sim_matrix)): |
| for j in range(len(sim_matrix)): |
| if max(sim_matrix[i], sim_matrix[j]) != 0: |
| similarity_matrix[i][j] = min(sim_matrix[i], sim_matrix[j]) / max(sim_matrix[i], sim_matrix[j]) |
|
|
| return similarity_matrix, sim_matrix |
|
|
| |
|
|
| def ceil_with_precision(value, decimal_places): |
| factor = 10 ** decimal_places |
| return math.ceil(value * factor) / factor |
|
|
| |
|
|
| def augment_enhanced_score_notes(enhanced_score_notes, |
| timings_divider=16, |
| full_sorting=True, |
| timings_shift=0, |
| pitch_shift=0, |
| legacy_timings=False |
| ): |
|
|
| esn = copy.deepcopy(enhanced_score_notes) |
|
|
| pe = enhanced_score_notes[0] |
|
|
| abs_time = max(0, int(enhanced_score_notes[0][1] / timings_divider)) |
|
|
| for i, e in enumerate(esn): |
| |
| dtime = (e[1] / timings_divider) - (pe[1] / timings_divider) |
|
|
| if 0.5 < dtime < 1: |
| dtime = 1 |
| |
| else: |
| dtime = int(dtime) |
|
|
| if legacy_timings: |
| abs_time = int(e[1] / timings_divider) + timings_shift |
|
|
| else: |
| abs_time += dtime |
|
|
| e[1] = max(0, abs_time + timings_shift) |
|
|
| e[2] = max(1, int(e[2] / timings_divider)) + timings_shift |
| |
| e[4] = max(1, min(127, e[4] + pitch_shift)) |
|
|
| pe = enhanced_score_notes[i] |
|
|
| if full_sorting: |
|
|
| |
| esn.sort(key=lambda x: x[6]) |
| esn.sort(key=lambda x: x[4], reverse=True) |
| esn.sort(key=lambda x: x[1]) |
|
|
| return esn |
|
|
| |
|
|
| def stack_list(lst, base=12): |
| return sum(j * base**i for i, j in enumerate(lst[::-1])) |
|
|
| def destack_list(num, base=12): |
| lst = [] |
| while num: |
| lst.append(num % base) |
| num //= base |
| return lst[::-1] |
|
|
| |
|
|
| def extract_melody(chordified_enhanced_score, |
| melody_range=[48, 84], |
| melody_channel=0, |
| melody_patch=0, |
| melody_velocity=0, |
| stacked_melody=False, |
| stacked_melody_base_pitch=60 |
| ): |
|
|
| if stacked_melody: |
|
|
| |
| all_pitches_chords = [] |
| for e in chordified_enhanced_score: |
| all_pitches_chords.append(sorted(set([p[4] for p in e]), reverse=True)) |
| |
| melody_score = [] |
| for i, chord in enumerate(chordified_enhanced_score): |
|
|
| if melody_velocity > 0: |
| vel = melody_velocity |
| else: |
| vel = chord[0][5] |
|
|
| melody_score.append(['note', chord[0][1], chord[0][2], melody_channel, stacked_melody_base_pitch+(stack_list([p % 12 for p in all_pitches_chords[i]]) % 12), vel, melody_patch]) |
| |
| else: |
|
|
| melody_score = copy.deepcopy([c[0] for c in chordified_enhanced_score if c[0][3] != 9]) |
| |
| for e in melody_score: |
| |
| e[3] = melody_channel |
|
|
| if melody_velocity > 0: |
| e[5] = melody_velocity |
|
|
| e[6] = melody_patch |
|
|
| if e[4] < melody_range[0]: |
| e[4] = (e[4] % 12) + melody_range[0] |
| |
| if e[4] >= melody_range[1]: |
| e[4] = (e[4] % 12) + (melody_range[1]-12) |
|
|
| return fix_monophonic_score_durations(melody_score) |
|
|
| |
|
|
| def flip_enhanced_score_notes(enhanced_score_notes): |
|
|
| min_pitch = min([e[4] for e in enhanced_score_notes if e[3] != 9]) |
|
|
| fliped_score_pitches = [127 - e[4]for e in enhanced_score_notes if e[3] != 9] |
|
|
| delta_min_pitch = min_pitch - min([p for p in fliped_score_pitches]) |
|
|
| output_score = copy.deepcopy(enhanced_score_notes) |
|
|
| for e in output_score: |
| if e[3] != 9: |
| e[4] = (127 - e[4]) + delta_min_pitch |
|
|
| return output_score |
|
|
| |
|
|
| ALL_CHORDS_SORTED = [[0], [0, 2], [0, 3], [0, 4], [0, 2, 4], [0, 5], [0, 2, 5], [0, 3, 5], [0, 6], |
| [0, 2, 6], [0, 3, 6], [0, 4, 6], [0, 2, 4, 6], [0, 7], [0, 2, 7], [0, 3, 7], |
| [0, 4, 7], [0, 5, 7], [0, 2, 4, 7], [0, 2, 5, 7], [0, 3, 5, 7], [0, 8], |
| [0, 2, 8], [0, 3, 8], [0, 4, 8], [0, 5, 8], [0, 6, 8], [0, 2, 4, 8], |
| [0, 2, 5, 8], [0, 2, 6, 8], [0, 3, 5, 8], [0, 3, 6, 8], [0, 4, 6, 8], |
| [0, 2, 4, 6, 8], [0, 9], [0, 2, 9], [0, 3, 9], [0, 4, 9], [0, 5, 9], [0, 6, 9], |
| [0, 7, 9], [0, 2, 4, 9], [0, 2, 5, 9], [0, 2, 6, 9], [0, 2, 7, 9], |
| [0, 3, 5, 9], [0, 3, 6, 9], [0, 3, 7, 9], [0, 4, 6, 9], [0, 4, 7, 9], |
| [0, 5, 7, 9], [0, 2, 4, 6, 9], [0, 2, 4, 7, 9], [0, 2, 5, 7, 9], |
| [0, 3, 5, 7, 9], [0, 10], [0, 2, 10], [0, 3, 10], [0, 4, 10], [0, 5, 10], |
| [0, 6, 10], [0, 7, 10], [0, 8, 10], [0, 2, 4, 10], [0, 2, 5, 10], |
| [0, 2, 6, 10], [0, 2, 7, 10], [0, 2, 8, 10], [0, 3, 5, 10], [0, 3, 6, 10], |
| [0, 3, 7, 10], [0, 3, 8, 10], [0, 4, 6, 10], [0, 4, 7, 10], [0, 4, 8, 10], |
| [0, 5, 7, 10], [0, 5, 8, 10], [0, 6, 8, 10], [0, 2, 4, 6, 10], |
| [0, 2, 4, 7, 10], [0, 2, 4, 8, 10], [0, 2, 5, 7, 10], [0, 2, 5, 8, 10], |
| [0, 2, 6, 8, 10], [0, 3, 5, 7, 10], [0, 3, 5, 8, 10], [0, 3, 6, 8, 10], |
| [0, 4, 6, 8, 10], [0, 2, 4, 6, 8, 10], [1], [1, 3], [1, 4], [1, 5], [1, 3, 5], |
| [1, 6], [1, 3, 6], [1, 4, 6], [1, 7], [1, 3, 7], [1, 4, 7], [1, 5, 7], |
| [1, 3, 5, 7], [1, 8], [1, 3, 8], [1, 4, 8], [1, 5, 8], [1, 6, 8], [1, 3, 5, 8], |
| [1, 3, 6, 8], [1, 4, 6, 8], [1, 9], [1, 3, 9], [1, 4, 9], [1, 5, 9], [1, 6, 9], |
| [1, 7, 9], [1, 3, 5, 9], [1, 3, 6, 9], [1, 3, 7, 9], [1, 4, 6, 9], |
| [1, 4, 7, 9], [1, 5, 7, 9], [1, 3, 5, 7, 9], [1, 10], [1, 3, 10], [1, 4, 10], |
| [1, 5, 10], [1, 6, 10], [1, 7, 10], [1, 8, 10], [1, 3, 5, 10], [1, 3, 6, 10], |
| [1, 3, 7, 10], [1, 3, 8, 10], [1, 4, 6, 10], [1, 4, 7, 10], [1, 4, 8, 10], |
| [1, 5, 7, 10], [1, 5, 8, 10], [1, 6, 8, 10], [1, 3, 5, 7, 10], |
| [1, 3, 5, 8, 10], [1, 3, 6, 8, 10], [1, 4, 6, 8, 10], [1, 11], [1, 3, 11], |
| [1, 4, 11], [1, 5, 11], [1, 6, 11], [1, 7, 11], [1, 8, 11], [1, 9, 11], |
| [1, 3, 5, 11], [1, 3, 6, 11], [1, 3, 7, 11], [1, 3, 8, 11], [1, 3, 9, 11], |
| [1, 4, 6, 11], [1, 4, 7, 11], [1, 4, 8, 11], [1, 4, 9, 11], [1, 5, 7, 11], |
| [1, 5, 8, 11], [1, 5, 9, 11], [1, 6, 8, 11], [1, 6, 9, 11], [1, 7, 9, 11], |
| [1, 3, 5, 7, 11], [1, 3, 5, 8, 11], [1, 3, 5, 9, 11], [1, 3, 6, 8, 11], |
| [1, 3, 6, 9, 11], [1, 3, 7, 9, 11], [1, 4, 6, 8, 11], [1, 4, 6, 9, 11], |
| [1, 4, 7, 9, 11], [1, 5, 7, 9, 11], [1, 3, 5, 7, 9, 11], [2], [2, 4], [2, 5], |
| [2, 6], [2, 4, 6], [2, 7], [2, 4, 7], [2, 5, 7], [2, 8], [2, 4, 8], [2, 5, 8], |
| [2, 6, 8], [2, 4, 6, 8], [2, 9], [2, 4, 9], [2, 5, 9], [2, 6, 9], [2, 7, 9], |
| [2, 4, 6, 9], [2, 4, 7, 9], [2, 5, 7, 9], [2, 10], [2, 4, 10], [2, 5, 10], |
| [2, 6, 10], [2, 7, 10], [2, 8, 10], [2, 4, 6, 10], [2, 4, 7, 10], |
| [2, 4, 8, 10], [2, 5, 7, 10], [2, 5, 8, 10], [2, 6, 8, 10], [2, 4, 6, 8, 10], |
| [2, 11], [2, 4, 11], [2, 5, 11], [2, 6, 11], [2, 7, 11], [2, 8, 11], |
| [2, 9, 11], [2, 4, 6, 11], [2, 4, 7, 11], [2, 4, 8, 11], [2, 4, 9, 11], |
| [2, 5, 7, 11], [2, 5, 8, 11], [2, 5, 9, 11], [2, 6, 8, 11], [2, 6, 9, 11], |
| [2, 7, 9, 11], [2, 4, 6, 8, 11], [2, 4, 6, 9, 11], [2, 4, 7, 9, 11], |
| [2, 5, 7, 9, 11], [3], [3, 5], [3, 6], [3, 7], [3, 5, 7], [3, 8], [3, 5, 8], |
| [3, 6, 8], [3, 9], [3, 5, 9], [3, 6, 9], [3, 7, 9], [3, 5, 7, 9], [3, 10], |
| [3, 5, 10], [3, 6, 10], [3, 7, 10], [3, 8, 10], [3, 5, 7, 10], [3, 5, 8, 10], |
| [3, 6, 8, 10], [3, 11], [3, 5, 11], [3, 6, 11], [3, 7, 11], [3, 8, 11], |
| [3, 9, 11], [3, 5, 7, 11], [3, 5, 8, 11], [3, 5, 9, 11], [3, 6, 8, 11], |
| [3, 6, 9, 11], [3, 7, 9, 11], [3, 5, 7, 9, 11], [4], [4, 6], [4, 7], [4, 8], |
| [4, 6, 8], [4, 9], [4, 6, 9], [4, 7, 9], [4, 10], [4, 6, 10], [4, 7, 10], |
| [4, 8, 10], [4, 6, 8, 10], [4, 11], [4, 6, 11], [4, 7, 11], [4, 8, 11], |
| [4, 9, 11], [4, 6, 8, 11], [4, 6, 9, 11], [4, 7, 9, 11], [5], [5, 7], [5, 8], |
| [5, 9], [5, 7, 9], [5, 10], [5, 7, 10], [5, 8, 10], [5, 11], [5, 7, 11], |
| [5, 8, 11], [5, 9, 11], [5, 7, 9, 11], [6], [6, 8], [6, 9], [6, 10], |
| [6, 8, 10], [6, 11], [6, 8, 11], [6, 9, 11], [7], [7, 9], [7, 10], [7, 11], |
| [7, 9, 11], [8], [8, 10], [8, 11], [9], [9, 11], [10], [11]] |
|
|
| |
|
|
| MIDI_Instruments_Families = { |
| 0: 'Piano Family', |
| 1: 'Chromatic Percussion Family', |
| 2: 'Organ Family', |
| 3: 'Guitar Family', |
| 4: 'Bass Family', |
| 5: 'Strings Family', |
| 6: 'Ensemble Family', |
| 7: 'Brass Family', |
| 8: 'Reed Family', |
| 9: 'Pipe Family', |
| 10: 'Synth Lead Family', |
| 11: 'Synth Pad Family', |
| 12: 'Synth Effects Family', |
| 13: 'Ethnic Family', |
| 14: 'Percussive Family', |
| 15: 'Sound Effects Family', |
| 16: 'Drums Family', |
| -1: 'Unknown Family', |
| } |
|
|
| |
|
|
| def patch_to_instrument_family(MIDI_patch, drums_patch=128): |
|
|
| if 0 <= MIDI_patch < 128: |
| return MIDI_patch // 8, MIDI_Instruments_Families[MIDI_patch // 8] |
|
|
| elif MIDI_patch == drums_patch: |
| return MIDI_patch // 8, MIDI_Instruments_Families[16] |
|
|
| else: |
| return -1, MIDI_Instruments_Families[-1] |
|
|
| |
|
|
| def patch_list_from_enhanced_score_notes(enhanced_score_notes, |
| default_patch=0, |
| drums_patch=9, |
| verbose=False |
| ): |
|
|
| patches = [-1] * 16 |
|
|
| for idx, e in enumerate(enhanced_score_notes): |
| if e[3] != 9: |
| if patches[e[3]] == -1: |
| patches[e[3]] = e[6] |
| else: |
| if patches[e[3]] != e[6]: |
| if e[6] in patches: |
| e[3] = patches.index(e[6]) |
| else: |
| if -1 in patches: |
| patches[patches.index(-1)] = e[6] |
| else: |
| patches[-1] = e[6] |
|
|
| if verbose: |
| print('=' * 70) |
| print('WARNING! Composition has more than 15 patches!') |
| print('Conflict note number:', idx) |
| print('Conflict channel number:', e[3]) |
| print('Conflict patch number:', e[6]) |
|
|
| patches = [p if p != -1 else default_patch for p in patches] |
|
|
| patches[9] = drums_patch |
|
|
| if verbose: |
| print('=' * 70) |
| print('Composition patches') |
| print('=' * 70) |
| for c, p in enumerate(patches): |
| print('Cha', str(c).zfill(2), '---', str(p).zfill(3), Number2patch[p]) |
| print('=' * 70) |
|
|
| return patches |
|
|
| |
|
|
| def patch_enhanced_score_notes(enhanced_score_notes, |
| default_patch=0, |
| drums_patch=9, |
| verbose=False |
| ): |
| |
| |
| |
| enhanced_score_notes_with_patch_changes = [] |
|
|
| patches = [-1] * 16 |
|
|
| overflow_idx = -1 |
|
|
| for idx, e in enumerate(enhanced_score_notes): |
| if e[3] != 9: |
| if patches[e[3]] == -1: |
| patches[e[3]] = e[6] |
| else: |
| if patches[e[3]] != e[6]: |
| if e[6] in patches: |
| e[3] = patches.index(e[6]) |
| else: |
| if -1 in patches: |
| patches[patches.index(-1)] = e[6] |
| else: |
| overflow_idx = idx |
| break |
|
|
| enhanced_score_notes_with_patch_changes.append(e) |
|
|
| |
|
|
| overflow_patches = [] |
|
|
| if overflow_idx != -1: |
| for idx, e in enumerate(enhanced_score_notes[overflow_idx:]): |
| if e[3] != 9: |
| if e[6] not in patches: |
| if e[6] not in overflow_patches: |
| overflow_patches.append(e[6]) |
| enhanced_score_notes_with_patch_changes.append(['patch_change', e[1], e[3], e[6]]) |
| else: |
| e[3] = patches.index(e[6]) |
|
|
| enhanced_score_notes_with_patch_changes.append(e) |
|
|
| |
|
|
| patches = [p if p != -1 else default_patch for p in patches] |
|
|
| patches[9] = drums_patch |
|
|
| |
|
|
| if verbose: |
| print('=' * 70) |
| print('Composition patches') |
| print('=' * 70) |
| for c, p in enumerate(patches): |
| print('Cha', str(c).zfill(2), '---', str(p).zfill(3), Number2patch[p]) |
| print('=' * 70) |
|
|
| if overflow_patches: |
| print('Extra composition patches') |
| print('=' * 70) |
| for c, p in enumerate(overflow_patches): |
| print(str(p).zfill(3), Number2patch[p]) |
| print('=' * 70) |
|
|
| return enhanced_score_notes_with_patch_changes, patches, overflow_patches |
|
|
| |
|
|
| def create_enhanced_monophonic_melody(monophonic_melody): |
|
|
| enhanced_monophonic_melody = [] |
|
|
| for i, note in enumerate(monophonic_melody[:-1]): |
|
|
| enhanced_monophonic_melody.append(note) |
|
|
| if note[1]+note[2] < monophonic_melody[i+1][1]: |
| |
| delta_time = monophonic_melody[i+1][1] - (note[1]+note[2]) |
| enhanced_monophonic_melody.append(['silence', note[1]+note[2], delta_time, note[3], 0, 0, note[6]]) |
| |
| enhanced_monophonic_melody.append(monophonic_melody[-1]) |
|
|
| return enhanced_monophonic_melody |
|
|
| |
|
|
| def frame_monophonic_melody(monophonic_melody, min_frame_time_threshold=10): |
|
|
| mzip = list(zip(monophonic_melody[:-1], monophonic_melody[1:])) |
|
|
| times_counts = Counter([(b[1]-a[1]) for a, b in mzip]).most_common() |
|
|
| mc_time = next((item for item, count in times_counts if item >= min_frame_time_threshold), min_frame_time_threshold) |
|
|
| times = [(b[1]-a[1]) // mc_time for a, b in mzip] + [monophonic_melody[-1][2] // mc_time] |
|
|
| framed_melody = [] |
|
|
| for i, note in enumerate(monophonic_melody): |
| |
| stime = note[1] |
| count = times[i] |
| |
| if count != 0: |
| for j in range(count): |
|
|
| new_note = copy.deepcopy(note) |
| new_note[1] = stime + (j * mc_time) |
| new_note[2] = mc_time |
| framed_melody.append(new_note) |
| |
| else: |
| framed_melody.append(note) |
|
|
| return [framed_melody, mc_time] |
|
|
| |
|
|
| def delta_score_notes(score_notes, |
| timings_clip_value=255, |
| even_timings=False, |
| compress_timings=False |
| ): |
|
|
| delta_score = [] |
|
|
| pe = score_notes[0] |
|
|
| for n in score_notes: |
|
|
| note = copy.deepcopy(n) |
|
|
| time = n[1] - pe[1] |
| dur = n[2] |
|
|
| if even_timings: |
| if time != 0 and time % 2 != 0: |
| time += 1 |
| if dur % 2 != 0: |
| dur += 1 |
|
|
| time = max(0, min(timings_clip_value, time)) |
| dur = max(0, min(timings_clip_value, dur)) |
|
|
| if compress_timings: |
| time /= 2 |
| dur /= 2 |
|
|
| note[1] = int(time) |
| note[2] = int(dur) |
|
|
| delta_score.append(note) |
|
|
| pe = n |
|
|
| return delta_score |
|
|
| |
|
|
| def check_and_fix_chords_in_chordified_score(chordified_score, |
| channels_index=3, |
| pitches_index=4 |
| ): |
| fixed_chordified_score = [] |
|
|
| bad_chords_counter = 0 |
|
|
| for c in chordified_score: |
|
|
| tones_chord = sorted(set([t[pitches_index] % 12 for t in c if t[channels_index] != 9])) |
|
|
| if tones_chord: |
|
|
| if tones_chord not in ALL_CHORDS_SORTED: |
| bad_chords_counter += 1 |
|
|
| while tones_chord not in ALL_CHORDS_SORTED: |
| tones_chord.pop(0) |
|
|
| new_chord = [] |
|
|
| c.sort(key = lambda x: x[pitches_index], reverse=True) |
|
|
| for e in c: |
| if e[channels_index] != 9: |
| if e[pitches_index] % 12 in tones_chord: |
| new_chord.append(e) |
|
|
| else: |
| new_chord.append(e) |
|
|
| fixed_chordified_score.append(new_chord) |
|
|
| return fixed_chordified_score, bad_chords_counter |
|
|
| |
|
|
| from itertools import combinations, groupby |
|
|
| |
|
|
| def advanced_check_and_fix_chords_in_chordified_score(chordified_score, |
| channels_index=3, |
| pitches_index=4, |
| patches_index=6, |
| use_filtered_chords=True, |
| remove_duplicate_pitches=True, |
| skip_drums=False |
| ): |
| fixed_chordified_score = [] |
|
|
| bad_chords_counter = 0 |
| duplicate_pitches_counter = 0 |
|
|
