def test_track():
default_trackid = 'AClassicEducation_NightOwl_STEM_08'
data_home = 'tests/resources/mir_datasets/MedleyDB-Pitch'
track = medleydb_pitch.Track(default_trackid, data_home=data_home)
expected_attributes = {
'track_id': 'AClassicEducation_NightOwl_STEM_08',
'audio_path': 'tests/resources/mir_datasets/' +
'MedleyDB-Pitch/audio/AClassicEducation_NightOwl_STEM_08.wav',
'pitch_path': 'tests/resources/mir_datasets/' +
'MedleyDB-Pitch/pitch/AClassicEducation_NightOwl_STEM_08.csv',
'instrument': 'male singer',
'artist': 'AClassicEducation',
'title': 'NightOwl',
'genre': 'Singer/Songwriter'
}
expected_property_types = {
'pitch': utils.F0Data,
}
run_track_tests(track, expected_attributes, expected_property_types)
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2, )
def test_track():
default_trackid = "1"
data_home = "tests/resources/mir_datasets/beatport_key"
dataset = beatport_key.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"audio_path": "tests/resources/mir_datasets/beatport_key/audio/100066 Lindstrom - Monsteer (Original Mix).mp3",
"keys_path": "tests/resources/mir_datasets/beatport_key/keys/100066 Lindstrom - Monsteer (Original Mix).txt",
"metadata_path": "tests/resources/mir_datasets/beatport_key/meta/100066 Lindstrom - Monsteer (Original Mix).json",
"title": "100066 Lindstrom - Monsteer (Original Mix)",
"track_id": "1",
}
expected_property_types = {
"key": list,
"genres": dict,
"artists": list,
"tempo": int,
"audio": tuple,
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 44100, "sample rate {} is not 44100".format(sr)
assert audio.shape == (88200,), "audio shape {} was not (88200,)".format(
audio.shape
)
def test_track():
default_trackid = "RM-J004"
data_home = "tests/resources/mir_datasets/rwc_jazz"
track = rwc_jazz.Track(default_trackid, data_home=data_home)
expected_attributes = {
"track_id": "RM-J004",
"audio_path": "tests/resources/mir_datasets/rwc_jazz/"
+ "audio/rwc-j-m01/4.wav",
"sections_path": "tests/resources/mir_datasets/rwc_jazz/"
+ "annotations/AIST.RWC-MDB-J-2001.CHORUS/RM-J004.CHORUS.TXT",
"beats_path": "tests/resources/mir_datasets/rwc_jazz/"
+ "annotations/AIST.RWC-MDB-J-2001.BEAT/RM-J004.BEAT.TXT",
"piece_number": "No. 4",
"suffix": "M01",
"track_number": "Tr. 04",
"title": "Crescent Serenade (Piano Solo)",
"artist": "Makoto Nakamura",
"duration": 167,
"variation": "Instrumentation 1",
"instruments": "Pf",
}
expected_property_types = {"beats": utils.BeatData, "sections": utils.SectionData}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2,)
def test_track():
default_trackid = '113'
data_home = 'tests/resources/mir_datasets/GiantSteps_tempo'
track = giantsteps_tempo.Track(default_trackid, data_home=data_home)
expected_attributes = {
'audio_path':
'tests/resources/mir_datasets/GiantSteps_tempo/audio/28952.LOFI.mp3',
'annotation_v1_path':
'tests/resources/mir_datasets/GiantSteps_tempo/giantsteps-tempo-dataset'
'-0b7d47ba8cae59d3535a02e3db69e2cf6d0af5bb/annotations/jams/28952.LOFI.jams',
'annotation_v2_path':
'tests/resources/mir_datasets/GiantSteps_tempo/giantsteps-tempo-dataset'
'-0b7d47ba8cae59d3535a02e3db69e2cf6d0af5bb/annotations_v2/jams/28952.LOFI.jams',
'title':
'28952',
'track_id':
'113',
}
expected_property_types = {
'tempo': utils.TempoData,
'tempo_v2': utils.TempoData,
'genre': str
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 22050, 'sample rate {} is not 22050'.format(sr)
print(audio.shape)
assert audio.shape == (
2646720, ), 'audio shape {} was not (2646720,)'.format(audio.shape)
def test_track():
default_trackid = "0"
data_home = "tests/resources/mir_datasets/queen"
dataset = queen.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"audio_path":
"tests/resources/mir_datasets/queen/audio/Greatest Hits I/01 Bohemian Rhapsody.flac",
"chords_path": "tests/resources/mir_datasets/queen/"
"annotations/chordlab/Queen/Greatest Hits I/01 Bohemian Rhapsody.lab",
"keys_path": "tests/resources/mir_datasets/queen/" +
