def assign_note_ids(parts):
# assign note ids to ensure uniqueness across all parts, discarding any
# existing note ids
i = 0
for part in score.iter_parts(parts):
for n in part.notes:
n.id = 'n{}'.format(i)
i += 1
def assign_note_ids(parts, keep=False):
if keep:
# Keep existing note id's
for p, part in enumerate(score.iter_parts(parts)):
for ni, n in enumerate(
part.iter_all(score.GenericNote, include_subclasses=True)):
if isinstance(n, score.Rest):
n.id = "p{0}r{1}".format(p, ni) if n.id is None else n.id
else:
n.id = "p{0}n{1}".format(p, ni) if n.id is None else n.id
else:
# assign note ids to ensure uniqueness across all parts, discarding any
# existing note ids
ni = 0
ri = 0
for part in score.iter_parts(parts):
for n in part.iter_all(score.GenericNote, include_subclasses=True):
if isinstance(n, score.Rest):
n.id = "r{}".format(ri)
ri += 1
else:
n.id = "n{}".format(ni)
ni += 1
def test_midi_export_mode_4(self):
m = self._export_and_read(mode=4)
msg = ('Number of tracks {} does not equal 1 while '
'testing part_voice_assign_mode=4 in save_score_midi'.format(
len(m.tracks)))
self.assertEqual(1, len(m.tracks), msg)
note_ch = note_channels(m.tracks[0])
n_ch = len(set(note_ch))
msg = ('Track should have 1 channel, '
'but has {} channels'.format(n_ch))
self.assertEqual(1, n_ch, msg)
n_notes_trg = sum(
len(part.notes_tied) for part in score.iter_parts(self.parts))
n_notes = len(note_ch)
msg = ('Track should have {} notes, '
'but has {} notes'.format(n_notes_trg, n_notes))
def get_ppq(parts):
ppqs = np.concatenate(
[part.quarter_durations()[:, 1] for part in score.iter_parts(parts)])
ppq = np.lcm.reduce(ppqs)
return ppq
def save_score_midi(parts,
out,
part_voice_assign_mode=0,
velocity=64,
anacrusis_behavior="shift"):
"""Write data from Part objects to a MIDI file
Parameters
----------
parts : Part, PartGroup or list of these
The musical score to be saved.
out : str or file-like object
Either a filename or a file-like object to write the MIDI data
to.
part_voice_assign_mode : {0, 1, 2, 3, 4, 5}, optional
This keyword controls how part and voice information is
associated to track and channel information in the MIDI file.
The semantics of the modes is as follows:
0
Write one track for each Part, with channels assigned by
voices
1
Write one track for each PartGroup, with channels assigned by
Parts (voice info is lost) (There can be multiple levels of
partgroups, I suggest using the highest level of
partgroup/part) [note: this will e.g. lead to all strings into
the same track] Each part not in a PartGroup will be assigned
its own track
2
Write a single track with channels assigned by Part (voice
info is lost)
3
Write one track per Part, and a single channel for all voices
(voice info is lost)
4
Write a single track with a single channel (Part and voice
info is lost)
5
Return one track per <Part, voice> combination, each track
having a single channel.
The default mode is 0.
velocity : int, optional
Default velocity for all MIDI notes. Defaults to 64.
anacrusis_behavior : {"shift", "pad_bar"}, optional
Strategy to deal with anacrusis. If "shift", all
time points are shifted by the anacrusis (i.e., the first
note starts at 0). If "pad_bar", the "incomplete" bar of
the anacrusis is padded with silence. Defaults to 'shift'.
