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test_audio_filters.py
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# encoding: utf-8
# pylint: skip-file
"""
This file contains tests for the madmom.audio.filters module.
"""
from __future__ import absolute_import, division, print_function
import unittest
import types
from madmom.audio.filters import *
# Mel frequency scale
HZ = np.asarray([20, 258.7484, 576.6645, 1000])
MEL = np.asarray([31.749, 354.5, 677.25, 1000])
FFT_FREQS_1024 = np.fft.fftfreq(2048, 1. / 44100)[:1024]
LOG_FILTERBANK_CENTER_FREQS = np.array(
[43.066406, 64.5996093, 86.1328125, 107.6660156, 129.199218, 150.732421,
172.265625, 193.798828, 215.332031, 236.865234, 258.398437, 279.931640,
301.464843, 322.998046, 344.531250, 366.064453, 387.597656, 409.130859,
430.664062, 452.197265, 495.263671, 516.796875, 538.330078, 581.396484,
624.462890, 645.996093, 689.062500, 732.128906, 775.195312, 839.794921,
882.861328, 925.927734, 990.527343, 1055.126953, 1098.193359, 1184.326171,
1248.925781, 1313.525390, 1399.658203, 1485.791015, 1571.923828,
1658.056640, 1765.722656, 1873.388671, 1981.054687, 2088.720703,
2217.919921, 2347.119140, 2497.851562, 2627.050781, 2799.316406,
2950.048828, 3143.847656, 3316.113281, 3509.912109, 3725.244140,
3940.576171, 4177.441406, 4435.839843, 4694.238281, 4974.169921,
5275.634765, 5577.099609, 5921.630859, 6266.162109, 6653.759765,
7041.357421, 7450.488281, 7902.685546, 8376.416015, 8871.679687,
9388.476562, 9948.339843, 10551.269531, 11175.732421, 11843.261718,
12553.857421, 13285.986328, 14082.714843, 14922.509765, 15805.37109375])
LOG_FILTERBANK_CORNER_FREQS = np.array(
[[43.066406, 43.066406], [64.599609, 64.599609], [86.132812, 86.132812],
[107.666015, 107.666015], [129.199218, 129.199218],
[150.732421, 150.732421], [172.265625, 172.265625],
[193.798828, 193.798828], [215.332031, 215.332031],
[236.865234, 236.865234], [258.398437, 258.398437],
[279.931640, 279.931640], [301.464843, 301.464843],
[322.998046, 322.998046], [344.531250, 344.531250],
[366.064453, 366.064453], [387.597656, 387.597656],
[409.130859, 409.130859], [430.664062, 452.197265],
[452.197265, 473.730468], [495.263671, 495.263671],
[516.796875, 538.330078], [538.330078, 559.863281],
[581.396484, 602.929687], [602.929687, 645.996093],
[645.996093, 667.529296], [689.062500, 710.595703],
[710.595703, 753.662109], [753.662109, 818.261718],
[796.728515, 861.328125], [861.328125, 904.394531],
[904.394531, 968.994140], [947.460937, 1033.59375],
[1012.060546, 1076.660156], [1076.660156, 1162.792968],
[1119.726562, 1227.392578], [1205.859375, 1291.992187],
[1270.458984, 1378.125000], [1335.058593, 1464.257812],
[1421.191406, 1550.390625], [1507.324218, 1636.523437],
[1593.457031, 1744.189453], [1679.589843, 1851.855468],
[1787.255859, 1959.521484], [1894.921875, 2067.187500],
[2002.587890, 2196.386718], [2110.253906, 2325.585937],
[2239.453125, 2476.318359], [2368.652343, 2605.517578],
[2519.384765, 2777.783203], [2648.583984, 2928.515625],
[2820.849609, 3122.314453], [2971.582031, 3294.580078],
[3165.380859, 3488.378906], [3337.646484, 3703.710937],
[3531.445312, 3919.042968], [3746.777343, 4155.908203],
[3962.109375, 4414.306640], [4198.974609, 4672.705078],
[4457.373046, 4952.636718], [4715.771484, 5254.101562],
[4995.703125, 5555.566406], [5297.167968, 5900.097656],
[5598.632812, 6244.628906], [5943.164062, 6632.226562],
[6287.695312, 7019.824218], [6675.292968, 7428.955078],
[7062.890625, 7881.152343], [7472.021484, 8354.882812],
[7924.218750, 8850.146484], [8397.949218, 9366.943359],
[8893.212890, 9926.806640], [9410.009765, 10529.736328],
[9969.873046, 11154.199218], [10572.802734, 11821.728515],
[11197.265625, 12532.324218], [11864.794921, 13264.453125],
[12575.390625, 14061.181640], [13307.519531, 14900.976562],
[14104.248046, 15783.837890], [14944.042968, 16731.298828]])
class TestHz2MelFunction(unittest.TestCase):
def test_types(self):
# array
result = hz2mel(HZ)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# list
result = hz2mel([1, 2.])