| if use_filtered_chords: |
| CHORDS = ALL_CHORDS_FILTERED |
| else: |
| CHORDS = ALL_CHORDS_SORTED |
|
|
| for c in chordified_score: |
|
|
| if remove_duplicate_pitches: |
|
|
| c.sort(key = lambda x: x[pitches_index], reverse=True) |
|
|
| seen = set() |
| ddchord = [] |
|
|
| for cc in c: |
| if cc[channels_index] != 9: |
|
|
| if tuple([cc[pitches_index], cc[patches_index]]) not in seen: |
| ddchord.append(cc) |
| seen.add(tuple([cc[pitches_index], cc[patches_index]])) |
| else: |
| duplicate_pitches_counter += 1 |
| |
| else: |
| ddchord.append(cc) |
| |
| c = copy.deepcopy(ddchord) |
| |
| tones_chord = sorted(set([t[pitches_index] % 12 for t in c if t[channels_index] != 9])) |
|
|
| if tones_chord: |
|
|
| if tones_chord not in CHORDS: |
| |
| pitches_chord = sorted(set([p[pitches_index] for p in c if p[channels_index] != 9]), reverse=True) |
| |
| if len(tones_chord) == 2: |
| tones_counts = Counter([p % 12 for p in pitches_chord]).most_common() |
|
|
| if tones_counts[0][1] > 1: |
| tones_chord = [tones_counts[0][0]] |
| elif tones_counts[1][1] > 1: |
| tones_chord = [tones_counts[1][0]] |
| else: |
| tones_chord = [pitches_chord[0] % 12] |
|
|
| else: |
| tones_chord_combs = [list(comb) for i in range(len(tones_chord)-2, 0, -1) for comb in combinations(tones_chord, i+1)] |
|
|
| for co in tones_chord_combs: |
| if co in CHORDS: |
| tones_chord = co |
| break |
|
|
| bad_chords_counter += 1 |
|
|
| new_chord = [] |
|
|
| c.sort(key = lambda x: x[pitches_index], reverse=True) |
|
|
| for e in c: |
| if e[channels_index] != 9: |
| if e[pitches_index] % 12 in tones_chord: |
| new_chord.append(e) |
|
|
| else: |
| if not skip_drums: |
| new_chord.append(e) |
|
|
| fixed_chordified_score.append(new_chord) |
|
|
| return fixed_chordified_score, bad_chords_counter, duplicate_pitches_counter |
|
|
| |
|
|
| def score_chord_to_tones_chord(chord, |
| transpose_value=0, |
| channels_index=3, |
| pitches_index=4): |
|
|
| return sorted(set([(p[4]+transpose_value) % 12 for p in chord if p[channels_index] != 9])) |
|
|
| |
|
|
| def grouped_set(seq): |
| return [k for k, v in groupby(seq)] |
|
|
| |
|
|
| def ordered_set(seq): |
| dic = {} |
| return [k for k, v in dic.fromkeys(seq).items()] |
|
|
| |
|
|
| def add_melody_to_enhanced_score_notes(enhanced_score_notes, |
| melody_start_time=0, |
| melody_start_chord=0, |
| melody_notes_min_duration=-1, |
| melody_notes_max_duration=255, |
| melody_duration_overlap_tolerance=4, |
| melody_avg_duration_divider=2, |
| melody_base_octave=5, |
| melody_channel=3, |
| melody_patch=40, |
| melody_max_velocity=110, |
| acc_max_velocity=90, |
| pass_drums=True, |
| return_melody=False |
| ): |
| |
| if pass_drums: |
| score = copy.deepcopy(enhanced_score_notes) |
| else: |
| score = [e for e in copy.deepcopy(enhanced_score_notes) if e[3] !=9] |
|
|
| if melody_notes_min_duration > 0: |
| min_duration = melody_notes_min_duration |
| else: |
| durs = [d[2] for d in score] |
| min_duration = Counter(durs).most_common()[0][0] |
|
|
| adjust_score_velocities(score, acc_max_velocity) |
|
|
| cscore = chordify_score([1000, score]) |
|
|
| melody_score = [] |
| acc_score = [] |
|
|
| pt = melody_start_time |
|
|
| for c in cscore[:melody_start_chord]: |
| acc_score.extend(c) |
|
|
| for c in cscore[melody_start_chord:]: |
|
|
| durs = [d[2] if d[3] != 9 else -1 for d in c] |
|
|
| if not all(d == -1 for d in durs): |
| ndurs = [d for d in durs if d != -1] |
| avg_dur = (sum(ndurs) / len(ndurs)) / melody_avg_duration_divider |
| best_dur = min(durs, key=lambda x:abs(x-avg_dur)) |
| pidx = durs.index(best_dur) |
|
|
| cc = copy.deepcopy(c[pidx]) |
|
|
| if c[0][1] >= pt - melody_duration_overlap_tolerance and best_dur >= min_duration: |
|
|
| cc[3] = melody_channel |
| cc[4] = (c[pidx][4] % 24) |
| cc[5] = 100 + ((c[pidx][4] % 12) * 2) |
| cc[6] = melody_patch |
|
|
| melody_score.append(cc) |
| acc_score.extend(c) |
|
|
| pt = c[0][1]+c[pidx][2] |
|
|
| else: |
| acc_score.extend(c) |
|
|
| else: |
| acc_score.extend(c) |
|
|
| values = [e[4] % 24 for e in melody_score] |
| smoothed = [values[0]] |
| for i in range(1, len(values)): |
| if abs(smoothed[-1] - values[i]) >= 12: |
| if smoothed[-1] < values[i]: |
| smoothed.append(values[i] - 12) |
| else: |
| smoothed.append(values[i] + 12) |
| else: |
| smoothed.append(values[i]) |
|
|
| smoothed_melody = copy.deepcopy(melody_score) |
|
|
| for i, e in enumerate(smoothed_melody): |
| e[4] = (melody_base_octave * 12) + smoothed[i] |
|
|
| for i, m in enumerate(smoothed_melody[1:]): |
| if m[1] - smoothed_melody[i][1] < melody_notes_max_duration: |
| smoothed_melody[i][2] = m[1] - smoothed_melody[i][1] |
|
|
| adjust_score_velocities(smoothed_melody, melody_max_velocity) |
|
|
| if return_melody: |
| final_score = sorted(smoothed_melody, key=lambda x: (x[1], -x[4])) |
|
|
| else: |
| final_score = sorted(smoothed_melody + acc_score, key=lambda x: (x[1], -x[4])) |
|
|
| return final_score |
| |
| |
|
|
| def find_paths(list_of_lists, path=[]): |
| if not list_of_lists: |
| return [path] |
| return [p for sublist in list_of_lists[0] for p in find_paths(list_of_lists[1:], path+[sublist])] |
|
|
| |
|
|
| def recalculate_score_timings(score, |
| start_time=0, |
| timings_index=1 |
| ): |
|
|
| rscore = copy.deepcopy(score) |
|
|
| pe = rscore[0] |
|
|
| abs_time = start_time |
|
|
| for e in rscore: |
|
|
| dtime = e[timings_index] - pe[timings_index] |
| pe = copy.deepcopy(e) |
| abs_time += dtime |
| e[timings_index] = abs_time |
| |
| return rscore |
|
|
| |
|
|
| WHITE_NOTES = [0, 2, 4, 5, 7, 9, 11] |
| BLACK_NOTES = [1, 3, 6, 8, 10] |
|
|
| |
|
|
| ALL_CHORDS_FILTERED = [[0], [0, 3], [0, 3, 5], [0, 3, 5, 8], [0, 3, 5, 9], [0, 3, 5, 10], [0, 3, 7], |
| [0, 3, 7, 10], [0, 3, 8], [0, 3, 9], [0, 3, 10], [0, 4], [0, 4, 6], |
| [0, 4, 6, 9], [0, 4, 6, 10], [0, 4, 7], [0, 4, 7, 10], [0, 4, 8], [0, 4, 9], |
| [0, 4, 10], [0, 5], [0, 5, 8], [0, 5, 9], [0, 5, 10], [0, 6], [0, 6, 9], |
| [0, 6, 10], [0, 7], [0, 7, 10], [0, 8], [0, 9], [0, 10], [1], [1, 4], |
| [1, 4, 6], [1, 4, 6, 9], [1, 4, 6, 10], [1, 4, 6, 11], [1, 4, 7], |
| [1, 4, 7, 10], [1, 4, 7, 11], [1, 4, 8], [1, 4, 8, 11], [1, 4, 9], [1, 4, 10], |
| [1, 4, 11], [1, 5], [1, 5, 8], [1, 5, 8, 11], [1, 5, 9], [1, 5, 10], |
| [1, 5, 11], [1, 6], [1, 6, 9], [1, 6, 10], [1, 6, 11], [1, 7], [1, 7, 10], |
| [1, 7, 11], [1, 8], [1, 8, 11], [1, 9], [1, 10], [1, 11], [2], [2, 5], |
| [2, 5, 8], [2, 5, 8, 11], [2, 5, 9], [2, 5, 10], [2, 5, 11], [2, 6], [2, 6, 9], |
| [2, 6, 10], [2, 6, 11], [2, 7], [2, 7, 10], [2, 7, 11], [2, 8], [2, 8, 11], |
| [2, 9], [2, 10], [2, 11], [3], [3, 5], [3, 5, 8], [3, 5, 8, 11], [3, 5, 9], |
| [3, 5, 10], [3, 5, 11], [3, 7], [3, 7, 10], [3, 7, 11], [3, 8], [3, 8, 11], |
| [3, 9], [3, 10], [3, 11], [4], [4, 6], [4, 6, 9], [4, 6, 10], [4, 6, 11], |
| [4, 7], [4, 7, 10], [4, 7, 11], [4, 8], [4, 8, 11], [4, 9], [4, 10], [4, 11], |
| [5], [5, 8], [5, 8, 11], [5, 9], [5, 10], [5, 11], [6], [6, 9], [6, 10], |
| [6, 11], [7], [7, 10], [7, 11], [8], [8, 11], [9], [10], [11]] |
|
|
| |
|
|
| def harmonize_enhanced_melody_score_notes(enhanced_melody_score_notes): |
| |
| mel_tones = [e[4] % 12 for e in enhanced_melody_score_notes] |
|
|
| cur_chord = [] |
|
|
| song = [] |
|
|
| for i, m in enumerate(mel_tones): |
| cur_chord.append(m) |
| cc = sorted(set(cur_chord)) |
|
|
| if cc in ALL_CHORDS_FILTERED: |
| song.append(cc) |
|
|
| else: |
| while sorted(set(cur_chord)) not in ALL_CHORDS_FILTERED: |
| cur_chord.pop(0) |
| cc = sorted(set(cur_chord)) |
| song.append(cc) |
|
|
| return song |
|
|
| |
|
|
| def split_melody(enhanced_melody_score_notes, |
| split_time=-1, |
| max_score_time=255 |
| ): |
|
|
| mel_chunks = [] |
|
|
| if split_time == -1: |
|
|
| durs = [max(0, min(max_score_time, e[2])) for e in enhanced_melody_score_notes] |
| stime = max(durs) |
| |
| else: |
| stime = split_time |
|
|
| pe = enhanced_melody_score_notes[0] |
| chu = [] |
| |
| for e in enhanced_melody_score_notes: |
| dtime = max(0, min(max_score_time, e[1]-pe[1])) |
|
|
| if dtime > max(durs): |
| if chu: |
| mel_chunks.append(chu) |
| chu = [] |
| chu.append(e) |
| else: |
| chu.append(e) |
|
|
| pe = e |
|
|
| if chu: |
| mel_chunks.append(chu) |
|
|
| return mel_chunks, [[m[0][1], m[-1][1]] for m in mel_chunks], len(mel_chunks) |
|
|
| |
|
|
| def flatten(list_of_lists): |
| return [x for y in list_of_lists for x in y] |
|
|
| |
|
|
| def enhanced_delta_score_notes(enhanced_score_notes, |
| start_time=0, |
| max_score_time=255 |
| ): |
|
|
| delta_score = [] |
|
|
| pe = ['note', max(0, enhanced_score_notes[0][1]-start_time)] |
|
|
| for e in enhanced_score_notes: |
|
|
| dtime = max(0, min(max_score_time, e[1]-pe[1])) |
| dur = max(1, min(max_score_time, e[2])) |
| cha = max(0, min(15, e[3])) |
| ptc = max(1, min(127, e[4])) |
| vel = max(1, min(127, e[5])) |
| pat = max(0, min(128, e[6])) |
|
|
| delta_score.append([dtime, dur, cha, ptc, vel, pat]) |
|
|
| pe = e |
|
|
| return delta_score |
|
|
| |
|
|
| def basic_enhanced_delta_score_notes_tokenizer(enhanced_delta_score_notes, |
| tokenize_start_times=True, |
| tokenize_durations=True, |
| tokenize_channels=True, |
| tokenize_pitches=True, |
| tokenize_velocities=True, |
| tokenize_patches=True, |
| score_timings_range=256, |
| max_seq_len=-1, |
| seq_pad_value=-1 |
| ): |
| |
| |
| |
| score_tokens_ints_seq = [] |
|
|
| tokens_shifts = [-1] * 7 |
|
|
| for d in enhanced_delta_score_notes: |
|
|
| seq = [] |
| shift = 0 |
|
|
| if tokenize_start_times: |
| seq.append(d[0]) |
| tokens_shifts[0] = shift |
| shift += score_timings_range |
|
|
| if tokenize_durations: |
| seq.append(d[1]+shift) |
| tokens_shifts[1] = shift |
| shift += score_timings_range |
|
|
| if tokenize_channels: |
| tokens_shifts[2] = shift |
| seq.append(d[2]+shift) |
| shift += 16 |
| |
| if tokenize_pitches: |
| tokens_shifts[3] = shift |
| seq.append(d[3]+shift) |
| shift += 128 |
| |
| if tokenize_velocities: |
| tokens_shifts[4] = shift |
| seq.append(d[4]+shift) |
| shift += 128 |
|
|
| if tokenize_patches: |
| tokens_shifts[5] = shift |
| seq.append(d[5]+shift) |
| shift += 129 |
|
|
| tokens_shifts[6] = shift |
| score_tokens_ints_seq.append(seq) |
|
|
| final_score_tokens_ints_seq = flatten(score_tokens_ints_seq) |
|
|
| if max_seq_len > -1: |
| final_score_tokens_ints_seq = flat_score_tokens_ints_seq[:max_seq_len] |
|
|
| if seq_pad_value > -1: |
| final_score_tokens_ints_seq += [seq_pad_value] * (max_seq_len - len(final_score_tokens_ints_seq)) |
|
|
| return [score_tokens_ints_seq, |
| final_score_tokens_ints_seq, |
| tokens_shifts, |
| seq_pad_value, |
| max_seq_len, |
| len(score_tokens_ints_seq), |
| len(final_score_tokens_ints_seq) |
| ] |
|
|
| |
|
|
| def basic_enhanced_delta_score_notes_detokenizer(tokenized_seq, |
| tokens_shifts, |
| timings_multiplier=16 |
| ): |
|
|
| song_f = [] |
|
|
| time = 0 |
| dur = 16 |
| channel = 0 |
| pitch = 60 |
| vel = 90 |
| pat = 0 |
|
|
| note_seq_len = len([t for t in tokens_shifts if t > -1])-1 |
| tok_shifts_idxs = [i for i in range(len(tokens_shifts[:-1])) if tokens_shifts[i] > - 1] |
|
|
| song = [] |
|
|
| for i in range(0, len(tokenized_seq), note_seq_len): |
| note = tokenized_seq[i:i+note_seq_len] |
| song.append(note) |
|
|
| for note in song: |
| for i, idx in enumerate(tok_shifts_idxs): |
| if idx == 0: |
| time += (note[i]-tokens_shifts[0]) * timings_multiplier |
| elif idx == 1: |
| dur = (note[i]-tokens_shifts[1]) * timings_multiplier |
| elif idx == 2: |
| channel = (note[i]-tokens_shifts[2]) |
| elif idx == 3: |
| pitch = (note[i]-tokens_shifts[3]) |
| elif idx == 4: |
| vel = (note[i]-tokens_shifts[4]) |
| elif idx == 5: |
| pat = (note[i]-tokens_shifts[5]) |
|
|
| song_f.append(['note', time, dur, channel, pitch, vel, pat ]) |
|
|
| return song_f |
|
|
| |
|
|
| def enhanced_chord_to_chord_token(enhanced_chord, |
| channels_index=3, |
| pitches_index=4, |
| use_filtered_chords=True |
| ): |
| |
| bad_chords_counter = 0 |
| duplicate_pitches_counter = 0 |
|
|
| if use_filtered_chords: |
| CHORDS = ALL_CHORDS_FILTERED |
| else: |
| CHORDS = ALL_CHORDS_SORTED |
|
|
| tones_chord = sorted(set([t[pitches_index] % 12 for t in enhanced_chord if t[channels_index] != 9])) |
|
|
| original_tones_chord = copy.deepcopy(tones_chord) |
|
|
| if tones_chord: |
|
|
| if tones_chord not in CHORDS: |
| |
| pitches_chord = sorted(set([p[pitches_index] for p in enhanced_chord if p[channels_index] != 9]), reverse=True) |
| |
| if len(tones_chord) == 2: |
| tones_counts = Counter([p % 12 for p in pitches_chord]).most_common() |
|
|
| if tones_counts[0][1] > 1: |
| tones_chord = [tones_counts[0][0]] |
| elif tones_counts[1][1] > 1: |
| tones_chord = [tones_counts[1][0]] |
| else: |
| tones_chord = [pitches_chord[0] % 12] |
|
|
| else: |
| tones_chord_combs = [list(comb) for i in range(len(tones_chord)-2, 0, -1) for comb in combinations(tones_chord, i+1)] |
|
|
| for co in tones_chord_combs: |
| if co in CHORDS: |
| tones_chord = co |
| break |
|
|
| if use_filtered_chords: |
| chord_token = ALL_CHORDS_FILTERED.index(tones_chord) |
| else: |
| chord_token = ALL_CHORDS_SORTED.index(tones_chord) |
|
|
| return [chord_token, tones_chord, original_tones_chord, sorted(set(original_tones_chord) ^ set(tones_chord))] |
|
|
| |
|
|
| def enhanced_chord_to_tones_chord(enhanced_chord): |
| return sorted(set([t[4] % 12 for t in enhanced_chord if t[3] != 9])) |
|
|
| |
|
|
| import hashlib |
|
|
| |
|
|
| def md5_hash(file_path_or_data=None, original_md5_hash=None): |
|
|
| if type(file_path_or_data) == str: |
|
|
| with open(file_path_or_data, 'rb') as file_to_check: |
| data = file_to_check.read() |
| |
| if data: |
| md5 = hashlib.md5(data).hexdigest() |
|
|
| else: |
| if file_path_or_data: |
| md5 = hashlib.md5(file_path_or_data).hexdigest() |
|
|
| if md5: |
|
|
| if original_md5_hash: |
|
|
| if md5 == original_md5_hash: |
| check = True |
| else: |
| check = False |
| |
| else: |
| check = None |
|
|
| return [md5, check] |
|
|
| else: |
|
|
| md5 = None |
| check = None |
|
|
| return [md5, check] |
|
|
| |
|
|
| ALL_PITCHES_CHORDS_FILTERED = [[67], [64], [62], [69], [60], [65], [59], [70], [66], [63], [68], [61], |
| [64, 60], [67, 64], [65, 62], [62, 59], [69, 65], [60, 57], [66, 62], [59, 55], |
| [62, 57], [67, 62], [64, 59], [64, 60, 55], [60, 55], [65, 60], [64, 61], |
| [69, 64], [66, 62, 57], [69, 66], [62, 59, 55], [64, 60, 57], [62, 58], |
| [65, 60, 57], [70, 67], [67, 63], [64, 61, 57], [61, 57], [63, 60], [68, 64], |
| [65, 62, 58], [65, 62, 57], [59, 56], [63, 58], [68, 65], [59, 54, 47, 35], |
| [70, 65], [66, 61], [64, 59, 56], [65, 61], [64, 59, 55], [63, 59], [61, 58], |