"""
ppq = get_ppq(parts)
events = defaultdict(lambda: defaultdict(list))
meta_events = defaultdict(lambda: defaultdict(list))
event_keys = OrderedDict()
tempos = {}
quarter_maps = [part.quarter_map for part in score.iter_parts(parts)]
first_time_point = min(qm(0) for qm in quarter_maps)
ftp = 0
# Deal with anacrusis
if first_time_point < 0:
if anacrusis_behavior == "shift":
ftp = first_time_point
elif anacrusis_behavior == "pad_bar":
time_signatures = []
for qm, part in zip(quarter_maps, score.iter_parts(parts)):
ts_beats, ts_beat_type = part.time_signature_map(0)
time_signatures.append((ts_beats, ts_beat_type, qm(0)))
# sort ts according to time
time_signatures.sort(key=lambda x: x[2])
ftp = -time_signatures[0][0] / (time_signatures[0][1] / 4)
else:
raise Exception(
'Invalid anacrusis_behavior value, must be one of ("shift", "pad_bar")'
)
for qm, part in zip(quarter_maps, score.iter_parts(parts)):
pg = get_partgroup(part)
notes = part.notes_tied
def to_ppq(t):
# convert div times to new ppq
return int(ppq * (qm(t) - ftp))
for tp in part.iter_all(score.Tempo):
tempos[to_ppq(tp.start.t)] = MetaMessage(
"set_tempo", tempo=tp.microseconds_per_quarter)
for ts in part.iter_all(score.TimeSignature):
meta_events[part][to_ppq(ts.start.t)].append(
MetaMessage("time_signature",
numerator=ts.beats,
denominator=ts.beat_type))
for ks in part.iter_all(score.KeySignature):
meta_events[part][to_ppq(ks.start.t)].append(
MetaMessage("key_signature", key=ks.name))
for note in notes:
# key is a tuple (part_group, part, voice) that will be
# converted into a (track, channel) pair.
key = (pg, part, note.voice)
events[key][to_ppq(note.start.t)].append(
Message("note_on", note=note.midi_pitch))
events[key][to_ppq(note.start.t + note.duration_tied)].append(
Message("note_off", note=note.midi_pitch))
event_keys[key] = True
tr_ch_map = map_to_track_channel(list(event_keys.keys()),
part_voice_assign_mode)
# replace original event keys (partgroup, part, voice) by (track, ch) keys:
for key in list(events.keys()):
evs_by_time = events[key]
del events[key]
tr, ch = tr_ch_map[key]
for t, evs in evs_by_time.items():
events[tr][t].extend((ev.copy(channel=ch) for ev in evs))
# figure out in which tracks to replicate the time/key signatures of each part
part_track_map = partition(lambda x: x[0][1], tr_ch_map.items())
for part, rest in part_track_map.items():
part_track_map[part] = set(x[1][0] for x in rest)
# add the time/key sigs to their corresponding tracks
for part, m_events in meta_events.items():
tracks = part_track_map[part]
for tr in tracks:
for t, me in m_events.items():
events[tr][t] = me + events[tr][t]
n_tracks = max(tr for tr, _ in tr_ch_map.values()) + 1
tracks = [MidiTrack() for _ in range(n_tracks)]
# tempo events are handled differently from key/time sigs because the have a
# global effect. Instead of adding to each relevant track, like the key/time
# sig events, we add them only to the first track
for t, tp in tempos.items():
events[0][t].insert(0, tp)
for tr, events_by_time in events.items():
t_prev = 0
for t in sorted(events_by_time.keys()):
evs = events_by_time[t]
delta = t - t_prev
for ev in evs:
tracks[tr].append(ev.copy(time=delta))
delta = 0
t_prev = t
midi_type = 0 if n_tracks == 1 else 1
mf = MidiFile(type=midi_type, ticks_per_beat=ppq)
for track in tracks:
mf.tracks.append(track)
if out:
if hasattr(out, "write"):
mf.save(file=out)
else:
mf.save(out)
def musicxml_to_notearray(fn, flatten_parts=True, sort_onsets=True,
expand_grace_notes=True, validate=False,
beat_times=True):
"""Return pitch, onset, and duration information for notes from a
MusicXML file as a structured array.