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# single value
result = hz2mel(1.1)
self.assertIsInstance(result, float)
self.assertEqual(result.dtype, float)
def test_value(self):
self.assertTrue(np.allclose(hz2mel(HZ), MEL))
class TestMel2HzFunction(unittest.TestCase):
def test_types(self):
# array
result = mel2hz(HZ)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# list
result = mel2hz([1, 2.])
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# single value
result = mel2hz(1.1)
self.assertIsInstance(result, float)
self.assertEqual(result.dtype, float)
def test_values(self):
self.assertTrue(np.allclose(mel2hz(MEL), HZ))
class TestMelFrequenciesFunction(unittest.TestCase):
def test_types(self):
result = mel_frequencies(4, 20, 1000)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
def test_values(self):
# HZ is already mel-scaled, so use this for comparison
result = mel_frequencies(4, 20, 1000)
self.assertTrue(np.allclose(result, HZ))
self.assertEqual(len(result), 4)
# Bark frequency scale
BARK = np.array([20, 100, 200, 300, 400, 510, 630, 770, 920, 1080,
1270, 1480, 1720, 2000, 2320, 2700, 3150, 3700,
4400, 5300, 6400, 7700, 9500, 12000, 15500])
BARK_DOUBLE = np.array([20, 50, 100, 150, 200, 250, 300, 350, 400, 450,
510, 570, 630, 700, 770, 840, 920, 1000, 1080,
1170, 1270, 1370, 1480, 1600, 1720, 1850, 2000,
2150, 2320, 2500, 2700, 2900, 3150, 3400, 3700,
4000, 4400, 4800, 5300, 5800, 6400, 7000, 7700,
8500, 9500, 10500, 12000, 13500, 15500])
class TestHz2BarkFunction(unittest.TestCase):
def test_raises_warning(self):
with self.assertRaises(NotImplementedError):
# TODO: write test when implemented
hz2bark(HZ)
class TestBark2HzFunction(unittest.TestCase):
def test_raises_warning(self):
with self.assertRaises(NotImplementedError):
# TODO: write test when implemented
bark2hz(BARK)
class TestBarkFrequenciesFunction(unittest.TestCase):
def test_types(self):
# array
result = bark_frequencies()
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, int)
def test_values(self):
# all values
self.assertTrue(np.allclose(bark_frequencies(), BARK))
# limit range
result = bark_frequencies(20, 18000)
self.assertTrue(np.allclose(result, BARK))
result = bark_frequencies(40, 18000)
self.assertTrue(np.allclose(result, BARK[1:]))
result = bark_frequencies(40, 12000)
self.assertTrue(np.allclose(result, BARK[1:-1]))
result = bark_frequencies(40, 11999)
self.assertTrue(np.allclose(result, BARK[1:-2]))
class TestBarkDoubleFrequenciesFunction(unittest.TestCase):
def test_types(self):
# array
result = bark_double_frequencies()
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, int)
def test_values(self):
# all values
self.assertTrue(np.allclose(bark_double_frequencies(), BARK_DOUBLE))
# limit range
result = bark_double_frequencies(20, 18000)
self.assertTrue(np.allclose(result, BARK_DOUBLE))
result = bark_double_frequencies(40, 18000)
self.assertTrue(np.allclose(result, BARK_DOUBLE[1:]))
result = bark_double_frequencies(40, 12000)
self.assertTrue(np.allclose(result, BARK_DOUBLE[1:-2]))
result = bark_double_frequencies(40, 11999)
self.assertTrue(np.allclose(result, BARK_DOUBLE[1:-3]))
# logarithmic frequency scale stuff
class TestLogFrequenciesFunction(unittest.TestCase):
def test_num_arguments(self):
# number of arguments arguments
with self.assertRaises(TypeError):
log_frequencies()
with self.assertRaises(TypeError):
log_frequencies(1)
with self.assertRaises(TypeError):
log_frequencies(1, 2)
with self.assertRaises(TypeError):
log_frequencies(1, 2, 3, 4, 5)
def test_types(self):
# return types
result = log_frequencies(12, 20, 20000)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
def test_values(self):
# all values
result = log_frequencies(6, 30, 17000)
self.assertTrue(len(result) == 55)
# 1 band per octave
result = log_frequencies(1, 100, 1000)
self.assertTrue(np.allclose(result, [110., 220., 440., 880.]))
# different reference frequency
result = log_frequencies(1, 100, 1000, 441)
self.assertTrue(np.allclose(result, [110.25, 220.5, 441., 882.]))