| [68, 63], [60, 56], [67, 63, 60], [67, 63, 58], [66, 62, 59], [61, 56], |
| [70, 66], [67, 62, 58], [63, 60, 56], [65, 61, 56], [66, 61, 58], [66, 61, 57], |
| [65, 60, 56], [65, 61, 58], [65, 59], [68, 64, 61], [66, 60], [64, 58], |
| [62, 56], [63, 57], [61, 55], [66, 64], [60, 58], [65, 63], [63, 59, 56], |
| [65, 62, 59], [61, 59], [66, 60, 57], [64, 61, 55], [64, 58, 55], [62, 59, 56], |
| [64, 60, 58], [63, 60, 57], [64, 60, 58, 55], [65, 62, 56], [64, 61, 58], |
| [66, 64, 59], [60, 58, 55], [65, 63, 60], [63, 57, 53], [65, 63, 60, 57], |
| [65, 59, 56], [63, 60, 58, 55], [67, 61, 58], [64, 61, 57, 54], [64, 61, 59], |
| [70, 65, 60], [68, 65, 63, 60], [63, 60, 58], [65, 63, 58], [69, 66, 64], |
| [64, 60, 54], [64, 60, 57, 54], [66, 64, 61], [66, 61, 59], [67, 63, 59], |
| [65, 61, 57], [68, 65, 63], [64, 61, 59, 56], [65, 61, 59], [66, 64, 61, 58], |
| [64, 61, 58, 55], [64, 60, 56], [65, 61, 59, 56], [66, 62, 58], [61, 59, 56], |
| [64, 58, 54], [63, 59, 53], [65, 62, 59, 56], [61, 59, 55], [64, 61, 59, 55], |
| [68, 65, 63, 59], [70, 66, 60], [65, 63, 60, 58], [64, 61, 59, 54], |
| [70, 64, 60, 54]] |
|
|
| |
|
|
| ALL_PITCHES_CHORDS_SORTED = [[60], [62, 60], [63, 60], [64, 60], [64, 62, 60], [65, 60], [65, 62, 60], |
| [65, 63, 60], [66, 60], [66, 62, 60], [66, 63, 60], [64, 60, 54], |
| [64, 60, 54, 50], [60, 55], [67, 62, 60], [67, 63, 60], [64, 60, 55], |
| [65, 60, 55], [64, 62, 60, 55], [67, 65, 62, 60], [67, 65, 63, 60], [60, 56], |
| [62, 60, 56], [63, 60, 56], [64, 60, 56], [65, 60, 56], [66, 60, 56], |
| [72, 68, 64, 62], [65, 62, 60, 56], [66, 62, 60, 56], [68, 65, 63, 60], |
| [68, 66, 63, 60], [60, 44, 42, 40], [88, 80, 74, 66, 60, 56], [60, 57], |
| [62, 60, 57], [63, 60, 57], [64, 60, 57], [65, 60, 57], [66, 60, 57], |
| [67, 60, 57], [64, 62, 60, 57], [65, 62, 60, 57], [69, 66, 62, 60], |
| [67, 62, 60, 57], [65, 63, 60, 57], [66, 63, 60, 57], [67, 63, 60, 57], |
| [64, 60, 57, 54], [67, 64, 60, 57], [67, 65, 60, 57], [69, 64, 60, 54, 38], |
| [67, 64, 62, 60, 57], [67, 65, 62, 60, 57], [67, 65, 63, 60, 57], [60, 58], |
| [62, 60, 58], [63, 60, 58], [64, 60, 58], [70, 65, 60], [70, 66, 60], |
| [60, 58, 55], [70, 60, 56], [74, 64, 60, 58], [65, 62, 60, 58], |
| [70, 66, 62, 60], [62, 60, 58, 55], [72, 68, 62, 58], [65, 63, 60, 58], |
| [70, 66, 63, 60], [63, 60, 58, 55], [70, 63, 60, 56], [70, 64, 60, 54], |
| [64, 60, 58, 55], [68, 64, 60, 58], [65, 60, 58, 55], [70, 65, 60, 56], |
| [70, 66, 60, 56], [78, 76, 74, 72, 70, 66], [67, 64, 62, 58, 36], |
| [74, 68, 64, 58, 48], [65, 62, 58, 55, 36], [65, 62, 60, 56, 46], |
| [72, 66, 62, 56, 46], [79, 65, 63, 58, 53, 36], [65, 60, 56, 51, 46, 41], |
| [70, 66, 63, 60, 44], [68, 66, 64, 58, 56, 48], |
| [94, 92, 90, 88, 86, 84, 82, 80, 78, 76, 74, 72, 70, 68, 66, 64, 62, 60, 58, |
| 56, 54, 52, 50, 48, 46, 44, 42, 40, 38, 36, 34, 32, 30, 28, 26, 24], |
| [61], [63, 61], [64, 61], [65, 61], [65, 63, 61], [66, 61], [66, 63, 61], |
| [66, 64, 61], [61, 55], [67, 63, 61], [64, 61, 55], [65, 61, 55], |
| [65, 61, 55, 39], [61, 56], [63, 61, 56], [68, 64, 61], [65, 61, 56], |
| [66, 61, 56], [68, 65, 63, 61], [54, 49, 44, 39], [68, 64, 61, 42], [61, 57], |
| [63, 61, 57], [64, 61, 57], [65, 61, 57], [66, 61, 57], [67, 61, 57], |
| [69, 65, 63, 61], [66, 63, 61, 57], [67, 63, 61, 57], [64, 61, 57, 54], |
| [67, 64, 61, 57], [65, 61, 55, 45], [67, 65, 63, 61, 57], [61, 58], |
| [63, 61, 58], [64, 61, 58], [65, 61, 58], [66, 61, 58], [67, 61, 58], |
| [61, 58, 56], [65, 63, 61, 58], [66, 63, 61, 58], [67, 63, 61, 58], |
| [63, 61, 58, 56], [66, 64, 61, 58], [64, 61, 58, 55], [68, 64, 61, 58], |
| [65, 61, 58, 55], [65, 61, 58, 56], [58, 54, 49, 44], [70, 65, 61, 55, 39], |
| [80, 68, 65, 63, 61, 58], [63, 58, 54, 49, 44, 39], [73, 68, 64, 58, 54], |
| [61, 59], [63, 61, 59], [64, 61, 59], [65, 61, 59], [66, 61, 59], [61, 59, 55], |
| [61, 59, 56], [61, 59, 57], [63, 59, 53, 49], [66, 63, 61, 59], |
| [71, 67, 63, 61], [63, 61, 59, 56], [61, 57, 51, 47], [64, 61, 59, 54], |
| [64, 61, 59, 55], [64, 61, 59, 56], [64, 61, 59, 57], [65, 61, 59, 55], |
| [65, 61, 59, 56], [69, 65, 61, 59], [66, 61, 59, 56], [71, 66, 61, 57], |
| [71, 67, 61, 57], [67, 63, 59, 53, 49], [68, 65, 63, 59, 37], |
| [65, 63, 61, 59, 57], [66, 63, 61, 59, 56], [73, 69, 66, 63, 59], |
| [79, 75, 73, 61, 59, 33], [61, 56, 52, 47, 42, 35], [76, 73, 69, 66, 35], |
| [71, 67, 64, 61, 57], [73, 71, 69, 67, 65], |
| [95, 93, 91, 89, 87, 85, 83, 81, 79, 77, 75, 73, 71, 69, 67, 65, 63, 61, 59, |
| 57, 55, 53, 51, 49, 47, 45, 43, 41, 39, 37, 35, 33, 31, 29, 27, 25], |
| [62], [64, 62], [65, 62], [66, 62], [66, 64, 62], [67, 62], [67, 64, 62], |
| [67, 65, 62], [62, 56], [68, 64, 62], [65, 62, 56], [66, 62, 56], |
| [66, 62, 56, 52], [62, 57], [50, 45, 40], [65, 62, 57], [66, 62, 57], |
| [55, 50, 45], [66, 64, 62, 57], [55, 50, 45, 40], [69, 67, 65, 62], [62, 58], |
| [64, 62, 58], [65, 62, 58], [66, 62, 58], [67, 62, 58], [62, 58, 56], |
| [66, 64, 62, 58], [67, 64, 62, 58], [64, 62, 58, 56], [65, 62, 58, 55], |
| [65, 62, 58, 56], [66, 62, 58, 56], [66, 64, 58, 44, 38], [62, 59], |
| [64, 62, 59], [65, 62, 59], [66, 62, 59], [62, 59, 55], [62, 59, 56], |
| [62, 59, 57], [66, 64, 62, 59], [67, 64, 62, 59], [64, 62, 59, 56], |
| [64, 62, 59, 57], [67, 65, 62, 59], [65, 62, 59, 56], [69, 65, 62, 59], |
| [66, 62, 59, 56], [69, 66, 62, 59], [59, 55, 50, 45], [64, 62, 59, 56, 54], |
| [69, 66, 62, 59, 40], [64, 59, 55, 50, 45, 40], [69, 65, 62, 59, 55], [63], |
| [65, 63], [66, 63], [67, 63], [67, 65, 63], [68, 63], [68, 65, 63], |
| [68, 66, 63], [63, 57], [63, 57, 53], [66, 63, 57], [67, 63, 57], |
| [67, 63, 57, 53], [63, 58], [65, 63, 58], [66, 63, 58], [67, 63, 58], |
| [68, 63, 58], [67, 65, 63, 58], [63, 58, 56, 53], [70, 68, 66, 63], [63, 59], |
| [63, 59, 53], [66, 63, 59], [67, 63, 59], [63, 59, 56], [63, 59, 57], |
| [63, 59, 55, 53], [68, 65, 63, 59], [69, 65, 63, 59], [66, 63, 59, 56], |
| [66, 63, 59, 57], [67, 63, 59, 57], [67, 63, 59, 57, 41], [64], [66, 64], |
| [67, 64], [68, 64], [68, 66, 64], [69, 64], [69, 66, 64], [69, 67, 64], |
| [64, 58], [64, 58, 54], [64, 58, 55], [68, 64, 58], [68, 64, 58, 42], [64, 59], |
| [66, 64, 59], [64, 59, 55], [64, 59, 56], [64, 59, 57], [64, 59, 56, 54], |
| [64, 59, 57, 54], [69, 64, 59, 55], [65], [67, 65], [68, 65], [69, 65], |
| [69, 67, 65], [70, 65], [65, 58, 55], [70, 68, 65], [65, 59], [65, 59, 55], |
| [65, 59, 56], [59, 57, 53], [69, 65, 59, 55], [66], [68, 66], [69, 66], |
| [70, 66], [80, 70, 54], [59, 54, 47, 35], [66, 59, 56], [71, 69, 66], [67], |
| [69, 67], [70, 67], [59, 55], [71, 69, 67], [68], [70, 68], [59, 56], [69], |
| [71, 69], [70], [59]] |
|
|
| |
|
|
| def sort_list_by_other(list1, list2): |
| return sorted(list1, key=lambda x: list2.index(x) if x in list2 else len(list2)) |
|
|
| |
|
|
| ALL_CHORDS_PAIRS_SORTED = [[[0], [0, 4, 7]], [[0, 2], [0, 4, 7]], [[0, 3], [0, 3, 7]], |
| [[0, 4], [0, 4, 7]], [[0, 2, 4], [0, 2, 4, 7]], [[0, 5], [0, 5, 9]], |
| [[0, 2, 5], [0, 2, 5, 9]], [[0, 3, 5], [0, 3, 5, 9]], [[0, 6], [0, 2, 6, 9]], |
| [[0, 2, 6], [0, 2, 6, 9]], [[0, 3, 6], [0, 3, 6, 8]], |
| [[0, 4, 6], [0, 4, 6, 9]], [[0, 2, 4, 6], [0, 2, 4, 6, 9]], |
| [[0, 7], [0, 4, 7]], [[0, 2, 7], [0, 2, 4, 7]], [[0, 3, 7], [0, 3, 7, 10]], |
| [[0, 4, 7], [0, 4, 7, 9]], [[0, 5, 7], [0, 5, 7, 9]], |
| [[0, 2, 4, 7], [0, 2, 4, 7, 9]], [[0, 2, 5, 7], [0, 2, 5, 7, 9]], |
| [[0, 3, 5, 7], [0, 3, 5, 7, 10]], [[0, 8], [0, 3, 8]], |
| [[0, 2, 8], [0, 2, 5, 8]], [[0, 3, 8], [0, 3, 5, 8]], |
| [[0, 4, 8], [2, 4, 8, 11]], [[0, 5, 8], [0, 3, 5, 8]], |
| [[0, 6, 8], [0, 3, 6, 8]], [[0, 2, 4, 8], [0, 2, 4, 6, 8]], |
| [[0, 2, 5, 8], [0, 2, 5, 8, 10]], [[0, 2, 6, 8], [0, 2, 6, 8, 10]], |
| [[0, 3, 5, 8], [0, 3, 5, 8, 10]], [[0, 3, 6, 8], [0, 3, 6, 8, 10]], |
| [[0, 4, 6, 8], [2, 4, 6, 8, 11]], [[0, 2, 4, 6, 8], [2, 4, 6, 8, 11]], |
| [[0, 9], [0, 4, 9]], [[0, 2, 9], [0, 2, 6, 9]], [[0, 3, 9], [0, 3, 5, 9]], |
| [[0, 4, 9], [0, 4, 7, 9]], [[0, 5, 9], [0, 2, 5, 9]], |
| [[0, 6, 9], [0, 2, 6, 9]], [[0, 7, 9], [0, 4, 7, 9]], |
| [[0, 2, 4, 9], [0, 2, 4, 7, 9]], [[0, 2, 5, 9], [0, 2, 5, 7, 9]], |
| [[0, 2, 6, 9], [0, 2, 4, 6, 9]], [[0, 2, 7, 9], [0, 2, 4, 7, 9]], |
| [[0, 3, 5, 9], [0, 3, 5, 7, 9]], [[0, 3, 6, 9], [0, 2, 4, 6, 9]], |
| [[0, 3, 7, 9], [0, 3, 5, 7, 9]], [[0, 4, 6, 9], [0, 2, 4, 6, 9]], |
| [[0, 4, 7, 9], [0, 2, 4, 7, 9]], [[0, 5, 7, 9], [0, 2, 5, 7, 9]], |
| [[0, 2, 4, 6, 9], [2, 4, 6, 9, 11]], [[0, 2, 4, 7, 9], [2, 4, 7, 9, 11]], |
| [[0, 2, 5, 7, 9], [2, 5, 7, 9, 11]], [[0, 3, 5, 7, 9], [2, 4, 6, 8, 11]], |
| [[0, 10], [2, 5, 10]], [[0, 2, 10], [0, 2, 5, 10]], |
| [[0, 3, 10], [0, 3, 7, 10]], [[0, 4, 10], [0, 4, 7, 10]], |
| [[0, 5, 10], [0, 2, 5, 10]], [[0, 6, 10], [0, 3, 6, 10]], |
| [[0, 7, 10], [0, 4, 7, 10]], [[0, 8, 10], [0, 3, 8, 10]], |
| [[0, 2, 4, 10], [0, 2, 4, 7, 10]], [[0, 2, 5, 10], [0, 2, 5, 7, 10]], |
| [[0, 2, 6, 10], [0, 2, 6, 8, 10]], [[0, 2, 7, 10], [0, 2, 5, 7, 10]], |
| [[0, 2, 8, 10], [0, 2, 5, 8, 10]], [[0, 3, 5, 10], [0, 3, 5, 7, 10]], |
| [[0, 3, 6, 10], [0, 3, 6, 8, 10]], [[0, 3, 7, 10], [0, 3, 5, 7, 10]], |
| [[0, 3, 8, 10], [0, 3, 5, 8, 10]], [[0, 4, 6, 10], [0, 2, 4, 6, 10]], |
| [[0, 4, 7, 10], [0, 2, 4, 7, 10]], [[0, 4, 8, 10], [0, 2, 4, 8, 10]], |
| [[0, 5, 7, 10], [0, 3, 5, 7, 10]], [[0, 5, 8, 10], [0, 3, 5, 8, 10]], |
| [[0, 6, 8, 10], [0, 3, 6, 8, 10]], [[0, 2, 4, 6, 10], [0, 2, 4, 8, 10]], |
| [[0, 2, 4, 7, 10], [1, 3, 6, 9, 11]], [[0, 2, 4, 8, 10], [1, 3, 7, 9, 11]], |
| [[0, 2, 5, 7, 10], [0, 3, 5, 7, 10]], [[0, 2, 5, 8, 10], [1, 4, 7, 9, 11]], |
| [[0, 2, 6, 8, 10], [2, 4, 6, 8, 10]], [[0, 3, 5, 7, 10], [0, 2, 5, 7, 10]], |
| [[0, 3, 5, 8, 10], [1, 3, 5, 8, 10]], [[0, 3, 6, 8, 10], [1, 3, 6, 8, 10]], |
| [[0, 4, 6, 8, 10], [0, 2, 4, 6, 9]], |
| [[0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11]], [[1], [1, 8]], [[1, 3], [1, 5, 8]], |
| [[1, 4], [1, 4, 9]], [[1, 5], [1, 5, 8]], [[1, 3, 5], [1, 3, 5, 10]], |
| [[1, 6], [1, 6, 10]], [[1, 3, 6], [1, 3, 6, 10]], [[1, 4, 6], [1, 4, 6, 9]], |
| [[1, 7], [1, 4, 7]], [[1, 3, 7], [1, 3, 7, 10]], [[1, 4, 7], [1, 4, 7, 9]], |
| [[1, 5, 7], [1, 5, 7, 10]], [[1, 3, 5, 7], [1, 3, 5, 7, 10]], |
| [[1, 8], [1, 5, 8]], [[1, 3, 8], [1, 3, 5, 8]], [[1, 4, 8], [1, 4, 8, 11]], |
| [[1, 5, 8], [1, 5, 8, 10]], [[1, 6, 8], [1, 3, 6, 8]], |
| [[1, 3, 5, 8], [1, 3, 5, 8, 10]], [[1, 3, 6, 8], [1, 3, 6, 8, 10]], |
| [[1, 4, 6, 8], [1, 4, 6, 8, 11]], [[1, 9], [1, 4, 9]], |
| [[1, 3, 9], [1, 3, 6, 9]], [[1, 4, 9], [1, 4, 6, 9]], |
| [[1, 5, 9], [0, 3, 5, 9]], [[1, 6, 9], [1, 4, 6, 9]], |
| [[1, 7, 9], [1, 4, 7, 9]], [[1, 3, 5, 9], [0, 3, 5, 7, 9]], |
| [[1, 3, 6, 9], [1, 3, 6, 9, 11]], [[1, 3, 7, 9], [1, 3, 5, 7, 9]], |
| [[1, 4, 6, 9], [1, 4, 6, 9, 11]], [[1, 4, 7, 9], [1, 4, 7, 9, 11]], |
| [[1, 5, 7, 9], [1, 3, 7, 9, 11]], [[1, 3, 5, 7, 9], [2, 4, 6, 8, 11]], |
| [[1, 10], [1, 5, 10]], [[1, 3, 10], [1, 3, 7, 10]], |
| [[1, 4, 10], [1, 4, 6, 10]], [[1, 5, 10], [1, 5, 8, 10]], |
| [[1, 6, 10], [1, 4, 6, 10]], [[1, 7, 10], [1, 3, 7, 10]], |
| [[1, 8, 10], [1, 5, 8, 10]], [[1, 3, 5, 10], [1, 3, 5, 8, 10]], |
| [[1, 3, 6, 10], [1, 3, 6, 8, 10]], [[1, 3, 7, 10], [1, 3, 5, 7, 10]], |
| [[1, 3, 8, 10], [1, 3, 5, 8, 10]], [[1, 4, 6, 10], [1, 4, 6, 8, 10]], |
| [[1, 4, 7, 10], [0, 2, 4, 7, 10]], [[1, 4, 8, 10], [1, 4, 6, 8, 10]], |
| [[1, 5, 7, 10], [1, 3, 5, 7, 10]], [[1, 5, 8, 10], [1, 3, 5, 8, 10]], |
| [[1, 6, 8, 10], [1, 3, 6, 8, 10]], [[1, 3, 5, 7, 10], [2, 4, 6, 8, 11]], |
| [[1, 3, 5, 8, 10], [0, 3, 5, 8, 10]], [[1, 3, 6, 8, 10], [0, 3, 6, 8, 10]], |
| [[1, 4, 6, 8, 10], [0, 3, 5, 7, 9]], [[1, 11], [2, 6, 11]], |
| [[1, 3, 11], [1, 3, 6, 11]], [[1, 4, 11], [1, 4, 8, 11]], |
| [[1, 5, 11], [1, 5, 8, 11]], [[1, 6, 11], [1, 4, 6, 11]], |
| [[1, 7, 11], [1, 4, 7, 11]], [[1, 8, 11], [1, 4, 8, 11]], |
| [[1, 9, 11], [1, 4, 9, 11]], [[1, 3, 5, 11], [1, 3, 5, 8, 11]], |
| [[1, 3, 6, 11], [1, 3, 6, 8, 11]], [[1, 3, 7, 11], [1, 3, 7, 9, 11]], |
| [[1, 3, 8, 11], [1, 3, 6, 8, 11]], [[1, 3, 9, 11], [1, 3, 6, 9, 11]], |
| [[1, 4, 6, 11], [1, 4, 6, 9, 11]], [[1, 4, 7, 11], [1, 4, 7, 9, 11]], |
| [[1, 4, 8, 11], [1, 4, 6, 8, 11]], [[1, 4, 9, 11], [1, 4, 6, 9, 11]], |
| [[1, 5, 7, 11], [0, 4, 6, 8, 10]], [[1, 5, 8, 11], [1, 3, 5, 8, 11]], |
| [[1, 5, 9, 11], [1, 5, 7, 9, 11]], [[1, 6, 8, 11], [1, 3, 6, 8, 11]], |
| [[1, 6, 9, 11], [1, 4, 6, 9, 11]], [[1, 7, 9, 11], [1, 4, 7, 9, 11]], |
| [[1, 3, 5, 7, 11], [0, 2, 4, 6, 8]], [[1, 3, 5, 8, 11], [0, 2, 4, 7, 10]], |
| [[1, 3, 5, 9, 11], [1, 3, 7, 9, 11]], [[1, 3, 6, 8, 11], [1, 4, 6, 8, 11]], |
| [[1, 3, 6, 9, 11], [0, 2, 5, 8, 10]], [[1, 3, 7, 9, 11], [1, 3, 6, 9, 11]], |
| [[1, 4, 6, 8, 11], [1, 4, 6, 9, 11]], [[1, 4, 6, 9, 11], [2, 4, 6, 9, 11]], |
| [[1, 4, 7, 9, 11], [2, 4, 7, 9, 11]], [[1, 5, 7, 9, 11], [2, 4, 7, 9, 11]], |
| [[1, 3, 5, 7, 9, 11], [0, 2, 4, 6, 8, 10]], [[2], [2, 9]], [[2, 4], [2, 6, 9]], |
| [[2, 5], [2, 5, 9]], [[2, 6], [2, 6, 9]], [[2, 4, 6], [2, 4, 6, 9]], |
| [[2, 7], [2, 7, 11]], [[2, 4, 7], [2, 4, 7, 11]], [[2, 5, 7], [2, 5, 7, 11]], |
| [[2, 8], [4, 8, 11]], [[2, 4, 8], [2, 4, 8, 11]], [[2, 5, 8], [2, 5, 8, 10]], |
| [[2, 6, 8], [2, 6, 8, 11]], [[2, 4, 6, 8], [2, 4, 6, 8, 11]], |
| [[2, 9], [2, 6, 9]], [[2, 4, 9], [2, 4, 6, 9]], [[2, 5, 9], [0, 2, 5, 9]], |
| [[2, 6, 9], [2, 6, 9, 11]], [[2, 7, 9], [2, 7, 9, 11]], |
| [[2, 4, 6, 9], [2, 4, 6, 9, 11]], [[2, 4, 7, 9], [2, 4, 7, 9, 11]], |
| [[2, 5, 7, 9], [0, 2, 5, 7, 9]], [[2, 10], [2, 5, 10]], |
| [[2, 4, 10], [2, 4, 7, 10]], [[2, 5, 10], [2, 5, 7, 10]], |
| [[2, 6, 10], [1, 4, 6, 10]], [[2, 7, 10], [2, 5, 7, 10]], |
| [[2, 8, 10], [2, 5, 8, 10]], [[2, 4, 6, 10], [0, 2, 4, 6, 10]], |
| [[2, 4, 7, 10], [0, 2, 4, 7, 10]], [[2, 4, 8, 10], [2, 4, 7, 9, 11]], |
| [[2, 5, 7, 10], [0, 2, 5, 7, 10]], [[2, 5, 8, 10], [0, 2, 5, 8, 10]], |
| [[2, 6, 8, 10], [1, 3, 5, 7, 10]], [[2, 4, 6, 8, 10], [0, 2, 6, 8, 10]], |
| [[2, 11], [2, 7, 11]], [[2, 4, 11], [2, 4, 8, 11]], |
| [[2, 5, 11], [2, 5, 7, 11]], [[2, 6, 11], [2, 6, 9, 11]], |
| [[2, 7, 11], [2, 4, 7, 11]], [[2, 8, 11], [2, 4, 8, 11]], |
| [[2, 9, 11], [2, 6, 9, 11]], [[2, 4, 6, 11], [2, 4, 6, 9, 11]], |
| [[2, 4, 7, 11], [2, 4, 7, 9, 11]], [[2, 4, 8, 11], [2, 4, 6, 8, 11]], |
| [[2, 4, 9, 11], [2, 4, 7, 9, 11]], [[2, 5, 7, 11], [2, 5, 7, 9, 11]], |
| [[2, 5, 8, 11], [1, 3, 5, 8, 11]], [[2, 5, 9, 11], [2, 5, 7, 9, 11]], |
| [[2, 6, 8, 11], [2, 4, 6, 8, 11]], [[2, 6, 9, 11], [2, 4, 6, 9, 11]], |
| [[2, 7, 9, 11], [2, 4, 7, 9, 11]], [[2, 4, 6, 8, 11], [2, 4, 6, 9, 11]], |
| [[2, 4, 6, 9, 11], [2, 4, 7, 9, 11]], [[2, 4, 7, 9, 11], [0, 2, 4, 7, 9]], |
| [[2, 5, 7, 9, 11], [2, 4, 7, 9, 11]], [[3], [3, 10]], [[3, 5], [3, 7, 10]], |
| [[3, 6], [3, 6, 11]], [[3, 7], [3, 7, 10]], [[3, 5, 7], [3, 5, 7, 10]], |
