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test_audio_signal.py
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# encoding: utf-8
# pylint: skip-file
"""
This file contains tests for the madmom.audio.signal module.
"""
from __future__ import absolute_import, division, print_function
import os
import tempfile
import unittest
from os.path import join as pj
import sys
from . import AUDIO_PATH, DATA_PATH
from .test_audio_comb_filters import sig_1d, sig_2d
from madmom.audio.signal import *
sample_file = pj(AUDIO_PATH, 'sample.wav')
sample_file_22k = pj(AUDIO_PATH, 'sample_22050.wav')
stereo_sample_file = pj(AUDIO_PATH, 'stereo_sample.wav')
tmp_file = tempfile.NamedTemporaryFile(delete=False).name
# test signal functions
class TestSmoothFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = smooth(sig_1d, None)
self.assertTrue(type(result) == type(sig_1d))
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
result = smooth(sig_1d, 3)
self.assertTrue(type(result) == type(sig_1d))
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
# multi-channel signals
result = smooth(sig_2d, None)
self.assertTrue(type(result) == type(sig_2d))
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
result = smooth(sig_2d, 3)
self.assertTrue(type(result) == type(sig_2d))
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
def test_errors(self):
with self.assertRaises(ValueError):
smooth(np.zeros(9).reshape(3, 3), -1)
with self.assertRaises(ValueError):
smooth(np.zeros(9).reshape(3, 3), 'bla')
with self.assertRaises(ValueError):
smooth(np.zeros(18).reshape(3, 3, 2), 4)
def test_values(self):
# mono signals
result = smooth(sig_1d, None)
self.assertTrue(np.allclose(result, sig_1d))
result = smooth(sig_1d, 0)
self.assertTrue(np.allclose(result, sig_1d))
result = smooth(sig_1d, 3)
result_3 = [0, 0.08, 1, 0.08, 0.08, 1, 0.08, 0.08, 1]
self.assertTrue(np.allclose(result, result_3))
result = smooth(sig_1d, 5)
result_5 = [0.08, 0.54, 1, 0.62, 0.62, 1, 0.62, 0.62, 1]
self.assertTrue(np.allclose(result, result_5))
result = smooth(sig_1d, 7)
result_7 = [0.31, 0.77, 1.08, 1.08, 1.08, 1.16, 1.08, 1.08, 1.08]
self.assertTrue(np.allclose(result, result_7))
result = smooth(sig_1d, np.ones(3))
result_3_ones = [0, 1, 1, 1, 1, 1, 1, 1, 1]
self.assertTrue(np.allclose(result, result_3_ones))
result = smooth(sig_1d, np.ones(4))
result_4_ones = [0, 1, 1, 1, 2, 1, 1, 2, 1]
self.assertTrue(np.allclose(result, result_4_ones))
# multi-channel signals
result = smooth(sig_2d, None)
self.assertTrue(np.allclose(result, sig_2d))
result = smooth(sig_2d, 3)
result_3 = [[0, 0.08, 1, 0.08, 0.08, 1, 0.08, 0.08, 1],
[1, 0.16, 1, 0.16, 1, 0.16, 1, 0.16, 1]]
self.assertTrue(np.allclose(result, np.asarray(result_3).T))
result = smooth(sig_2d, 5)
result_5 = [[0.08, 0.54, 1, 0.62, 0.62, 1, 0.62, 0.62, 1],
[1.08, 1.08, 1.16, 1.08, 1.16, 1.08, 1.16, 1.08, 1.08]]
self.assertTrue(np.allclose(result, np.asarray(result_5).T))
result = smooth(sig_2d, 7)
result_7 = [[0.31, 0.77, 1.08, 1.08, 1.08, 1.16, 1.08, 1.08, 1.08],
[1.31, 1.62, 1.62, 1.7, 1.62, 1.7, 1.62, 1.62, 1.31]]
self.assertTrue(np.allclose(result, np.asarray(result_7).T))
class TestAdjustGainFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = adjust_gain(sig_1d, 0)
self.assertTrue(type(result) == type(sig_1d))
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == sig_1d.dtype)
# same with int16 dtype
result = adjust_gain(sig_1d.astype(np.int16), 0)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == np.int16)
# from file
signal = Signal(sample_file)
result = adjust_gain(signal, 0)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.dtype == signal.dtype)
# multi-channel signals
result = adjust_gain(sig_2d, 0)
self.assertTrue(type(result) == type(sig_2d))
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == sig_2d.dtype)
# same with int dtype
result = adjust_gain(sig_2d.astype(np.int), 0)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == np.int)
def test_values(self):
# mono signals
result = adjust_gain(sig_1d, 0)
self.assertTrue(np.allclose(result, sig_1d))
result = adjust_gain(sig_1d, -10)
self.assertTrue(np.allclose(result, 0.31622777 * sig_1d))
result = adjust_gain(sig_1d, 10)
self.assertTrue(np.allclose(result, 3.1622777 * sig_1d))
# same with int dtype
result = adjust_gain(sig_1d.astype(np.int), 0)
self.assertTrue(np.allclose(result, sig_1d.astype(np.int)))