"annotations/keylab/Queen/Greatest Hits I/01 Bohemian Rhapsody.lab",
"sections_path": "tests/resources/mir_datasets/queen/" +
"annotations/seglab/Queen/Greatest Hits I/01 Bohemian Rhapsody.lab",
"title": "01 Bohemian Rhapsody",
"track_id": "0",
}
expected_property_types = {
"chords": annotations.ChordData,
"key": annotations.KeyData,
"sections": annotations.SectionData,
"audio": tuple,
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 44100, "sample rate {} is not 44100".format(sr)
assert audio.shape == (
144384, ), "audio shape {} was not (144384,)".format(audio.shape)
def test_track():
default_trackid = '008'
track = cante100.Track(default_trackid, data_home=TEST_DATA_HOME)
expected_attributes = {
'artist':
'Toronjo',
'duration':
179.0,
'audio_path':
'tests/resources/mir_datasets/cante100/cante100audio/008_PacoToronjo_'
+ 'Fandangos.mp3',
'f0_path':
'tests/resources/mir_datasets/cante100/cante100midi_f0/008_PacoToronjo_'
+ 'Fandangos.f0.csv',
'identifier':
'4eebe839-82bb-426e-914d-7c4525dd9dad',
'notes_path':
'tests/resources/mir_datasets/cante100/cante100_automaticTranscription/008_PacoToronjo_'
+ 'Fandangos.notes.csv',
'release':
'Atlas del cante flamenco',
'spectrogram_path':
'tests/resources/mir_datasets/cante100/cante100_spectrum/008_PacoToronjo_'
+ 'Fandangos.spectrum.csv',
'title':
'Huelva Como Capital',
'track_id':
'008',
}
expected_property_types = {'melody': utils.F0Data, 'notes': utils.NoteData}
run_track_tests(track, expected_attributes, expected_property_types)
def test_track():
default_trackid = 'Fl-ord-C4-mf-N-T14d'
data_home = 'tests/resources/mir_datasets/TinySOL'
track = tinysol.Track(default_trackid, data_home=data_home)
expected_attributes = {
'track_id': 'Fl-ord-C4-mf-N-T14d',
'audio_path': 'tests/resources/mir_datasets/TinySOL/' +
'audio/Winds/Flute/ordinario/Fl-ord-C4-mf-N-T14d.wav',
'dynamics': 'mf',
'fold': 0,
'family': 'Winds',
'instrument_abbr': 'Fl',
'instrument_full': 'Flute',
'technique_abbr': 'ord',
'technique_full': 'ordinario',
'pitch': 'C4',
'pitch_id': 60,
'dynamics_id': 2,
'instance_id': 0,
'is_resampled': True,
'string_id': None,
}
expected_property_types = {}
run_track_tests(track, expected_attributes, expected_property_types)
y, sr = track.audio
assert y.shape == (272417, )
assert sr == 44100
# test with a string instrument
track = tinysol.Track('Cb-ord-A2-mf-2c-N', data_home=data_home)
def test_track():
default_trackid = 'MusicDelta_Beethoven'
data_home = 'tests/resources/mir_datasets/MedleyDB-Melody'
track = medleydb_melody.Track(default_trackid, data_home=data_home)
expected_attributes = {
'track_id': 'MusicDelta_Beethoven',
'audio_path': 'tests/resources/mir_datasets/' +
'MedleyDB-Melody/audio/MusicDelta_Beethoven_MIX.wav',
'melody1_path': 'tests/resources/mir_datasets/' +
'MedleyDB-Melody/melody1/MusicDelta_Beethoven_MELODY1.csv',
'melody2_path': 'tests/resources/mir_datasets/' +
'MedleyDB-Melody/melody2/MusicDelta_Beethoven_MELODY2.csv',
'melody3_path': 'tests/resources/mir_datasets/' +
'MedleyDB-Melody/melody3/MusicDelta_Beethoven_MELODY3.csv',
'artist': 'MusicDelta',
'title': 'Beethoven',
'genre': 'Classical',
'is_excerpt': True,
'is_instrumental': True,
'n_sources': 18,
}
expected_property_types = {
'melody1': utils.F0Data,
'melody2': utils.F0Data,
'melody3': utils.MultipitchData,
}
run_track_tests(track, expected_attributes, expected_property_types)
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2, )
def test_track():
default_trackid = "some_id"
data_home = "tests/resources/mir_datasets/dataset"
dataset = example.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"track_id":
"some_id",
"audio_path":
"tests/resources/mir_datasets/example/" + "Wavfile/some_id.wav",
"song_id":
"some_id",
"annotation_path":
"tests/resources/mir_datasets/example/annotation/some_id.pv",
}
expected_property_types = {"annotation": annotations.XData}
assert track._track_paths == {
"audio": ["Wavfile/some_id.wav", "278ae003cb0d323e99b9a643c0f2eeda"],