class TestSemitoneFrequenciesFunction(unittest.TestCase):
def test_num_arguments(self):
# number of arguments
with self.assertRaises(TypeError):
semitone_frequencies()
with self.assertRaises(TypeError):
semitone_frequencies(1)
with self.assertRaises(TypeError):
semitone_frequencies(1, 2, 3, 4)
def test_types(self):
# return types
result = semitone_frequencies(20, 20000)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
def test_values(self):
# all values
result = semitone_frequencies(30, 17000)
self.assertTrue(len(result) == 110)
# 12 bands per octave
result = semitone_frequencies(250, 500)
result_ = [261.6255653, 277.18263098, 293.66476792, 311.12698372,
329.62755691, 349.22823143, 369.99442271, 391.99543598,
415.30469758, 440, 466.16376152, 493.88330126]
self.assertTrue(len(result) == 12)
self.assertTrue(np.allclose(result, result_))
# different reference frequency
result = semitone_frequencies(441, 500, 441)
self.assertTrue(np.allclose(result, [441, 467.22322461, 495.0057633]))
# MIDI
class TestHz2MidiFunction(unittest.TestCase):
def test_num_arguments(self):
# number of arguments
with self.assertRaises(TypeError):
hz2midi()
with self.assertRaises(TypeError):
hz2midi(1, 2, 3)
def test_types(self):
# return types
result = hz2midi(20, 440)
self.assertIsInstance(result, float)
result = hz2midi([20, 40], 440)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
result = hz2midi(np.arange(10, 20), 440)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
def test_values(self):
# single value
result = hz2midi(440, 440)
self.assertTrue(result == 69)
# 12 bands per octave
result = hz2midi([220, 440], 440)
self.assertTrue(len(result) == 2)
self.assertTrue(np.allclose(result, [57, 69]))
class TestMidi2HzFunction(unittest.TestCase):
def test_num_arguments(self):
# number of arguments
with self.assertRaises(TypeError):
midi2hz()
with self.assertRaises(TypeError):
midi2hz(1, 2, 3)
def test_types(self):
# return types
result = midi2hz(20, 440)
self.assertIsInstance(result, float)
result = midi2hz([20, 40], 440)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
result = midi2hz(np.arange(10, 20), 440)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
def test_values(self):
# single value
result = midi2hz(69, 440)
self.assertTrue(result == 440)
# 12 bands per octave
result = midi2hz([57, 69], 440)
self.assertTrue(len(result) == 2)
self.assertTrue(np.allclose(result, [220, 440]))
# ERB
ERB = np.asarray([0.77873163, 7.03051042, 11.69607601, 15.62144971])
class TestHz2ErbFunction(unittest.TestCase):
def test_types(self):
# array
result = hz2erb(HZ)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# list
result = hz2erb([1, 2.])
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# single value
result = hz2erb(1.1)
self.assertIsInstance(result, float)
self.assertEqual(result.dtype, float)
def test_value(self):
self.assertTrue(np.allclose(hz2erb(HZ), ERB))
class TestErb2HzFunction(unittest.TestCase):
def test_types(self):
# array
result = erb2hz(ERB)
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# list
result = erb2hz([1, 2.])
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
# single value
result = erb2hz(1.1)
self.assertIsInstance(result, float)
self.assertEqual(result.dtype, float)
def test_value(self):
self.assertTrue(np.allclose(erb2hz(ERB), HZ))
# helper functions for filter creation
class TestFrequencies2BinsFunction(unittest.TestCase):
freqs = np.asarray([0, 1, 2, 3, 4])
def test_num_arguments(self):
# number of arguments arguments
with self.assertRaises(TypeError):
frequencies2bins()
with self.assertRaises(TypeError):
frequencies2bins(1)
with self.assertRaises(TypeError):
frequencies2bins(1, 2, 3, 4)
def test_types(self):
result = frequencies2bins([0, 1, 2, 3, 4], [0, 1, 2, 3, 4])
self.assertIsInstance(result, np.ndarray)
self.assertTrue(np.issubdtype(result.dtype, np.integer))
def test_value(self):
# normal frequencies
result = frequencies2bins([0, 1, 2, 3, 4], [0, 1, 2, 3, 4])
self.assertTrue(np.allclose(result, [0, 1, 2, 3, 4]))
# double mapping frequencies
result = frequencies2bins([0, 1, 1.1, 1.2, 2, 3, 3.5], [0, 1, 2, 3, 4])
self.assertTrue(np.allclose(result, [0, 1, 1, 1, 2, 3, 4]))
# higher frequencies should be mapped to the last bin
result = frequencies2bins([0, 1, 2, 3, 11], [0, 1, 2, 3, 4])
self.assertTrue(np.allclose(result, [0, 1, 2, 3, 4]))
# lower frequencies should be mapped to the first bin
result = frequencies2bins([-1, 0, 1, 2, 3, 4], [0, 1, 2, 3, 4])
self.assertTrue(np.allclose(result, [0, 0, 1, 2, 3, 4]))
def test_unique_bins(self):
# duplicate bins should be kept
result = frequencies2bins([0, 1, 2, 3, 4, 5], [0, 2, 4])
self.assertTrue(np.allclose(result, [0, 1, 1, 2, 2, 2]))