result = adjust_gain(sig_1d.astype(np.int), -5)
self.assertTrue(np.allclose(result, 0 * sig_1d))
# multi-channel signals
result = adjust_gain(sig_2d, 0)
self.assertTrue(np.allclose(result, sig_2d))
result = adjust_gain(sig_2d, -3)
self.assertTrue(np.allclose(result, 0.70794578 * sig_2d))
# same with int16 dtype
result = adjust_gain(sig_2d.astype(np.int16), 0)
self.assertTrue(np.allclose(result, sig_2d))
result = adjust_gain(sig_2d.astype(np.int16), -1)
self.assertTrue(np.allclose(result, 0 * sig_2d))
def test_errors(self):
with self.assertRaises(ValueError):
adjust_gain(sig_2d.astype(np.int16), +60)
class TestAttenuateFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = attenuate(sig_1d, 0)
self.assertTrue(type(result) == type(sig_1d))
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == sig_1d.dtype)
# same as int16 dtype
result = attenuate(sig_1d.astype(np.int16), 0)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == np.int16)
# from file
signal = Signal(sample_file)
result = attenuate(signal, 0)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.dtype == np.int16)
# multi-channel signals
result = attenuate(sig_2d, 0)
self.assertTrue(type(result) == type(sig_2d))
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == sig_2d.dtype)
# same as int dtype
result = attenuate(sig_2d.astype(np.int), 0)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == np.int)
def test_values(self):
# mono signals
result = attenuate(sig_1d, 0)
self.assertTrue(np.allclose(result, sig_1d))
result = attenuate(sig_1d, 10)
self.assertTrue(np.allclose(result, 0.31622777 * sig_1d))
result = attenuate(sig_1d, -10)
self.assertTrue(np.allclose(result, 3.1622777 * sig_1d))
# same with int dtype
result = attenuate(sig_1d.astype(np.int), 0)
self.assertTrue(np.allclose(result, sig_1d.astype(np.int)))
result = attenuate(sig_1d.astype(np.int), 5)
self.assertTrue(np.allclose(result, 0 * sig_1d))
# multi-channel signals
result = attenuate(sig_2d, 0)
self.assertTrue(np.allclose(result, sig_2d))
result = attenuate(sig_2d, 3)
self.assertTrue(np.allclose(result, 0.70794578 * sig_2d))
# same with int16 dtype
result = attenuate(sig_2d.astype(np.int16), 0)
self.assertTrue(np.allclose(result, sig_2d))
result = attenuate(sig_2d.astype(np.int16), 1)
self.assertTrue(np.allclose(result, 0 * sig_2d))
def test_errors(self):
with self.assertRaises(ValueError):
attenuate(sig_2d.astype(np.int16), -10)
class TestNormalizeFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = normalize(sig_1d)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == sig_1d.dtype)
# same as int16 dtype
result = normalize(sig_1d.astype(np.int16))
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == np.int16)
# from file
signal = Signal(sample_file)
result = normalize(signal)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.dtype == np.int16)
# multi-channel signals
result = normalize(sig_2d)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == sig_2d.dtype)
# same as int32 dtype
result = normalize(sig_2d.astype(np.int32))
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == np.int32)
def test_values(self):
# mono signals
result = normalize(sig_1d)
self.assertTrue(np.allclose(result, sig_1d))
result = normalize(sig_1d * 0.5)
self.assertTrue(np.allclose(result, sig_1d))
self.assertTrue(np.max(result) == 1)
# same as int16 dtype
result = normalize(10 * sig_1d.astype(np.int16))
self.assertTrue(np.allclose(result, sig_1d * 32767))
self.assertTrue(np.max(result) == 32767)
# multi-channel signals
result = normalize(sig_2d)
self.assertTrue(np.allclose(result, sig_2d))
self.assertTrue(np.max(result) == 1)
# negative values
result = normalize(sig_2d * 4 - 2)
self.assertTrue(np.allclose(result, sig_2d * 2 - 1))
self.assertTrue(result.max() == 1)
self.assertTrue(result.min() == -1)
# same as int32 dtype
result = normalize(3 * sig_2d.astype(np.int32))
self.assertTrue(np.allclose(result, sig_2d * 2147483647))
self.assertTrue(np.max(result) == 2147483647)
def test_errors(self):
with self.assertRaises(ValueError):
normalize(sig_2d.astype(np.int64))
class TestMixFunction(unittest.TestCase):
mono_2d = np.asarray([0.5, 0, 1, 0, 0.5, 0.5, 0.5, 0, 1], dtype=np.float)
def test_types(self):
# mono signals
result = remix(sig_1d, 1)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == sig_1d.dtype)
result = remix(sig_1d, 2)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == (len(sig_1d), 2))