"annotation":
["Annotation/some_id.pv", "0d93a011a9e668fd80673049089bbb14"],
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
audio, sr = track.audio
assert sr == 44100
assert audio.shape == (44100 * 2, )
def test_track():
default_trackid = "Fl-ord-C4-mf-N-T14d"
data_home = "tests/resources/mir_datasets/tinysol"
track = tinysol.Track(default_trackid, data_home=data_home)
expected_attributes = {
"track_id": "Fl-ord-C4-mf-N-T14d",
"audio_path": "tests/resources/mir_datasets/tinysol/" +
"audio/Winds/Flute/ordinario/Fl-ord-C4-mf-N-T14d.wav",
"dynamics": "mf",
"fold": 0,
"family": "Winds",
"instrument_abbr": "Fl",
"instrument_full": "Flute",
"technique_abbr": "ord",
"technique_full": "ordinario",
"pitch": "C4",
"pitch_id": 60,
"dynamics_id": 2,
"instance_id": 0,
"is_resampled": True,
"string_id": None,
}
expected_property_types = {}
run_track_tests(track, expected_attributes, expected_property_types)
y, sr = track.audio
assert y.shape == (272417, )
assert sr == 44100
# test with a string instrument
track = tinysol.Track("Cb-ord-A2-mf-2c-N", data_home=data_home)
def test_track():
default_trackid = "0"
data_home = "tests/resources/mir_datasets/tonality_classicaldb"
dataset = tonality_classicaldb.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"audio_path":
"tests/resources/mir_datasets/tonality_classicaldb/audio/01-Allegro__Gloria_in_excelsis_Deo_in_D_Major - D.wav",
"key_path":
"tests/resources/mir_datasets/tonality_classicaldb/keys/01-Allegro__Gloria_in_excelsis_Deo_in_D_Major - D.txt",
"spectrum_path":
"tests/resources/mir_datasets/tonality_classicaldb/spectrums/01-Allegro__Gloria_in_excelsis_Deo_in_D_Major - D.json",
"hpcp_path":
"tests/resources/mir_datasets/tonality_classicaldb/HPCPs/01-Allegro__Gloria_in_excelsis_Deo_in_D_Major - D.json",
"musicbrainz_path":
"tests/resources/mir_datasets/tonality_classicaldb/musicbrainz_metadata/01-Allegro__Gloria_in_excelsis_Deo_in_D_Major - D.json",
"title": "01-Allegro__Gloria_in_excelsis_Deo_in_D_Major - D",
"track_id": "0",
}
expected_property_types = {
"key": str,
"spectrum": np.ndarray,
"hpcp": np.ndarray,
"musicbrainz_metadata": dict,
"audio": tuple,
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 44100, "sample rate {} is not 44100".format(sr)
assert audio.shape == (88200, ), "audio shape {} was not (88200,)".format(
audio.shape)
def test_track():
default_trackid = "3"
data_home = "tests/resources/mir_datasets/giantsteps_key"
dataset = giantsteps_key.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"audio_path": "tests/resources/mir_datasets/giantsteps_key/audio/10089 Jason Sparks - Close My Eyes feat. J. "
"Little (Original Mix).mp3",
"keys_path": "tests/resources/mir_datasets/giantsteps_key/keys_gs+/10089 Jason Sparks - Close My Eyes feat. J. "
"Little (Original Mix).txt",
"metadata_path": "tests/resources/mir_datasets/giantsteps_key/meta/10089 Jason Sparks - Close My Eyes feat. J. "
"Little (Original Mix).json",
"title": "10089 Jason Sparks - Close My Eyes feat. J. Little (Original Mix)",
"track_id": "3",
}
expected_property_types = {
"key": str,
"genres": dict,
"artists": list,
"tempo": int,
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 44100, "sample rate {} is not 44100".format(sr)
assert audio.shape == (88200,), "audio shape {} was not (88200,)".format(
audio.shape
)
def test_track():
default_trackid = "AClassicEducation_NightOwl_STEM_08"
data_home = "tests/resources/mir_datasets/medleydb_pitch"
dataset = medleydb_pitch.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"track_id": "AClassicEducation_NightOwl_STEM_08",
"audio_path": "tests/resources/mir_datasets/"
+ "medleydb_pitch/audio/AClassicEducation_NightOwl_STEM_08.wav",
"pitch_path": "tests/resources/mir_datasets/"
+ "medleydb_pitch/pitch/AClassicEducation_NightOwl_STEM_08.csv",
"instrument": "male singer",
"artist": "AClassicEducation",
"title": "NightOwl",
"genre": "Singer/Songwriter",
}
expected_property_types = {"pitch": annotations.F0Data}