# duplicate bins should be removed
result = frequencies2bins([0, 1, 2, 3, 4, 5], [0, 2, 4],
unique_bins=True)
self.assertTrue(np.allclose(result, [0, 1, 2]))
# duplicated bins at lower frequencies should be mapped to the first
# bin and removed
result = frequencies2bins([-1, 0, 1, 2, 3, 4], [0, 1, 2, 3, 4],
unique_bins=True)
self.assertTrue(np.allclose(result, [0, 1, 2, 3, 4]))
class TestBins2FrequenciesFunction(unittest.TestCase):
def test_num_arguments(self):
# number of arguments arguments
with self.assertRaises(TypeError):
bins2frequencies()
with self.assertRaises(TypeError):
bins2frequencies(1)
with self.assertRaises(TypeError):
bins2frequencies(1, 2, 3)
def test_types(self):
result = bins2frequencies([0, 1, 2, 3, 4], [0, 1, 2, 3, 4])
self.assertIsInstance(result, np.ndarray)
self.assertEqual(result.dtype, float)
def test_value(self):
result = bins2frequencies([0, 1, 2, 3, 4], [0, 1, 2, 3, 4])
self.assertTrue(np.allclose(result, [0, 1, 2, 3, 4]))
result = bins2frequencies([0, 1, 2, 3, 4], [0, 1, 1.1, 1.2, 2, 3, 4])
self.assertTrue(np.allclose(result, [0, 1, 1.1, 1.2, 2]))
result = bins2frequencies([-1, 0, 1, 2, 3, 4], [0, 1, 2, 3, 4])
self.assertTrue(np.allclose(result, [4, 0, 1, 2, 3, 4]))
# test classes
class TestFilterClass(unittest.TestCase):
def test_types(self):
filt = Filter(np.arange(5))
self.assertIsInstance(filt, Filter)
self.assertIsInstance(filt.start, int)
self.assertIsInstance(filt.stop, int)
def test_conversion(self):
with self.assertRaises(TypeError):
Filter([0, 1, 2, 3, 4])
with self.assertRaises(TypeError):
Filter(0, 1)
with self.assertRaises(TypeError):
Filter(np.arange(5), [0, 1])
with self.assertRaises(NotImplementedError):
# TODO: write test when implemented
Filter(np.zeros((10, 2)), 1)
def test_value(self):
filt = Filter(np.arange(5))
self.assertTrue(np.allclose(filt, [0, 1, 2, 3, 4]))
self.assertTrue(filt.start == 0)
self.assertTrue(filt.stop == 5)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 4))
filt = Filter(np.arange(5), 1)
self.assertTrue(np.allclose(filt, [0, 1, 2, 3, 4]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.stop == 6)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 4))
def test_normalization(self):
filt = Filter(np.arange(5), norm=True)
self.assertTrue(np.allclose(filt, [0, 0.1, 0.2, 0.3, 0.4]))
self.assertTrue(filt.start == 0)
self.assertTrue(filt.stop == 5)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 0.4))
def test_filters_method(self):
with self.assertRaises(NotImplementedError):
# TODO: write test when implemented
Filter(np.arange(5)).filters(3, norm=True)
class TestTriangularFilterClass(unittest.TestCase):
bins = np.asarray([0, 1, 2, 3, 4, 6, 9])
def test_types(self):
filt = TriangularFilter(0, 1, 2)
self.assertIsInstance(filt, TriangularFilter)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertIsInstance(filt.band_bins(np.arange(8)),
types.GeneratorType)
def test_errors(self):
# filter bins ascending order
with self.assertRaises(ValueError):
TriangularFilter(0, 2, 1)
def test_values(self):
filt = TriangularFilter(0, 1, 2, norm=False)
self.assertTrue(np.allclose(filt, [0, 1]))
self.assertTrue(filt.start == 0)
self.assertTrue(filt.center == 1)
self.assertTrue(filt.stop == 2)
filt = TriangularFilter(1, 2, 3, norm=True)
self.assertTrue(np.allclose(filt, [0, 1]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.center == 2)
self.assertTrue(filt.stop == 3)
filt = TriangularFilter(1, 2, 4, norm=False)
self.assertTrue(np.allclose(filt, [0, 1, 0.5]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.center == 2)
self.assertTrue(filt.stop == 4)
filt = TriangularFilter(1, 2, 4, norm=True)
self.assertTrue(np.allclose(filt, [0, 0.66667, 0.33333]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.center == 2)
self.assertTrue(filt.stop == 4)
filt = TriangularFilter(4, 6, 9, norm=True)
self.assertTrue(np.allclose(filt, [0, 0.2, 0.4, 0.266667, 0.133333]))
self.assertTrue(filt.start == 4)
self.assertTrue(filt.center == 6)
self.assertTrue(filt.stop == 9)
# test small filters
filt = TriangularFilter(0, 0, 1, norm=True)
self.assertTrue(np.allclose(filt, [1]))
self.assertTrue(filt.start == 0)
self.assertTrue(filt.center == 0)
self.assertTrue(filt.stop == 1)
filt = TriangularFilter(0, 0, 1, norm=False)
self.assertTrue(np.allclose(filt, [1]))
self.assertTrue(filt.start == 0)
self.assertTrue(filt.center == 0)
self.assertTrue(filt.stop == 1)
def test_band_bins_method_too_few_bins(self):
with self.assertRaises(ValueError):
list(TriangularFilter.band_bins(np.arange(2)))
def test_band_bins_method_overlap(self):
# test overlapping
result = list(TriangularFilter.band_bins(self.bins))
self.assertTrue(result == [(0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 6),
(4, 6, 9)])