By default a single array is returned by combining the note
information of all parts in the MusicXML file.
Parameters
----------
fn : str
Path to a MusicXML file
flatten_parts : bool
If `True`, returns a single array containing all notes.
Otherwise, returns a list of arrays for each part.
expand_grace_notes : bool or 'delete'
When True, grace note onset and durations will be adjusted to
have a non-zero duration.
beat_times : bool
When True (default) return onset and duration in beats.
Otherwise, return the onset and duration in divisions.
Returns
-------
score : structured array or list of structured arrays
Structured array containing the score. The fields are 'pitch',
'onset' and 'duration'.
"""
if not isinstance(expand_grace_notes, (bool, str)):
raise ValueError('`expand_grace_notes` must be a boolean or '
'"delete"')
delete_grace_notes = False
if isinstance(expand_grace_notes, str):
if expand_grace_notes in ('omit', 'delete', 'd'):
expand_grace_notes = False
delete_grace_notes = True
else:
raise ValueError('`expand_grace_notes` must be a boolean or '
'"delete"')
# Parse MusicXML
parts = load_musicxml(fn, ensure_list=True, validate=validate)
scr = []
for part in score.iter_parts(parts):
# Unfold any repetitions in part
part = score.unfold_part_maximal(part)
if expand_grace_notes:
LOGGER.debug('Expanding grace notes...')
score.expand_grace_notes(part)
if beat_times:
# get beat map
bm = part.beat_map
# Build score from beat map
_score = np.array(
[(n.midi_pitch, bm(n.start.t), bm(n.end_tied.t) - bm(n.start.t))
for n in part.notes_tied],
dtype=[('pitch', 'i4'), ('onset', 'f4'), ('duration', 'f4')])
else:
_score = np.array(
[(n.midi_pitch, n.start.t, n.end_tied.t - n.start.t)
for n in part.notes_tied],
dtype=[('pitch', 'i4'), ('onset', 'i4'), ('duration', 'i4')])
# Sort notes according to onset
if sort_onsets:
_score = _score[_score['onset'].argsort()]
if delete_grace_notes:
LOGGER.debug('Deleting grace notes...')
_score = _score[_score['duration'] != 0]
scr.append(_score)
# Return a structured array if the score has only one part
if len(scr) == 1:
return scr[0]
elif len(scr) > 1 and flatten_parts:
scr = np.vstack(scr)
if sort_onsets:
return scr[scr['onset'].argsort()]
else:
return scr
def n_items_per_part_voice(pg, cls):
n_items = []
for part in score.iter_parts(pg):
n = sum(1 for _ in part.iter_all(cls))
n_items.extend([n] * len(set(n.voice for n in part.notes_tied)))
return n_items
def get_part_voice_numbers(parts):
counter = Counter()
for i, part in enumerate(score.iter_parts(parts)):
for note in part.notes_tied:
counter.update(((i, note.voice), ))
return counter
def setUp(self):
self.parts = make_assignment_mode_example()
# self.targets = get_partgroup_part_voice_numbers(self.parts)
self.parts_list = list(score.iter_parts(self.parts))
def n_notes(pg):
return sum(len(part.notes_tied) for part in score.iter_parts(pg))
def save_musicxml(parts, out=None):
"""Save a one or more Part or PartGroup instances in MusicXML format.
Parameters
----------
parts : list, Part, or PartGroup
A :class:`partitura.score.Part` object,
:class:`partitura.score.PartGroup` or a list of these
out: str, file-like object, or None, optional
Output file
Returns
-------
None or str
If no output file is specified using `out` the function returns the
MusicXML data as a string. Otherwise the function returns None.