run_track_tests(track, expected_attributes, expected_property_types)
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2,)
def test_track():
default_trackid = '3'
data_home = 'tests/resources/mir_datasets/GiantSteps_key'
track = giantsteps_key.Track(default_trackid, data_home=data_home)
expected_attributes = {
'audio_path':
'tests/resources/mir_datasets/GiantSteps_key/audio/10089 Jason Sparks - Close My Eyes feat. J. '
'Little (Original Mix).mp3',
'keys_path':
'tests/resources/mir_datasets/GiantSteps_key/keys_gs+/10089 Jason Sparks - Close My Eyes feat. J. '
'Little (Original Mix).txt',
'metadata_path':
'tests/resources/mir_datasets/GiantSteps_key/meta/10089 Jason Sparks - Close My Eyes feat. J. '
'Little (Original Mix).json',
'title':
'10089 Jason Sparks - Close My Eyes feat. J. Little (Original Mix)',
'track_id':
'3',
}
expected_property_types = {
'key': str,
'genres': dict,
'artists': list,
'tempo': int
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 44100, 'sample rate {} is not 44100'.format(sr)
assert audio.shape == (
5294592, ), 'audio shape {} was not (5294592,)'.format(audio.shape)
def test_track():
default_trackid = "tagtraum#validation#be9e01e5-8f93-494d-bbaa-ddcc5a52f629#2b6bfcfd-46a5-3f98-a58f-2c51d7c9e960#trance########"
data_home = "tests/resources/mir_datasets/acousticbrainz_genre"
dataset = acousticbrainz_genre.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"path":
"tests/resources/mir_datasets/acousticbrainz_genre/acousticbrainz-mediaeval-validation/be/be9e01e5-8f93-494d-bbaa-ddcc5a52f629.json",
"track_id":
"tagtraum#validation#be9e01e5-8f93-494d-bbaa-ddcc5a52f629#2b6bfcfd-46a5-3f98-a58f-2c51d7c9e960#trance########",
"genre": ["trance"],
"mbid": "be9e01e5-8f93-494d-bbaa-ddcc5a52f629",
"mbid_group": "2b6bfcfd-46a5-3f98-a58f-2c51d7c9e960",
"split": "validation",
}
expected_property_types = {
"artist": list,
"title": list,
"date": list,
"file_name": str,
"album": list,
"tracknumber": list,
"tonal": dict,
"low_level": dict,
"rhythm": dict,
"acousticbrainz_metadata": dict,
}
run_track_tests(track, expected_attributes, expected_property_types)
def test_track():
default_trackid = 'RM-J004'
data_home = 'tests/resources/mir_datasets/RWC-Jazz'
track = rwc_jazz.Track(default_trackid, data_home=data_home)
expected_attributes = {
'track_id': 'RM-J004',
'audio_path':
'tests/resources/mir_datasets/RWC-Jazz/' + 'audio/rwc-j-m01/4.wav',
'sections_path': 'tests/resources/mir_datasets/RWC-Jazz/' +
'annotations/AIST.RWC-MDB-J-2001.CHORUS/RM-J004.CHORUS.TXT',
'beats_path': 'tests/resources/mir_datasets/RWC-Jazz/' +
'annotations/AIST.RWC-MDB-J-2001.BEAT/RM-J004.BEAT.TXT',
'piece_number': 'No. 4',
'suffix': 'M01',
'track_number': 'Tr. 04',
'title': 'Crescent Serenade (Piano Solo)',
'artist': 'Makoto Nakamura',
'duration': 167,
'variation': 'Instrumentation 1',
'instruments': 'Pf',
}
expected_property_types = {
'beats': utils.BeatData,
'sections': utils.SectionData
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2, )
def test_track():
default_trackid = "59_Bairagi"
data_home = "tests/resources/mir_datasets/saraga_hindustani"
dataset = saraga_hindustani.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"track_id":
"59_Bairagi",
"title":
"Bairagi",
"audio_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+ "Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.mp3.mp3",
"ctonic_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+
"Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.ctonic.txt",
"pitch_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+ "Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.pitch.txt",
"tempo_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+
"Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.tempo-manual.txt",
"sama_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+
"Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.sama-manual.txt",
"sections_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+
"Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.sections-manual-p.txt",
"phrases_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+
"Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.mphrases-manual.txt",
"metadata_path":
"tests/resources/mir_datasets/saraga_hindustani/saraga1.5_hindustani/"
+ "Geetinandan : Part-3 by Ajoy Chakrabarty/Bairagi/Bairagi.json",
}
expected_property_types = {
"tempo": dict,
"phrases": annotations.EventData,
"pitch": annotations.F0Data,
"sama": annotations.BeatData,
"sections": annotations.SectionData,
"tonic": float,
"metadata": dict,
"audio": tuple,
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
audio, sr = track.audio
assert sr == 44100
assert audio.shape[0] == 2
def test_track():
default_trackid = "RM-C003"
data_home = "tests/resources/mir_datasets/rwc_classical"
dataset = rwc_classical.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"track_id": "RM-C003",
"audio_path": "tests/resources/mir_datasets/rwc_classical/" +
"audio/rwc-c-m01/3.wav",
"sections_path": "tests/resources/mir_datasets/rwc_classical/" +
"annotations/AIST.RWC-MDB-C-2001.CHORUS/RM-C003.CHORUS.TXT",
"beats_path": "tests/resources/mir_datasets/rwc_classical/" +
"annotations/AIST.RWC-MDB-C-2001.BEAT/RM-C003.BEAT.TXT",
"piece_number": "No. 3",
"suffix": "M01",
"track_number": "Tr. 03",
"title": "Symphony no.5 in C minor, op.67. 1st mvmt.",
"composer": "Beethoven, Ludwig van",
"artist": "Tokyo City Philharmonic Orchestra",
"duration": 435,
"category": "Symphony",
}
expected_property_types = {
"beats": annotations.BeatData,
"sections": annotations.SectionData,
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2, )
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_track():
default_trackid = "MusicDelta_Beethoven"
data_home = "tests/resources/mir_datasets/medleydb_melody"
track = medleydb_melody.Track(default_trackid, data_home=data_home)
expected_attributes = {
"track_id": "MusicDelta_Beethoven",
"audio_path": "tests/resources/mir_datasets/" +
"medleydb_melody/audio/MusicDelta_Beethoven_MIX.wav",
"melody1_path": "tests/resources/mir_datasets/" +
"medleydb_melody/melody1/MusicDelta_Beethoven_MELODY1.csv",
"melody2_path": "tests/resources/mir_datasets/" +
"medleydb_melody/melody2/MusicDelta_Beethoven_MELODY2.csv",
"melody3_path": "tests/resources/mir_datasets/" +
"medleydb_melody/melody3/MusicDelta_Beethoven_MELODY3.csv",
"artist": "MusicDelta",
"title": "Beethoven",
"genre": "Classical",
"is_excerpt": True,
"is_instrumental": True,
"n_sources": 18,
}
expected_property_types = {
"melody1": utils.F0Data,
"melody2": utils.F0Data,
"melody3": utils.MultipitchData,
}
run_track_tests(track, expected_attributes, expected_property_types)
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2, )
def test_track():
default_trackid = 'RM-C003'
data_home = 'tests/resources/mir_datasets/RWC-Classical'
track = rwc_classical.Track(default_trackid, data_home=data_home)
expected_attributes = {
'track_id': 'RM-C003',
'audio_path': 'tests/resources/mir_datasets/RWC-Classical/' +
'audio/rwc-c-m01/3.wav',
'sections_path': 'tests/resources/mir_datasets/RWC-Classical/' +
'annotations/AIST.RWC-MDB-C-2001.CHORUS/RM-C003.CHORUS.TXT',
'beats_path': 'tests/resources/mir_datasets/RWC-Classical/' +
'annotations/AIST.RWC-MDB-C-2001.BEAT/RM-C003.BEAT.TXT',
'piece_number': 'No. 3',
'suffix': 'M01',
'track_number': 'Tr. 03',
'title': 'Symphony no.5 in C minor, op.67. 1st mvmt.',
'composer': 'Beethoven, Ludwig van',
'artist': 'Tokyo City Philharmonic Orchestra',
'duration': 435,
'category': 'Symphony',
}
expected_property_types = {
'beats': utils.BeatData,
'sections': utils.SectionData
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
y, sr = track.audio
assert sr == 44100
assert y.shape == (44100 * 2, )
def test_track():
default_trackid = "113"
data_home = "tests/resources/mir_datasets/giantsteps_tempo"
dataset = giantsteps_tempo.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"audio_path":
