def test_note_data():
intervals = np.array([[1.0, 2.0], [1.5, 3.0], [2.0, 3.0]])
notes = np.array([100.0, 150.0, 120.0])
confidence = np.array([0.1, 0.4, 0.2])
note_data = annotations.NoteData(intervals, notes)
assert np.allclose(note_data.intervals, intervals)
assert np.allclose(note_data.notes, notes)
assert note_data.confidence is None
note_data2 = annotations.NoteData(intervals, notes, confidence)
assert np.allclose(note_data2.intervals, intervals)
assert np.allclose(note_data2.notes, notes)
assert np.allclose(note_data2.confidence, confidence)
with pytest.raises(ValueError):
annotations.NoteData(None, notes)
with pytest.raises(ValueError):
annotations.NoteData(intervals, None)
with pytest.raises(TypeError):
annotations.NoteData([1.0, 2.0], notes)
with pytest.raises(TypeError):
annotations.NoteData(intervals, [3.0, 4.0])
with pytest.raises(TypeError):
annotations.NoteData(intervals.astype(int), notes)
with pytest.raises(ValueError):
annotations.NoteData(intervals, np.array([1.0]))
def load_notes(fhandle: TextIO) -> annotations.NoteData:
"""Load note data from the annotation files
Args:
fhandle (str or file-like): path or file-like object pointing to a notes annotation file
Returns:
NoteData: note annotations
"""
intervals = []
pitches = []
confidence = []
reader = csv.reader(fhandle, delimiter=",")
for line in reader:
intervals.append([line[0], float(line[0]) + float(line[1])])
# Convert midi value to frequency
pitches.append((440 / 32) * (2**((int(line[2]) - 9) / 12)))
confidence.append(1.0)
return annotations.NoteData(
np.array(intervals, dtype="float"),
np.array(pitches, dtype="float"),
np.array(confidence, dtype="float"),
)
def load_notes(midi_path, midi=None):
"""Load note data from the midi file.
Args:
midi_path (str): path to midi file
midi (pretty_midi.PrettyMIDI): pre-loaded midi object or None
if None, the midi object is loaded using midi_path
Returns:
NoteData: note annotations
"""
if midi is None:
midi = load_midi(midi_path)
intervals = []
pitches = []
confidence = []
for note in midi.instruments[0].notes:
intervals.append([note.start, note.end])
pitches.append(librosa.midi_to_hz(note.pitch))
confidence.append(note.velocity / 127.0)
return annotations.NoteData(
np.array(intervals), np.array(pitches), np.array(confidence)
)
def load_notes(notes_path):
"""Load note data from the annotation files
Args:
notes_path (str): path to notes file
Returns:
NoteData: note annotations
"""
if not os.path.exists(notes_path):
raise IOError("notes_path {} does not exist".format(notes_path))
intervals = []
pitches = []
confidence = []
with open(notes_path, "r") as fhandle:
reader = csv.reader(fhandle, delimiter=",")
for line in reader:
intervals.append([line[0], float(line[0]) + float(line[1])])
# Convert midi value to frequency
pitches.append((440 / 32) * (2**((int(line[2]) - 9) / 12)))
confidence.append(1.0)
return annotations.NoteData(
np.array(intervals, dtype="float"),
np.array(pitches, dtype="float"),
np.array(confidence, dtype="float"),
)
def get_notes_target(self, track_keys, notes_property="notes"):
"""Get the notes for all the tracks
Args:
track_keys (list): list of track keys to get the NoteData for
notes_property (str): the attribute associated with NoteData, notes or notes_original
Returns:
NoteData: Note data for the tracks
"""
values = []
intervals = []
for k in track_keys:
score = getattr(self.tracks[k], notes_property)
values.append(score.notes)
intervals.append(score.intervals)
values = np.hstack(values)
intervals = np.vstack(intervals)
#### sort on the start time
ind = np.argsort(intervals[:, 0], axis=0)
start_times = np.take_along_axis(intervals[:, 0], ind, axis=0)
end_times = np.take_along_axis(intervals[:, 1], ind, axis=0)
intervals = np.vstack([start_times, end_times]).T
values = np.take_along_axis(values, ind, axis=0)
return annotations.NoteData(intervals, values)
def load_annotations_granularity(annotations_path, granularity):
"""Load annotations at the specified level of granularity
Args:
annotations_path (str): path to a DALI annotation file
granularity (str): one of 'notes', 'words', 'lines', 'paragraphs'
Returns:
NoteData for granularity='notes' or LyricData otherwise
"""
try:
with gzip.open(annotations_path, "rb") as f:
output = pickle.load(f)
except Exception as e:
with gzip.open(annotations_path, "r") as f:
output = pickle.load(f)
text = []
notes = []
begs = []
ends = []
for annot in output.annotations["annot"][granularity]:
notes.append(round(annot["freq"][0], 3))
begs.append(round(annot["time"][0], 3))
ends.append(round(annot["time"][1], 3))
text.append(annot["text"])
if granularity == "notes":
annotation = annotations.NoteData(
np.array([begs, ends]).T, np.array(notes), None)
else:
annotation = annotations.LyricData(
np.array([begs, ends]).T, text, None)
return annotation
def load_score(fhandle: TextIO) -> annotations.NoteData:
"""Load a Dagstuhl ChoirSet time-aligned score representation.