self.assertTrue(result.dtype == sig_1d.dtype)
result = remix(sig_1d, 3)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == (len(sig_1d), 3))
self.assertTrue(result.dtype == sig_1d.dtype)
# same as int dtype
result = remix(sig_1d.astype(np.int), 1)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == np.int)
result = remix(sig_1d.astype(np.int), 2)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == (len(sig_1d), 2))
self.assertTrue(result.dtype == np.int)
# from file
signal = Signal(sample_file)
result = remix(signal, 1)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == np.int16)
# multi-channel signals
result = remix(sig_2d, 1)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == sig_2d.dtype)
result = remix(sig_2d, 2)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == sig_2d.dtype)
# from file
signal = Signal(stereo_sample_file)
result = remix(signal, 1)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == np.int16)
result = remix(signal, 2)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == np.int16)
with self.assertRaises(NotImplementedError):
remix(sig_2d, 3)
# same as int dtype
result = remix(sig_2d.astype(np.int), 1)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == np.int)
result = remix(sig_2d.astype(np.int), 2)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == np.int)
def test_values(self):
# mono signals
result = remix(sig_1d, 1)
self.assertTrue(np.allclose(result, sig_1d))
# same as int dtype
result = remix(sig_2d.astype(np.int), 1)
self.assertTrue(np.allclose(result, self.mono_2d.astype(np.int)))
# multi-channel signals
result = remix(sig_2d, 1)
self.assertTrue(np.allclose(result, self.mono_2d))
# same as int dtype
result = remix(2 * sig_2d.astype(np.int), 1)
self.assertTrue(np.allclose(result, 2 * self.mono_2d))
class TestResampleFunction(unittest.TestCase):
def setUp(self):
self.signal = Signal(sample_file)
self.signal_22k = Signal(sample_file_22k)
self.signal_float = Signal(sample_file, dtype=np.float32)
self.stereo_signal = Signal(stereo_sample_file)
self.float_target = np.array([-0.07537885, -0.077897, -0.08440731,
-0.07527363, -0.06685895, -0.05827513])
def test_types(self):
# mono signal
result = resample(self.signal, 22050)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == self.signal.dtype)
# stereo signal
result = resample(self.stereo_signal, 22050)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == self.stereo_signal.dtype)
def test_values_mono(self):
result = resample(self.signal, 22050)
self.assertEqual(result.sample_rate, 22050)
self.assertEqual(result.num_samples, 61741)
self.assertEqual(result.dtype, self.signal.dtype)
self.assertEqual(result.num_channels, self.signal.num_channels)
self.assertTrue(np.allclose(result.length, self.signal.length))
self.assertTrue(np.allclose(result, self.signal_22k))
def test_values_mono_float(self):
result = resample(self.signal_float, 22050)
self.assertEqual(result.sample_rate, 22050)
self.assertEqual(result.num_samples, 61741)
self.assertEqual(result.dtype, self.signal_float.dtype)
self.assertEqual(result.num_channels, self.signal_float.num_channels)
self.assertTrue(np.allclose(result.length, self.signal_float.length))
self.assertTrue(np.allclose(result[:6], self.float_target))
def test_values_dtype(self):
result = resample(self.signal, 22050, dtype=np.float32)
self.assertEqual(result.sample_rate, 22050)
self.assertEqual(result.num_samples, 61741)
self.assertEqual(result.dtype, np.float32)
self.assertEqual(result.num_channels, self.signal_float.num_channels)
self.assertTrue(np.allclose(result.length, self.signal_float.length))
self.assertTrue(np.allclose(result[:6], self.float_target))
def test_values_stereo(self):
result = resample(self.stereo_signal, 22050)
self.assertEqual(result.sample_rate, 22050)
self.assertEqual(result.num_samples, 91460)
self.assertEqual(result.dtype, self.stereo_signal.dtype)
self.assertEqual(result.num_channels, self.stereo_signal.num_channels)
self.assertTrue(np.allclose(result.length, self.stereo_signal.length))
self.assertTrue(np.allclose(result[:6],
[[34, 38], [32, 33], [37, 31],
[35, 35], [32, 34], [33, 34]]))
def test_values_upmixing(self):
result = resample(self.signal, 22050, num_channels=2)
self.assertEqual(result.sample_rate, 22050)
self.assertEqual(result.num_samples, 61741)
self.assertEqual(result.dtype, self.signal.dtype)
self.assertEqual(result.num_channels, 2)