"tests/resources/mir_datasets/giantsteps_tempo/audio/28952.LOFI.mp3",
"annotation_v1_path":
"tests/resources/mir_datasets/giantsteps_tempo/giantsteps-tempo-dataset"
"-0b7d47ba8cae59d3535a02e3db69e2cf6d0af5bb/annotations/jams/28952.LOFI.jams",
"annotation_v2_path":
"tests/resources/mir_datasets/giantsteps_tempo/giantsteps-tempo-dataset"
"-0b7d47ba8cae59d3535a02e3db69e2cf6d0af5bb/annotations_v2/jams/28952.LOFI.jams",
"title":
"28952",
"track_id":
"113",
}
expected_property_types = {
"tempo": annotations.TempoData,
"tempo_v2": annotations.TempoData,
"genre": str,
}
run_track_tests(track, expected_attributes, expected_property_types)
audio, sr = track.audio
assert sr == 22050, "sample rate {} is not 22050".format(sr)
print(audio.shape)
def test_track():
default_trackid = 'drummer1/eval_session/1'
data_home = 'tests/resources/mir_datasets/Groove MIDI'
track = groove_midi.Track(default_trackid, data_home=data_home)
expected_attributes = {
'drummer':
'drummer1',
'session':
'drummer1/eval_session',
'track_id':
'drummer1/eval_session/1',
'style':
'funk/groove1',
'bpm':
138,
'beat_type':
'beat',
'time_signature':
'4-4',
'midi_filename':
'drummer1/eval_session/1_funk-groove1_138_beat_4-4.mid',
'audio_filename':
'drummer1/eval_session/1_funk-groove1_138_beat_4-4.wav',
'midi_path':
os.path.join(data_home,
'drummer1/eval_session/1_funk-groove1_138_beat_4-4.mid'),
'audio_path':
os.path.join(data_home,
'drummer1/eval_session/1_funk-groove1_138_beat_4-4.wav'),
'duration':
27.872308,
'split':
'test',
}
assert track._track_paths == {
'audio': [
'drummer1/eval_session/1_funk-groove1_138_beat_4-4.wav',
'7f94a191506f70ac9d313b7978203c3c',
],
'midi': [
'drummer1/eval_session/1_funk-groove1_138_beat_4-4.mid',
'b01a609cee84cfbc2c154bb9b6566955',
],
}
run_track_tests(track, expected_attributes, {})
# test audio loading functions
audio, sr = track.audio
assert sr == 22050
assert audio.shape == (613566, )
# test midi loading functions
midi_data = track.midi
assert len(midi_data.instruments) == 1
assert len(midi_data.instruments[0].notes) == 410
assert midi_data.estimate_tempo() == 198.7695135305443
assert midi_data.get_piano_roll().shape == (128, 2787)
def test_track():
default_trackid = "10161_chorus"
data_home = "tests/resources/mir_datasets/ikala"
dataset = ikala.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"track_id":
"10161_chorus",
"audio_path":
"tests/resources/mir_datasets/ikala/" + "Wavfile/10161_chorus.wav",
"song_id":
"10161",
"section":
"chorus",
"singer_id":
"1",
"f0_path":
"tests/resources/mir_datasets/ikala/PitchLabel/10161_chorus.pv",
"lyrics_path":
"tests/resources/mir_datasets/ikala/Lyrics/10161_chorus.lab",
}
expected_property_types = {
"f0": annotations.F0Data,
"lyrics": annotations.LyricData,
"vocal_audio": tuple,
"instrumental_audio": tuple,
"mix_audio": tuple,
}
assert track._track_paths == {
"audio":
["Wavfile/10161_chorus.wav", "278ae003cb0d323e99b9a643c0f2eeda"],
"pitch":
["PitchLabel/10161_chorus.pv", "0d93a011a9e668fd80673049089bbb14"],
"lyrics":
["Lyrics/10161_chorus.lab", "79bbeb72b422056fd43be4e8d63319ce"],
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
vocal, sr_vocal = track.vocal_audio
assert sr_vocal == 44100
assert vocal.shape == (44100 * 2, )
instrumental, sr_instrumental = track.instrumental_audio
assert sr_instrumental == 44100
assert instrumental.shape == (44100 * 2, )
# make sure we loaded the correct channels to vocal/instrumental
# (in this example, the first quarter second has only instrumentals)
assert np.mean(np.abs(vocal[:8820])) < np.mean(np.abs(instrumental[:8820]))
mix, sr_mix = track.mix_audio
assert sr_mix == 44100
assert mix.shape == (44100 * 2, )
assert np.array_equal(mix, instrumental + vocal)
def test_multitrack():
default_trackid = "beethoven"
data_home = "tests/resources/mir_datasets/phenicx_anechoic"
dataset = phenicx_anechoic.Dataset(data_home)
mtrack = dataset.multitrack(default_trackid)
