def load_sama(sama_path):
"""Load sama
Args:
sama_path (str): Local path where the sama annotation is stored.
If `None`, returns None.
Returns:
SectionData: sama annotations
"""
if sama_path is None:
return None
if not os.path.exists(sama_path):
raise IOError("sama_path {} does not exist".format(sama_path))
timestamps = []
sama_cycles = []
intervals = []
with open(sama_path, 'r') as reader:
for line in reader.readlines():
timestamps.append(float(line))
for i in np.arange(1, len(timestamps)):
intervals.append([timestamps[i - 1], timestamps[i]])
sama_cycles.append('sama cycle ' + str(i))
if not intervals:
return None
return utils.SectionData(np.array(intervals), sama_cycles)
def load_sections(sections_path):
"""Load Beatles format section data from a file
Args:
sections_path (str): path to section annotation file
Returns:
(utils.SectionData): loaded section data
"""
if sections_path is None:
return None
if not os.path.exists(sections_path):
raise IOError("sections_path {} does not exist".format(sections_path))
start_times, end_times, sections = [], [], []
with open(sections_path, "r") as fhandle:
reader = csv.reader(fhandle, delimiter="\t")
for line in reader:
start_times.append(float(line[0]))
end_times.append(float(line[1]))
sections.append(line[3])
section_data = utils.SectionData(
np.array([start_times, end_times]).T, sections)
return section_data
def load_sections(sections_path, iam_style):
"""Load sections from carnatic collection
Args:
sections_path (str): Local path where the section annotation is stored.
iam_style (str): Flag to differentiate between hindustani and carnatic tracks
Returns:
SectionData: section annotations for track
"""
if sections_path is None:
return None
if not os.path.exists(sections_path):
raise IOError("sections_path {} does not exist".format(sections_path))
intervals = []
section_labels = []
if iam_style == 'carnatic':
with open(sections_path, 'r') as reader:
for line in reader.readlines():
if line != '\n':
intervals.append([
float(line.split('\t')[0]),
float(line.split('\t')[0]) +
float(line.split('\t')[2]),
])
section_labels.append(
str(line.split('\t')[3].split('\n')[0]))
if not intervals:
return None
if iam_style == 'hindustani':
with open(sections_path, 'r') as reader:
for line in reader.readlines():
if line != '\n':
intervals.append([
float(line.split(',')[0]),
float(line.split(',')[0]) + float(line.split(',')[2]),
])
section_labels.append(
str(line.split(',')[3].split('\n')[0]) + '-' +
str(line.split(',')[1]))
if not intervals:
return None
return utils.SectionData(np.array(intervals), section_labels)
def _load_sections(sections_path):
if not os.path.exists(sections_path):
return None
begs = [] # timestamps of section beginnings
ends = [] # timestamps of section endings
secs = [] # section labels
with open(sections_path, 'r') as fhandle:
reader = csv.reader(fhandle, delimiter='\t')
for line in reader:
begs.append(float(line[0]) / 100.0)
ends.append(float(line[1]) / 100.0)
secs.append(line[2])
return utils.SectionData(np.array(begs), np.array(ends), np.array(secs))
def load_sections(sections_path):
if not os.path.exists(sections_path):
raise IOError("sections_path {} does not exist".format(sections_path))
begs = [] # timestamps of section beginnings
ends = [] # timestamps of section endings
secs = [] # section labels
with open(sections_path, 'r') as fhandle:
reader = csv.reader(fhandle, delimiter='\t')
for line in reader:
begs.append(float(line[0]) / 100.0)
ends.append(float(line[1]) / 100.0)
secs.append(line[2])
return utils.SectionData(np.array([begs, ends]).T, secs)
def load_sections(sections_path):
if sections_path is None or not os.path.exists(sections_path):
return None
times = []
secs = []
with open(sections_path, 'r') as fhandle:
reader = csv.reader(fhandle, delimiter='\t')
for line in reader:
times.append(float(line[0]))
secs.append(line[1])
times = np.array(times)
secs = np.array(secs)
# remove sections with length == 0
times_revised = np.delete(times, np.where(np.diff(times) == 0))
secs_revised = np.delete(secs, np.where(np.diff(times) == 0))
return utils.SectionData(