def test_band_bins_method_non_overlap(self):
# test non-overlapping
result = list(TriangularFilter.band_bins(self.bins, overlap=False))
self.assertTrue(result == [(0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5),
(5, 6, 8)])
def test_filters_method_normalized(self):
# normalized filters
result = TriangularFilter.filters(self.bins, norm=True)
filters = [[0, 1], [0, 1], [0, 1], [0, 0.66667, 0.33333],
[0, 0.2, 0.4, 0.266667, 0.133333]]
starts = [0, 1, 2, 3, 4]
stops = [2, 3, 4, 6, 9]
# test the values of the filters itself
for i, res in enumerate(result):
self.assertTrue(np.allclose(res, filters[i]))
# test start positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.start, starts[i]))
# test stop positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.stop, stops[i]))
def test_filters_method_non_normalized(self):
# non-normalized filters
result = TriangularFilter.filters(self.bins, norm=False)
filters = [[0, 1], [0, 1], [0, 1], [0, 1, 0.5],
[0, 0.5, 1, 0.66667, 0.33333]]
starts = [0, 1, 2, 3, 4]
stops = [2, 3, 4, 6, 9]
# test the values of the filters itself
for i, res in enumerate(result):
self.assertTrue(np.allclose(res, filters[i]))
# test start positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.start, starts[i]))
# test stop positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.stop, stops[i]))
class TestRectangularFilterClass(unittest.TestCase):
bins = np.asarray([0, 1, 2, 3, 4, 6, 9])
def test_types(self):
filt = RectangularFilter(0, 1, False)
self.assertIsInstance(filt, RectangularFilter)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertIsInstance(filt.band_bins(np.arange(8)),
types.GeneratorType)
def test_errors(self):
# TODO: why is this error not raised? it does not really matter, though
# # integer bin numbers
# with self.assertRaises(ValueError):
# RectangularFilter(0, 1.1, False)
# filter bins ascending order
with self.assertRaises(ValueError):
# stop bigger than start
RectangularFilter(2, 1)
def test_values(self):
filt = RectangularFilter(0, 1, norm=False)
self.assertTrue(np.allclose(filt, [1]))
self.assertTrue(filt.start == 0)
self.assertTrue(filt.stop == 1)
filt = RectangularFilter(1, 3, norm=True)
self.assertTrue(np.allclose(filt, [0.5, 0.5]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.stop == 3)
filt = RectangularFilter(1, 4, norm=False)
self.assertTrue(np.allclose(filt, [1, 1, 1]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.stop == 4)
filt = RectangularFilter(1, 4, norm=True)
self.assertTrue(np.allclose(filt, [0.33333, 0.33333, 0.33333]))
self.assertTrue(filt.start == 1)
self.assertTrue(filt.stop == 4)
filt = RectangularFilter(4, 9, norm=True)
self.assertTrue(np.allclose(filt, [0.2, 0.2, 0.2, 0.2, 0.2]))
self.assertTrue(filt.start == 4)
self.assertTrue(filt.stop == 9)
def test_band_bins_method_too_few_bins(self):
with self.assertRaises(ValueError):
list(RectangularFilter.band_bins(np.arange(1)))
def test_band_bins_method_overlap(self):
with self.assertRaises(NotImplementedError):
list(RectangularFilter.band_bins(self.bins, overlap=True))
def test_band_bins_method(self):
result = list(RectangularFilter.band_bins(self.bins))
self.assertEqual(result, [(0, 1), (1, 2), (2, 3), (3, 4), (4, 6),
(6, 9)])
def test_filters_method_normalized(self):
# normalized filters
# resulting bins: [0, 1, 2, 3, 4, 6, 9]
result = RectangularFilter.filters(self.bins, norm=True)
filters = [[1], [1], [1], [1], [0.5, 0.5], [0.33333, 0.33333, 0.33333]]
starts = [0, 1, 2, 3, 4, 6]
stops = [1, 2, 3, 4, 6, 9]
# test the values of the filters itself
for i, res in enumerate(result):
self.assertTrue(np.allclose(res, filters[i]))
# test start positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.start, starts[i]))
# test stop positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.stop, stops[i]))
def test_filters_method_non_normalized(self):
# non-normalized filters
# resulting bins: [0, 0, 1, 1, 2, 3, 4, 6, 9]
result = RectangularFilter.filters(self.bins, norm=False)
filters = [[1], [1], [1], [1], [1, 1], [1, 1, 1]]
starts = [0, 1, 2, 3, 4, 6]
stops = [1, 2, 3, 4, 6, 9]
# test the values of the filters itself
for i, res in enumerate(result):
self.assertTrue(np.allclose(res, filters[i]))
# test start positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.start, starts[i]))
# test stop positions
for i, res in enumerate(result):
self.assertTrue(np.allclose(res.stop, stops[i]))
class TestConstantsClass(unittest.TestCase):
def test_types(self):
self.assertIsInstance(FMIN, float)
self.assertIsInstance(FMAX, float)
self.assertIsInstance(NUM_BANDS, int)
self.assertIsInstance(NORM_FILTERS, bool)
self.assertIsInstance(UNIQUE_FILTERS, bool)
def test_values(self):
self.assertEqual(FMIN, 30.)