# import pdb;pdb.set_trace()
expected_attributes = {
"mtrack_id": "beethoven",
"track_audio_property": "audio",
"track_ids": [
"beethoven-horn",
"beethoven-doublebass",
"beethoven-violin",
"beethoven-bassoon",
"beethoven-flute",
"beethoven-clarinet",
"beethoven-viola",
"beethoven-oboe",
"beethoven-cello",
"beethoven-trumpet",
],
"instruments": {
"horn": "beethoven-horn",
"doublebass": "beethoven-doublebass",
"violin": "beethoven-violin",
"bassoon": "beethoven-bassoon",
"flute": "beethoven-flute",
"clarinet": "beethoven-clarinet",
"viola": "beethoven-viola",
"oboe": "beethoven-oboe",
"cello": "beethoven-cello",
"trumpet": "beethoven-trumpet",
},
"sections": {
"brass": ["beethoven-horn", "beethoven-trumpet"],
"strings": [
"beethoven-doublebass",
"beethoven-violin",
"beethoven-viola",
"beethoven-cello",
],
"woodwinds": [
"beethoven-bassoon",
"beethoven-flute",
"beethoven-clarinet",
"beethoven-oboe",
],
},
"piece": "beethoven",
}
expected_property_types = {
"tracks": dict,
"track_audio_property": str,
}
run_track_tests(mtrack, expected_attributes, expected_property_types)
run_multitrack_tests(mtrack)
def test_track():
default_trackid = "1"
default_trackid_train = "0189__2"
data_home = "tests/resources/mir_datasets/irmas"
dataset = irmas.Dataset(data_home)
track = dataset.track(default_trackid)
track_train = dataset.track(default_trackid_train)
expected_attributes = {
"annotation_path":
"tests/resources/mir_datasets/irmas/IRMAS-TestingData-Part1/Part1/" +
"02 - And The Body Will Die-8.txt",
"audio_path":
"tests/resources/mir_datasets/irmas/IRMAS-TestingData-Part1/Part1/" +
"02 - And The Body Will Die-8.wav",
"track_id":
"1",
"predominant_instrument":
None,
"genre":
None,
"drum":
None,
"train":
False,
}
expected_attributes_train = {
"annotation_path":
"tests/resources/mir_datasets/irmas/IRMAS-TrainingData/cla/" +
"[cla][cla]0189__2.wav",
"audio_path":
"tests/resources/mir_datasets/irmas/IRMAS-TrainingData/cla/" +
"[cla][cla]0189__2.wav",
"track_id":
"0189__2",
"predominant_instrument":
"cla",
"genre":
"cla",
"drum":
None,
"train":
True,
}
expected_property_test_types = {
"instrument": list,
"audio": tuple,
}
run_track_tests(track, expected_attributes, expected_property_test_types)
run_track_tests(track_train, expected_attributes_train,
expected_property_test_types)
audio, sr = track.audio
assert sr == 44100
assert len(audio) == 2
assert len(audio[1, :]) == 88200
def test_track():
default_trackid = "drummer1/eval_session/1"
data_home = "tests/resources/mir_datasets/groove_midi"
dataset = groove_midi.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"drummer": "drummer1",
"session": "drummer1/eval_session",
"track_id": "drummer1/eval_session/1",
"style": "funk/groove1",
"tempo": 138,
"beat_type": "beat",
"time_signature": "4-4",
"midi_filename": "drummer1/eval_session/1_funk-groove1_138_beat_4-4.mid",
"audio_filename": "drummer1/eval_session/1_funk-groove1_138_beat_4-4.wav",
"midi_path": os.path.join(
data_home, "drummer1/eval_session/1_funk-groove1_138_beat_4-4.mid"
),
"audio_path": os.path.join(
data_home, "drummer1/eval_session/1_funk-groove1_138_beat_4-4.wav"
),
"duration": 27.872308,
"split": "test",
}
expected_property_types = {
"beats": annotations.BeatData,
"drum_events": annotations.EventData,
"midi": pretty_midi.PrettyMIDI,
"audio": tuple,
}
assert track._track_paths == {
"audio": [
"drummer1/eval_session/1_funk-groove1_138_beat_4-4.wav",
"7f94a191506f70ac9d313b7978203c3c",
],
"midi": [
"drummer1/eval_session/1_funk-groove1_138_beat_4-4.mid",
"b01a609cee84cfbc2c154bb9b6566955",
],
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
audio, sr = track.audio
assert sr == 22050
assert audio.shape == (613566,)
# test midi loading functions
midi_data = track.midi
assert len(midi_data.instruments) == 1
assert len(midi_data.instruments[0].notes) == 410
assert midi_data.estimate_tempo() == 198.7695135305443
assert midi_data.get_piano_roll().shape == (128, 2787)
def test_track():