| [[3, 8], [0, 3, 8]], [[3, 5, 8], [0, 3, 5, 8]], [[3, 6, 8], [0, 3, 6, 8]], |
| [[3, 9], [0, 3, 9]], [[3, 5, 9], [0, 3, 5, 9]], [[3, 6, 9], [3, 6, 9, 11]], |
| [[3, 7, 9], [0, 3, 7, 9]], [[3, 5, 7, 9], [0, 3, 5, 7, 9]], |
| [[3, 10], [3, 7, 10]], [[3, 5, 10], [3, 5, 7, 10]], |
| [[3, 6, 10], [1, 3, 6, 10]], [[3, 7, 10], [0, 3, 7, 10]], |
| [[3, 8, 10], [0, 3, 8, 10]], [[3, 5, 7, 10], [0, 3, 5, 7, 10]], |
| [[3, 5, 8, 10], [0, 3, 5, 8, 10]], [[3, 6, 8, 10], [1, 3, 6, 8, 10]], |
| [[3, 11], [3, 6, 11]], [[3, 5, 11], [3, 5, 8, 11]], |
| [[3, 6, 11], [3, 6, 9, 11]], [[3, 7, 11], [2, 5, 7, 11]], |
| [[3, 8, 11], [3, 6, 8, 11]], [[3, 9, 11], [3, 6, 9, 11]], |
| [[3, 5, 7, 11], [3, 5, 7, 9, 11]], [[3, 5, 8, 11], [1, 3, 5, 8, 11]], |
| [[3, 5, 9, 11], [3, 5, 7, 9, 11]], [[3, 6, 8, 11], [1, 3, 6, 8, 11]], |
| [[3, 6, 9, 11], [1, 3, 6, 9, 11]], [[3, 7, 9, 11], [2, 4, 7, 9, 11]], |
| [[3, 5, 7, 9, 11], [2, 5, 7, 9, 11]], [[4], [4, 11]], [[4, 6], [4, 7, 11]], |
| [[4, 7], [0, 4, 7]], [[4, 8], [4, 8, 11]], [[4, 6, 8], [4, 6, 8, 11]], |
| [[4, 9], [1, 4, 9]], [[4, 6, 9], [1, 4, 6, 9]], [[4, 7, 9], [1, 4, 7, 9]], |
| [[4, 10], [4, 7, 10]], [[4, 6, 10], [1, 4, 6, 10]], |
| [[4, 7, 10], [0, 4, 7, 10]], [[4, 8, 10], [1, 4, 8, 10]], |
| [[4, 6, 8, 10], [1, 4, 6, 8, 10]], [[4, 11], [4, 8, 11]], |
| [[4, 6, 11], [4, 6, 8, 11]], [[4, 7, 11], [2, 4, 7, 11]], |
| [[4, 8, 11], [2, 4, 8, 11]], [[4, 9, 11], [2, 4, 9, 11]], |
| [[4, 6, 8, 11], [1, 4, 6, 8, 11]], [[4, 6, 9, 11], [2, 4, 6, 9, 11]], |
| [[4, 7, 9, 11], [2, 4, 7, 9, 11]], [[5], [0, 5, 9]], [[5, 7], [0, 4, 7]], |
| [[5, 8], [0, 5, 8]], [[5, 9], [0, 5, 9]], [[5, 7, 9], [0, 4, 7, 9]], |
| [[5, 10], [2, 5, 10]], [[5, 7, 10], [2, 5, 7, 10]], |
| [[5, 8, 10], [2, 5, 8, 10]], [[5, 11], [0, 5, 9]], [[5, 7, 11], [2, 5, 7, 11]], |
| [[5, 8, 11], [1, 5, 8, 11]], [[5, 9, 11], [2, 5, 9, 11]], |
| [[5, 7, 9, 11], [2, 5, 7, 9, 11]], [[6], [1, 6]], [[6, 8], [1, 5, 8]], |
| [[6, 9], [2, 6, 9]], [[6, 10], [1, 6, 10]], [[6, 8, 10], [1, 5, 8, 10]], |
| [[6, 11], [3, 6, 11]], [[6, 8, 11], [3, 6, 8, 11]], |
| [[6, 9, 11], [3, 6, 9, 11]], [[7], [2, 7, 11]], [[7, 9], [2, 6, 9]], |
| [[7, 10], [2, 7, 10]], [[7, 11], [2, 7, 11]], [[7, 9, 11], [2, 7, 9, 11]], |
| [[8], [3, 8]], [[8, 10], [3, 7, 10]], [[8, 11], [4, 8, 11]], [[9], [4, 9]], |
| [[9, 11], [4, 8, 11]], [[10], [2, 5, 10]], [[11], [6, 11]]] |
|
|
| |
|
|
| ALL_CHORDS_PAIRS_FILTERED = [[[0], [0, 4, 7]], [[0, 3], [0, 3, 7]], [[0, 3, 5], [0, 3, 5, 9]], |
| [[0, 3, 5, 8], [0, 3, 7, 10]], [[0, 3, 5, 9], [0, 3, 7, 10]], |
| [[0, 3, 5, 10], [0, 3, 5, 9]], [[0, 3, 7], [0, 3, 7, 10]], |
| [[0, 3, 7, 10], [0, 3, 5, 9]], [[0, 3, 8], [0, 3, 5, 8]], |
| [[0, 3, 9], [0, 3, 5, 9]], [[0, 3, 10], [0, 3, 7, 10]], [[0, 4], [0, 4, 7]], |
| [[0, 4, 6], [0, 4, 6, 9]], [[0, 4, 6, 9], [1, 4, 6, 9]], |
| [[0, 4, 6, 10], [0, 4, 7, 10]], [[0, 4, 7], [0, 4, 7, 10]], |
| [[0, 4, 7, 10], [1, 4, 7, 10]], [[0, 4, 8], [0, 4, 7, 10]], |
| [[0, 4, 9], [0, 4, 6, 9]], [[0, 4, 10], [0, 4, 7, 10]], [[0, 5], [0, 5, 9]], |
| [[0, 5, 8], [0, 3, 5, 8]], [[0, 5, 9], [0, 3, 5, 9]], |
| [[0, 5, 10], [0, 3, 5, 10]], [[0, 6], [0, 6, 9]], [[0, 6, 9], [0, 4, 6, 9]], |
| [[0, 6, 10], [0, 4, 7, 10]], [[0, 7], [0, 4, 7]], [[0, 7, 10], [0, 4, 7, 10]], |
| [[0, 8], [0, 3, 8]], [[0, 9], [0, 4, 9]], [[0, 10], [2, 5, 10]], [[1], [1, 8]], |
| [[1, 4], [1, 4, 9]], [[1, 4, 6], [1, 4, 6, 9]], [[1, 4, 6, 9], [1, 4, 8, 11]], |
| [[1, 4, 6, 10], [0, 3, 5, 9]], [[1, 4, 6, 11], [1, 4, 6, 9]], |
| [[1, 4, 7], [1, 4, 7, 10]], [[1, 4, 7, 10], [0, 4, 7, 10]], |
| [[1, 4, 7, 11], [1, 4, 6, 10]], [[1, 4, 8], [1, 4, 8, 11]], |
| [[1, 4, 8, 11], [1, 4, 6, 9]], [[1, 4, 9], [1, 4, 6, 9]], |
| [[1, 4, 10], [1, 4, 6, 10]], [[1, 4, 11], [1, 4, 8, 11]], [[1, 5], [1, 5, 8]], |
| [[1, 5, 8], [1, 5, 8, 11]], [[1, 5, 8, 11], [2, 5, 8, 11]], |
| [[1, 5, 9], [0, 3, 5, 9]], [[1, 5, 10], [0, 4, 7, 10]], |
| [[1, 5, 11], [1, 5, 8, 11]], [[1, 6], [1, 6, 10]], [[1, 6, 9], [1, 4, 6, 9]], |
| [[1, 6, 10], [1, 4, 6, 10]], [[1, 6, 11], [1, 4, 6, 11]], [[1, 7], [1, 4, 7]], |
| [[1, 7, 10], [1, 4, 7, 10]], [[1, 7, 11], [1, 4, 7, 11]], [[1, 8], [1, 5, 8]], |
| [[1, 8, 11], [1, 4, 8, 11]], [[1, 9], [1, 4, 9]], [[1, 10], [1, 5, 10]], |
| [[1, 11], [2, 6, 11]], [[2], [2, 9]], [[2, 5], [2, 5, 9]], |
| [[2, 5, 8], [2, 5, 8, 11]], [[2, 5, 8, 11], [1, 4, 7, 10]], |
| [[2, 5, 9], [0, 3, 5, 9]], [[2, 5, 10], [0, 3, 5, 9]], |
| [[2, 5, 11], [2, 5, 8, 11]], [[2, 6], [2, 6, 9]], [[2, 6, 9], [1, 4, 6, 9]], |
| [[2, 6, 10], [1, 4, 6, 10]], [[2, 6, 11], [1, 4, 6, 10]], [[2, 7], [2, 7, 11]], |
| [[2, 7, 10], [0, 4, 7, 10]], [[2, 7, 11], [1, 4, 6, 9]], [[2, 8], [4, 8, 11]], |
| [[2, 8, 11], [2, 5, 8, 11]], [[2, 9], [2, 6, 9]], [[2, 10], [2, 5, 10]], |
| [[2, 11], [2, 7, 11]], [[3], [3, 10]], [[3, 5], [3, 7, 10]], |
| [[3, 5, 8], [0, 3, 5, 8]], [[3, 5, 8, 11], [2, 5, 8, 11]], |
| [[3, 5, 9], [0, 3, 5, 9]], [[3, 5, 10], [0, 3, 5, 10]], |
| [[3, 5, 11], [3, 5, 8, 11]], [[3, 7], [3, 7, 10]], [[3, 7, 10], [0, 3, 7, 10]], |
| [[3, 7, 11], [0, 3, 7, 10]], [[3, 8], [0, 3, 8]], [[3, 8, 11], [3, 5, 8, 11]], |
| [[3, 9], [0, 3, 9]], [[3, 10], [3, 7, 10]], [[3, 11], [3, 8, 11]], |
| [[4], [4, 11]], [[4, 6], [4, 7, 11]], [[4, 6, 9], [1, 4, 6, 9]], |
| [[4, 6, 10], [1, 4, 6, 10]], [[4, 6, 11], [1, 4, 6, 11]], [[4, 7], [0, 4, 7]], |
| [[4, 7, 10], [0, 4, 7, 10]], [[4, 7, 11], [1, 4, 7, 11]], [[4, 8], [4, 8, 11]], |
| [[4, 8, 11], [1, 4, 8, 11]], [[4, 9], [1, 4, 9]], [[4, 10], [4, 7, 10]], |
| [[4, 11], [4, 8, 11]], [[5], [0, 5, 9]], [[5, 8], [0, 5, 8]], |
| [[5, 8, 11], [1, 5, 8, 11]], [[5, 9], [0, 5, 9]], [[5, 10], [2, 5, 10]], |
| [[5, 11], [0, 5, 9]], [[6], [1, 6]], [[6, 9], [2, 6, 9]], |
| [[6, 10], [1, 6, 10]], [[6, 11], [2, 6, 11]], [[7], [2, 7, 11]], |
| [[7, 10], [2, 7, 10]], [[7, 11], [2, 7, 11]], [[8], [3, 8]], |
| [[8, 11], [4, 8, 11]], [[9], [4, 9]], [[10], [2, 5, 10]], [[11], [6, 11]]] |
|
|
| |
|
|
| ALL_CHORDS_TRIPLETS_SORTED = [[[0], [0, 4, 7], [0]], [[0, 2], [0, 4, 7], [0]], [[0, 3], [0, 3, 7], [0]], |
| [[0, 4], [0, 4, 7], [0, 4]], [[0, 2, 4], [0, 2, 4, 7], [0]], |
| [[0, 5], [0, 5, 9], [0, 5]], [[0, 2, 5], [0, 2, 5, 9], [0, 2, 5]], |
| [[0, 3, 5], [0, 3, 5, 9], [0, 3, 5]], [[0, 6], [0, 2, 6, 9], [2]], |
| [[0, 2, 6], [0, 2, 6, 9], [0, 2, 6]], [[0, 3, 6], [0, 3, 6, 8], [0, 3, 6]], |
| [[0, 4, 6], [0, 4, 6, 9], [0, 4, 6]], |
| [[0, 2, 4, 6], [0, 2, 4, 6, 9], [0, 2, 4, 6]], [[0, 7], [0, 4, 7], [0, 7]], |
| [[0, 2, 7], [0, 2, 4, 7], [0, 2, 7]], [[0, 3, 7], [0, 3, 7, 10], [0, 3, 7]], |
| [[0, 4, 7], [0, 4, 7, 9], [0, 4, 7]], [[0, 5, 7], [0, 5, 7, 9], [0, 5, 7]], |
| [[0, 2, 4, 7], [0, 2, 4, 7, 9], [0, 2, 4, 7]], |
| [[0, 2, 5, 7], [0, 2, 5, 7, 9], [0, 2, 5, 7]], |
| [[0, 3, 5, 7], [0, 3, 5, 7, 10], [0, 3, 5, 7]], [[0, 8], [0, 3, 8], [8]], |
| [[0, 2, 8], [0, 2, 5, 8], [0, 2, 8]], [[0, 3, 8], [0, 3, 5, 8], [0, 3, 8]], |
| [[0, 4, 8], [2, 4, 8, 11], [0, 4, 9]], [[0, 5, 8], [0, 3, 5, 8], [0, 5, 8]], |
| [[0, 6, 8], [0, 3, 6, 8], [0, 6, 8]], |
| [[0, 2, 4, 8], [0, 2, 4, 6, 8], [0, 2, 4, 8]], |
| [[0, 2, 5, 8], [0, 2, 5, 8, 10], [0, 2, 5, 8]], |
| [[0, 2, 6, 8], [0, 2, 6, 8, 10], [0, 2, 6, 8]], |
| [[0, 3, 5, 8], [0, 3, 5, 8, 10], [0, 3, 5, 8]], |
| [[0, 3, 6, 8], [0, 3, 6, 8, 10], [0, 3, 6, 8]], |
| [[0, 4, 6, 8], [2, 4, 6, 8, 11], [2, 6, 8, 11]], |
| [[0, 2, 4, 6, 8], [2, 4, 6, 8, 11], [2, 6, 8, 11]], [[0, 9], [0, 4, 9], [9]], |
| [[0, 2, 9], [0, 2, 6, 9], [0, 2, 9]], [[0, 3, 9], [0, 3, 5, 9], [0, 3, 9]], |
| [[0, 4, 9], [0, 4, 7, 9], [0, 4, 9]], [[0, 5, 9], [0, 2, 5, 9], [0, 5, 9]], |
| [[0, 6, 9], [0, 2, 6, 9], [0, 6, 9]], [[0, 7, 9], [0, 4, 7, 9], [0, 7, 9]], |
| [[0, 2, 4, 9], [0, 2, 4, 7, 9], [0, 2, 4, 9]], |
| [[0, 2, 5, 9], [0, 2, 5, 7, 9], [0, 2, 5, 9]], |
| [[0, 2, 6, 9], [0, 2, 4, 6, 9], [0, 2, 6, 9]], |
| [[0, 2, 7, 9], [0, 2, 4, 7, 9], [0, 2, 7, 9]], |
| [[0, 3, 5, 9], [0, 3, 5, 7, 9], [0, 3, 5, 9]], |
| [[0, 3, 6, 9], [0, 2, 4, 6, 9], [4, 6, 9]], |
| [[0, 3, 7, 9], [0, 3, 5, 7, 9], [0, 3, 7, 9]], |
| [[0, 4, 6, 9], [0, 2, 4, 6, 9], [0, 4, 6, 9]], |
| [[0, 4, 7, 9], [0, 2, 4, 7, 9], [0, 4, 7, 9]], |
| [[0, 5, 7, 9], [0, 2, 5, 7, 9], [0, 5, 7, 9]], |
| [[0, 2, 4, 6, 9], [2, 4, 6, 9, 11], [0, 2, 4, 6, 9]], |
| [[0, 2, 4, 7, 9], [2, 4, 7, 9, 11], [0, 2, 4, 7, 9]], |
| [[0, 2, 5, 7, 9], [2, 5, 7, 9, 11], [7]], |
| [[0, 3, 5, 7, 9], [2, 4, 6, 8, 11], [1, 4, 6, 8, 10]], |
| [[0, 10], [2, 5, 10], [10]], [[0, 2, 10], [0, 2, 5, 10], [10]], |
| [[0, 3, 10], [0, 3, 7, 10], [0, 3, 10]], |
| [[0, 4, 10], [0, 4, 7, 10], [0, 4, 10]], |
| [[0, 5, 10], [0, 2, 5, 10], [0, 5, 10]], |
| [[0, 6, 10], [0, 3, 6, 10], [0, 6, 10]], |
| [[0, 7, 10], [0, 4, 7, 10], [0, 7, 10]], [[0, 8, 10], [0, 3, 8, 10], [8]], |
| [[0, 2, 4, 10], [0, 2, 4, 7, 10], [0, 4, 10]], |
| [[0, 2, 5, 10], [0, 2, 5, 7, 10], [0, 2, 5, 10]], |
| [[0, 2, 6, 10], [0, 2, 6, 8, 10], [8]], |
| [[0, 2, 7, 10], [0, 2, 5, 7, 10], [2, 7, 10]], |
| [[0, 2, 8, 10], [0, 2, 5, 8, 10], [8, 10]], |
| [[0, 3, 5, 10], [0, 3, 5, 7, 10], [0, 3, 5, 10]], |
| [[0, 3, 6, 10], [0, 3, 6, 8, 10], [0, 3, 6, 10]], |
| [[0, 3, 7, 10], [0, 3, 5, 7, 10], [0, 3, 7, 10]], |
| [[0, 3, 8, 10], [0, 3, 5, 8, 10], [0, 3, 8, 10]], |
| [[0, 4, 6, 10], [0, 2, 4, 6, 10], [2]], |
| [[0, 4, 7, 10], [0, 2, 4, 7, 10], [0, 4, 7, 10]], |
| [[0, 4, 8, 10], [0, 2, 4, 8, 10], [0, 4, 8, 10]], |
| [[0, 5, 7, 10], [0, 3, 5, 7, 10], [0, 5, 7, 10]], |
| [[0, 5, 8, 10], [0, 3, 5, 8, 10], [10]], |
| [[0, 6, 8, 10], [0, 3, 6, 8, 10], [6]], |
| [[0, 2, 4, 6, 10], [0, 2, 4, 8, 10], [0, 2, 6, 8, 10]], |
| [[0, 2, 4, 7, 10], [1, 3, 6, 9, 11], [0, 2, 5, 8, 10]], |
| [[0, 2, 4, 8, 10], [1, 3, 7, 9, 11], [0, 2, 6, 8, 10]], |
| [[0, 2, 5, 7, 10], [0, 3, 5, 7, 10], [5, 10]], |
| [[0, 2, 5, 8, 10], [1, 4, 7, 9, 11], [8]], |
| [[0, 2, 6, 8, 10], [2, 4, 6, 8, 10], [0, 2, 6, 8, 10]], |
| [[0, 3, 5, 7, 10], [0, 2, 5, 7, 10], [9]], |
| [[0, 3, 5, 8, 10], [1, 3, 5, 8, 10], [0, 3, 5, 8, 10]], |
| [[0, 3, 6, 8, 10], [1, 3, 6, 8, 10], [0, 3, 6, 8, 10]], |
| [[0, 4, 6, 8, 10], [0, 2, 4, 6, 9], [1, 3, 5, 8, 10]], |
| [[0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11], [0, 2, 4, 6, 8, 10]], |
| [[1], [1, 8], [1]], [[1, 3], [1, 5, 8], [1]], [[1, 4], [1, 4, 9], [9]], |
| [[1, 5], [1, 5, 8], [1, 5]], [[1, 3, 5], [1, 3, 5, 10], [1, 3, 5]], |
| [[1, 6], [1, 6, 10], [1, 6]], [[1, 3, 6], [1, 3, 6, 10], [1, 3, 6]], |
| [[1, 4, 6], [1, 4, 6, 9], [1, 4, 6]], [[1, 7], [1, 4, 7], [1, 7]], |
| [[1, 3, 7], [1, 3, 7, 10], [1, 3, 7]], [[1, 4, 7], [1, 4, 7, 9], [1, 4, 7]], |
| [[1, 5, 7], [1, 5, 7, 10], [1, 5, 7]], [[1, 3, 5, 7], [1, 3, 5, 7, 10], [7]], |
| [[1, 8], [1, 5, 8], [1, 8]], [[1, 3, 8], [1, 3, 5, 8], [1, 3, 8]], |
| [[1, 4, 8], [1, 4, 8, 11], [1, 4, 8]], [[1, 5, 8], [1, 5, 8, 10], [1, 5, 8]], |
| [[1, 6, 8], [1, 3, 6, 8], [1, 6, 8]], |
| [[1, 3, 5, 8], [1, 3, 5, 8, 10], [1, 3, 5, 8]], |
| [[1, 3, 6, 8], [1, 3, 6, 8, 10], [1, 3, 6, 8]], |
| [[1, 4, 6, 8], [1, 4, 6, 8, 11], [1, 4, 6, 8]], [[1, 9], [1, 4, 9], [9]], |
| [[1, 3, 9], [1, 3, 6, 9], [1, 3, 9]], [[1, 4, 9], [1, 4, 6, 9], [1, 4, 9]], |
| [[1, 5, 9], [0, 3, 5, 9], [0, 5, 9]], [[1, 6, 9], [1, 4, 6, 9], [1, 6, 9]], |
| [[1, 7, 9], [1, 4, 7, 9], [1, 7, 9]], |
| [[1, 3, 5, 9], [0, 3, 5, 7, 9], [1, 5, 9]], |
| [[1, 3, 6, 9], [1, 3, 6, 9, 11], [1, 3, 6, 9]], |
| [[1, 3, 7, 9], [1, 3, 5, 7, 9], [1, 7]], |
| [[1, 4, 6, 9], [1, 4, 6, 9, 11], [1, 4, 6, 9]], |
| [[1, 4, 7, 9], [1, 4, 7, 9, 11], [1, 4, 7, 9]], |
| [[1, 5, 7, 9], [1, 3, 7, 9, 11], [1, 5, 7, 9]], |
| [[1, 3, 5, 7, 9], [2, 4, 6, 8, 11], [9]], [[1, 10], [1, 5, 10], [10]], |
| [[1, 3, 10], [1, 3, 7, 10], [1, 3, 10]], |
| [[1, 4, 10], [1, 4, 6, 10], [1, 4, 10]], |
| [[1, 5, 10], [1, 5, 8, 10], [1, 5, 10]], |
| [[1, 6, 10], [1, 4, 6, 10], [1, 6, 10]], |
| [[1, 7, 10], [1, 3, 7, 10], [1, 7, 10]], [[1, 8, 10], [1, 5, 8, 10], [10]], |
| [[1, 3, 5, 10], [1, 3, 5, 8, 10], [1, 3, 5, 10]], |
| [[1, 3, 6, 10], [1, 3, 6, 8, 10], [1, 3, 6, 10]], |
| [[1, 3, 7, 10], [1, 3, 5, 7, 10], [1, 3, 7, 10]], |
| [[1, 3, 8, 10], [1, 3, 5, 8, 10], [1, 3, 8, 10]], |
| [[1, 4, 6, 10], [1, 4, 6, 8, 10], [1, 4, 6, 10]], |
| [[1, 4, 7, 10], [0, 2, 4, 7, 10], [0, 4, 7, 10]], |
| [[1, 4, 8, 10], [1, 4, 6, 8, 10], [1, 4, 8, 10]], |
| [[1, 5, 7, 10], [1, 3, 5, 7, 10], [1, 5, 7, 10]], |
| [[1, 5, 8, 10], [1, 3, 5, 8, 10], [1, 5, 8, 10]], |
| [[1, 6, 8, 10], [1, 3, 6, 8, 10], [1, 6, 8, 10]], |
| [[1, 3, 5, 7, 10], [2, 4, 6, 8, 11], [0, 3, 5, 7, 9]], |
| [[1, 3, 5, 8, 10], [0, 3, 5, 8, 10], [6, 8, 10]], |
| [[1, 3, 6, 8, 10], [0, 3, 6, 8, 10], [8]], |
| [[1, 4, 6, 8, 10], [0, 3, 5, 7, 9], [2, 4, 6, 8, 11]], |
| [[1, 11], [2, 6, 11], [11]], [[1, 3, 11], [1, 3, 6, 11], [11]], |
| [[1, 4, 11], [1, 4, 8, 11], [1]], [[1, 5, 11], [1, 5, 8, 11], [1, 5, 11]], |
| [[1, 6, 11], [1, 4, 6, 11], [1, 6, 11]], |
| [[1, 7, 11], [1, 4, 7, 11], [1, 7, 11]], |
| [[1, 8, 11], [1, 4, 8, 11], [1, 8, 11]], [[1, 9, 11], [1, 4, 9, 11], [9]], |
| [[1, 3, 5, 11], [1, 3, 5, 8, 11], [1, 3, 5, 11]], |
| [[1, 3, 6, 11], [1, 3, 6, 8, 11], [1, 3, 6, 11]], |
| [[1, 3, 7, 11], [1, 3, 7, 9, 11], [0]], |
| [[1, 3, 8, 11], [1, 3, 6, 8, 11], [1, 3, 8, 11]], |
| [[1, 3, 9, 11], [1, 3, 6, 9, 11], [1, 3, 9, 11]], |
| [[1, 4, 6, 11], [1, 4, 6, 9, 11], [1, 4, 6, 11]], |
| [[1, 4, 7, 11], [1, 4, 7, 9, 11], [1, 4, 7, 11]], |
| [[1, 4, 8, 11], [1, 4, 6, 8, 11], [1, 4, 8, 11]], |
| [[1, 4, 9, 11], [1, 4, 6, 9, 11], [1, 4, 9, 11]], |
| [[1, 5, 7, 11], [0, 4, 6, 8, 10], [5, 7, 9, 11]], |
| [[1, 5, 8, 11], [1, 3, 5, 8, 11], [1, 5, 8, 11]], |
| [[1, 5, 9, 11], [1, 5, 7, 9, 11], [9]], |
| [[1, 6, 8, 11], [1, 3, 6, 8, 11], [1, 6, 8, 11]], |
| [[1, 6, 9, 11], [1, 4, 6, 9, 11], [1, 6, 9, 11]], |
| [[1, 7, 9, 11], [1, 4, 7, 9, 11], [1, 7, 9, 11]], |
| [[1, 3, 5, 7, 11], [0, 2, 4, 6, 8], [7, 9]], |
| [[1, 3, 5, 8, 11], [0, 2, 4, 7, 10], [1, 3, 6, 9, 11]], |
| [[1, 3, 5, 9, 11], [1, 3, 7, 9, 11], [0, 2, 6, 8, 10]], |
| [[1, 3, 6, 8, 11], [1, 4, 6, 8, 11], [6, 8, 11]], |
| [[1, 3, 6, 9, 11], [0, 2, 5, 8, 10], [1, 4, 7, 9, 11]], |
| [[1, 3, 7, 9, 11], [1, 3, 6, 9, 11], [11]], |
| [[1, 4, 6, 8, 11], [1, 4, 6, 9, 11], [9, 11]], |
| [[1, 4, 6, 9, 11], [2, 4, 6, 9, 11], [1, 4, 6, 9, 11]], |
| [[1, 4, 7, 9, 11], [2, 4, 7, 9, 11], [7, 9, 11]], |
| [[1, 5, 7, 9, 11], [2, 4, 7, 9, 11], [5, 7, 9]], |
| [[1, 3, 5, 7, 9, 11], [0, 2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 11]], |
| [[2], [2, 9], [2]], [[2, 4], [2, 6, 9], [2]], [[2, 5], [2, 5, 9], [2]], |
| [[2, 6], [2, 6, 9], [2]], [[2, 4, 6], [2, 4, 6, 9], [2, 4, 6]], |
| [[2, 7], [2, 7, 11], [2, 7]], [[2, 4, 7], [2, 4, 7, 11], [2, 4, 7]], |
| [[2, 5, 7], [2, 5, 7, 11], [2, 5, 7]], [[2, 8], [4, 8, 11], [4]], |
| [[2, 4, 8], [2, 4, 8, 11], [2, 4, 8]], [[2, 5, 8], [2, 5, 8, 10], [2, 5, 8]], |
| [[2, 6, 8], [2, 6, 8, 11], [2, 6, 8]], |
