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test_features_tempo.py
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test_features_tempo.py
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# encoding: utf-8
# pylint: skip-file
"""
This file contains tests for the madmom.features.tempo module.
"""
from __future__ import absolute_import, division, print_function
import unittest
from os.path import join as pj
from madmom.features import Activations
from madmom.features.tempo import *
from madmom.io import write_tempo, load_tempo
from . import ACTIVATIONS_PATH
act_file = np.load(pj(ACTIVATIONS_PATH, "sample.beats_blstm.npz"))
act = act_file['activations'].astype(float)
fps = float(act_file['fps'])
COMB_TEMPI = np.array([[176.470, 0.475], [117.647, 0.177],
[240.0, 0.154], [68.966, 0.099], [82.192, 0.096]])
COMB_TEMPI_ONLINE = [[176.470588, 0.289414003], [115.384615, 0.124638601],
[230.769231, 0.0918372569], [84.5070423, 0.0903815502],
[75.0000000, 0.0713704506], [53.5714286, 0.0701783497],
[65.9340659, 0.0696296514], [49.1803279, 0.0676349815],
[61.2244898, 0.0646209647], [40.8163265, 0.0602941909]]
ACF_TEMPI = np.array([[176.470, 0.246], [86.956, 0.226], [58.823, 0.181],
[43.795, 0.137], [115.384, 0.081], [70.588, 0.067],
[50.847, 0.058]])
ACF_TEMPI_ONLINE = [[176.470588, 0.253116038], [88.2352941, 0.231203195],
[58.8235294, 0.187827698], [43.7956204, 0.139373027],
[115.384615, 0.0749783568], [69.7674419, 0.0599632291],
[50.4201681, 0.0535384559]]
DBN_TEMPI = np.array([[176.470, 1]])
DBN_TEMPI_ONLINE = [[176.470588, 0.580877380], [86.9565217, 0.244729904],
[74.0740741, 0.127887992], [40.8163265, 0.0232523621],
[250.000000, 0.0232523621]]
TCN_TEMPI = np.array([[87, 0.62103526], [175, 0.2131467], [58, 0.1607556],
[41, 0.00323059], [115, 0.0008726]])
HIST = interval_histogram_comb(act, 0.79, min_tau=24, max_tau=150)
class TestIntervalHistogramAcfFunction(unittest.TestCase):
def test_values(self):
hist = interval_histogram_acf(act, min_tau=24, max_tau=150)
self.assertTrue(np.allclose(hist[0][:6], [0.10034907, 0.10061631,
0.11078519, 0.13461014,
0.17694432, 0.24372872]))
self.assertTrue(np.allclose(hist[1], np.arange(24, 151)))
class TestIntervalHistogramCombFunction(unittest.TestCase):
def setUp(self):
self.hist_0_6 = np.array([3.16024358, 2.00690881, 2.52592621,
2.00221429, 1.73527979, 1.47528936])
def test_values(self):
hist = interval_histogram_comb(act, 0.79, min_tau=24, max_tau=150)
self.assertTrue(np.allclose(hist[0][:6], self.hist_0_6))
self.assertTrue(np.allclose(hist[1], np.arange(24, 151)))
def test_values_2d(self):
act_2d = np.vstack((act, act)).T
hist = interval_histogram_comb(act_2d, 0.79, min_tau=24, max_tau=150)
# test both channels individually
self.assertTrue(np.allclose(hist[0][0, :6], self.hist_0_6))
# 2nd channel is the same
self.assertTrue(np.allclose(hist[0][1, :6], self.hist_0_6))
self.assertTrue(np.allclose(hist[1], np.arange(24, 151)))
class TestSmoothHistogramFunction(unittest.TestCase):
def test_values(self):
hist = smooth_histogram(HIST, 3)
self.assertTrue(np.allclose(hist[0][:6], [3.32079628, 2.46180239,
2.84665606, 2.34311077,
2.01348008, 1.73241048]))
self.assertTrue(np.allclose(hist[1], HIST[1]))
class TestDominantIntervalFunction(unittest.TestCase):
def test_values(self):
result = dominant_interval(HIST)
self.assertTrue(result == 34)
class TestDetectTempoFunction(unittest.TestCase):
def setUp(self):
self.bpm_result = np.array([[176.47, 0.169], [117.65, 0.064],
[250.0, 0.051], [230.77, 0.041],
[105.26, 0.040], [82.19, 0.015]])
def test_values(self):
result = detect_tempo(HIST, fps)
self.assertTrue(np.allclose(result[:6], self.bpm_result, atol=0.1))
# treat histogram values as tempi in BPM
result = detect_tempo(HIST)
self.assertTrue(np.allclose(result[:6, 0],
6000. / self.bpm_result[:, 0], atol=0.1))