"""
root = etree.Element('score-partwise')
partlist_e = etree.SubElement(root, 'part-list')
state = {
'note_id_counter': {},
'range_counter': {},
}
group_stack = []
def close_group_stack():
while group_stack:
# close group
etree.SubElement(partlist_e, 'part-group',
number='{}'.format(group_stack[-1].number),
type='stop')
# remove from stack
group_stack.pop()
def handle_parents(part):
# 1. get deepest parent that is in group_stack (keep track of parents to
# add)
pg = part.parent
to_add = []
while pg:
if pg in group_stack:
break
to_add.append(pg)
pg = pg.parent
# close groups while not equal to pg
while group_stack:
if pg == group_stack[-1]:
break
else:
# close group
etree.SubElement(partlist_e, 'part-group',
number='{}'.format(group_stack[-1].number),
type='stop')
# remove from stack
group_stack.pop()
# start all parents in to_add
for pg in reversed(to_add):
# start group
pg_e = etree.SubElement(partlist_e, 'part-group',
number='{}'.format(pg.number),
type='start')
if pg.group_symbol is not None:
symb_e = etree.SubElement(pg_e, 'group-symbol')
symb_e.text = pg.group_symbol
if pg.group_name is not None:
name_e = etree.SubElement(pg_e, 'group-name')
name_e.text = pg.group_name
group_stack.append(pg)
for part in score.iter_parts(parts):
handle_parents(part)
# handle part list entry
scorepart_e = etree.SubElement(partlist_e, 'score-part', id=part.id)
partname_e = etree.SubElement(scorepart_e, 'part-name')
if part.part_name:
partname_e.text = filter_string(part.part_name)
if part.part_abbreviation:
partabbrev_e = etree.SubElement(scorepart_e, 'part-abbreviation')
partabbrev_e.text = filter_string(part.part_abbreviation)
# write the part itself
part_e = etree.SubElement(root, 'part', id=part.id)
# store quarter_map in a variable to avoid re-creating it for each call
quarter_map = part.quarter_map
beat_map = part.beat_map
# ts = part.get_all(score.TimeSignature)
for measure in part.iter_all(score.Measure):
part_e.append(etree.Comment(MEASURE_SEP_COMMENT))
attrib = {}
if measure.number is not None:
attrib['number'] = str(measure.number)
measure_e = etree.SubElement(part_e, 'measure', **attrib)
contents = linearize_measure_contents(part,
measure.start,
measure.end,
state)
measure_e.extend(contents)
close_group_stack()
if out:
if hasattr(out, 'write'):
out.write(etree.tostring(root.getroottree(), encoding='UTF-8',
xml_declaration=True,
pretty_print=True, doctype=DOCTYPE))
else:
with open(out, 'wb') as f:
f.write(etree.tostring(root.getroottree(), encoding='UTF-8',
xml_declaration=True,
pretty_print=True, doctype=DOCTYPE))
else:
return etree.tostring(root.getroottree(), encoding='UTF-8',
xml_declaration=True,
pretty_print=True, doctype=DOCTYPE)
def load_score_midi(fn, part_voice_assign_mode=0, ensure_list=False,
quantization_unit=None, estimate_voice_info=True,
estimate_key=False, assign_note_ids=True):
"""Load a musical score from a MIDI file and return it as a Part
instance.
This function interprets MIDI information as describing a score.
Pitch names are estimated using Meredith's PS13 algorithm [1]_.
Assignment of notes to voices can either be done using Chew and
Wu's voice separation algorithm [2]_, or by choosing one of the
part/voice assignment modes that assign voices based on
track/channel information. Furthermore, the key signature can be
estimated based on Krumhansl's 1990 key profiles [3]_.
This function expects times to be metrical/quantized. Optionally a
quantization unit may be specified. If you wish to access the non-
quantized time of MIDI events you may wish to used the
`load_performance_midi` function instead.
Parameters
----------
fn : str
Path to MIDI file
part_voice_assign_mode : {0, 1, 2, 3, 4, 5}, optional
This keyword controls how part and voice information is
associated to track and channel information in the MIDI file.