| [[2, 4, 6, 8], [2, 4, 6, 8, 11], [2, 4, 6, 8]], [[2, 9], [2, 6, 9], [2, 9]], |
| [[2, 4, 9], [2, 4, 6, 9], [2, 4, 9]], [[2, 5, 9], [0, 2, 5, 9], [2, 5, 9]], |
| [[2, 6, 9], [2, 6, 9, 11], [2, 6, 9]], [[2, 7, 9], [2, 7, 9, 11], [2, 7, 9]], |
| [[2, 4, 6, 9], [2, 4, 6, 9, 11], [2, 4, 6, 9]], |
| [[2, 4, 7, 9], [2, 4, 7, 9, 11], [2, 4, 7, 9]], |
| [[2, 5, 7, 9], [0, 2, 5, 7, 9], [2, 5, 7, 9]], [[2, 10], [2, 5, 10], [10]], |
| [[2, 4, 10], [2, 4, 7, 10], [2, 4, 10]], |
| [[2, 5, 10], [2, 5, 7, 10], [2, 5, 10]], |
| [[2, 6, 10], [1, 4, 6, 10], [1, 6, 10]], |
| [[2, 7, 10], [2, 5, 7, 10], [2, 7, 10]], |
| [[2, 8, 10], [2, 5, 8, 10], [2, 8, 10]], |
| [[2, 4, 6, 10], [0, 2, 4, 6, 10], [2, 4, 6, 10]], |
| [[2, 4, 7, 10], [0, 2, 4, 7, 10], [2, 4, 7, 10]], |
| [[2, 4, 8, 10], [2, 4, 7, 9, 11], [2, 4, 7, 11]], |
| [[2, 5, 7, 10], [0, 2, 5, 7, 10], [2, 5, 7, 10]], |
| [[2, 5, 8, 10], [0, 2, 5, 8, 10], [2, 5, 8, 10]], |
| [[2, 6, 8, 10], [1, 3, 5, 7, 10], [1, 7]], |
| [[2, 4, 6, 8, 10], [0, 2, 6, 8, 10], [2, 4, 6, 8, 10]], |
| [[2, 11], [2, 7, 11], [7]], [[2, 4, 11], [2, 4, 8, 11], [2, 4, 11]], |
| [[2, 5, 11], [2, 5, 7, 11], [2, 5, 11]], |
| [[2, 6, 11], [2, 6, 9, 11], [2, 6, 11]], |
| [[2, 7, 11], [2, 4, 7, 11], [2, 7, 11]], |
| [[2, 8, 11], [2, 4, 8, 11], [2, 8, 11]], |
| [[2, 9, 11], [2, 6, 9, 11], [2, 9, 11]], |
| [[2, 4, 6, 11], [2, 4, 6, 9, 11], [2, 4, 6, 11]], |
| [[2, 4, 7, 11], [2, 4, 7, 9, 11], [2, 4, 7, 11]], |
| [[2, 4, 8, 11], [2, 4, 6, 8, 11], [2, 4, 8, 11]], |
| [[2, 4, 9, 11], [2, 4, 7, 9, 11], [2, 4, 9, 11]], |
| [[2, 5, 7, 11], [2, 5, 7, 9, 11], [2, 5, 7, 11]], |
| [[2, 5, 8, 11], [1, 3, 5, 8, 11], [1, 5, 8, 11]], |
| [[2, 5, 9, 11], [2, 5, 7, 9, 11], [2, 5, 9, 11]], |
| [[2, 6, 8, 11], [2, 4, 6, 8, 11], [2, 6, 8, 11]], |
| [[2, 6, 9, 11], [2, 4, 6, 9, 11], [2, 6, 9, 11]], |
| [[2, 7, 9, 11], [2, 4, 7, 9, 11], [2, 7, 9, 11]], |
| [[2, 4, 6, 8, 11], [2, 4, 6, 9, 11], [2, 4, 6, 8, 11]], |
| [[2, 4, 6, 9, 11], [2, 4, 7, 9, 11], [2, 7, 9]], |
| [[2, 4, 7, 9, 11], [0, 2, 4, 7, 9], [11]], |
| [[2, 5, 7, 9, 11], [2, 4, 7, 9, 11], [2, 7, 9, 11]], [[3], [3, 10], [3]], |
| [[3, 5], [3, 7, 10], [3]], [[3, 6], [3, 6, 11], [11]], |
| [[3, 7], [3, 7, 10], [3]], [[3, 5, 7], [3, 5, 7, 10], [3, 5, 7]], |
| [[3, 8], [0, 3, 8], [3, 8]], [[3, 5, 8], [0, 3, 5, 8], [8]], |
| [[3, 6, 8], [0, 3, 6, 8], [3, 6, 8]], [[3, 9], [0, 3, 9], [3, 9]], |
| [[3, 5, 9], [0, 3, 5, 9], [3, 5, 9]], [[3, 6, 9], [3, 6, 9, 11], [3, 6, 9]], |
| [[3, 7, 9], [0, 3, 7, 9], [3, 7, 9]], |
| [[3, 5, 7, 9], [0, 3, 5, 7, 9], [0, 3, 5, 9]], [[3, 10], [3, 7, 10], [3, 10]], |
| [[3, 5, 10], [3, 5, 7, 10], [3, 5, 10]], |
| [[3, 6, 10], [1, 3, 6, 10], [3, 6, 10]], |
| [[3, 7, 10], [0, 3, 7, 10], [3, 7, 10]], |
| [[3, 8, 10], [0, 3, 8, 10], [3, 8, 10]], |
| [[3, 5, 7, 10], [0, 3, 5, 7, 10], [3, 5, 7, 10]], |
| [[3, 5, 8, 10], [0, 3, 5, 8, 10], [3, 5, 8, 10]], |
| [[3, 6, 8, 10], [1, 3, 6, 8, 10], [3, 6, 8, 10]], [[3, 11], [3, 6, 11], [11]], |
| [[3, 5, 11], [3, 5, 8, 11], [3, 5, 11]], |
| [[3, 6, 11], [3, 6, 9, 11], [3, 6, 11]], |
| [[3, 7, 11], [2, 5, 7, 11], [2, 7, 11]], |
| [[3, 8, 11], [3, 6, 8, 11], [3, 8, 11]], |
| [[3, 9, 11], [3, 6, 9, 11], [3, 9, 11]], |
| [[3, 5, 7, 11], [3, 5, 7, 9, 11], [3, 5, 7, 11]], |
| [[3, 5, 8, 11], [1, 3, 5, 8, 11], [3, 5, 8, 11]], |
| [[3, 5, 9, 11], [3, 5, 7, 9, 11], [5, 7, 9, 11]], |
| [[3, 6, 8, 11], [1, 3, 6, 8, 11], [3, 6, 8, 11]], |
| [[3, 6, 9, 11], [1, 3, 6, 9, 11], [3, 6, 9, 11]], |
| [[3, 7, 9, 11], [2, 4, 7, 9, 11], [7, 9, 11]], |
| [[3, 5, 7, 9, 11], [2, 5, 7, 9, 11], [2, 5, 7, 11]], [[4], [4, 11], [4]], |
| [[4, 6], [4, 7, 11], [4]], [[4, 7], [0, 4, 7], [0]], [[4, 8], [4, 8, 11], [4]], |
| [[4, 6, 8], [4, 6, 8, 11], [4]], [[4, 9], [1, 4, 9], [4, 9]], |
| [[4, 6, 9], [1, 4, 6, 9], [4, 6, 9]], [[4, 7, 9], [1, 4, 7, 9], [4, 7, 9]], |
| [[4, 10], [4, 7, 10], [4, 10]], [[4, 6, 10], [1, 4, 6, 10], [4, 6, 10]], |
| [[4, 7, 10], [0, 4, 7, 10], [4, 7, 10]], [[4, 8, 10], [1, 4, 8, 10], [1]], |
| [[4, 6, 8, 10], [1, 4, 6, 8, 10], [6]], [[4, 11], [4, 8, 11], [4, 11]], |
| [[4, 6, 11], [4, 6, 8, 11], [4, 6, 11]], |
| [[4, 7, 11], [2, 4, 7, 11], [4, 7, 11]], |
| [[4, 8, 11], [2, 4, 8, 11], [4, 8, 11]], |
| [[4, 9, 11], [2, 4, 9, 11], [4, 9, 11]], |
| [[4, 6, 8, 11], [1, 4, 6, 8, 11], [4, 6, 8, 11]], |
| [[4, 6, 9, 11], [2, 4, 6, 9, 11], [4, 6, 9, 11]], |
| [[4, 7, 9, 11], [2, 4, 7, 9, 11], [4, 7, 9, 11]], [[5], [0, 5, 9], [5]], |
| [[5, 7], [0, 4, 7], [0]], [[5, 8], [0, 5, 8], [5]], [[5, 9], [0, 5, 9], [5]], |
| [[5, 7, 9], [0, 4, 7, 9], [5]], [[5, 10], [2, 5, 10], [5, 10]], |
| [[5, 7, 10], [2, 5, 7, 10], [7]], [[5, 8, 10], [2, 5, 8, 10], [5, 8, 10]], |
| [[5, 11], [0, 5, 9], [5]], [[5, 7, 11], [2, 5, 7, 11], [5, 7, 11]], |
| [[5, 8, 11], [1, 5, 8, 11], [5, 8, 11]], |
| [[5, 9, 11], [2, 5, 9, 11], [5, 9, 11]], |
| [[5, 7, 9, 11], [2, 5, 7, 9, 11], [5, 7, 9]], [[6], [1, 6], [6]], |
| [[6, 8], [1, 5, 8], [8]], [[6, 9], [2, 6, 9], [2]], [[6, 10], [1, 6, 10], [6]], |
| [[6, 8, 10], [1, 5, 8, 10], [6, 8, 10]], [[6, 11], [3, 6, 11], [6, 11]], |
| [[6, 8, 11], [3, 6, 8, 11], [6, 8, 11]], |
| [[6, 9, 11], [3, 6, 9, 11], [6, 9, 11]], [[7], [2, 7, 11], [7]], |
| [[7, 9], [2, 6, 9], [2]], [[7, 10], [2, 7, 10], [7]], |
| [[7, 11], [2, 7, 11], [7]], [[7, 9, 11], [2, 7, 9, 11], [7, 9, 11]], |
| [[8], [3, 8], [8]], [[8, 10], [3, 7, 10], [3]], [[8, 11], [4, 8, 11], [4]], |
| [[9], [4, 9], [9]], [[9, 11], [4, 8, 11], [4]], [[10], [2, 5, 10], [10]], |
| [[11], [6, 11], [11]]] |
|
|
| |
|
|
| ALL_CHORDS_TRIPLETS_FILTERED = [[[0], [0, 4, 7], [7]], [[0, 3], [0, 3, 7], [0]], |
| [[0, 3, 5], [0, 3, 5, 9], [5]], [[0, 3, 5, 8], [0, 3, 7, 10], [0]], |
| [[0, 3, 5, 9], [0, 3, 7, 10], [10]], [[0, 3, 5, 10], [0, 3, 5, 9], [5]], |
| [[0, 3, 7], [0, 3, 7, 10], [0]], [[0, 3, 7, 10], [0, 3, 5, 9], [2, 5, 10]], |
| [[0, 3, 8], [0, 3, 5, 8], [8]], [[0, 3, 9], [0, 3, 5, 9], [5]], |
| [[0, 3, 10], [0, 3, 7, 10], [0]], [[0, 4], [0, 4, 7], [0]], |
| [[0, 4, 6], [0, 4, 6, 9], [4]], [[0, 4, 6, 9], [1, 4, 6, 9], [9]], |
| [[0, 4, 6, 10], [0, 4, 7, 10], [0, 4, 10]], [[0, 4, 7], [0, 4, 7, 10], [0]], |
| [[0, 4, 7, 10], [1, 4, 7, 10], [0]], [[0, 4, 8], [0, 4, 7, 10], [0, 5, 8]], |
| [[0, 4, 9], [0, 4, 6, 9], [9]], [[0, 4, 10], [0, 4, 7, 10], [0]], |
| [[0, 5], [0, 5, 9], [5]], [[0, 5, 8], [0, 3, 5, 8], [5]], |
| [[0, 5, 9], [0, 3, 5, 9], [5]], [[0, 5, 10], [0, 3, 5, 10], [10]], |
| [[0, 6], [0, 6, 9], [9]], [[0, 6, 9], [0, 4, 6, 9], [6]], |
| [[0, 6, 10], [0, 4, 7, 10], [10]], [[0, 7], [0, 4, 7], [0]], |
| [[0, 7, 10], [0, 4, 7, 10], [0]], [[0, 8], [0, 3, 8], [8]], |
| [[0, 9], [0, 4, 9], [9]], [[0, 10], [2, 5, 10], [10]], [[1], [1, 8], [8]], |
| [[1, 4], [1, 4, 9], [9]], [[1, 4, 6], [1, 4, 6, 9], [6]], |
| [[1, 4, 6, 9], [1, 4, 8, 11], [4]], [[1, 4, 6, 10], [0, 3, 5, 9], [5]], |
| [[1, 4, 6, 11], [1, 4, 6, 9], [6]], [[1, 4, 7], [1, 4, 7, 10], [10]], |
| [[1, 4, 7, 10], [0, 4, 7, 10], [0]], |
| [[1, 4, 7, 11], [1, 4, 6, 10], [1, 6, 10]], [[1, 4, 8], [1, 4, 8, 11], [1]], |
| [[1, 4, 8, 11], [1, 4, 6, 9], [1, 4, 9]], [[1, 4, 9], [1, 4, 6, 9], [9]], |
| [[1, 4, 10], [1, 4, 6, 10], [6]], [[1, 4, 11], [1, 4, 8, 11], [1]], |
| [[1, 5], [1, 5, 8], [1]], [[1, 5, 8], [1, 5, 8, 11], [1]], |
| [[1, 5, 8, 11], [2, 5, 8, 11], [1]], [[1, 5, 9], [0, 3, 5, 9], [0, 5, 9]], |
| [[1, 5, 10], [0, 4, 7, 10], [0]], [[1, 5, 11], [1, 5, 8, 11], [11]], |
| [[1, 6], [1, 6, 10], [6]], [[1, 6, 9], [1, 4, 6, 9], [6]], |
| [[1, 6, 10], [1, 4, 6, 10], [6]], [[1, 6, 11], [1, 4, 6, 11], [11]], |
| [[1, 7], [1, 4, 7], [4]], [[1, 7, 10], [1, 4, 7, 10], [4]], |
| [[1, 7, 11], [1, 4, 7, 11], [7]], [[1, 8], [1, 5, 8], [1]], |
| [[1, 8, 11], [1, 4, 8, 11], [1]], [[1, 9], [1, 4, 9], [9]], |
| [[1, 10], [1, 5, 10], [10]], [[1, 11], [2, 6, 11], [11]], [[2], [2, 9], [9]], |
| [[2, 5], [2, 5, 9], [2]], [[2, 5, 8], [2, 5, 8, 11], [2]], |
| [[2, 5, 8, 11], [1, 4, 7, 10], [0, 3, 8]], |
| [[2, 5, 9], [0, 3, 5, 9], [2, 5, 10]], [[2, 5, 10], [0, 3, 5, 9], [2, 10]], |
| [[2, 5, 11], [2, 5, 8, 11], [8]], [[2, 6], [2, 6, 9], [2]], |
| [[2, 6, 9], [1, 4, 6, 9], [1, 4, 9]], [[2, 6, 10], [1, 4, 6, 10], [1, 6, 10]], |
| [[2, 6, 11], [1, 4, 6, 10], [1, 6, 10]], [[2, 7], [2, 7, 11], [7]], |
| [[2, 7, 10], [0, 4, 7, 10], [0]], [[2, 7, 11], [1, 4, 6, 9], [1, 4, 9]], |
| [[2, 8], [4, 8, 11], [4]], [[2, 8, 11], [2, 5, 8, 11], [4]], |
| [[2, 9], [2, 6, 9], [2]], [[2, 10], [2, 5, 10], [10]], |
| [[2, 11], [2, 7, 11], [7]], [[3], [3, 10], [10]], [[3, 5], [3, 7, 10], [3]], |
| [[3, 5, 8], [0, 3, 5, 8], [8]], [[3, 5, 8, 11], [2, 5, 8, 11], [2]], |
| [[3, 5, 9], [0, 3, 5, 9], [5]], [[3, 5, 10], [0, 3, 5, 10], [5, 10]], |
| [[3, 5, 11], [3, 5, 8, 11], [5]], [[3, 7], [3, 7, 10], [3]], |
| [[3, 7, 10], [0, 3, 7, 10], [10]], [[3, 7, 11], [0, 3, 7, 10], [3, 7, 10]], |
| [[3, 8], [0, 3, 8], [8]], [[3, 8, 11], [3, 5, 8, 11], [11]], |
| [[3, 9], [0, 3, 9], [9]], [[3, 10], [3, 7, 10], [3]], |
| [[3, 11], [3, 8, 11], [8]], [[4], [4, 11], [11]], [[4, 6], [4, 7, 11], [4]], |
| [[4, 6, 9], [1, 4, 6, 9], [9]], [[4, 6, 10], [1, 4, 6, 10], [6]], |
| [[4, 6, 11], [1, 4, 6, 11], [11]], [[4, 7], [0, 4, 7], [0]], |
| [[4, 7, 10], [0, 4, 7, 10], [0]], [[4, 7, 11], [1, 4, 7, 11], [11]], |
| [[4, 8], [4, 8, 11], [4]], [[4, 8, 11], [1, 4, 8, 11], [4]], |
| [[4, 9], [1, 4, 9], [9]], [[4, 10], [4, 7, 10], [7]], |
| [[4, 11], [4, 8, 11], [4]], [[5], [0, 5, 9], [0]], [[5, 8], [0, 5, 8], [5]], |
| [[5, 8, 11], [1, 5, 8, 11], [1]], [[5, 9], [0, 5, 9], [5]], |
| [[5, 10], [2, 5, 10], [10]], [[5, 11], [0, 5, 9], [5]], [[6], [1, 6], [1]], |
| [[6, 9], [2, 6, 9], [2]], [[6, 10], [1, 6, 10], [6]], |
| [[6, 11], [2, 6, 11], [11]], [[7], [2, 7, 11], [2]], |
| [[7, 10], [2, 7, 10], [7]], [[7, 11], [2, 7, 11], [7]], [[8], [3, 8], [3]], |
| [[8, 11], [4, 8, 11], [4]], [[9], [4, 9], [4]], [[10], [2, 5, 10], [5]], |
| [[11], [6, 11], [6]]] |
|
|
| |
|
|
| def pitches_to_tones(pitches): |
| return [p % 12 for p in pitches] |
|
|
| |
|
|
| def tones_to_pitches(tones, base_octave=5): |
| return [(base_octave * 12) + t for t in tones] |
|
|
| |
|
|
| def find_closest_value(lst, val): |
|
|
| closest_value = min(lst, key=lambda x: abs(val - x)) |
| closest_value_indexes = [i for i in range(len(lst)) if lst[i] == closest_value] |
| |
| return [closest_value, abs(val - closest_value), closest_value_indexes] |
|
|
| |
|
|
| def transpose_tones_chord(tones_chord, transpose_value=0): |
| return sorted([((60+t)+transpose_value) % 12 for t in sorted(set(tones_chord))]) |
|
|
| |
|
|
| def transpose_tones(tones, transpose_value=0): |
| return [((60+t)+transpose_value) % 12 for t in tones] |
|
|
| |
|
|
| def transpose_pitches_chord(pitches_chord, transpose_value=0): |
| return [max(1, min(127, p+transpose_value)) for p in sorted(set(pitches_chord), reverse=True)] |
|
|
| |
|
|
| def transpose_pitches(pitches, transpose_value=0): |
| return [max(1, min(127, p+transpose_value)) for p in pitches] |
|
|
| |
|
|
| def reverse_enhanced_score_notes(escore_notes): |
|
|
| score = recalculate_score_timings(escore_notes) |
|
|
| ematrix = escore_notes_to_escore_matrix(score, reverse_matrix=True) |
| e_score = escore_matrix_to_original_escore_notes(ematrix) |
|
|
| reversed_score = recalculate_score_timings(e_score) |
|
|
| return reversed_score |
|
|
| |
|
|
| def count_patterns(lst, sublist): |
| count = 0 |
| idx = 0 |
| for i in range(len(lst) - len(sublist) + 1): |
| if lst[idx:idx + len(sublist)] == sublist: |
| count += 1 |
| idx += len(sublist) |
| else: |
| idx += 1 |
| return count |
|
|
| |
|
|
| def find_lrno_patterns(seq): |
|
|
| all_seqs = Counter() |
|
|
| max_pat_len = math.ceil(len(seq) / 2) |
|
|
| num_iter = 0 |
|
|
| for i in range(len(seq)): |
| for j in range(i+1, len(seq)+1): |
| if j-i <= max_pat_len: |
| all_seqs[tuple(seq[i:j])] += 1 |
| num_iter += 1 |
|
|
| max_count = 0 |
| max_len = 0 |
|
|
| for val, count in all_seqs.items(): |
|
|
| if max_len < len(val): |
| max_count = max(2, count) |
|
|
| if count > 1: |
| max_len = max(max_len, len(val)) |
| pval = val |
|
|
| max_pats = [] |
|
|
| for val, count in all_seqs.items(): |
| if count == max_count and len(val) == max_len: |
| max_pats.append(val) |
|
|
| found_patterns = [] |
|
|
| for pat in max_pats: |
| count = count_patterns(seq, list(pat)) |
| if count > 1: |
| found_patterns.append([count, len(pat), pat]) |
|
|
| return found_patterns |
|
|
| |
|
|
| def delta_pitches(escore_notes, pitches_index=4): |
|
|
| pitches = [p[pitches_index] for p in escore_notes] |
| |
| return [a-b for a, b in zip(pitches[:-1], pitches[1:])] |
|
|
| |
|
|
| def split_list(lst, val): |
| return [lst[i:j] for i, j in zip([0] + [k + 1 for k, x in enumerate(lst) if x == val], [k for k, x in enumerate(lst) if x == val] + [len(lst)]) if j > i] |
|
|
| |
|
|
| def even_timings(escore_notes, |
| times_idx=1, |
| durs_idx=2 |
| ): |
|
|
| esn = copy.deepcopy(escore_notes) |
|
|
| for e in esn: |
|
|
| if e[times_idx] != 0: |
| if e[times_idx] % 2 != 0: |
| e[times_idx] += 1 |
|
|
| if e[durs_idx] % 2 != 0: |
| e[durs_idx] += 1 |
|
|
| return esn |
|
|
| |
|
|
| def delta_score_to_abs_score(delta_score_notes, |
| times_idx=1 |
| ): |
|
|
| abs_score = copy.deepcopy(delta_score_notes) |
|
|
| abs_time = 0 |
|
|
| for i, e in enumerate(delta_score_notes): |
|
|
| dtime = e[times_idx] |
| |
| abs_time += dtime |
|
|
| abs_score[i][times_idx] = abs_time |
| |
| return abs_score |
|
|
| |
|
|
|
|
| def adjust_numbers_to_sum(numbers, target_sum): |
|
|
| current_sum = sum(numbers) |
| difference = target_sum - current_sum |
|
|
| non_zero_elements = [(i, num) for i, num in enumerate(numbers) if num != 0] |
|
|
| total_non_zero = sum(num for _, num in non_zero_elements) |
|
|
| increments = [] |
| for i, num in non_zero_elements: |
| proportion = num / total_non_zero |
| increment = proportion * difference |
| increments.append(increment) |
|
|
| for idx, (i, num) in enumerate(non_zero_elements): |
| numbers[i] += int(round(increments[idx])) |
|
|
| current_sum = sum(numbers) |
| difference = target_sum - current_sum |
| non_zero_indices = [i for i, num in enumerate(numbers) if num != 0] |
|
|
| for i in range(abs(difference)): |
| numbers[non_zero_indices[i % len(non_zero_indices)]] += 1 if difference > 0 else -1 |
|
|
| return numbers |
|
|
| |
|
|
| def find_next_bar(escore_notes, bar_time, start_note_idx, cur_bar): |
| for e in escore_notes[start_note_idx:]: |
| if e[1] // bar_time > cur_bar: |
| return e, escore_notes.index(e) |
|
|
| |
|
|
| def align_escore_notes_to_bars(escore_notes, |
| bar_time=4000, |
| trim_durations=False, |
| split_durations=False |
| ): |
|
|
| |
|
|
| aligned_escore_notes = copy.deepcopy(escore_notes) |
|
|
| abs_time = 0 |
| nidx = 0 |
| delta = 0 |
| bcount = 0 |
| next_bar = [0] |
|
|
| |
|
|
| while next_bar: |
|
