def test_track():
default_trackid = "01-D_AMairena"
dataset = tonas.Dataset(TEST_DATA_HOME)
track = dataset.track(default_trackid)
expected_attributes = {
"singer": "En el barrio de Triana",
"style": "Debla",
"title": "Antonio Mairena",
"tuning_frequency": 451.0654725341684,
"f0_path":
"tests/resources/mir_datasets/tonas/Deblas/01-D_AMairena.f0.Corrected",
"notes_path":
"tests/resources/mir_datasets/tonas/Deblas/01-D_AMairena.notes.Corrected",
"audio_path":
"tests/resources/mir_datasets/tonas/Deblas/01-D_AMairena.wav",
"track_id": "01-D_AMairena",
}
expected_property_types = {
"f0": tonas.F0Data,
"notes": tonas.NoteData,
"audio": tuple,
"singer": str,
"style": str,
"title": str,
"tuning_frequency": float,
}
run_track_tests(track, expected_attributes, expected_property_types)
def test_load_melody():
default_trackid = "01-D_AMairena"
dataset = tonas.Dataset(TEST_DATA_HOME)
track = dataset.track(default_trackid)
f0_path = track.f0_path
f0_data = tonas.load_f0(f0_path)
# check types
assert type(f0_data) == tonas.F0Data
assert type(f0_data.times) is np.ndarray
assert type(f0_data.automatic_frequencies) is np.ndarray
assert type(f0_data.frequencies) is np.ndarray
assert type(f0_data.energies) is np.ndarray
assert type(f0_data.confidence) is np.ndarray
# check values
assert np.array_equal(
f0_data.times,
np.array([0.197, 0.209, 0.221, 0.232]),
)
assert np.array_equal(
f0_data.automatic_frequencies,
np.array([
0.000,
0.000,
143.918,
143.918,
]),
)
assert np.array_equal(f0_data.frequencies,
np.array([0.000, 379.299, 379.299, 379.299]))
assert np.array_equal(
f0_data.energies,
np.array([0.00000309, 0.00000286, 0.00000715, 0.00001545]))
assert np.array_equal(f0_data.confidence, np.array([0.0, 1.0, 1.0, 1.0]))
def test_load_audio():
default_trackid = "01-D_AMairena"
dataset = tonas.Dataset(TEST_DATA_HOME)
track = dataset.track(default_trackid)
audio_path = track.audio_path
audio, sr = tonas.load_audio(audio_path)
assert sr == 44100
assert type(audio) is np.ndarray
def test_to_jams():
default_trackid = "01-D_AMairena"
dataset = tonas.Dataset(TEST_DATA_HOME)
track = dataset.track(default_trackid)
jam = track.to_jams()
# Validate cante100 jam schema
assert jam.validate()
# Validate melody
f0 = jam.search(namespace="pitch_contour")[0]["data"]
assert [note.time for note in f0] == [0.197, 0.209, 0.221, 0.232]
assert [note.duration for note in f0] == [0.0, 0.0, 0.0, 0.0]
assert [note.value for note in f0] == [
{
"index": 0,
"frequency": 0.0,
"voiced": False
},
{
"index": 0,
"frequency": 379.299,
"voiced": True
},
{
"index": 0,
"frequency": 379.299,
"voiced": True
},
{
"index": 0,
"frequency": 379.299,
"voiced": True
},
]
assert [note.confidence for note in f0] == [0.0, 1.0, 1.0, 1.0]
# Validate note transciption
notes = jam.search(namespace="note_hz")[0]["data"]
assert [note.time for note in notes] == [
0.216667,
0.65,
2.183333,
2.566667,
]
assert [note.duration for note in notes] == [
0.433333,
1.016667,
0.3833329999999999,
0.3333330000000001,
]
assert [note.value for note in notes] == [
388.8382625732775,
411.9597888711769,
388.8382625732775,
411.9597888711769,
]
assert [note.confidence for note in notes] == [None, None, None, None]
def test_metadata():
default_trackid = "01-D_AMairena"
dataset = tonas.Dataset(TEST_DATA_HOME)
metadata = dataset._metadata
assert metadata[default_trackid] == {
"title": "En el barrio de Triana",
"style": "Debla",
"singer": "Antonio Mairena",
}
def test_load_notes():
default_trackid = "01-D_AMairena"
dataset = tonas.Dataset(TEST_DATA_HOME)
track = dataset.track(default_trackid)
notes_path = track.notes_path
notes_data = tonas.load_notes(notes_path)
tuning_frequency = tonas._load_tuning_frequency(notes_path)
# check types
assert type(notes_data) == tonas.NoteData
assert type(notes_data.intervals) is np.ndarray
assert type(notes_data.notes) is np.ndarray
assert type(notes_data.energies) is np.ndarray
assert type(notes_data.confidence) is np.ndarray
assert type(tuning_frequency) is float
# check tuning frequency
assert tuning_frequency == 451.0654725341684
# check values
assert np.array_equal(notes_data.intervals[:, 0],
np.array([0.216667, 0.65, 2.183333, 2.566667]))
assert np.array_equal(notes_data.intervals[:, 1],
np.array([0.65, 1.666667, 2.566666, 2.9]))
assert np.array_equal(
notes_data.energies,
np.array([
0.018007,
0.010794,
0.00698,
0.03265,
]),
)
assert np.array_equal(
notes_data.notes,
np.array([
388.8382625732775, 411.9597888711769, 388.8382625732775,
411.9597888711769
]),
)
assert np.array_equal(notes_data.confidence, np.array([1.0, 1.0, 1.0,
1.0]))