def test_section_data():
intervals = np.array([[1.0, 2.0], [1.5, 3.0], [2.0, 3.0]])
labels = ["a", "b", "c"]
section_data = annotations.SectionData(intervals)
assert np.allclose(section_data.intervals, intervals)
assert section_data.labels is None
section_data2 = annotations.SectionData(intervals, labels)
assert np.allclose(section_data2.intervals, intervals)
assert section_data2.labels == labels
with pytest.raises(ValueError):
annotations.SectionData(None, None)
with pytest.raises(TypeError):
annotations.SectionData([1.0, 2.0])
with pytest.raises(TypeError):
annotations.SectionData(intervals, np.array(labels))
with pytest.raises(TypeError):
annotations.SectionData(intervals.astype(int))
with pytest.raises(ValueError):
annotations.SectionData(intervals, ["a"])
with pytest.raises(ValueError):
annotations.SectionData(np.array([1.0, 2.0, 3.0]))
with pytest.raises(ValueError):
annotations.SectionData(np.array([[1.0, 2.0], [2.0, 1.0]]))
def load_sections(sections_path):
"""Load salami sections data from a file
Args:
sections_path (str): path to sectin annotation file
Returns:
SectionData: 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))
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 annotations.SectionData(
np.array([times_revised[:-1], times_revised[1:]]).T,
list(secs_revised[:-1]))
def load_sections(sections_path):
"""Load Beatles format section data from a file
Args:
sections_path (str): path to section annotation file
Returns:
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 = annotations.SectionData(
np.array([start_times, end_times]).T, sections)
return section_data
def load_sections(sections_path):
"""Load rwc section data from a file
Args:
sections_path (str): path to sections annotation file
Returns:
SectionData: section data
"""
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])
if not begs: # some files are empty
return None
return annotations.SectionData(np.array([begs, ends]).T, secs)
def load_sections(sections_path):
"""Load tracks sections
Args:
sections_path (str): Local path where the section annotation is stored.
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 = []
with open(sections_path, "r") as fhandle:
reader = csv.reader(fhandle, delimiter=",")
for line in reader:
if line:
intervals.append([
float(line[0]),
float(line[0]) + float(line[2]),
])
section_labels.append(str(line[3]) + "-" + str(line[1]))
# Return None if sections file is empty
if not intervals:
return None
return annotations.SectionData(np.array(intervals), section_labels)
def load_sections(fhandle: TextIO) -> annotations.SectionData:
"""Load salami sections data from a file
Args:
fhandle (str or file-like): File-like object or path to sectin annotation file
Returns:
SectionData: section data
"""
times = []
secs = []
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 annotations.SectionData(
np.array([times_revised[:-1], times_revised[1:]]).T,
list(secs_revised[:-1]))
def load_sections(fhandle: TextIO) -> annotations.SectionData:
"""Load Beatles format section data from a file
Args:
fhandle (str or file-like): path or file-like object pointing to a section annotation file
Returns:
SectionData: loaded section data
"""
start_times, end_times, sections = [], [], []
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])
return annotations.SectionData(
np.array([start_times, end_times]).T, sections)
def load_sections(fhandle: TextIO) -> Optional[annotations.SectionData]:
"""Load rwc section data from a file
Args:
fhandle (str or file-like): File-like object or path to sections annotation file
Returns:
SectionData: section data
"""
begs = [] # timestamps of section beginnings
ends = [] # timestamps of section endings
secs = [] # section labels
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])
if not begs: # some files are empty
return None
return annotations.SectionData(np.array([begs, ends]).T, secs)
def _load_sections(fpath: str, section_type: str):
timed_sections = _parse_timed_sections(fpath)
assert timed_sections is not None
# Clean sections
timed_sections_clean = [
ts for ts in timed_sections if ts["section"] is not None
]
start_times = []
end_times = []
sections = []
if section_type == "letter":
section_label_idx = 0
elif section_type == "name":
section_label_idx = 1
else:
raise ValueError("This section type is not available.")
for idx, ts in enumerate(timed_sections_clean):
if idx < len(timed_sections_clean) - 1:
start_times.append(timed_sections_clean[idx]["time"])
end_times.append(timed_sections_clean[idx + 1]["time"])
sections.append(
timed_sections_clean[idx]["section"][section_label_idx])
else:
start_times.append(timed_sections_clean[idx]["time"])
end_times.append(timed_sections[-1]["time"]) # end of song
sections.append(
timed_sections_clean[idx]["section"][section_label_idx])
section_data = annotations.SectionData(
np.array([start_times, end_times]).T, sections)
return section_data
def test_multi_sections():
multi_section_data_1 = [
(
[
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
None,
),
],
None,
)
]
multi_section_data_2 = [
(
[
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
0,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
1,
),
],
"annotator_1",
)
]
multi_section_data_3 = [
(
[
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
0,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
1,
),
],
"annotator_1",
),
(
[
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
0,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
1,
),
],
"annotator_2",
),
]
multi_section_data_4 = (
[
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
None,
),
],
None,
)
multi_section_data_5 = [
[
[
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
None,
),
],
None,
]
]
multi_section_data_6 = [
(
(
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 25.0]]).T,
["verse a", "verse b", "verse a"],
),
None,
),
),
None,
)
]
multi_section_data_7 = [([(None, None), (None, None)], None)]
multi_section_data_8 = [
(
[
(
annotations.EventData(
np.array([[0.2, 0.3], [0.3, 0.4]]).T,
["event A", "event B"],
),
None,
),
(
annotations.EventData(
np.array([[0.2, 0.3], [0.3, 0.4]]).T,
["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 = [
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
)
]
section_data_2 = [
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
"sections_2",
)
]
section_data_3 = [
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
"sections_1",
),
(
annotations.SectionData(
np.array([[0.0, 15.0, 20.0], [15.0, 20.0, 30.0]]).T,
["verse A", "verse B", "verse C"],
),
"sections_2",
),
]
section_data_4 = (
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
)
section_data_5 = [
[
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
None,
],
(
annotations.SectionData(
np.array([[0.0, 10.0, 20.0], [10.0, 20.0, 25.0]]).T,
["verse A", "verse B", "verse A"],
),
"sections_2",
),
]
section_data_6 = [(None, None)]
section_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(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)