The semantics of the modes is as follows:
0
Return one Part per track, with voices assigned by channel
1
Return one PartGroup per track, with Parts assigned by channel
(no voices)
2
Return single Part with voices assigned by track (tracks are
combined, channel info is ignored)
3
Return one Part per track, without voices (channel info is
ignored)
4
Return single Part without voices (channel and track info is
ignored)
5
Return one Part per <track, channel> combination, without
voices Defaults to 0.
ensure_list : bool, optional
When True, return a list independent of how many part or partgroup
elements were created from the MIDI file. By default, when the
return value of `load_score_midi` produces a single
:class:`partitura.score.Part` or :class:`partitura.score.PartGroup`
element, the element itself is returned instead of a list
containing the element. Defaults to False.
quantization_unit : integer or None, optional
Quantize MIDI times to multiples of this unit. If None, the
quantization unit is chosen automatically as the smallest
division of the parts per quarter (MIDI "ticks") that can be
represented as a symbolic duration. Defaults to None.
estimate_key : bool, optional
When True use Krumhansl's 1990 key profiles [3]_ to determine
the most likely global key, discarding any key information in
the MIDI file.
estimate_voice_info : bool, optional
When True use Chew and Wu's voice separation algorithm [2]_ to
estimate voice information. This option is ignored for
part/voice assignment modes that infer voice information from
the track/channel info (i.e. `part_voice_assign_mode` equals
1, 3, 4, or 5). Defaults to True.
Returns
-------
:class:`partitura.score.Part`, :class:`partitura.score.PartGroup`, or a list of these
One or more part or partgroup objects
References
----------
.. [1] Meredith, D. (2006). "The ps13 Pitch Spelling Algorithm". Journal
of New Music Research, 35(2):121.
.. [2] Chew, E. and Wu, Xiaodan (2004) "Separating Voices in
Polyphonic Music: A Contig Mapping Approach". In Uffe Kock,
editor, Computer Music Modeling and Retrieval (CMMR), pp. 1–20,
Springer Berlin Heidelberg.
.. [3] Krumhansl, Carol L. (1990) "Cognitive foundations of musical pitch",
Oxford University Press, New York.
"""
mid = mido.MidiFile(fn)
divs = mid.ticks_per_beat
# these lists will contain information from dedicated tracks for meta
# information (i.e. without notes)
global_time_sigs = []
global_key_sigs = []
global_tempos = []
# these dictionaries will contain meta information indexed by track (only
# for tracks that contain notes)
time_sigs_by_track = {}
key_sigs_by_track = {}
tempos_by_track = {}
track_names_by_track = {}
# notes are indexed by (track, channel) tuples
notes_by_track_ch = {}
relevant = {'time_signature',
'key_signature',
'set_tempo',
'note_on',
'note_off'}
for track_nr, track in enumerate(mid.tracks):
time_sigs = []
key_sigs = []
# tempos = []
notes = defaultdict(list)
# dictionary for storing the last onset time and velocity for each
# individual note (i.e. same pitch and channel)
sounding_notes = {}
# current time (will be updated by delta times in messages)
t_raw = 0
for msg in track:
t_raw = t_raw + msg.time
if msg.type not in relevant:
continue
if quantization_unit:
t = quantize(t_raw, quantization_unit)
else:
t = t_raw
if msg.type == 'time_signature':
time_sigs.append((t, msg.numerator, msg.denominator))
if msg.type == 'key_signature':
key_sigs.append((t, msg.key))
if msg.type == 'set_tempo':
global_tempos.append((t, 60*10**6/msg.tempo))
else:
note_on = msg.type == 'note_on'
note_off = msg.type == 'note_off'
if not (note_on or note_off):
continue
# hash sounding note
note = note_hash(msg.channel, msg.note)
# start note if it's a 'note on' event with velocity > 0
if note_on and msg.velocity > 0:
# save the onset time and velocity
sounding_notes[note] = (t, msg.velocity)
# end note if it's a 'note off' event or 'note on' with velocity 0
elif note_off or (note_on and msg.velocity == 0):
if note not in sounding_notes:
warnings.warn('ignoring MIDI message %s' % msg)