self.assertTrue(np.allclose(result[:6, 1],
[0.1689, 0.0635, 0.0508, 0.0406, 0.0402,
0.04], atol=1e-4))
def test_interpolation(self):
result = detect_tempo(HIST, fps, interpolate=True)
self.assertTrue(np.allclose(result[:5], [[176.16, 0.111],
[116.75, 0.044],
[250., 0.033],
[82.37, 0.027],
[230.33, 0.027]], atol=0.1))
class TestTempoEstimationProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = TempoEstimationProcessor(fps=fps)
self.online_processor = TempoEstimationProcessor(fps=fps, online=True)
def test_types(self):
self.assertIsInstance(self.processor.method, str)
self.assertIsInstance(self.processor.min_bpm, float)
self.assertIsInstance(self.processor.max_bpm, float)
self.assertIsInstance(self.processor.act_smooth, float)
self.assertIsInstance(self.processor.hist_smooth, int)
self.assertIsInstance(self.processor.fps, float)
self.assertIsInstance(self.processor.histogram_processor,
TempoHistogramProcessor)
def test_values(self):
self.assertTrue(self.processor.method == 'comb')
self.assertTrue(self.processor.min_bpm == 40)
self.assertTrue(self.processor.max_bpm == 250)
self.assertTrue(self.processor.act_smooth == 0.14)
self.assertTrue(self.processor.hist_smooth == 9)
self.assertTrue(self.processor.fps == 100)
# test default values of the histogram processor
self.assertTrue(self.processor.histogram_processor.alpha == 0.79)
self.assertTrue(self.processor.histogram_processor.min_interval == 24)
self.assertTrue(self.processor.histogram_processor.max_interval == 150)
def test_process(self):
tempi = self.processor(act)
self.assertTrue(np.allclose(tempi, COMB_TEMPI, atol=0.01))
def test_process_online(self):
# process all activations at once
tempi = self.online_processor(act, reset=False)
self.assertTrue(np.allclose(tempi, COMB_TEMPI_ONLINE))
# process frame by frame; with resetting results are the same
self.online_processor.reset()
tempi = [self.online_processor(np.atleast_1d(a), reset=False)
for a in act]
self.assertTrue(np.allclose(tempi[-1], COMB_TEMPI_ONLINE))
# without resetting results are different
tempi = [self.online_processor(np.atleast_1d(a), reset=False)
for a in act]
self.assertTrue(np.allclose(tempi[-1][:3], [[176.470588, 0.31322337],
[85.7142857, 0.11437361],
[115.384615, 0.10919612]]))
class TestCombFilterTempoHistogramProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = CombFilterTempoHistogramProcessor(fps=fps)
self.online_processor = CombFilterTempoHistogramProcessor(fps=fps,
online=True)
def test_types(self):
self.assertIsInstance(self.processor.min_bpm, float)
self.assertIsInstance(self.processor.max_bpm, float)
self.assertIsInstance(self.processor.alpha, float)
self.assertIsInstance(self.processor.fps, float)
# properties
self.assertIsInstance(self.processor.min_interval, int)
self.assertIsInstance(self.processor.max_interval, int)
def test_values(self):
self.assertTrue(self.processor.min_bpm == 40)
self.assertTrue(self.processor.max_bpm == 250)
self.assertTrue(self.processor.alpha == 0.79)
self.assertTrue(self.processor.fps == 100)
self.assertTrue(self.processor.min_interval == 24)
self.assertTrue(self.processor.max_interval == 150)
def test_tempo(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.processor, fps=fps)
tempi = tempo_processor(act)
self.assertTrue(np.allclose(tempi, COMB_TEMPI, atol=0.01))
def test_tempo_online(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.online_processor, fps=fps, online=True)
# process all activations at once
tempi = tempo_processor(act, reset=False)
self.assertTrue(np.allclose(tempi, COMB_TEMPI_ONLINE))
# process frame by frame; with resetting results are the same
tempo_processor.reset()
tempi = [tempo_processor(np.atleast_1d(a), reset=False) for a in act]
self.assertTrue(np.allclose(tempi[-1], COMB_TEMPI_ONLINE))