np.array([times_revised[:-1], times_revised[1:]]).T,
list(secs_revised[:-1]))
def _load_sections(sections_path):
"""Private function to load Beatles format sections data from a file
Args:
sections_path (str):
"""
if sections_path is None or not os.path.exists(sections_path):
return None
start_times, end_times, sections = [], [], []
with open(sections_path, 'r') as fhandle:
reader = csv.reader(fhandle, delimiter='\t')
for line in reader:
start_times.append(float(line[0]))
end_times.append(float(line[1]))
sections.append(line[3])
section_data = utils.SectionData(np.array([start_times, end_times]).T, sections)
return section_data
def test_multi_sections():
multi_section_data_1 = [
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
None,
),
],
None,
)
]
multi_section_data_2 = [
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
0,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
1,
),
],
"annotator_1",
)
]
multi_section_data_3 = [
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
0,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
1,
),
],
"annotator_1",
),
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
0,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
1,
),
],
"annotator_2",
),
]
multi_section_data_4 = (
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
None,
),
],
None,
)
multi_section_data_5 = [
[
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
None,
),
],
None,
]
]
multi_section_data_6 = [
(
(
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(["verse a", "verse b", "verse a"]),
),
None,
),
),
None,
)
]
multi_section_data_7 = [([(None, None), (None, None)], None)]
multi_section_data_8 = [
(
[
(
utils.EventData(
np.array([0.2, 0.3]),
np.array([0.3, 0.4]),
np.array(["event A", "event B"]),
),
None,
),
(
utils.EventData(
np.array([0.2, 0.3]),
np.array([0.3, 0.4]),
np.array(["event A", "event B"]),
),
None,
),
],
None,
)
]
jam_1 = jams_utils.jams_converter(multi_section_data=multi_section_data_1)
jam_2 = jams_utils.jams_converter(multi_section_data=multi_section_data_2)
jam_3 = jams_utils.jams_converter(multi_section_data=multi_section_data_3)
jam_7 = jams_utils.jams_converter(multi_section_data=multi_section_data_7)
time, duration, value, confidence = get_jam_data(jam_1, "multi_segment", 0)
assert time == [0.0, 0.0, 10.0, 15.0, 20.0, 20.0]
assert duration == [10.0, 15.0, 10.0, 5.0, 5.0, 5.0]
assert value == [
{"label": "verse A", "level": None},
{"label": "verse a", "level": None},
{"label": "verse B", "level": None},
{"label": "verse b", "level": None},
{"label": "verse A", "level": None},
{"label": "verse a", "level": None},
]
assert confidence == [None, None, None, None, None, None]
assert (
jam_2.annotations[0]["annotation_metadata"]["annotator"]["name"]
== "annotator_1"
)
time, duration, value, confidence = get_jam_data(jam_3, "multi_segment", 0)
assert time == [0.0, 0.0, 10.0, 15.0, 20.0, 20.0]
assert duration == [10.0, 15.0, 10.0, 5.0, 5.0, 5.0]
assert value == [
{"label": "verse A", "level": 0},
{"label": "verse a", "level": 1},
{"label": "verse B", "level": 0},
{"label": "verse b", "level": 1},
{"label": "verse A", "level": 0},
{"label": "verse a", "level": 1},
]
assert confidence == [None, None, None, None, None, None]
time, duration, value, confidence = get_jam_data(jam_3, "multi_segment", 1)
assert time == [0.0, 0.0, 10.0, 15.0, 20.0, 20.0]
assert duration == [10.0, 15.0, 10.0, 5.0, 5.0, 5.0]
assert value == [
{"label": "verse A", "level": 0},
{"label": "verse a", "level": 1},
{"label": "verse B", "level": 0},
{"label": "verse b", "level": 1},
{"label": "verse A", "level": 0},
{"label": "verse a", "level": 1},
]
assert confidence == [None, None, None, None, None, None]
time, duration, value, confidence = get_jam_data(jam_7, "multi_segment", 0)
assert time == []
assert duration == []
assert value == []
assert confidence == []
assert type(jam_1) == jams.JAMS
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_4)
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_5)
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_6)