continue
# append the note to the list associated with the channel
notes[msg.channel].append((sounding_notes[note][0], msg.note, t-sounding_notes[note][0]))
# sounding_notes[note][1]])
# remove hash from dict
del sounding_notes[note]
# if a track has no notes, we assume it may contain global time/key sigs
if not notes:
global_time_sigs.extend(time_sigs)
global_key_sigs.extend(key_sigs)
else:
# if there are note, we store the info under the track number
time_sigs_by_track[track_nr] = time_sigs
key_sigs_by_track[track_nr] = key_sigs
track_names_by_track[track_nr] = track.name
for ch, ch_notes in notes.items():
# if there are any notes, store the notes along with key sig / time
# sig / tempo information under the key (track_nr, ch_nr)
if len(ch_notes) > 0:
notes_by_track_ch[(track_nr, ch)] = ch_notes
tr_ch_keys = sorted(notes_by_track_ch.keys())
group_part_voice_keys, part_names, group_names = assign_group_part_voice(
part_voice_assign_mode,
tr_ch_keys,
track_names_by_track)
# for key and time sigs:
track_to_part_mapping = make_track_to_part_mapping(
tr_ch_keys,
group_part_voice_keys)
# pairs of (part, voice) for each note
part_voice_list = [[part, voice] for tr_ch, (_, part, voice)
in zip(tr_ch_keys, group_part_voice_keys)
for i in range(len(notes_by_track_ch[tr_ch]))]
# pitch spelling, voice estimation and key estimation are done on a
# structured array (onset, pitch, duration) of all notes in the piece
# jointly, so we concatenate all notes
# note_list = sorted(note for notes in (notes_by_track_ch[key] for key in tr_ch_keys) for note in notes)
note_list = [note for notes in (notes_by_track_ch[key]
for key in tr_ch_keys)
for note in notes]
note_array = np.array(note_list, dtype=[('onset', np.int),
('pitch', np.int),
('duration', np.int)])
LOGGER.debug('pitch spelling')
spelling_global = analysis.estimate_spelling(note_array)
if estimate_voice_info:
LOGGER.debug('voice estimation')
# TODO: deal with zero duration notes in note_array. Zero duration notes are currently deleted
estimated_voices = analysis.estimate_voices(note_array)
assert len(part_voice_list) == len(estimated_voices)
for part_voice, voice_est in zip(part_voice_list, estimated_voices):
if part_voice[1] is None:
part_voice[1] = voice_est
if estimate_key:
LOGGER.debug('key estimation')
_, mode, fifths = analysis.estimate_key(note_array)
key_sigs_by_track = {}
global_key_sigs = [(0, fifths_mode_to_key_name(fifths, mode))]
if assign_note_ids:
note_ids = ['n{}'.format(i) for i in range(len(note_array))]
else:
note_ids = [None for i in range(len(note_array))]
time_sigs_by_part = defaultdict(set)
for tr, ts_list in time_sigs_by_track.items():
for ts in ts_list:
for part in track_to_part_mapping[tr]:
time_sigs_by_part[part].add(ts)
for ts in global_time_sigs:
for part in set(part for _, part, _ in group_part_voice_keys):
time_sigs_by_part[part].add(ts)
key_sigs_by_part = defaultdict(set)
for tr, ks_list in key_sigs_by_track.items():
for ks in ks_list:
for part in track_to_part_mapping[tr]:
key_sigs_by_part[part].add(ks)
for ks in global_key_sigs:
for part in set(part for _, part, _ in group_part_voice_keys):
key_sigs_by_part[part].add(ks)
# names_by_part = defaultdict(set)
# for tr_ch, pg_p_v in zip(tr_ch_keys, group_part_voice_keys):
# print(tr_ch, pg_p_v)
# for tr, name in track_names_by_track.items():
# print(tr, track_to_part_mapping, name)
# for part in track_to_part_mapping[tr]:
# names_by_part[part] = name
notes_by_part = defaultdict(list)
for (part, voice), note, spelling, note_id in zip(part_voice_list,
note_list,
spelling_global,
note_ids):
notes_by_part[part].append((note, voice, spelling, note_id))
partlist = []
part_to_part_group = dict((p, pg) for pg, p, _ in group_part_voice_keys)
part_groups = {}
for part_nr, note_info in notes_by_part.items():
notes, voices, spellings, note_ids = zip(*note_info)
part = create_part(divs, notes, spellings, voices, note_ids,
sorted(time_sigs_by_part[part_nr]),
sorted(key_sigs_by_part[part_nr]),
part_id='P{}'.format(part_nr+1),
part_name=part_names.get(part_nr, None))