default_trackid = '10161_chorus'
data_home = 'tests/resources/mir_datasets/iKala'
track = ikala.Track(default_trackid, data_home=data_home)
expected_attributes = {
'track_id':
'10161_chorus',
'audio_path':
'tests/resources/mir_datasets/iKala/' + 'Wavfile/10161_chorus.wav',
'song_id':
'10161',
'section':
'chorus',
'singer_id':
'1',
'f0_path':
'tests/resources/mir_datasets/iKala/PitchLabel/10161_chorus.pv',
'lyrics_path':
'tests/resources/mir_datasets/iKala/Lyrics/10161_chorus.lab',
}
expected_property_types = {
'f0': utils.F0Data,
'lyrics': utils.LyricData,
}
assert track._track_paths == {
'audio':
['Wavfile/10161_chorus.wav', '278ae003cb0d323e99b9a643c0f2eeda'],
'pitch':
['PitchLabel/10161_chorus.pv', '0d93a011a9e668fd80673049089bbb14'],
'lyrics':
['Lyrics/10161_chorus.lab', '79bbeb72b422056fd43be4e8d63319ce'],
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
vocal, sr_vocal = track.vocal_audio
assert sr_vocal == 44100
assert vocal.shape == (44100 * 2, )
instrumental, sr_instrumental = track.instrumental_audio
assert sr_instrumental == 44100
assert instrumental.shape == (44100 * 2, )
# make sure we loaded the correct channels to vocal/instrumental
# (in this example, the first quarter second has only instrumentals)
assert np.mean(np.abs(vocal[:8820])) < np.mean(np.abs(instrumental[:8820]))
mix, sr_mix = track.mix_audio
assert sr_mix == 44100
assert mix.shape == (44100 * 2, )
assert np.array_equal(mix, instrumental + vocal)
def test_track():
default_trackid = '1'
default_trackid_train = '0189__2'
data_home = "tests/resources/mir_datasets/irmas"
track = irmas.Track(default_trackid, data_home=data_home)
track_train = irmas.Track(default_trackid_train, data_home=data_home)
expected_attributes = {
'annotation_path':
"tests/resources/mir_datasets/irmas/IRMAS-TestingData-Part1/Part1/" +
"02 - And The Body Will Die-8.txt",
'audio_path':
"tests/resources/mir_datasets/irmas/IRMAS-TestingData-Part1/Part1/" +
"02 - And The Body Will Die-8.wav",
'track_id':
'1',
'predominant_instrument':
None,
'genre':
None,
'drum':
None,
'train':
False
}
expected_attributes_train = {
'annotation_path':
"tests/resources/mir_datasets/irmas/IRMAS-TrainingData/cla/" +
"[cla][cla]0189__2.wav",
'audio_path':
"tests/resources/mir_datasets/irmas/IRMAS-TrainingData/cla/" +
"[cla][cla]0189__2.wav",
'track_id':
'0189__2',
'predominant_instrument':
'cla',
'genre':
'cla',
'drum':
None,
'train':
True
}
expected_property_test_types = {'instrument': list}
run_track_tests(track, expected_attributes, expected_property_test_types)
run_track_tests(track_train, expected_attributes_train,
expected_property_test_types)
audio, sr = track.audio
assert sr == 44100
assert len(audio) == 2
assert len(audio[1, :]) == 882000
def test_track():
default_trackid = "2018/MIDI-Unprocessed_Chamber3_MID--AUDIO_10_R3_2018_wav--1"
data_home = "tests/resources/mir_datasets/maestro"
dataset = maestro.Dataset(data_home)
track = dataset.track(default_trackid)
expected_attributes = {
"track_id":
"2018/MIDI-Unprocessed_Chamber3_MID--AUDIO_10_R3_2018_wav--1",
"midi_path":
os.path.join(
data_home,
"2018/MIDI-Unprocessed_Chamber3_MID--AUDIO_10_R3_2018_wav--1.midi",
),
"audio_path":
os.path.join(
data_home,
"2018/MIDI-Unprocessed_Chamber3_MID--AUDIO_10_R3_2018_wav--1.wav"),
"canonical_composer":
"Alban Berg",
"canonical_title":
"Sonata Op. 1",
"year":
2018,
"duration":
698.661160312,
"split":
"train",
}
expected_property_types = {
"notes": annotations.NoteData,
"midi": pretty_midi.PrettyMIDI,
"audio": tuple,
}
assert track._track_paths == {
"audio": [
"2018/MIDI-Unprocessed_Chamber3_MID--AUDIO_10_R3_2018_wav--1.wav",
"1694d8431f01eeb2a18444196550b99d",
],
"midi": [
"2018/MIDI-Unprocessed_Chamber3_MID--AUDIO_10_R3_2018_wav--1.midi",
"4901b1578ee4fe8c1696e02f60924949",
],
}
run_track_tests(track, expected_attributes, expected_property_types)
# test audio loading functions
audio, sr = track.audio
assert sr == 48000
assert audio.shape == (48000 * 2, )