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_8)
def test_sections():
section_data_1 = [
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
)
]
section_data_2 = [
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
"sections_2",
)
]
section_data_3 = [
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
"sections_1",
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 30.0]]).T,
np.array(["verse A", "verse B", "verse C"]),
),
"sections_2",
),
]
section_data_4 = (
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
)
section_data_5 = [
[
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
None,
],
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(["verse A", "verse B", "verse A"]),
),
"sections_2",
),
]
section_data_6 = [(None, None)]
section_data_7 = [
(
utils.EventData(
np.array([0.2, 0.3]),
np.array([0.3, 0.4]),
np.array(["event A", "event B"]),
),
None,
)
]
jam_1 = jams_utils.jams_converter(section_data=section_data_1)
jam_2 = jams_utils.jams_converter(section_data=section_data_2)
jam_3 = jams_utils.jams_converter(section_data=section_data_3)
jam_6 = jams_utils.jams_converter(section_data=section_data_6)
time, duration, value, confidence = get_jam_data(jam_1, "segment", 0)
assert time == [0.0, 10.0, 20.0]
assert duration == [10.0, 10.0, 5.0]
assert value == ["verse A", "verse B", "verse A"]
assert confidence == [None, None, None]
assert jam_2.annotations[0]["sandbox"]["name"] == "sections_2"
time, duration, value, confidence = get_jam_data(jam_3, "segment", 0)
assert time == [0.0, 10.0, 20.0]
assert duration == [10.0, 10.0, 5.0]
assert value == ["verse A", "verse B", "verse A"]
assert confidence == [None, None, None]
time, duration, value, confidence = get_jam_data(jam_3, "segment", 1)
assert time == [0.0, 15.0, 20.0]
assert duration == [15.0, 5.0, 10.0]
assert value == ["verse A", "verse B", "verse C"]
assert confidence == [None, None, None]
time, duration, value, confidence = get_jam_data(jam_6, "segment", 0)
assert time == []
assert duration == []
assert value == []
assert confidence == []
assert type(jam_1) == jams.JAMS
with pytest.raises(TypeError):
jams_utils.jams_converter(section_data=section_data_4)
with pytest.raises(TypeError):
jams_utils.jams_converter(section_data=section_data_5)
with pytest.raises(TypeError):
jams_utils.jams_converter(section_data=section_data_7)
def test_multi_sections():
multi_section_data_1 = [
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
None,
),
],
None,
)
]
multi_section_data_2 = [
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
0,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
1,
),
],
'annotator_1',
)
]
multi_section_data_3 = [
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
0,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
1,
),
],
'annotator_1',
),
(
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
0,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
1,
),
],
'annotator_2',
),
]
multi_section_data_4 = (
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
None,
),
],
None,
)
multi_section_data_5 = [
[
[
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
None,
),
],
None,
]
]
multi_section_data_6 = [
(
(
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
np.array(['verse a', 'verse b', 'verse a']),
),
None,
),
),
None,
)
]
multi_section_data_7 = [([(None, None), (None, None)], None)]
multi_section_data_8 = [
(
[
(
utils.EventData(
np.array([0.2, 0.3]),
np.array([0.3, 0.4]),
np.array(['event A', 'event B']),
),
None,
),
(
utils.EventData(
np.array([0.2, 0.3]),
np.array([0.3, 0.4]),
np.array(['event A', 'event B']),
),
None,
),
],
None,
)
]
jam_1 = jams_utils.jams_converter(multi_section_data=multi_section_data_1)
jam_2 = jams_utils.jams_converter(multi_section_data=multi_section_data_2)
jam_3 = jams_utils.jams_converter(multi_section_data=multi_section_data_3)
jam_7 = jams_utils.jams_converter(multi_section_data=multi_section_data_7)
time, duration, value, confidence = get_jam_data(jam_1, 'multi_segment', 0)
assert time == [0.0, 0.0, 10.0, 15.0, 20.0, 20.0]
assert duration == [10.0, 15.0, 10.0, 5.0, 5.0, 5.0]