self.assertEqual(FMAX, 17000.)
self.assertEqual(NUM_BANDS, 12)
self.assertEqual(NORM_FILTERS, True)
self.assertEqual(UNIQUE_FILTERS, True)
class TestFilterbankClass(unittest.TestCase):
rect_filters = [RectangularFilter(0, 10),
RectangularFilter(10, 25),
RectangularFilter(25, 50),
RectangularFilter(50, 100)]
triang_filters = [TriangularFilter(0, 6, 15),
TriangularFilter(6, 15, 25),
TriangularFilter(15, 25, 50),
TriangularFilter(25, 50, 70)]
def test_types(self):
filt = Filterbank(np.zeros((100, 10)), np.arange(100))
self.assertIsInstance(filt, Filterbank)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertTrue(filt.bin_frequencies.dtype == float)
def test_errors(self):
with self.assertRaises(TypeError):
Filterbank(np.zeros((100, 10)))
with self.assertRaises(TypeError):
Filterbank(np.zeros(10), np.arange(10))
with self.assertRaises(ValueError):
Filterbank(np.zeros((100, 10)), np.arange(10))
def test_put_filter_function(self):
# normal filter placement
filt = np.ones(50) * 0.5
Filterbank._put_filter(RectangularFilter(10, 25), filt)
self.assertTrue(np.allclose(filt[:10], np.ones(10) * 0.5))
self.assertTrue(np.allclose(filt[10:25], np.ones(15)))
self.assertTrue(np.allclose(filt[25:50], np.ones(25) * 0.5))
# out of range end
filt = np.zeros(20)
Filterbank._put_filter(RectangularFilter(10, 25), filt)
self.assertTrue(np.allclose(filt[:10], np.zeros(10)))
self.assertTrue(np.allclose(filt[10:], np.ones(10)))
# out of range start
filt = np.zeros(20)
Filterbank._put_filter(RectangularFilter(-5, 10), filt)
self.assertTrue(np.allclose(filt[:10], np.ones(10)))
self.assertTrue(np.allclose(filt[10:], np.zeros(10)))
# non filter placement
filt = np.zeros(20)
with self.assertRaises(ValueError):
Filterbank._put_filter([10], filt)
def test_from_filters_function(self):
# a list of filters
filt = Filterbank.from_filters(self.rect_filters, np.arange(100))
self.assertIsInstance(filt, Filterbank)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertTrue(filt.bin_frequencies.dtype == float)
# a list of list of filters
filt = Filterbank.from_filters([self.rect_filters,
self.triang_filters], np.arange(100))
self.assertIsInstance(filt, Filterbank)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertTrue(filt.bin_frequencies.dtype == float)
def test_values_rectangular(self):
filt = Filterbank.from_filters(self.rect_filters, np.arange(100))
self.assertTrue(filt.num_bands == 4)
self.assertTrue(filt.num_bins == 100)
self.assertTrue(filt.fmin == 0)
self.assertTrue(filt.fmax == 99)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 1))
self.assertTrue(np.allclose(filt.bin_frequencies, np.arange(100)))
self.assertTrue(np.allclose(filt.corner_frequencies,
[[0, 9], [10, 24], [25, 49], [50, 99]]))
self.assertTrue(np.allclose(filt.center_frequencies,
[4, 17, 37, 74]))
result = np.zeros((100, 4))
result[0:10, 0] = 1
result[10:25, 1] = 1
result[25:50, 2] = 1
result[50:100, 3] = 1
self.assertTrue(np.allclose(filt, result))
def test_values_triangular(self):
filt = Filterbank.from_filters(self.triang_filters, np.arange(100))
self.assertTrue(filt.num_bands == 4)
self.assertTrue(filt.num_bins == 100)
self.assertTrue(filt.fmin == 1)
self.assertTrue(filt.fmax == 69)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 1))
self.assertTrue(np.allclose(filt.bin_frequencies, np.arange(100)))
self.assertTrue(np.allclose(filt.corner_frequencies,
[[1, 14], [7, 24], [16, 49], [26, 69]]))
self.assertTrue(np.allclose(filt.center_frequencies,
[6, 15, 25, 50]))
def test_values_rectangular_and_triangular(self):
# put all triangular filter in a band, always selecting the maximum
# ad all rectangular filters in the second band
filt = Filterbank.from_filters([self.triang_filters,
self.rect_filters], np.arange(100))
self.assertTrue(filt.num_bands == 2)
self.assertTrue(filt.num_bins == 100)
self.assertTrue(filt.fmin == 0)
self.assertTrue(filt.fmax == 99)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 1))
# all triangular filters
correct = np.zeros(100)
correct[1:70] = [1. / 6, 2. / 6, 3. / 6, 4. / 6, 5. / 6, 1., 8. / 9,
7. / 9, 6. / 9, 5. / 9, 5. / 9, 6. / 9, 7. / 9,
8. / 9, 1., 0.9, 0.8, 0.7, 0.6, 0.5, 0.6, 0.7, 0.8,
0.9, 1., 0.96, 0.92, 0.88, 0.84, 0.8, 0.76, 0.72,
0.68, 0.64, 0.6, 0.56, 0.52, 0.52, 0.56, 0.6, 0.64,
0.68, 0.72, 0.76, 0.8, 0.84, 0.88, 0.92, 0.96, 1.,
0.95, 0.9, 0.85, 0.8, 0.75, 0.7, 0.65, 0.6, 0.55,
0.5, 0.45, 0.4, 0.35, 0.3, 0.25, 0.2, 0.15, 0.1, 0.05]
self.assertTrue(np.allclose(filt[:, 0], correct))
# all rectangular filters are 1
self.assertTrue(np.allclose(filt[:, 1], np.ones(100)))