# without resetting results are different
tempi = [tempo_processor(np.atleast_1d(a), reset=False) for a in act]
self.assertTrue(np.allclose(tempi[-1][:3], [[176.470588, 0.31322337],
[85.7142857, 0.11437361],
[115.384615, 0.10919612]]))
def test_process(self):
hist, delays = self.processor(act)
self.assertTrue(np.allclose(delays, np.arange(24, 151)))
self.assertTrue(np.allclose(hist.max(), 10.5064280455))
self.assertTrue(np.allclose(hist.min(), 1.23250838113))
self.assertTrue(np.allclose(hist.argmax(), 10))
self.assertTrue(np.allclose(hist.argmin(), 44))
self.assertTrue(np.allclose(np.sum(hist), 231.568316445))
self.assertTrue(np.allclose(np.mean(hist), 1.82337257043))
self.assertTrue(np.allclose(np.median(hist), 1.48112542203))
def test_process_online(self):
# offline results
hist_offline, delays_offline = self.processor(act)
# calling with all activations at once
hist, delays = self.online_processor(act)
# result must be the same as for offline processing
self.assertTrue(np.allclose(hist, hist_offline))
self.assertTrue(np.allclose(delays, delays_offline))
# calling frame by frame after resetting
self.online_processor.reset()
result = [self.online_processor(np.atleast_1d(a), reset=False)
for a in act]
# the final result must be the same as for offline processing
hist, delays = result[-1]
hist_, delays_ = self.processor(act)
self.assertTrue(np.allclose(hist, hist_))
self.assertTrue(np.allclose(delays, delays_))
# result after 100 frames
hist, delays = result[99]
self.assertTrue(np.allclose(hist.max(), 2.03108930086))
self.assertTrue(np.allclose(hist.min(), 1.23250838113))
self.assertTrue(np.allclose(hist.argmax(), 12))
self.assertTrue(np.allclose(hist.argmin(), 44))
self.assertTrue(np.allclose(np.sum(hist), 175.034206851))
self.assertTrue(np.allclose(np.mean(hist), 1.37822210119))
self.assertTrue(np.allclose(np.median(hist), 1.23250838113))
# the final result must be the same as for offline processing
hist, delays = result[-1]
self.assertTrue(np.allclose(hist, hist_offline))
self.assertTrue(np.allclose(delays, delays_offline))
# results must be different without resetting
result = [self.online_processor(np.atleast_1d(a), reset=False)
for a in act]
hist, delays = result[-1]
self.assertTrue(np.allclose(hist.max(), 18.1385269354))
self.assertTrue(np.allclose(hist.min(), 1.23250838113))
self.assertTrue(np.allclose(hist.argmax(), 11))
self.assertTrue(np.allclose(hist.argmin(), 72))
self.assertTrue(np.allclose(np.sum(hist), 332.668525522))
self.assertTrue(np.allclose(np.mean(hist), 2.61943720884))
self.assertTrue(np.allclose(np.median(hist), 1.96220625848))
class TestACFTempoHistogramProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = ACFTempoHistogramProcessor(fps=fps)
self.online_processor = ACFTempoHistogramProcessor(fps=fps,
online=True)
def test_types(self):
self.assertIsInstance(self.processor.min_bpm, float)
self.assertIsInstance(self.processor.max_bpm, float)
self.assertIsInstance(self.processor.fps, float)
# properties
self.assertIsInstance(self.processor.min_interval, int)
self.assertIsInstance(self.processor.max_interval, int)
def test_values(self):
self.assertTrue(self.processor.min_bpm == 40)
self.assertTrue(self.processor.max_bpm == 250)
self.assertTrue(self.processor.fps == 100)
self.assertTrue(self.processor.min_interval == 24)
self.assertTrue(self.processor.max_interval == 150)
def test_tempo(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.processor, fps=fps)
tempi = tempo_processor(act)
self.assertTrue(np.allclose(tempi, ACF_TEMPI, atol=0.01))
def test_tempo_online(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.online_processor, fps=fps, online=True)
# process all activations at once
tempi = tempo_processor(act, reset=False)
self.assertTrue(np.allclose(tempi, ACF_TEMPI_ONLINE))
# process frame by frame; with resetting results are the same
tempo_processor.reset()