# print(part.pretty())
# if this part has an associated part_group number we create a PartGroup
# if necessary, and add the part to that. The newly created PartGroup is
# then added to the partlist.
pg_nr = part_to_part_group[part_nr]
if pg_nr is None:
partlist.append(part)
else:
if pg_nr not in part_groups:
part_groups[pg_nr] = score.PartGroup(group_name=group_names.get(pg_nr, None))
partlist.append(part_groups[pg_nr])
part_groups[pg_nr].children.append(part)
# add tempos to first part
part = next(score.iter_parts(partlist))
for t, qpm in global_tempos:
part.add(score.Tempo(qpm, unit='q'), t)
if not ensure_list and len(partlist) == 1:
return partlist[0]
else:
return partlist
def save_score_midi(parts, out, part_voice_assign_mode=0, velocity=64):
"""Write data from Part objects to a MIDI file
Parameters
----------
parts : Part, PartGroup or list of these
The musical score to be saved.
out : str or file-like object
Either a filename or a file-like object to write the MIDI data
to.
part_voice_assign_mode : {0, 1, 2, 3, 4, 5}, optional
This keyword controls how part and voice information is
associated to track and channel information in the MIDI file.
The semantics of the modes is as follows:
0
Write one track for each Part, with channels assigned by
voices
1
Write one track for each PartGroup, with channels assigned by
Parts (voice info is lost) (There can be multiple levels of
partgroups, I suggest using the highest level of
partgroup/part) [note: this will e.g. lead to all strings into
the same track] Each part not in a PartGroup will be assigned
its own track
2
Write a single track with channels assigned by Part (voice
info is lost)
3
Write one track per Part, and a single channel for all voices
(voice info is lost)
4
Write a single track with a single channel (Part and voice
info is lost)
5
Return one track per <Part, voice> combination, each track
having a single channel.
velocity : int, optional
Default velocity for all MIDI notes.
"""
ppq = get_ppq(parts)
events = defaultdict(lambda: defaultdict(list))
meta_events = defaultdict(lambda: defaultdict(list))
event_keys = OrderedDict()
tempos = {}
for i, part in enumerate(score.iter_parts(parts)):
pg = get_partgroup(part)
notes = part.notes_tied
qm = part.quarter_map
q_offset = qm(part.first_point.t)
def to_ppq(t):
# convert div times to new ppq
return int(ppq * qm(t))
for tp in part.iter_all(score.Tempo):
tempos[to_ppq(tp.start.t)] = MetaMessage(
'set_tempo', tempo=tp.microseconds_per_quarter)
for ts in part.iter_all(score.TimeSignature):
meta_events[part][to_ppq(ts.start.t)].append(
MetaMessage('time_signature',
numerator=ts.beats,
denominator=ts.beat_type))
for ks in part.iter_all(score.KeySignature):
meta_events[part][to_ppq(ks.start.t)].append(
MetaMessage('key_signature', key=ks.name))
for note in notes:
# key is a tuple (part_group, part, voice) that will be converted into a (track, channel) pair.
key = (pg, part, note.voice)
events[key][to_ppq(note.start.t)].append(
Message('note_on', note=note.midi_pitch))
events[key][to_ppq(note.end_tied.t)].append(
Message('note_off', note=note.midi_pitch))
event_keys[key] = True
tr_ch_map = map_to_track_channel(list(event_keys.keys()),
part_voice_assign_mode)
# replace original event keys (partgroup, part, voice) by (track, ch) keys:
for key in list(events.keys()):
evs_by_time = events[key]
del events[key]
tr, ch = tr_ch_map[key]
for t, evs in evs_by_time.items():
events[tr][t].extend((ev.copy(channel=ch) for ev in evs))
# figure out in which tracks to replicate the time/key signatures of each part
part_track_map = partition(lambda x: x[0][1], tr_ch_map.items())
for part, rest in part_track_map.items():
part_track_map[part] = set(x[1][0] for x in rest)
# add the time/key sigs to their corresponding tracks
for part, m_events in meta_events.items():
tracks = part_track_map[part]
for tr in tracks:
for t, me in m_events.items():
events[tr][t] = me + events[tr][t]
n_tracks = max(tr for tr, _ in tr_ch_map.values()) + 1
tracks = [MidiTrack() for _ in range(n_tracks)]
# tempo events are handled differently from key/time sigs because the have a
# global effect. Instead of adding to each relevant track, like the key/time
# sig events, we add them only to the first track
track0_events = events[0]
for t, tp in tempos.items():
events[0][t].insert(0, tp)
for tr, events_by_time in events.items():
t_prev = 0
for t in sorted(events_by_time.keys()):
evs = events_by_time[t]
delta = t - t_prev
for ev in evs:
tracks[tr].append(ev.copy(time=delta))
delta = 0
t_prev = t
midi_type = 0 if n_tracks == 1 else 1
mf = MidiFile(type=midi_type, ticks_per_beat=ppq)
for track in tracks:
mf.tracks.append(track)
if out:
if hasattr(out, 'write'):
mf.save(file=out)
else:
mf.save(out)
def musicxml_to_notearray(
fn,
flatten_parts=True,
include_pitch_spelling=False,
include_key_signature=False,
include_time_signature=False,
):
"""Return pitch, onset, and duration information for notes from a
MusicXML file as a structured array.
By default a single array is returned by combining the note
information of all parts in the MusicXML file.
Parameters
----------
fn : str
Path to a MusicXML file
flatten_parts : bool
If `True`, returns a single array containing all notes.
Otherwise, returns a list of arrays for each part.
include_pitch_spelling : bool (optional)
If `True`, includes pitch spelling information for each
note. Default is False
include_key_signature : bool (optional)
If `True`, includes key signature information, i.e.,
the key signature at the onset time of each note (all
notes starting at the same time have the same key signature).
Default is False
include_time_signature : bool (optional)
If `True`, includes time signature information, i.e.,
the time signature at the onset time of each note (all
notes starting at the same time have the same time signature).
Default is False
Returns
-------
score : structured array or list of structured arrays
Structured array or list of structured arrays containing
score information.
"""
parts = load_musicxml(fn, ensure_list=True, force_note_ids="keep")
note_arrays = []
for part in score.iter_parts(parts):
# Unfold any repetitions in part
unfolded_part = score.unfold_part_maximal(part)
# Compute note array
note_array = ensure_notearray(
notearray_or_part=unfolded_part,
include_pitch_spelling=include_pitch_spelling,
include_key_signature=include_key_signature,
include_time_signature=include_time_signature)
note_arrays.append(note_array)
if len(note_arrays) == 1:
return note_arrays[0]
elif len(note_arrays) > 1 and flatten_parts:
return np.hstack(note_arrays)
else:
return note_arrays