self.assertTrue(np.allclose(filt.bin_frequencies, np.arange(100)))
self.assertTrue(np.allclose(filt.corner_frequencies,
[[1, 69], [0, 99]]))
self.assertTrue(np.allclose(filt.center_frequencies, [6, 49]))
class TestFilterbankProcessorClass(unittest.TestCase):
def setUp(self):
self.processor = FilterbankProcessor.from_filters(
TestFilterbankClass.triang_filters, np.arange(100))
def test_process(self):
result = self.processor.process(np.zeros((20, 100)))
self.assertTrue(np.allclose(result, np.zeros((20, 4))))
class TestMelFilterbankClass(unittest.TestCase):
def test_types(self):
filt = MelFilterbank(np.arange(20000))
self.assertIsInstance(filt, MelFilterbank)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertTrue(filt.bin_frequencies.dtype == float)
def test_constant_types(self):
self.assertIsInstance(MelFilterbank.FMIN, float)
self.assertIsInstance(MelFilterbank.FMAX, float)
self.assertIsInstance(MelFilterbank.NUM_BANDS, int)
self.assertIsInstance(MelFilterbank.NORM_FILTERS, bool)
self.assertIsInstance(MelFilterbank.UNIQUE_FILTERS, bool)
def test_constant_values(self):
self.assertEqual(MelFilterbank.FMIN, 20.)
self.assertEqual(MelFilterbank.FMAX, 17000.)
self.assertEqual(MelFilterbank.NUM_BANDS, 40)
self.assertEqual(MelFilterbank.NORM_FILTERS, True)
self.assertEqual(MelFilterbank.UNIQUE_FILTERS, True)
def test_values(self):
filt = MelFilterbank(np.arange(1000) * 20, 10)
self.assertTrue(filt.num_bands == 10)
self.assertTrue(filt.num_bins == 1000)
self.assertTrue(filt.fmin == 40)
self.assertTrue(filt.fmax == 16980)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 0.0714286))
self.assertTrue(np.allclose(filt.center_frequencies,
[260, 580, 1020, 1600, 2380, 3420, 4820,
6700, 9180, 12520]))
self.assertTrue(np.allclose(filt.corner_frequencies,
[[40, 560], [280, 1000], [600, 1580],
[1040, 2360], [1620, 3400], [2400, 4800],
[3440, 6680], [4840, 9160], [6720, 12500],
[9200, 16980]]))
def test_default_values(self):
filt = MelFilterbank(np.fft.fftfreq(2048, 1. / 44100)[:1024])
center = [86.132812, 150.732422, 215.332031, 279.931640,
366.064453, 452.197266, 538.330078, 645.996094,
753.662109, 882.861328, 990.527344, 1141.259766,
1291.992187, 1442.724609, 1614.990234, 1808.789063,
2024.121093, 2239.453125, 2476.318359, 2734.716797,
3014.648437, 3316.113281, 3639.111328, 3983.642578,
4371.240234, 4780.371094, 5232.568359, 5706.298828,
6223.095703, 6804.492187, 7407.421875, 8053.417969,
8785.546875, 9539.208984, 10379.003906, 11283.398437,
12252.392578, 13307.519531, 14448.779297, 15676.171875]
corner = [[43.066406, 129.199218], [107.666015, 193.798828],
[172.265625, 258.398437], [236.865234, 344.531250],
[301.464843, 430.664062], [387.597656, 516.796875],
[473.730468, 624.462890], [559.863281, 732.128906],
[667.529296, 861.328125], [775.195312, 968.994140],
[904.394531, 1119.72656], [1012.060546, 1270.458984],
[1162.792968, 1421.191406], [1313.525390, 1593.457031],
[1464.257812, 1787.255859], [1636.523437, 2002.587890],
[1830.322265, 2217.919921], [2045.654296, 2454.785156],
[2260.986328, 2713.183593], [2497.851562, 2993.115234],
[2756.250000, 3294.580078], [3036.181640, 3617.578125],
[3337.646484, 3962.109375], [3660.644531, 4349.707031],
[4005.175781, 4758.837890], [4392.773437, 5211.035156],
[4801.904296, 5684.765625], [5254.101562, 6201.562500],
[5727.832031, 6782.958984], [6244.628906, 7385.888671],
[6826.025390, 8031.884765], [7428.955078, 8764.013671],
[8074.951171, 9517.675781], [8807.080078, 10357.470702],
[9560.742187, 11261.865238], [10400.537109, 12230.859375],
[11304.931640, 13285.986328], [12273.925781, 14427.246093],
[13329.052734, 15654.638671], [14470.312500, 16968.164062]]
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(np.allclose(filt.max(), 1. / 3))
self.assertTrue(np.allclose(filt.center_frequencies, center))
self.assertTrue(np.allclose(filt.corner_frequencies, corner))
class TestBarkFilterbankClass(unittest.TestCase):
def test_types(self):
filt = BarkFilterbank(np.arange(20000))
self.assertIsInstance(filt, BarkFilterbank)
self.assertTrue(filt.dtype == FILTER_DTYPE)
self.assertTrue(filt.bin_frequencies.dtype == float)
def test_errors(self):
with self.assertRaises(ValueError):
BarkFilterbank(np.arange(20000), 'foo')
def test_constant_types(self):
self.assertIsInstance(BarkFilterbank.FMIN, float)
self.assertIsInstance(BarkFilterbank.FMAX, float)
self.assertIsInstance(BarkFilterbank.NUM_BANDS, str)
self.assertIsInstance(BarkFilterbank.NORM_FILTERS, bool)
self.assertIsInstance(BarkFilterbank.UNIQUE_FILTERS, bool)
def test_constant_values(self):
self.assertEqual(BarkFilterbank.FMIN, 20.)