tempi = [tempo_processor(np.atleast_1d(a), reset=False) for a in act]
self.assertTrue(np.allclose(tempi[-1], ACF_TEMPI_ONLINE))
# without resetting results are different
tempi = [tempo_processor(np.atleast_1d(a), reset=False) for a in act]
self.assertTrue(np.allclose(tempi[-1][:3], [[176.4705882, 0.2414368],
[86.95652174, 0.2248635],
[58.25242718, 0.1878183]]))
def test_process(self):
hist, delays = self.processor(act)
self.assertTrue(np.allclose(delays, np.arange(24, 151)))
self.assertTrue(np.allclose(hist.max(), 0.772242703961))
self.assertTrue(np.allclose(hist.min(), 0.0550745515184))
self.assertTrue(np.allclose(hist.argmax(), 11))
self.assertTrue(np.allclose(hist.argmin(), 103))
self.assertTrue(np.allclose(np.sum(hist), 28.4273056042))
self.assertTrue(np.allclose(np.mean(hist), 0.223837052001))
self.assertTrue(np.allclose(np.median(hist), 0.147368463433))
def test_process_online(self):
# offline results
hist_offline, delays_offline = self.processor(act)
# calling with all activations at once
hist, delays = self.online_processor(act)
# result must be the same as for offline processing
self.assertTrue(np.allclose(hist, hist_offline))
self.assertTrue(np.allclose(delays, delays_offline))
# calling frame by frame after resetting
self.online_processor.reset()
result = [self.online_processor(np.atleast_1d(a), reset=False)
for a in act]
# the final result must be the same as for offline processing
hist, delays = result[-1]
hist_, delays_ = self.processor(act)
self.assertTrue(np.allclose(hist, hist_))
self.assertTrue(np.allclose(delays, delays_))
# result after 100 frames
hist, delays = result[99]
self.assertTrue(np.allclose(hist.max(), 0.19544739526))
self.assertTrue(np.allclose(hist.min(), 0))
self.assertTrue(np.allclose(hist.argmax(), 46))
self.assertTrue(np.allclose(hist.argmin(), 76))
self.assertTrue(np.allclose(np.sum(hist), 3.58546628975))
self.assertTrue(np.allclose(np.mean(hist), 0.0282320180295))
self.assertTrue(np.allclose(np.median(hist), 0.00471735456373))
# the final result must be the same as for offline processing
hist, delays = result[-1]
self.assertTrue(np.allclose(hist, hist_offline))
self.assertTrue(np.allclose(delays, delays_offline))
class TestDBNTempoHistogramProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = DBNTempoHistogramProcessor(fps=fps)
self.online_processor = DBNTempoHistogramProcessor(fps=fps,
online=True)
def test_types(self):
self.assertIsInstance(self.processor.min_bpm, float)
self.assertIsInstance(self.processor.max_bpm, float)
self.assertIsInstance(self.processor.fps, float)
# properties
self.assertIsInstance(self.processor.min_interval, int)
self.assertIsInstance(self.processor.max_interval, int)
def test_values(self):
self.assertTrue(self.processor.min_bpm == 40)
self.assertTrue(self.processor.max_bpm == 250)
self.assertTrue(self.processor.fps == 100)
self.assertTrue(self.processor.min_interval == 24)
self.assertTrue(self.processor.max_interval == 150)
def test_tempo(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.processor, fps=fps)
tempi = tempo_processor(act)
self.assertTrue(np.allclose(tempi, DBN_TEMPI, atol=0.01))
def test_tempo_online(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.online_processor, fps=fps, online=True)
# process all activations at once
tempi = tempo_processor(act, reset=False)
self.assertTrue(np.allclose(tempi, DBN_TEMPI_ONLINE))
# process frame by frame; with resetting results are the same
tempo_processor.reset()
tempo_processor.reset()
tempi = [tempo_processor(np.atleast_1d(a), reset=False) for a in act]
self.assertTrue(np.allclose(tempi[-1], DBN_TEMPI_ONLINE))
# without resetting results are different
tempi = [tempo_processor(np.atleast_1d(a), reset=False) for a in act]
self.assertTrue(np.allclose(tempi[-1][:3],
[[176.4705882, 0.472499032],
[84.5070423, 0.432130320],