assert value == [
{'label': 'verse A', 'level': None},
{'label': 'verse a', 'level': None},
{'label': 'verse B', 'level': None},
{'label': 'verse b', 'level': None},
{'label': 'verse A', 'level': None},
{'label': 'verse a', 'level': None},
]
assert confidence == [None, None, None, None, None, None]
assert (
jam_2.annotations[0]['annotation_metadata']['annotator']['name']
== 'annotator_1'
)
time, duration, value, confidence = get_jam_data(jam_3, 'multi_segment', 0)
assert time == [0.0, 0.0, 10.0, 15.0, 20.0, 20.0]
assert duration == [10.0, 15.0, 10.0, 5.0, 5.0, 5.0]
assert value == [
{'label': 'verse A', 'level': 0},
{'label': 'verse a', 'level': 1},
{'label': 'verse B', 'level': 0},
{'label': 'verse b', 'level': 1},
{'label': 'verse A', 'level': 0},
{'label': 'verse a', 'level': 1},
]
assert confidence == [None, None, None, None, None, None]
time, duration, value, confidence = get_jam_data(jam_3, 'multi_segment', 1)
assert time == [0.0, 0.0, 10.0, 15.0, 20.0, 20.0]
assert duration == [10.0, 15.0, 10.0, 5.0, 5.0, 5.0]
assert value == [
{'label': 'verse A', 'level': 0},
{'label': 'verse a', 'level': 1},
{'label': 'verse B', 'level': 0},
{'label': 'verse b', 'level': 1},
{'label': 'verse A', 'level': 0},
{'label': 'verse a', 'level': 1},
]
assert confidence == [None, None, None, None, None, None]
time, duration, value, confidence = get_jam_data(jam_7, 'multi_segment', 0)
assert time == []
assert duration == []
assert value == []
assert confidence == []
assert type(jam_1) == jams.JAMS
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_4)
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_5)
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_6)
with pytest.raises(TypeError):
jams_utils.jams_converter(multi_section_data=multi_section_data_8)
def test_sections():
section_data_1 = [
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
)
]
section_data_2 = [
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
'sections_2',
)
]
section_data_3 = [
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
'sections_1',
),
(
utils.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 30.0]]).T,
np.array(['verse A', 'verse B', 'verse C']),
),
'sections_2',
),
]
section_data_4 = (
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
)
section_data_5 = [
[
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
None,
],
(
utils.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
np.array(['verse A', 'verse B', 'verse A']),
),
'sections_2',
),
]
section_data_6 = [(None, None)]
section_data_7 = [
(
utils.EventData(
np.array([0.2, 0.3]),
np.array([0.3, 0.4]),
np.array(['event A', 'event B']),
),
None,
)
]
jam_1 = jams_utils.jams_converter(section_data=section_data_1)
jam_2 = jams_utils.jams_converter(section_data=section_data_2)
jam_3 = jams_utils.jams_converter(section_data=section_data_3)
jam_6 = jams_utils.jams_converter(section_data=section_data_6)
time, duration, value, confidence = get_jam_data(jam_1, 'segment', 0)
assert time == [0.0, 10.0, 20.0]
assert duration == [10.0, 10.0, 5.0]
assert value == ['verse A', 'verse B', 'verse A']
assert confidence == [None, None, None]
assert jam_2.annotations[0]['sandbox']['name'] == 'sections_2'
time, duration, value, confidence = get_jam_data(jam_3, 'segment', 0)
assert time == [0.0, 10.0, 20.0]
assert duration == [10.0, 10.0, 5.0]
assert value == ['verse A', 'verse B', 'verse A']
assert confidence == [None, None, None]
time, duration, value, confidence = get_jam_data(jam_3, 'segment', 1)
assert time == [0.0, 15.0, 20.0]
assert duration == [15.0, 5.0, 10.0]
assert value == ['verse A', 'verse B', 'verse C']
assert confidence == [None, None, None]
time, duration, value, confidence = get_jam_data(jam_6, 'segment', 0)
assert time == []
assert duration == []
assert value == []
assert confidence == []
assert type(jam_1) == jams.JAMS
with pytest.raises(TypeError):
jams_utils.jams_converter(section_data=section_data_4)
with pytest.raises(TypeError):
jams_utils.jams_converter(section_data=section_data_5)
with pytest.raises(TypeError):
jams_utils.jams_converter(section_data=section_data_7)