|
| next_bar = find_next_bar(escore_notes, bar_time, nidx, bcount) |
|
|
| if next_bar: |
|
|
| gescore_notes = escore_notes[nidx:next_bar[1]] |
| else: |
| gescore_notes = escore_notes[nidx:] |
|
|
| original_timings = [delta] + [(b[1]-a[1]) for a, b in zip(gescore_notes[:-1], gescore_notes[1:])] |
| adj_timings = adjust_numbers_to_sum(original_timings, bar_time) |
|
|
| for t in adj_timings: |
|
|
| abs_time += t |
|
|
| aligned_escore_notes[nidx][1] = abs_time |
| aligned_escore_notes[nidx][2] -= int(bar_time // 200) |
|
|
| nidx += 1 |
|
|
| if next_bar: |
| delta = escore_notes[next_bar[1]][1]-escore_notes[next_bar[1]-1][1] |
| bcount += 1 |
|
|
| |
|
|
| aligned_adjusted_escore_notes = [] |
| bcount = 0 |
|
|
| for a in aligned_escore_notes: |
| bcount = a[1] // bar_time |
| nbtime = bar_time * (bcount+1) |
|
|
| if a[1]+a[2] > nbtime and a[3] != 9: |
| if trim_durations or split_durations: |
| ddiff = ((a[1]+a[2])-nbtime) |
| aa = copy.deepcopy(a) |
| aa[2] = a[2] - ddiff |
| aligned_adjusted_escore_notes.append(aa) |
|
|
| if split_durations: |
| aaa = copy.deepcopy(a) |
| aaa[1] = a[1]+aa[2] |
| aaa[2] = ddiff |
|
|
| aligned_adjusted_escore_notes.append(aaa) |
|
|
| else: |
| aligned_adjusted_escore_notes.append(a) |
|
|
| else: |
| aligned_adjusted_escore_notes.append(a) |
|
|
| |
|
|
| return aligned_adjusted_escore_notes |
|
|
| |
|
|
| def normalize_chord_durations(chord, |
| dur_idx=2, |
| norm_factor=100 |
| ): |
|
|
| nchord = copy.deepcopy(chord) |
| |
| for c in nchord: |
| c[dur_idx] = int(round(max(1 / norm_factor, c[dur_idx] // norm_factor) * norm_factor)) |
|
|
| return nchord |
|
|
| |
|
|
| def normalize_chordified_score_durations(chordified_score, |
| dur_idx=2, |
| norm_factor=100 |
| ): |
|
|
| ncscore = copy.deepcopy(chordified_score) |
| |
| for cc in ncscore: |
| for c in cc: |
| c[dur_idx] = int(round(max(1 / norm_factor, c[dur_idx] // norm_factor) * norm_factor)) |
|
|
| return ncscore |
|
|
| |
|
|
| def horizontal_ordered_list_search(list_of_lists, |
| query_list, |
| start_idx=0, |
| end_idx=-1 |
| ): |
|
|
| lol = list_of_lists |
|
|
| results = [] |
|
|
| if start_idx > 0: |
| lol = list_of_lists[start_idx:] |
|
|
| if start_idx == -1: |
| idx = -1 |
| for i, l in enumerate(list_of_lists): |
| try: |
| idx = l.index(query_list[0]) |
| lol = list_of_lists[i:] |
| break |
| except: |
| continue |
|
|
| if idx == -1: |
| results.append(-1) |
| return results |
| else: |
| results.append(i) |
|
|
| if end_idx != -1: |
| lol = list_of_lists[start_idx:start_idx+max(end_idx, len(query_list))] |
|
|
| for i, q in enumerate(query_list): |
| try: |
| idx = lol[i].index(q) |
| results.append(idx) |
| except: |
| results.append(-1) |
| return results |
|
|
| return results |
|
|
| |
|
|
| def escore_notes_to_escore_matrix(escore_notes, |
| alt_velocities=False, |
| flip_matrix=False, |
| reverse_matrix=False |
| ): |
|
|
| last_time = escore_notes[-1][1] |
| last_notes = [e for e in escore_notes if e[1] == last_time] |
| max_last_dur = max([e[2] for e in last_notes]) |
|
|
| time_range = last_time+max_last_dur |
|
|
| channels_list = sorted(set([e[3] for e in escore_notes])) |
|
|
| escore_matrixes = [] |
|
|
| for cha in channels_list: |
|
|
| escore_matrix = [[[-1, -1]] * 128 for _ in range(time_range)] |
|
|
| pe = escore_notes[0] |
|
|
| for i, note in enumerate(escore_notes): |
|
|
| etype, time, duration, channel, pitch, velocity, patch = note |
|
|
| time = max(0, time) |
| duration = max(1, duration) |
| channel = max(0, min(15, channel)) |
| pitch = max(0, min(127, pitch)) |
| velocity = max(0, min(127, velocity)) |
| patch = max(0, min(128, patch)) |
|
|
| if alt_velocities: |
| velocity -= (i % 2) |
|
|
| if channel == cha: |
|
|
| for t in range(time, min(time + duration, time_range)): |
|
|
| escore_matrix[t][pitch] = [velocity, patch] |
|
|
| pe = note |
|
|
| if flip_matrix: |
|
|
| temp_matrix = [] |
|
|
| for m in escore_matrix: |
| temp_matrix.append(m[::-1]) |
|
|
| escore_matrix = temp_matrix |
|
|
| if reverse_matrix: |
| escore_matrix = escore_matrix[::-1] |
|
|
| escore_matrixes.append(escore_matrix) |
|
|
| return [channels_list, escore_matrixes] |
|
|
| |
|
|
| def escore_matrix_to_merged_escore_notes(full_escore_matrix, |
| max_note_duration=4000 |
| ): |
|
|
| merged_escore_notes = [] |
|
|
| mat_channels_list = full_escore_matrix[0] |
| |
| for m, cha in enumerate(mat_channels_list): |
|
|
| escore_matrix = full_escore_matrix[1][m] |
|
|
| result = [] |
|
|
| for j in range(len(escore_matrix[0])): |
|
|
| count = 1 |
|
|
| for i in range(1, len(escore_matrix)): |
|
|
| if escore_matrix[i][j] != [-1, -1] and escore_matrix[i][j][1] == escore_matrix[i-1][j][1] and count < max_note_duration: |
| count += 1 |
|
|
| else: |
| if count > 1: |
| result.append([i-count, count, j, escore_matrix[i-1][j]]) |
|
|
| count = 1 |
|
|
| if count > 1: |
| result.append([len(escore_matrix)-count, count, j, escore_matrix[-1][j]]) |
|
|
| result.sort(key=lambda x: (x[0], -x[2])) |
|
|
| for r in result: |
| merged_escore_notes.append(['note', r[0], r[1], cha, r[2], r[3][0], r[3][1]]) |
|
|
| return sorted(merged_escore_notes, key=lambda x: (x[1], -x[4], x[6])) |
|
|
| |
|
|
| def escore_matrix_to_original_escore_notes(full_escore_matrix): |
|
|
| merged_escore_notes = [] |
|
|
| mat_channels_list = full_escore_matrix[0] |
|
|
| for m, cha in enumerate(mat_channels_list): |
|
|
| escore_matrix = full_escore_matrix[1][m] |
|
|
| result = [] |
|
|
| for j in range(len(escore_matrix[0])): |
|
|
| count = 1 |
|
|
| for i in range(1, len(escore_matrix)): |
|
|
| if escore_matrix[i][j] != [-1, -1] and escore_matrix[i][j] == escore_matrix[i-1][j]: |
| count += 1 |
|
|
| else: |
| if count > 1: |
| result.append([i-count, count, j, escore_matrix[i-1][j]]) |
|
|
| count = 1 |
|
|
| if count > 1: |
| result.append([len(escore_matrix)-count, count, j, escore_matrix[-1][j]]) |
|
|
| result.sort(key=lambda x: (x[0], -x[2])) |
|
|
| for r in result: |
| merged_escore_notes.append(['note', r[0], r[1], cha, r[2], r[3][0], r[3][1]]) |
|
|
| return sorted(merged_escore_notes, key=lambda x: (x[1], -x[4], x[6])) |
|
|
| |
|
|
| def escore_notes_to_binary_matrix(escore_notes, |
| channel=0, |
| patch=0, |
| flip_matrix=False, |
| reverse_matrix=False |
| ): |
|
|
| escore = [e for e in escore_notes if e[3] == channel and e[6] == patch] |
|
|
| if escore: |
| last_time = escore[-1][1] |
| last_notes = [e for e in escore if e[1] == last_time] |
| max_last_dur = max([e[2] for e in last_notes]) |
|
|
| time_range = last_time+max_last_dur |
|
|
| escore_matrix = [] |
|
|
| escore_matrix = [[0] * 128 for _ in range(time_range)] |
|
|
| for note in escore: |
|
|
| etype, time, duration, chan, pitch, velocity, pat = note |
|
|
| time = max(0, time) |
| duration = max(1, duration) |
| chan = max(0, min(15, chan)) |
| pitch = max(0, min(127, pitch)) |
| velocity = max(0, min(127, velocity)) |
| pat = max(0, min(128, pat)) |
|
|
| if channel == chan and patch == pat: |
|
|
| for t in range(time, min(time + duration, time_range)): |
|
|
| escore_matrix[t][pitch] = 1 |
|
|
| if flip_matrix: |
|
|
| temp_matrix = [] |
|
|
| for m in escore_matrix: |
| temp_matrix.append(m[::-1]) |
|
|
| escore_matrix = temp_matrix |
|
|
| if reverse_matrix: |
| escore_matrix = escore_matrix[::-1] |
|
|
| return escore_matrix |
|
|
| else: |
| return None |
|
|
| |
|
|
| def binary_matrix_to_original_escore_notes(binary_matrix, |
| channel=0, |
| patch=0, |
| velocity=-1 |
| ): |
|
|
| result = [] |
|
|
| for j in range(len(binary_matrix[0])): |
|
|
| count = 1 |
|
|
| for i in range(1, len(binary_matrix)): |
|
|
| if binary_matrix[i][j] != 0 and binary_matrix[i][j] == binary_matrix[i-1][j]: |
| count += 1 |
|
|
| else: |
| if count > 1: |
| result.append([i-count, count, j, binary_matrix[i-1][j]]) |
| |
| else: |
| if binary_matrix[i-1][j] != 0: |
| result.append([i-count, count, j, binary_matrix[i-1][j]]) |
|
|
| count = 1 |
|
|
| if count > 1: |
| result.append([len(binary_matrix)-count, count, j, binary_matrix[-1][j]]) |
| |
| else: |
| if binary_matrix[i-1][j] != 0: |
| result.append([i-count, count, j, binary_matrix[i-1][j]]) |
|
|
| result.sort(key=lambda x: (x[0], -x[2])) |
|
|
| original_escore_notes = [] |
|
|
| vel = velocity |
|
|
| for r in result: |
| |
| if velocity == -1: |
| vel = max(40, r[2]) |
|
|
| original_escore_notes.append(['note', r[0], r[1], channel, r[2], vel, patch]) |
|
|
| return sorted(original_escore_notes, key=lambda x: (x[1], -x[4], x[6])) |
|
|
| |
|
|
| def escore_notes_averages(escore_notes, |
| times_index=1, |
| durs_index=2, |
| chans_index=3, |
| ptcs_index=4, |
| vels_index=5, |
| average_drums=False, |
| score_is_delta=False, |
| return_ptcs_and_vels=False |
| ): |
| |
| if score_is_delta: |
| if average_drums: |
| times = [e[times_index] for e in escore_notes if e[times_index] != 0] |
| else: |
| times = [e[times_index] for e in escore_notes if e[times_index] != 0 and e[chans_index] != 9] |
|
|
| else: |
| descore_notes = delta_score_notes(escore_notes) |
| if average_drums: |
| times = [e[times_index] for e in descore_notes if e[times_index] != 0] |
| else: |
| times = [e[times_index] for e in descore_notes if e[times_index] != 0 and e[chans_index] != 9] |
| |
| if average_drums: |
| durs = [e[durs_index] for e in escore_notes] |
| else: |
| durs = [e[durs_index] for e in escore_notes if e[chans_index] != 9] |
|
|
| if return_ptcs_and_vels: |
| if average_drums: |
| ptcs = [e[ptcs_index] for e in escore_notes] |
| vels = [e[vels_index] for e in escore_notes] |
| else: |
| ptcs = [e[ptcs_index] for e in escore_notes if e[chans_index] != 9] |
| vels = [e[vels_index] for e in escore_notes if e[chans_index] != 9] |
|
|
| return [sum(times) / len(times), sum(durs) / len(durs), sum(ptcs) / len(ptcs), sum(vels) / len(vels)] |
| |
| else: |
| return [sum(times) / len(times), sum(durs) / len(durs)] |
|
|
| |
|
|
| def adjust_escore_notes_timings(escore_notes, |
| adj_k=1, |
| times_index=1, |
| durs_index=2, |
| score_is_delta=False, |
| return_delta_scpre=False |
| ): |
|
|
| if score_is_delta: |
| adj_escore_notes = copy.deepcopy(escore_notes) |
| else: |
| adj_escore_notes = delta_score_notes(escore_notes) |
|
|
| for e in adj_escore_notes: |
|
|
| if e[times_index] != 0: |
| e[times_index] = max(1, round(e[times_index] * adj_k)) |
|
|
| e[durs_index] = max(1, round(e[durs_index] * adj_k)) |
|
|
| if return_delta_scpre: |
| return adj_escore_notes |
|
|
| else: |
| return delta_score_to_abs_score(adj_escore_notes) |
|
|
| |
|
|
| def escore_notes_delta_times(escore_notes, |
| times_index=1 |
| ): |
|
|
| descore_notes = delta_score_notes(escore_notes) |
|
|
| return [e[times_index] for e in descore_notes] |
|
|
| |
|
|
| def escore_notes_durations(escore_notes, |
| durs_index=1 |
| ): |
|
|
| descore_notes = delta_score_notes(escore_notes) |
|
|
| return [e[durs_index] for e in descore_notes] |
|
|
| |
|
|
| def ordered_lists_match_ratio(src_list, trg_list): |
|
|
| zlist = list(zip(src_list, trg_list)) |
|
|
| return sum([a == b for a, b in zlist]) / len(list(zlist)) |
|
|
| |
|
|
| def lists_intersections(src_list, trg_list): |
| return list(set(src_list) & set(trg_list)) |
|
|
| |
|
|
| def transpose_escore_notes(escore_notes, |
| transpose_value=0, |
| channel_index=3, |
| pitches_index=4 |
| ): |
|
|
| tr_escore_notes = copy.deepcopy(escore_notes) |
|
|
| for e in tr_escore_notes: |
| if e[channel_index] != 9: |
| e[pitches_index] = max(1, min(127, e[pitches_index] + transpose_value)) |
|
|
| return tr_escore_notes |
|
|
| |
|
|
| def transpose_escore_notes_to_pitch(escore_notes, |
| target_pitch_value=60, |
| channel_index=3, |
| pitches_index=4 |
| ): |
|
|
| tr_escore_notes = copy.deepcopy(escore_notes) |
|
|
| transpose_delta = int(round(target_pitch_value)) - int(round(escore_notes_averages(escore_notes, return_ptcs_and_vels=True)[2])) |
|
|
| for e in tr_escore_notes: |
| if e[channel_index] != 9: |
| e[pitches_index] = max(1, min(127, e[pitches_index] + transpose_delta)) |
|
|
| return tr_escore_notes |
|
|
| |
|
|
| CHORDS_TYPES = ['WHITE', 'BLACK', 'UNKNOWN', 'MIXED WHITE', 'MIXED BLACK', 'MIXED GRAY'] |
|
|
| |
|
|
| def tones_chord_type(tones_chord, |
| return_chord_type_index=True, |
| use_filtered_chords=True |
| ): |
|
|
| WN = WHITE_NOTES |
| BN = BLACK_NOTES |
| MX = WHITE_NOTES + BLACK_NOTES |
|
|
| if use_filtered_chords: |
| CHORDS = ALL_CHORDS_FILTERED |
| |
| else: |
| CHORDS = ALL_CHORDS_SORTED |
|
|
| tones_chord = sorted(tones_chord) |
|
|
| ctype = 'UNKNOWN' |
|
|
| if tones_chord in CHORDS: |
|
|
| if sorted(set(tones_chord) & set(WN)) == tones_chord: |
| ctype = 'WHITE' |
|
|
| elif sorted(set(tones_chord) & set(BN)) == tones_chord: |
| ctype = 'BLACK' |
|
|
| if len(tones_chord) > 1 and sorted(set(tones_chord) & set(MX)) == tones_chord: |
|
|
| if len(sorted(set(tones_chord) & set(WN))) == len(sorted(set(tones_chord) & set(BN))): |
| ctype = 'MIXED GRAY' |
|
|
| elif len(sorted(set(tones_chord) & set(WN))) > len(sorted(set(tones_chord) & set(BN))): |
| ctype = 'MIXED WHITE' |
|
|
| elif len(sorted(set(tones_chord) & set(WN))) < len(sorted(set(tones_chord) & set(BN))): |
| ctype = 'MIXED BLACK' |
|
|
| if return_chord_type_index: |
| return CHORDS_TYPES.index(ctype) |
|
|
| else: |
| return ctype |
|
|
| |
|
|
| def tone_type(tone, |
| return_tone_type_index=True |
| ): |
|
|
| tone = tone % 12 |
|
|
| if tone in BLACK_NOTES: |
| if return_tone_type_index: |
| return CHORDS_TYPES.index('BLACK') |
| else: |
| return "BLACK" |
|
|
| else: |
| if return_tone_type_index: |
| return CHORDS_TYPES.index('WHITE') |
| else: |
| return "WHITE" |
|
|
| |
|
|
| def lists_sym_differences(src_list, trg_list): |
| return list(set(src_list) ^ set(trg_list)) |
|
|
| |
|
|
| def lists_differences(long_list, short_list): |
| return list(set(long_list) - set(short_list)) |
|
|
| |
|
|
| def find_best_tones_chord(src_tones_chords, |
| trg_tones_chords, |
| find_longest=True |
| ): |
|
|
| not_seen_trg_chords = [] |
|
|
| max_len = 0 |
|
|
| for tc in trg_tones_chords: |
| if sorted(tc) in src_tones_chords: |
| not_seen_trg_chords.append(sorted(tc)) |
| max_len = max(max_len, len(tc)) |
|
|
| if not not_seen_trg_chords: |
| max_len = len(max(trg_tones_chords, key=len)) |
| not_seen_trg_chords = trg_tones_chords |
|
|
| if find_longest: |
| return random.choice([c for c in not_seen_trg_chords if len(c) == max_len]) |
|
|
| else: |
| return random.choice(not_seen_trg_chords) |
|
|
| |
|
|
| def find_matching_tones_chords(tones_chord, |
| matching_chord_length=-1, |
| match_chord_type=True, |
| use_filtered_chords=True |
| ): |
|
|
| if use_filtered_chords: |
