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test_beat.py
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test_beat.py
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#!/usr/bin/env python
# CREATED:2013-03-11 18:14:30 by Brian McFee <brm2132@columbia.edu>
# unit tests for librosa.beat
from __future__ import print_function
from nose.tools import nottest, raises, eq_
# Disable cache
import os
try:
os.environ.pop('LIBROSA_CACHE_DIR')
except:
pass
import matplotlib
matplotlib.use('Agg')
import numpy as np
import librosa
from test_core import files, load
__EXAMPLE_FILE = 'data/test1_22050.wav'
def test_onset_strength():
def __test(infile):
DATA = load(infile)
# Compute onset envelope using the same spectrogram
onsets = librosa.onset.onset_strength(y=None,
sr=8000,
S=DATA['D'],
centering=False,
detrend=True,
aggregate=np.mean)
assert np.allclose(onsets[1:], DATA['onsetenv'][0])
pass
for infile in files('data/beat-onset-*.mat'):
yield (__test, infile)
def test_tempo():
def __test(infile):
DATA = load(infile)
# Estimate tempo from the given onset envelope
tempo = librosa.beat.estimate_tempo(DATA['onsetenv'][0],
sr=8000,
hop_length=32,
start_bpm=120.0)
assert (np.allclose(tempo, DATA['t'][0, 0]) or
np.allclose(tempo, DATA['t'][0, 1]))
for infile in files('data/beat-tempo-*.mat'):
yield (__test, infile)
@raises(librosa.ParameterError)
def test_beat_no_input():
librosa.beat.beat_track(y=None, onset_envelope=None)
def test_beat_no_onsets():
sr = 22050
hop_length = 512
duration = 30
onsets = np.zeros(duration * sr // hop_length)
tempo, beats = librosa.beat.beat_track(onset_envelope=onsets,
sr=sr,
hop_length=hop_length)
assert np.allclose(tempo, 0)
eq_(len(beats), 0)
def test_tempo_no_onsets():
sr = 22050
hop_length = 512
duration = 30
onsets = np.zeros(duration * sr // hop_length)
def __test(start_bpm):
tempo = librosa.beat.estimate_tempo(onsets, sr=sr,
hop_length=hop_length,
start_bpm=start_bpm)
eq_(tempo, start_bpm)
for start_bpm in [40, 60, 120, 240]:
yield __test, start_bpm
def test_beat():
y, sr = librosa.load(__EXAMPLE_FILE)
hop_length = 512
onset_env = librosa.onset.onset_strength(y=y, sr=sr, hop_length=hop_length)
def __test(with_audio, with_tempo, start_bpm, bpm, trim, tightness):
if with_audio:
_y = y
_ons = None
else:
_y = None
_ons = onset_env
tempo, beats = librosa.beat.beat_track(y=_y,
sr=sr,
onset_envelope=_ons,
hop_length=hop_length,
start_bpm=start_bpm,
tightness=tightness,
trim=trim,
bpm=bpm)
assert tempo >= 0
if len(beats) > 0:
assert beats.min() >= 0
assert beats.max() <= len(onset_env)
for with_audio in [False, True]:
for with_tempo in [False, True]:
for trim in [False, True]:
for start_bpm in [-20, 0, 60, 120, 240]:
for bpm in [-20, 0, None, 150, 360]:
for tightness in [0, 100, 10000]:
if (tightness <= 0 or
(bpm is not None and bpm <= 0) or
(start_bpm is not None and bpm is None and start_bpm <= 0)):
tf = raises(librosa.ParameterError)(__test)
else:
tf = __test
yield (tf, with_audio, with_tempo,
start_bpm, bpm, trim, tightness)
# Beat tracking regression test is no longer enabled due to librosa's
# corrections
@nottest
def deprecated_test_beat():
def __test(infile):
DATA = load(infile)
(bpm, beats) = librosa.beat.beat_track(y=None,
sr=8000,
hop_length=32,
onset_envelope=DATA['onsetenv'][0])
beat_times = librosa.frames_to_time(beats, sr=8000, hop_length=32)
assert np.allclose(beat_times, DATA['beats'])
for infile in files('data/beat-beat-*.mat'):
yield (__test, infile)