self.assertEqual(BarkFilterbank.FMAX, 15500.)
self.assertEqual(BarkFilterbank.NUM_BANDS, 'normal')
self.assertEqual(BarkFilterbank.NORM_FILTERS, True)
self.assertEqual(BarkFilterbank.UNIQUE_FILTERS, True)
def test_default_values(self):
filt = BarkFilterbank(FFT_FREQS_1024)
center = [43.066406, 129.199218, 236.865234, 344.53125, 452.197265,
559.863281, 689.0625, 839.794921, 990.527343, 1162.792968,
1356.591796, 1593.457031, 1851.855468, 2153.320312,
2497.851562, 2906.982421, 3402.246093, 4026.708984,
4823.4375, 5835.498046, 7041.357421, 8591.748046,
10723.535156, 13738.183593]
corner = [[21.533203, 86.132812], [107.666015, 172.265625],
[193.798828, 279.931640], [301.464843, 387.597656],
[409.130859, 495.263671], [516.796875, 602.929687],
[624.462890, 753.662109], [775.195312, 904.394531],
[925.927734, 1055.126953], [1076.660156, 1248.925781],
[1270.458984, 1464.257812], [1485.791015, 1701.123046],
[1722.656250, 1981.054687], [2002.587890, 2304.052734],
[2325.585937, 2670.117187], [2691.650390, 3122.314453],
[3143.847656, 3682.177734], [3703.710937, 4371.240234],
[4392.773437, 5275.634765], [5297.167968, 6373.828125],
[6395.361328, 7687.353515], [7708.886718, 9474.609375],
[9496.142578, 11972.460937], [11993.994140, 15482.373046]]
self.assertTrue(filt.num_bands == 24)
self.assertTrue(filt.num_bins == 1024)
self.assertTrue(np.allclose(filt.min(), 0))
self.assertTrue(filt.max() < 1)
self.assertTrue(np.allclose(filt.fmin, 21.5332031))
self.assertTrue(np.allclose(filt.fmax, 15482.3730468))
self.assertTrue(np.allclose(filt.center_frequencies, center))
self.assertTrue(np.allclose(filt.corner_frequencies, corner))
def test_double_values(self):
filt = BarkFilterbank(FFT_FREQS_1024, 'double')
center = [21.53320312, 64.59960938, 107.66601562, 150.73242188,
215.33203125, 258.3984375, 301.46484375, 366.06445312,
409.13085938, 473.73046875, 516.796875, 581.39648438,
645.99609375, 732.12890625, 796.72851562, 861.328125,
947.4609375, 1012.06054688, 1098.19335938, 1205.859375,
1313.52539062, 1421.19140625, 1528.85742188, 1636.5234375,
1765.72265625, 1916.45507812, 2067.1875, 2217.91992188,
2390.18554688, 2583.984375, 2777.78320312, 3014.6484375,
3251.51367188, 3531.4453125, 3832.91015625, 4177.44140625,
4586.57226562, 5038.76953125, 5534.03320312, 6072.36328125,
6675.29296875, 7342.82226562, 8096.484375, 8979.34570312,
9991.40625, 11240.33203125, 12726.12304688, 14491.84570312]
corner = [[21.53320312, 21.53320312], [43.06640625, 86.1328125],
[107.66601562, 129.19921875], [150.73242188, 172.265625],
[193.79882812, 236.86523438], [258.3984375, 279.93164062],
[301.46484375, 322.99804688], [344.53125, 387.59765625],
[409.13085938, 430.6640625], [452.19726562, 495.26367188],
[516.796875, 538.33007812], [559.86328125, 602.9296875],
[624.46289062, 689.0625], [710.59570312, 753.66210938],
[775.1953125, 818.26171875], [839.79492188, 904.39453125],
[925.92773438, 968.99414062], [990.52734375, 1055.12695312],