| CHORDS = ALL_CHORDS_FILTERED |
| else: |
| CHORDS = ALL_CHORDS_SORTED |
|
|
| tones_chord = sorted(tones_chord) |
|
|
| tclen = len(tones_chord) |
|
|
| tctype = tones_chord_type(tones_chord, use_filtered_chords=use_filtered_chords) |
|
|
| matches = [] |
|
|
| for tc in CHORDS: |
|
|
| if matching_chord_length == -1: |
| if len(tc) > tclen: |
| if sorted(lists_intersections(tc, tones_chord)) == tones_chord: |
| if match_chord_type: |
| if tones_chord_type(tc, use_filtered_chords=use_filtered_chords) == tctype: |
| tcdiffs = lists_differences(tc, tones_chord) |
| if all(tone_type(d) == tctype % 3 for d in tcdiffs): |
| matches.append(tc) |
| else: |
| matches.append(tc) |
|
|
| else: |
|
|
| if len(tc) == max(tclen, matching_chord_length): |
| if sorted(lists_intersections(tc, tones_chord)) == tones_chord: |
| if match_chord_type: |
| if tones_chord_type(tc, use_filtered_chords=use_filtered_chords) == tctype: |
| tcdiffs = lists_differences(tc, tones_chord) |
| if all(tone_type(d) == tctype % 3 for d in tcdiffs): |
| matches.append(tc) |
| else: |
| matches.append(tc) |
|
|
| return sorted(matches, key=len) |
|
|
| |
|
|
| def adjust_list_of_values_to_target_average(list_of_values, |
| trg_avg, |
| min_value, |
| max_value |
| ): |
|
|
| filtered_values = [value for value in list_of_values if min_value <= value <= max_value] |
|
|
| if not filtered_values: |
| return list_of_values |
|
|
| current_avg = sum(filtered_values) / len(filtered_values) |
| scale_factor = trg_avg / current_avg |
|
|
| adjusted_values = [value * scale_factor for value in filtered_values] |
|
|
| total_difference = trg_avg * len(filtered_values) - sum(adjusted_values) |
| adjustment_per_value = total_difference / len(filtered_values) |
|
|
| final_values = [value + adjustment_per_value for value in adjusted_values] |
|
|
| while abs(sum(final_values) / len(final_values) - trg_avg) > 1e-6: |
| total_difference = trg_avg * len(final_values) - sum(final_values) |
| adjustment_per_value = total_difference / len(final_values) |
| final_values = [value + adjustment_per_value for value in final_values] |
|
|
| final_values = [round(value) for value in final_values] |
|
|
| adjusted_values = copy.deepcopy(list_of_values) |
|
|
| j = 0 |
|
|
| for i in range(len(adjusted_values)): |
| if min_value <= adjusted_values[i] <= max_value: |
| adjusted_values[i] = final_values[j] |
| j += 1 |
|
|
| return adjusted_values |
|
|
| |
|
|
| def adjust_escore_notes_to_average(escore_notes, |
| trg_avg, |
| min_value=1, |
| max_value=4000, |
| times_index=1, |
| durs_index=2, |
| score_is_delta=False, |
| return_delta_scpre=False |
| ): |
| if score_is_delta: |
| delta_escore_notes = copy.deepcopy(escore_notes) |
|
|
| else: |
| delta_escore_notes = delta_score_notes(escore_notes) |
|
|
| times = [[e[times_index], e[durs_index]] for e in delta_escore_notes] |
|
|
| filtered_values = [value for value in times if min_value <= value[0] <= max_value] |
|
|
| if not filtered_values: |
| return escore_notes |
|
|
| current_avg = sum([v[0] for v in filtered_values]) / len([v[0] for v in filtered_values]) |
| scale_factor = trg_avg / current_avg |
|
|
| adjusted_values = [[value[0] * scale_factor, value[1] * scale_factor] for value in filtered_values] |
|
|
| total_difference = trg_avg * len([v[0] for v in filtered_values]) - sum([v[0] for v in adjusted_values]) |
| adjustment_per_value = total_difference / len(filtered_values) |
|
|
| final_values = [[value[0] + adjustment_per_value, value[1] + adjustment_per_value] for value in adjusted_values] |
|
|
| while abs(sum([v[0] for v in final_values]) / len(final_values) - trg_avg) > 1e-6: |
| total_difference = trg_avg * len(final_values) - sum([v[0] for v in final_values]) |
| adjustment_per_value = total_difference / len(final_values) |
| final_values = [[value[0] + adjustment_per_value, value[1] + adjustment_per_value] for value in final_values] |
|
|
| final_values = [[round(value[0]), round(value[1])] for value in final_values] |
|
|
| adjusted_delta_score = copy.deepcopy(delta_escore_notes) |
|
|
| j = 0 |
|
|
| for i in range(len(adjusted_delta_score)): |
| if min_value <= adjusted_delta_score[i][1] <= max_value: |
| adjusted_delta_score[i][times_index] = final_values[j][0] |
| adjusted_delta_score[i][durs_index] = final_values[j][1] |
| j += 1 |
|
|
| adjusted_escore_notes = delta_score_to_abs_score(adjusted_delta_score) |
|
|
| if return_delta_scpre: |
| return adjusted_delta_score |
|
|
| else: |
| return adjusted_escore_notes |
|
|
| |
|
|
| def harmonize_enhanced_melody_score_notes_to_ms_SONG(escore_notes, |
| melody_velocity=-1, |
| melody_channel=3, |
| melody_patch=40, |
| melody_base_octave=4, |
| harmonized_tones_chords_velocity=-1, |
| harmonized_tones_chords_channel=0, |
| harmonized_tones_chords_patch=0 |
| ): |
|
|
| harmonized_tones_chords = harmonize_enhanced_melody_score_notes(escore_notes) |
|
|
| harm_escore_notes = [] |
|
|
| time = 0 |
|
|
| for i, note in enumerate(escore_notes): |
|
|
| time = note[1] |
| dur = note[2] |
| ptc = note[4] |
|
|
| if melody_velocity == -1: |
| vel = int(110 + ((ptc % 12) * 1.5)) |
| else: |
| vel = melody_velocity |
|
|
| harm_escore_notes.append(['note', time, dur, melody_channel, ptc, vel, melody_patch]) |
|
|
| for t in harmonized_tones_chords[i]: |
|
|
| ptc = (melody_base_octave * 12) + t |
|
|
| if harmonized_tones_chords_velocity == -1: |
| vel = int(80 + ((ptc % 12) * 1.5)) |
| else: |
| vel = harmonized_tones_chords_velocity |
|
|
| harm_escore_notes.append(['note', time, dur, harmonized_tones_chords_channel, ptc, vel, harmonized_tones_chords_patch]) |
|
|
| return sorted(harm_escore_notes, key=lambda x: (x[1], -x[4], x[6])) |
|
|
| |
|
|
| def check_and_fix_pitches_chord(pitches_chord, |
| use_filtered_chords=True |
| ): |
| |
| pitches_chord = sorted(pitches_chord, reverse=True) |
|
|
| if use_filtered_chords: |
| CHORDS = ALL_CHORDS_FILTERED |
| else: |
| CHORDS = ALL_CHORDS_SORTED |
|
|
| tones_chord = sorted(set([p % 12 for p in pitches_chord])) |
|
|
| if tones_chord not in CHORDS: |
|
|
| if len(tones_chord) == 2: |
|
|
| tones_counts = Counter([p % 12 for p in pitches_chord]).most_common() |
|
|
| if tones_counts[0][1] > 1: |
| tones_chord = [tones_counts[0][0]] |
| elif tones_counts[1][1] > 1: |
| tones_chord = [tones_counts[1][0]] |
| else: |
| tones_chord = [pitches_chord[0] % 12] |
|
|
| if len(tones_chord) > 2: |
|
|
| tones_chord_combs = [list(comb) for i in range(len(tones_chord)-2, 0, -1) for comb in combinations(tones_chord, i+1)] |
|
|
| for co in tones_chord_combs: |
| if co in CHORDS: |
| tones_chord = co |
| break |
|
|
| new_pitches_chord = [] |
|
|
| for p in pitches_chord: |
|
|
| if p % 12 in tones_chord: |
| new_pitches_chord.append(p) |
|
|
| return sorted(new_pitches_chord, reverse=True) |
|
|
| |
|
|
| ALL_CHORDS_TRANS = [[0], [0, 4], [0, 4, 7], [0, 4, 8], [0, 5], [0, 6], [0, 7], [0, 8], [1], [1, 5], |
| [1, 5, 9], [1, 6], [1, 7], [1, 8], [1, 9], [2], [2, 6], [2, 6, 10], [2, 7], |
| [2, 8], [2, 9], [2, 10], [3], [3, 7], [3, 7, 11], [3, 8], [3, 9], [3, 10], |
| [3, 11], [4], [4, 7], [4, 7, 11], [4, 8], [4, 9], [4, 10], [4, 11], [5], |
| [5, 9], [5, 10], [5, 11], [6], [6, 10], [6, 11], [7], [7, 11], [8], [9], [10], |
| [11]] |
|
|
| |
|
|
| def minkowski_distance(x, y, p=3, pad_value=float('inf')): |
|
|
| if len(x) != len(y): |
| return -1 |
| |
| distance = 0 |
| |
| for i in range(len(x)): |
|
|
| if x[i] == pad_value or y[i] == pad_value: |
| continue |
|
|
| distance += abs(x[i] - y[i]) ** p |
|
|
| return distance ** (1 / p) |
|
|
| |
|
|
| def dot_product(x, y, pad_value=None): |
| return sum(xi * yi for xi, yi in zip(x, y) if xi != pad_value and yi != pad_value) |
|
|
| def norm(vector, pad_value=None): |
| return sum(xi ** 2 for xi in vector if xi != pad_value) ** 0.5 |
|
|
| def cosine_similarity(x, y, pad_value=None): |
| if len(x) != len(y): |
| return -1 |
| |
| dot_prod = dot_product(x, y, pad_value) |
| norm_x = norm(x, pad_value) |
| norm_y = norm(y, pad_value) |
| |
| if norm_x == 0 or norm_y == 0: |
| return 0.0 |
| |
| return dot_prod / (norm_x * norm_y) |
|
|
| |
|
|
| def hamming_distance(arr1, arr2, pad_value): |
| return sum(el1 != el2 for el1, el2 in zip(arr1, arr2) if el1 != pad_value and el2 != pad_value) |
|
|
| |
|
|
| def jaccard_similarity(arr1, arr2, pad_value): |
| intersection = sum(el1 and el2 for el1, el2 in zip(arr1, arr2) if el1 != pad_value and el2 != pad_value) |
| union = sum((el1 or el2) for el1, el2 in zip(arr1, arr2) if el1 != pad_value or el2 != pad_value) |
| return intersection / union if union != 0 else 0 |
|
|
| |
|
|
| def pearson_correlation(arr1, arr2, pad_value): |
| filtered_pairs = [(el1, el2) for el1, el2 in zip(arr1, arr2) if el1 != pad_value and el2 != pad_value] |
| if not filtered_pairs: |
| return 0 |
| n = len(filtered_pairs) |
| sum1 = sum(el1 for el1, el2 in filtered_pairs) |
| sum2 = sum(el2 for el1, el2 in filtered_pairs) |
| sum1_sq = sum(el1 ** 2 for el1, el2 in filtered_pairs) |
| sum2_sq = sum(el2 ** 2 for el1, el2 in filtered_pairs) |
| p_sum = sum(el1 * el2 for el1, el2 in filtered_pairs) |
| num = p_sum - (sum1 * sum2 / n) |
| den = ((sum1_sq - sum1 ** 2 / n) * (sum2_sq - sum2 ** 2 / n)) ** 0.5 |
| if den == 0: |
| return 0 |
| return num / den |
|
|
| |
|
|
| def calculate_combined_distances(array_of_arrays, |
| combine_hamming_distance=True, |
| combine_jaccard_similarity=True, |
| combine_pearson_correlation=True, |
| pad_value=None |
| ): |
|
|
| binary_arrays = array_of_arrays |
| binary_array_len = len(binary_arrays) |
|
|
| hamming_distances = [[0] * binary_array_len for _ in range(binary_array_len)] |
| jaccard_similarities = [[0] * binary_array_len for _ in range(binary_array_len)] |
| pearson_correlations = [[0] * binary_array_len for _ in range(binary_array_len)] |
|
|
| for i in range(binary_array_len): |
| for j in range(i + 1, binary_array_len): |
| hamming_distances[i][j] = hamming_distance(binary_arrays[i], binary_arrays[j], pad_value) |
| hamming_distances[j][i] = hamming_distances[i][j] |
| |
| jaccard_similarities[i][j] = jaccard_similarity(binary_arrays[i], binary_arrays[j], pad_value) |
| jaccard_similarities[j][i] = jaccard_similarities[i][j] |
| |
| pearson_correlations[i][j] = pearson_correlation(binary_arrays[i], binary_arrays[j], pad_value) |
| pearson_correlations[j][i] = pearson_correlations[i][j] |
|
|
| max_hamming = max(max(row) for row in hamming_distances) |
| min_hamming = min(min(row) for row in hamming_distances) |
| normalized_hamming = [[(val - min_hamming) / (max_hamming - min_hamming) for val in row] for row in hamming_distances] |
|
|
| max_jaccard = max(max(row) for row in jaccard_similarities) |
| min_jaccard = min(min(row) for row in jaccard_similarities) |
| normalized_jaccard = [[(val - min_jaccard) / (max_jaccard - min_jaccard) for val in row] for row in jaccard_similarities] |
|
|
| max_pearson = max(max(row) for row in pearson_correlations) |
| min_pearson = min(min(row) for row in pearson_correlations) |
| normalized_pearson = [[(val - min_pearson) / (max_pearson - min_pearson) for val in row] for row in pearson_correlations] |
|
|
| selected_metrics = 0 |
|
|
| if combine_hamming_distance: |
| selected_metrics += normalized_hamming[i][j] |
| |
| if combine_jaccard_similarity: |
| selected_metrics += (1 - normalized_jaccard[i][j]) |
|
|
| if combine_pearson_correlation: |
| selected_metrics += (1 - normalized_pearson[i][j]) |
|
|
| combined_metric = [[selected_metrics for i in range(binary_array_len)] for j in range(binary_array_len)] |
|
|
| return combined_metric |
|
|
| |
|
|
| def tones_chords_to_bits(tones_chords): |
|
|
| bits_tones_chords = [] |
|
|
| for c in tones_chords: |
|
|
| c.sort() |
|
|
| bits = tones_chord_to_bits(c) |
|
|
| bits_tones_chords.append(bits) |
|
|
| return bits_tones_chords |
|
|
| |
|
|
| def tones_chords_to_ints(tones_chords): |
|
|
| ints_tones_chords = [] |
|
|
| for c in tones_chords: |
|
|
| c.sort() |
|
|
| bits = tones_chord_to_bits(c) |
|
|
| number = bits_to_int(bits) |
|
|
| ints_tones_chords.append(number) |
|
|
| return ints_tones_chords |
|
|
| |
|
|
| def tones_chords_to_types(tones_chords, |
| return_chord_type_index=False |
| ): |
|
|
| types_tones_chords = [] |
|
|
| for c in tones_chords: |
|
|
| c.sort() |
|
|
| ctype = tones_chord_type(c, return_chord_type_index=return_chord_type_index) |
|
|
| types_tones_chords.append(ctype) |
|
|
| return types_tones_chords |
|
|
| |
|
|
| def morph_tones_chord(tones_chord, |
| trg_tone, |
| use_filtered_chords=True |
| ): |
|
|
| src_tones_chord = sorted(sorted(set(tones_chord)) + [trg_tone]) |
|
|
| combs = [list(comb) for i in range(len(src_tones_chord), 0, -1) for comb in combinations(src_tones_chord, i) if trg_tone in list(comb)] |
|
|
| matches = [] |
|
|
| if use_filtered_chords: |
| CHORDS = ALL_CHORDS_FILTERED |
| |
| else: |
| CHORDS = ALL_CHORDS_SORTED |
|
|
| for c in combs: |
| if sorted(set(c)) in CHORDS: |
| matches.append(sorted(set(c))) |
|
|
| max_len = len(max(matches, key=len)) |
|
|
| return random.choice([m for m in matches if len(m) == max_len]) |
|
|
| |
|
|
| def compress_binary_matrix(binary_matrix, |
| only_compress_zeros=False, |
| return_compression_ratio=False |
| ): |
|
|
| compressed_bmatrix = [] |
|
|
| zm = [0] * len(binary_matrix[0]) |
| pm = [0] * len(binary_matrix[0]) |
|
|
| mcount = 0 |
|
|
| for m in binary_matrix: |
| |
| if only_compress_zeros: |
| if m != zm: |
| compressed_bmatrix.append(m) |
| mcount += 1 |
| |
| else: |
| if m != pm: |
| compressed_bmatrix.append(m) |
| mcount += 1 |
| |
| pm = m |
|
|
| if return_compression_ratio: |
| return [compressed_bmatrix, mcount / len(binary_matrix)] |
|
|
| else: |
| return compressed_bmatrix |
|
|
| |
|
|
| def solo_piano_escore_notes(escore_notes, |
| channels_index=3, |
| pitches_index=4, |
| patches_index=6, |
| keep_drums=False, |
| ): |
|
|
| cscore = chordify_score([1000, escore_notes]) |
|
|
| sp_escore_notes = [] |
|
|
| for c in cscore: |
|
|
| seen = [] |
| chord = [] |
|
|
| for cc in c: |
| if cc[pitches_index] not in seen: |
|
|
| if cc[channels_index] != 9: |
| cc[channels_index] = 0 |
| cc[patches_index] = 0 |
| |
| chord.append(cc) |
| seen.append(cc[pitches_index]) |
| |
| else: |
| if keep_drums: |
| chord.append(cc) |
| seen.append(cc[pitches_index]) |
|
|
| sp_escore_notes.append(chord) |
|
|
| return flatten(sp_escore_notes) |
|
|
| |
|
|
| def strip_drums_from_escore_notes(escore_notes, |
| channels_index=3 |
| ): |
| |
| return [e for e in escore_notes if e[channels_index] != 9] |
|
|
| |
|
|
| def fixed_escore_notes_timings(escore_notes, |
| fixed_durations=False, |