[74.0740741, 0.0699384753]]))
def test_process(self):
hist, delays = self.processor(act)
self.assertTrue(np.allclose(delays, np.arange(24, 151)))
self.assertTrue(np.allclose(hist.max(), 281))
self.assertTrue(np.allclose(hist.min(), 0))
self.assertTrue(np.allclose(hist.argmax(), 10))
self.assertTrue(np.allclose(hist.argmin(), 0))
self.assertTrue(np.allclose(np.sum(hist), 281))
self.assertTrue(np.allclose(np.mean(hist), 2.2125984252))
self.assertTrue(np.allclose(np.median(hist), 0))
def test_process_online(self):
hist, delays = self.online_processor(act)
self.assertTrue(np.allclose(delays, np.arange(24, 151)))
self.assertTrue(np.allclose(hist.max(), 106))
self.assertTrue(np.allclose(hist.min(), 0))
self.assertTrue(np.allclose(hist.argmax(), 10))
self.assertTrue(np.allclose(hist.argmin(), 1))
self.assertTrue(np.allclose(np.sum(hist), 281))
self.assertTrue(np.allclose(np.mean(hist), 2.2125984252))
self.assertTrue(np.allclose(np.median(hist), 0))
class TestTCNTempoHistogramProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = TCNTempoHistogramProcessor(min_bpm=10, max_bpm=250)
self.act = Activations(pj(ACTIVATIONS_PATH,
"sample.beats_tcn_tempo.npz"))
def test_types(self):
self.assertIsInstance(self.processor.min_bpm, float)
self.assertIsInstance(self.processor.max_bpm, float)
self.assertIsNone(self.processor.fps)
def test_values(self):
self.assertTrue(self.processor.min_bpm == 10)
self.assertTrue(self.processor.max_bpm == 250)
self.assertTrue(np.sum(self.act) == 1)
def test_process(self):
hist, tempi = self.processor(self.act)
self.assertTrue(np.allclose(tempi, np.arange(10, 251)))
self.assertTrue(np.allclose(hist.max(), 0.1326968))
self.assertTrue(np.allclose(hist.min(), 5.05e-09))
self.assertTrue(np.allclose(hist.argmax(), 77))
self.assertTrue(np.allclose(hist.argmin(), 182))
# hist sum is not 1, since we excluded tempi < 10
self.assertTrue(np.allclose(np.sum(hist), 0.9999768))
self.assertTrue(np.allclose(np.mean(hist), 0.0041492814))
self.assertTrue(np.allclose(np.median(hist), 7.891e-06))
def test_tempo(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.processor, act_smooth=None)
tempi = tempo_processor(self.act)
self.assertTrue(tempi.shape == (14, 2))
self.assertTrue(np.allclose(tempi[:, 0],
[87, 174, 58, 41, 115, 132, 100,
32, 197, 246, 228, 23, 214, 14]))
self.assertTrue(np.allclose(np.sum(tempi[:, 1]), 1))
def test_tempo_hist_smooth(self):
tempo_processor = TempoEstimationProcessor(
histogram_processor=self.processor, act_smooth=None,
hist_smooth=15)
tempi = tempo_processor(self.act)
self.assertTrue(tempi.shape == (9, 2))
self.assertTrue(np.allclose(tempi[:5], TCN_TEMPI, atol=0.01))
class TestWriteTempoFunction(unittest.TestCase):
def setUp(self):
import tempfile
self.out_file = tempfile.NamedTemporaryFile(delete=False).name
def test_types(self):
# must work with 2d arrays
write_tempo(COMB_TEMPI[:1], self.out_file)
# but also with 1d arrays
write_tempo(COMB_TEMPI[0], self.out_file)
def test_values(self):
# only one tempo given (>68 bpm)
write_tempo(COMB_TEMPI[0], self.out_file)
result = load_tempo(self.out_file)
self.assertTrue(np.allclose(result, [[176.47, 1]],
atol=1e-4, equal_nan=True))
# only one tempo given (<68 bpm)
write_tempo(COMB_TEMPI[3] / 2, self.out_file)
result = load_tempo(self.out_file)
self.assertTrue(np.allclose(result, [[34.48, 1]],
atol=1e-4, equal_nan=True))
# multiple tempi given
write_tempo(COMB_TEMPI, self.out_file)
result = load_tempo(self.out_file)
self.assertTrue(np.allclose(result, [[176.47, 0.73],
[117.65, 0.27]], atol=1e-4))
def test_values_mirex(self):
# multiple tempi given
write_tempo(COMB_TEMPI, self.out_file, mirex=True)
result = load_tempo(self.out_file)
self.assertTrue(np.allclose(result, [[117.65, 0.27],
[176.47, 0.73]], atol=1e-4))
def tearDown(self):
import os
os.unlink(self.out_file)