Args:
fhandle (str or file-like): File-like object or path to score representation file
Returns:
NoteData Object - the time-aligned score representation
"""
intervals = np.empty((0, 2))
notes = []
reader = csv.reader(fhandle, delimiter=",")
for line in reader:
intervals = np.vstack([intervals, [float(line[0]), float(line[1])]])
notes.append(float(line[2]))
return annotations.NoteData(intervals, librosa.midi_to_hz(notes), None)
def load_notes(jams_path, string_num):
"""Load a guitarset note annotation for a given string
Args:
jams_path (str): Path of the jams annotation file
string_num (int), in range(6): Which string to load.
0 is the Low E string, 5 is the high e string.
Returns:
NoteData: Note data for the given string
"""
if not os.path.exists(jams_path):
raise IOError("jams_path {} does not exist".format(jams_path))
jam = jams.load(jams_path)
anno_arr = jam.search(namespace="note_midi")
anno = anno_arr.search(data_source=str(string_num))[0]
intervals, values = anno.to_interval_values()
if len(values) == 0:
return None
return annotations.NoteData(intervals, np.array(values))
def load_score(fhandle: TextIO) -> annotations.NoteData:
"""Load a Phenicx-Anechoic score file.
Args:
fhandle (str or file-like): File-like object or path to score file
Returns:
NoteData: Note data for the given track
"""
#### read start, end times
intervals = np.loadtxt(fhandle,
delimiter=",",
usecols=[0, 1],
dtype=np.float_)
#### read notes as string
fhandle.seek(0)
content = fhandle.readlines()
values = np.array([
librosa.note_to_hz(line.split(",")[2].strip("\n")) for line in content
])
return annotations.NoteData(intervals, values)
def test_notes():
note_data_1 = [
(
annotations.NoteData(
np.array([[0.0, 0.5, 1.0], [0.5, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
None,
)
]
note_data_2 = [
(
annotations.NoteData(
np.array([[0.0, 0.8, 1.0], [0.5, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
"notes_2",
)
]
note_data_3 = [
(
annotations.NoteData(
np.array([[0.0, 0.5, 1.0], [0.5, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
"notes_1",
),
(
annotations.NoteData(
np.array([[0.0, 0.7, 1.0], [0.7, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
"notes_2",
),
]
note_data_4 = (
annotations.NoteData(
np.array([[0.0, 0.5, 1.0], [0.5, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
None,
)
note_data_5 = [
[
annotations.NoteData(
np.array([[0.0, 0.5, 1.0], [0.5, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
None,
],
(
annotations.NoteData(
np.array([[0.0, 0.8, 1.0], [0.5, 1.0, 1.5]]).T,
np.array([1108.731, 1108.731, 1108.731]),
np.array([1.0, 1.0, 1.0]),
),
"notes_2",
),
]
note_data_6 = [(None, None)]
note_data_7 = [
(
annotations.EventData(
np.array([[0.2, 0.3], [0.3, 0.4]]).T,
["event A", "event B"],
),
None,
)
]
jam_1 = jams_utils.jams_converter(note_data=note_data_1)
jam_2 = jams_utils.jams_converter(note_data=note_data_2)
jam_3 = jams_utils.jams_converter(note_data=note_data_3)
jam_6 = jams_utils.jams_converter(note_data=note_data_6)
time, duration, value, confidence = get_jam_data(jam_1, "note_hz", 0)
assert time == [0.0, 0.5, 1.0]
assert duration == [0.5, 0.5, 0.5]
assert value == [1108.731, 1108.731, 1108.731]
assert confidence == [None, None, None]
assert jam_2.annotations[0]["sandbox"]["name"] == "notes_2"
time, duration, value, confidence = get_jam_data(jam_3, "note_hz", 0)
assert time == [0.0, 0.5, 1.0]
assert duration == [0.5, 0.5, 0.5]
assert value == [1108.731, 1108.731, 1108.731]
assert confidence == [None, None, None]
time, duration, value, confidence = get_jam_data(jam_3, "note_hz", 1)
assert time == [0.0, 0.7, 1.0]
assert duration == [0.7, 0.3, 0.5]
assert value == [1108.731, 1108.731, 1108.731]
assert confidence == [None, None, None]
time, duration, value, confidence = get_jam_data(jam_6, "note_hz", 0)
assert time == []
assert duration == []
assert value == []
assert confidence == []
assert type(jam_1) == jams.JAMS
with pytest.raises(TypeError):
jams_utils.jams_converter(note_data=note_data_4)
with pytest.raises(TypeError):
jams_utils.jams_converter(note_data=note_data_5)
with pytest.raises(TypeError):
jams_utils.jams_converter(note_data=note_data_7)