| fixed_timings_multiplier=1, |
| custom_fixed_time=-1, |
| custom_fixed_dur=-1 |
| ): |
|
|
| fixed_timings_escore_notes = delta_score_notes(escore_notes, even_timings=True) |
|
|
| mode_time = round(Counter([e[1] for e in fixed_timings_escore_notes if e[1] != 0]).most_common()[0][0] * fixed_timings_multiplier) |
|
|
| if mode_time % 2 != 0: |
| mode_time += 1 |
|
|
| mode_dur = round(Counter([e[2] for e in fixed_timings_escore_notes if e[2] != 0]).most_common()[0][0] * fixed_timings_multiplier) |
|
|
| if mode_dur % 2 != 0: |
| mode_dur += 1 |
|
|
| for e in fixed_timings_escore_notes: |
| if e[1] != 0: |
| |
| if custom_fixed_time > 0: |
| e[1] = custom_fixed_time |
| |
| else: |
| e[1] = mode_time |
|
|
| if fixed_durations: |
| |
| if custom_fixed_dur > 0: |
| e[2] = custom_fixed_dur |
| |
| else: |
| e[2] = mode_dur |
|
|
| return delta_score_to_abs_score(fixed_timings_escore_notes) |
|
|
| |
|
|
| def cubic_kernel(x): |
| abs_x = abs(x) |
| if abs_x <= 1: |
| return 1.5 * abs_x**3 - 2.5 * abs_x**2 + 1 |
| elif abs_x <= 2: |
| return -0.5 * abs_x**3 + 2.5 * abs_x**2 - 4 * abs_x + 2 |
| else: |
| return 0 |
|
|
| |
|
|
| def resize_matrix(matrix, new_height, new_width): |
| old_height = len(matrix) |
| old_width = len(matrix[0]) |
| resized_matrix = [[0] * new_width for _ in range(new_height)] |
| |
| for i in range(new_height): |
| for j in range(new_width): |
| old_i = i * old_height / new_height |
| old_j = j * old_width / new_width |
| |
| value = 0 |
| total_weight = 0 |
| for m in range(-1, 3): |
| for n in range(-1, 3): |
| i_m = min(max(int(old_i) + m, 0), old_height - 1) |
| j_n = min(max(int(old_j) + n, 0), old_width - 1) |
| |
| if matrix[i_m][j_n] == 0: |
| continue |
| |
| weight = cubic_kernel(old_i - i_m) * cubic_kernel(old_j - j_n) |
| value += matrix[i_m][j_n] * weight |
| total_weight += weight |
| |
| if total_weight > 0: |
| value /= total_weight |
| |
| resized_matrix[i][j] = int(value > 0.5) |
| |
| return resized_matrix |
|
|
| |
|
|
| def square_binary_matrix(binary_matrix, |
| matrix_size=128, |
| use_fast_squaring=False, |
| return_plot_points=False |
| ): |
|
|
| if use_fast_squaring: |
|
|
| step = round(len(binary_matrix) / matrix_size) |
|
|
| samples = [] |
|
|
| for i in range(0, len(binary_matrix), step): |
| samples.append(tuple([tuple(d) for d in binary_matrix[i:i+step]])) |
|
|
| resized_matrix = [] |
|
|
| zmatrix = [[0] * matrix_size] |
|
|
| for s in samples: |
|
|
| samples_counts = Counter(s).most_common() |
|
|
| best_sample = tuple([0] * matrix_size) |
| pm = tuple(zmatrix[0]) |
|
|
| for sc in samples_counts: |
| if sc[0] != tuple(zmatrix[0]) and sc[0] != pm: |
| best_sample = sc[0] |
| pm = sc[0] |
| break |
| |
| pm = sc[0] |
|
|
| resized_matrix.append(list(best_sample)) |
|
|
| resized_matrix = resized_matrix[:matrix_size] |
| resized_matrix += zmatrix * (matrix_size - len(resized_matrix)) |
| |
| else: |
| resized_matrix = resize_matrix(binary_matrix, matrix_size, matrix_size) |
|
|
| points = [(i, j) for i in range(matrix_size) for j in range(matrix_size) if resized_matrix[i][j] == 1] |
|
|
| if return_plot_points: |
| return [resized_matrix, points] |
|
|
| else: |
| return resized_matrix |
|
|
| |
|
|
| def mean(matrix): |
| return sum(sum(row) for row in matrix) / (len(matrix) * len(matrix[0])) |
|
|
| |
|
|
| def variance(matrix, mean_value): |
| return sum(sum((element - mean_value) ** 2 for element in row) for row in matrix) / (len(matrix) * len(matrix[0])) |
| |
| |
|
|
| def covariance(matrix1, matrix2, mean1, mean2): |
| return sum(sum((matrix1[i][j] - mean1) * (matrix2[i][j] - mean2) for j in range(len(matrix1[0]))) for i in range(len(matrix1))) / (len(matrix1) * len(matrix1[0])) |
|
|
| |
|
|
| def ssim_index(matrix1, matrix2, bit_depth=1): |
|
|
| if len(matrix1) != len(matrix2) and len(matrix1[0]) != len(matrix2[0]): |
| return -1 |
|
|
| K1, K2 = 0.01, 0.03 |
| L = bit_depth |
| C1 = (K1 * L) ** 2 |
| C2 = (K2 * L) ** 2 |
| |
| mu1 = mean(matrix1) |
| mu2 = mean(matrix2) |
| |
| sigma1_sq = variance(matrix1, mu1) |
| sigma2_sq = variance(matrix2, mu2) |
| |
| sigma12 = covariance(matrix1, matrix2, mu1, mu2) |
| |
| ssim = ((2 * mu1 * mu2 + C1) * (2 * sigma12 + C2)) / ((mu1 ** 2 + mu2 ** 2 + C1) * (sigma1_sq + sigma2_sq + C2)) |
| |
| return ssim |
|
|
| |
|
|
| def find_most_similar_matrix(array_of_matrices, |
| trg_matrix, |
| matrices_bit_depth=1, |
| return_most_similar_index=False |
| ): |
| |
| max_ssim = -float('inf') |
| most_similar_index = -1 |
|
|
| for i, matrix in enumerate(array_of_matrices): |
|
|
| ssim = ssim_index(matrix, trg_matrix, bit_depth=matrices_bit_depth) |
| |
| if ssim > max_ssim: |
| max_ssim = ssim |
| most_similar_index = i |
| |
| if return_most_similar_index: |
| return most_similar_index |
| |
| else: |
| return array_of_matrices[most_similar_index] |
|
|
| |
|
|
| def chord_to_pchord(chord): |
|
|
| pchord = [] |
|
|
| for cc in chord: |
| if cc[3] != 9: |
| pchord.append(cc[4]) |
|
|
| return pchord |
|
|
| |
|
|
| def summarize_escore_notes(escore_notes, |
| summary_length_in_chords=128, |
| preserve_timings=True, |
| preserve_durations=False, |
| time_threshold=12, |
| min_sum_chord_len=2, |
| use_tones_chords=True |
| ): |
|
|
| cscore = chordify_score([d[1:] for d in delta_score_notes(escore_notes)]) |
|
|
| summary_length_in_chords = min(len(cscore), summary_length_in_chords) |
|
|
| ltthresh = time_threshold // 2 |
| uttresh = time_threshold * 2 |
|
|
| mc_time = Counter([c[0][0] for c in cscore if c[0][2] != 9 and ltthresh < c[0][0] < uttresh]).most_common()[0][0] |
|
|
| pchords = [] |
|
|
| for c in cscore: |
| if use_tones_chords: |
| pchords.append([c[0][0]] + pitches_to_tones_chord(chord_to_pchord(c))) |
| |
| else: |
| pchords.append([c[0][0]] + chord_to_pchord(c)) |
|
|
| step = round(len(pchords) / summary_length_in_chords) |
|
|
| samples = [] |
|
|
| for i in range(0, len(pchords), step): |
| samples.append(tuple([tuple(d) for d in pchords[i:i+step]])) |
|
|
| summarized_escore_notes = [] |
|
|
| for i, s in enumerate(samples): |
|
|
| best_chord = list([v[0] for v in Counter(s).most_common() if v[0][0] == mc_time and len(v[0]) > min_sum_chord_len]) |
|
|
| if not best_chord: |
| best_chord = list([v[0] for v in Counter(s).most_common() if len(v[0]) > min_sum_chord_len]) |
| |
| if not best_chord: |
| best_chord = list([Counter(s).most_common()[0][0]]) |
|
|
| chord = copy.deepcopy(cscore[[ss for ss in s].index(best_chord[0])+(i*step)]) |
|
|
| if preserve_timings: |
|
|
| if not preserve_durations: |
|
|
| if i > 0: |
|
|
| pchord = summarized_escore_notes[-1] |
|
|
| for pc in pchord: |
| pc[1] = min(pc[1], chord[0][0]) |
|
|
| else: |
|
|
| chord[0][0] = 1 |
|
|
| for c in chord: |
| c[1] = 1 |
|
|
| summarized_escore_notes.append(chord) |
|
|
| summarized_escore_notes = summarized_escore_notes[:summary_length_in_chords] |
|
|
| return [['note'] + d for d in delta_score_to_abs_score(flatten(summarized_escore_notes), times_idx=0)] |
|
|
| |
|
|
| def compress_patches_in_escore_notes(escore_notes, |
| num_patches=4, |
| group_patches=False |
| ): |
|
|
| if num_patches > 4: |
| n_patches = 4 |
| elif num_patches < 1: |
| n_patches = 1 |
| else: |
| n_patches = num_patches |
|
|
| if group_patches: |
| patches_set = sorted(set([e[6] for e in c])) |
| trg_patch_list = [] |
| seen = [] |
| for p in patches_set: |
| if p // 8 not in seen: |
| trg_patch_list.append(p) |
| seen.append(p // 8) |
|
|
| trg_patch_list = sorted(trg_patch_list) |
|
|
| else: |
| trg_patch_list = sorted(set([e[6] for e in c])) |
|
|
| if 128 in trg_patch_list and n_patches > 1: |
| trg_patch_list = trg_patch_list[:n_patches-1] + [128] |
| else: |
| trg_patch_list = trg_patch_list[:n_patches] |
|
|
| new_escore_notes = [] |
|
|
| for e in escore_notes: |
| if e[6] in trg_patch_list: |
| new_escore_notes.append(e) |
|
|
| return new_escore_notes |
|
|
| |
|
|
| def compress_patches_in_escore_notes_chords(escore_notes, |
| max_num_patches_per_chord=4, |
| group_patches=True, |
| root_grouped_patches=False |
| ): |
|
|
| if max_num_patches_per_chord > 4: |
| n_patches = 4 |
| elif max_num_patches_per_chord < 1: |
| n_patches = 1 |
| else: |
| n_patches = max_num_patches_per_chord |
|
|
| cscore = chordify_score([1000, sorted(escore_notes, key=lambda x: (x[1], x[6]))]) |
|
|
| new_escore_notes = [] |
|
|
| for c in cscore: |
|
|
| if group_patches: |
| patches_set = sorted(set([e[6] for e in c])) |
| trg_patch_list = [] |
| seen = [] |
| for p in patches_set: |
| if p // 8 not in seen: |
| trg_patch_list.append(p) |
| seen.append(p // 8) |
|
|
| trg_patch_list = sorted(trg_patch_list) |
|
|
| else: |
| trg_patch_list = sorted(set([e[6] for e in c])) |
|
|
| if 128 in trg_patch_list and n_patches > 1: |
| trg_patch_list = trg_patch_list[:n_patches-1] + [128] |
| else: |
| trg_patch_list = trg_patch_list[:n_patches] |
|
|
| for ccc in c: |
|
|
| cc = copy.deepcopy(ccc) |
|
|
| if group_patches: |
| if cc[6] // 8 in [t // 8 for t in trg_patch_list]: |
| if root_grouped_patches: |
| cc[6] = (cc[6] // 8) * 8 |
| new_escore_notes.append(cc) |
|
|
| else: |
| if cc[6] in trg_patch_list: |
| new_escore_notes.append(cc) |
|
|
| return new_escore_notes |
|
|
| |
|
|
| def escore_notes_to_image_matrix(escore_notes, |
| num_img_channels=3, |
| filter_out_zero_rows=False, |
| filter_out_duplicate_rows=False, |
| flip_matrix=False, |
| reverse_matrix=False |
| ): |
|
|
| escore_notes = sorted(escore_notes, key=lambda x: (x[1], x[6])) |
|
|
| if num_img_channels > 1: |
| n_mat_channels = 3 |
| else: |
| n_mat_channels = 1 |
|
|
| if escore_notes: |
| last_time = escore_notes[-1][1] |
| last_notes = [e for e in escore_notes if e[1] == last_time] |
| max_last_dur = max([e[2] for e in last_notes]) |
|
|
| time_range = last_time+max_last_dur |
|
|
| escore_matrix = [] |
|
|
| escore_matrix = [[0] * 128 for _ in range(time_range)] |
|
|
| for note in escore_notes: |
|
|
| etype, time, duration, chan, pitch, velocity, pat = note |
|
|
| time = max(0, time) |
| duration = max(2, duration) |
| chan = max(0, min(15, chan)) |
| pitch = max(0, min(127, pitch)) |
| velocity = max(0, min(127, velocity)) |
| patch = max(0, min(128, pat)) |
|
|
| if chan != 9: |
| pat = patch + 128 |
| else: |
| pat = 127 |
|
|
| seen_pats = [] |
|
|
| for t in range(time, min(time + duration, time_range)): |
|
|
| mat_value = escore_matrix[t][pitch] |
|
|
| mat_value_0 = (mat_value // (256 * 256)) % 256 |
| mat_value_1 = (mat_value // 256) % 256 |
|
|
| cur_num_chans = 0 |
|
|
| if 0 < mat_value < 256 and pat not in seen_pats: |
| cur_num_chans = 1 |
| elif 256 < mat_value < (256 * 256) and pat not in seen_pats: |
| cur_num_chans = 2 |
|
|
| if cur_num_chans < n_mat_channels: |
|
|
| if n_mat_channels == 1: |
|
|
| escore_matrix[t][pitch] = pat |
| seen_pats.append(pat) |
|
|
| elif n_mat_channels == 3: |
|
|
| if cur_num_chans == 0: |
| escore_matrix[t][pitch] = pat |
| seen_pats.append(pat) |
| elif cur_num_chans == 1: |
| escore_matrix[t][pitch] = (256 * 256 * mat_value_0) + (256 * pat) |
| seen_pats.append(pat) |
| elif cur_num_chans == 2: |
| escore_matrix[t][pitch] = (256 * 256 * mat_value_0) + (256 * mat_value_1) + pat |
| seen_pats.append(pat) |
|
|
| if filter_out_zero_rows: |
| escore_matrix = [e for e in escore_matrix if sum(e) != 0] |
|
|
| if filter_out_duplicate_rows: |
|
|
| dd_escore_matrix = [] |
|
|
| pr = [-1] * 128 |
| for e in escore_matrix: |
| if e != pr: |
| dd_escore_matrix.append(e) |
| pr = e |
| |
| escore_matrix = dd_escore_matrix |
|
|
| if flip_matrix: |
|
|
| temp_matrix = [] |
|
|
| for m in escore_matrix: |
| temp_matrix.append(m[::-1]) |
|
|
| escore_matrix = temp_matrix |
|
|
| if reverse_matrix: |
| escore_matrix = escore_matrix[::-1] |
|
|
| return escore_matrix |
|
|
| else: |
| return None |
|
|
| |
|
|
| def find_value_power(value, number): |
| return math.floor(math.log(value, number)) |
|
|
| |
|
|
| def image_matrix_to_original_escore_notes(image_matrix, |
| velocity=-1 |
| ): |
|
|
| result = [] |
|
|
| for j in range(len(image_matrix[0])): |
|
|
| count = 1 |
|
|
| for i in range(1, len(image_matrix)): |
|
|
| if image_matrix[i][j] != 0 and image_matrix[i][j] == image_matrix[i-1][j]: |
| count += 1 |
|
|
| else: |
| if count > 1: |
| result.append([i-count, count, j, image_matrix[i-1][j]]) |
|
|
| else: |
| if image_matrix[i-1][j] != 0: |
| result.append([i-count, count, j, image_matrix[i-1][j]]) |
|
|
| count = 1 |
|
|
| if count > 1: |
| result.append([len(image_matrix)-count, count, j, image_matrix[-1][j]]) |
|
|
| else: |
| if image_matrix[i-1][j] != 0: |
| result.append([i-count, count, j, image_matrix[i-1][j]]) |
|
|
| result.sort(key=lambda x: (x[0], -x[2])) |
|
|
| original_escore_notes = [] |
|
|
| vel = velocity |
|
|
| for r in result: |
|
|
| if velocity == -1: |
| vel = max(40, r[2]) |
|
|
| ptc0 = 0 |
| ptc1 = 0 |
| ptc2 = 0 |
|
|
| if find_value_power(r[3], 256) == 0: |
| ptc0 = r[3] % 256 |
|
|
| elif find_value_power(r[3], 256) == 1: |
| ptc0 = r[3] // 256 |
| ptc1 = (r[3] // 256) % 256 |
|
|
| elif find_value_power(r[3], 256) == 2: |
| ptc0 = (r[3] // 256) // 256 |
| ptc1 = (r[3] // 256) % 256 |
| ptc2 = r[3] % 256 |
|
|
| ptcs = [ptc0, ptc1, ptc2] |
| patches = [p for p in ptcs if p != 0] |
|
|
| for i, p in enumerate(patches): |
|
|
| if p < 128: |
| patch = 128 |
| channel = 9 |
|
|
| else: |
| patch = p % 128 |
| chan = p // 8 |
|
|
| if chan == 9: |
| chan += 1 |
|
|
| channel = min(15, chan) |
|
|
| original_escore_notes.append(['note', r[0], r[1], channel, r[2], vel, patch]) |
|
|
| output_score = sorted(original_escore_notes, key=lambda x: (x[1], -x[4], x[6])) |
|
|
| adjust_score_velocities(output_score, 127) |
|
|
| return output_score |
|
|
| |
|
|
| def escore_notes_delta_times(escore_notes, |
| timings_index=1, |
| channels_index=3, |
| omit_zeros=False, |
| omit_drums=False |
| ): |
|
|
| if omit_drums: |
|
|
| score = [e for e in escore_notes if e[channels_index] != 9] |
| dtimes = [score[0][timings_index]] + [b[timings_index]-a[timings_index] for a, b in zip(score[:-1], score[1:])] |
|
|
| else: |
| dtimes = [escore_notes[0][timings_index]] + [b[timings_index]-a[timings_index] for a, b in zip(escore_notes[:-1], escore_notes[1:])] |
| |
| if omit_zeros: |
| dtimes = [d for d in dtimes if d != 0] |
| |
| return dtimes |
|
|
| |
|
|
| def monophonic_check(escore_notes, times_index=1): |
| return len(escore_notes) == len(set([e[times_index] for e in escore_notes])) |
|
|
| |
|
|
| def count_escore_notes_patches(escore_notes, patches_index=6): |
| return [list(c) for c in Counter([e[patches_index] for e in escore_notes]).most_common()] |
|
|
| |
| |
| |
| |
| |