self.assertTrue(np.allclose(result.length, self.signal.length))
stereo = np.vstack((self.signal_22k, self.signal_22k)).T / np.sqrt(2)
self.assertTrue(np.allclose(result, stereo, atol=np.sqrt(2)))
def test_values_downmixing(self):
result = resample(self.stereo_signal, 22050, num_channels=1)
self.assertEqual(result.sample_rate, 22050)
self.assertEqual(result.num_samples, 91460)
self.assertEqual(result.dtype, self.stereo_signal.dtype)
self.assertEqual(result.num_channels, 1)
self.assertTrue(np.allclose(result.length, self.stereo_signal.length))
self.assertTrue(np.allclose(result[:6], [36, 33, 34, 35, 33, 34]))
def test_errors(self):
with self.assertRaises(ValueError):
resample(sig_1d, 2)
class TestRescaleFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = rescale(sig_1d, np.float)
self.assertTrue(len(result) == len(sig_1d))
self.assertTrue(result.shape == sig_1d.shape)
self.assertTrue(result.dtype == np.float)
# from file
signal = Signal(sample_file)
result = rescale(signal)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == np.float32)
# multi-channel signals
result = rescale(sig_2d, np.float16)
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.shape == sig_2d.shape)
self.assertTrue(result.dtype == np.float16)
# from file
signal = Signal(stereo_sample_file)
result = rescale(signal, np.float)
self.assertTrue(isinstance(result, Signal))
self.assertTrue(isinstance(result, np.ndarray))
self.assertTrue(result.dtype == np.float)
def test_errors(self):
with self.assertRaises(ValueError):
rescale(sig_2d, np.complex)
with self.assertRaises(ValueError):
rescale(sig_2d, np.int)
def test_values(self):
# mono signals
result = rescale(sig_1d, np.float)
self.assertTrue(np.allclose(result, sig_1d))
# from file
signal = Signal(sample_file)
result = rescale(signal)
self.assertTrue(np.allclose(result[:6],
[-0.07611316, -0.07660146, -0.07580798,
-0.08172857, -0.08645894, -0.08212531]))
# multi-channel signals
result = rescale(sig_2d, np.float16)
self.assertTrue(np.allclose(result, sig_2d))
# from file
signal = Signal(stereo_sample_file)
result = rescale(signal, np.float)
self.assertTrue(np.allclose(result[:6], [[0.00100711, 0.0011597],
[0.00106815, 0.00109867],
[0.00088504, 0.00103763],
[0.00109867, 0.00094607],
[0.00112918, 0.00091556],
[0.00109867, 0.00103763]]))
class TestTrimFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = trim(sig_1d)
self.assertTrue(type(result) == type(sig_1d))
self.assertTrue(result.ndim == sig_1d.ndim)
self.assertTrue(result.dtype == sig_1d.dtype)
signal = Signal(sample_file)
result = trim(signal)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.ndim == signal.ndim)
self.assertTrue(result.dtype == np.int16)
# multi-channel signals
result = trim(sig_2d)
self.assertTrue(type(result) == type(sig_2d))
self.assertTrue(len(result) == len(sig_2d))
self.assertTrue(result.ndim == sig_2d.ndim)
self.assertTrue(result.dtype == sig_2d.dtype)
signal = Signal(stereo_sample_file)
result = trim(signal)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.ndim == signal.ndim)
self.assertTrue(result.dtype == np.int16)
def test_values(self):
# mono signals
result = trim(sig_1d)
trimmed_1d = [1, 0, 0, 1, 0, 0, 1]
self.assertTrue(np.allclose(result, trimmed_1d))
self.assertTrue(len(result) == len(sig_1d) - 2)
# multi-channel signals
# signal has leading zeros only in one channel
result = trim(sig_2d)
self.assertTrue(result.shape == sig_2d.shape)
signal = Signal(stereo_sample_file)
result = trim(signal)
self.assertTrue(result.shape == signal.shape)
# signal with leading zeros only in both channels
signal = np.tile(np.arange(5), 2).reshape(2, 5).T
result = trim(signal)
self.assertTrue(result.shape == (4, 2))
self.assertTrue(np.allclose(result[:, 0], np.arange(1, 5)))
self.assertTrue(np.allclose(result[:, 1], np.arange(1, 5)))
class TestEnergyFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = energy(sig_1d)
self.assertIsInstance(result, float)
# multi-channel signals
result = energy(sig_2d)
self.assertIsInstance(result, float)
def test_values(self):
# mono signals
result = energy(sig_1d)
self.assertTrue(np.allclose(result, 3))
result = energy(np.zeros(100))
self.assertTrue(np.allclose(result, 0))
# multi-channel signals
result = energy(sig_2d)
self.assertTrue(np.allclose(result, 8))
result = energy(np.zeros(100).reshape(-1, 2))
self.assertTrue(np.allclose(result, 0))
def test_frames(self):
# mono signals
frames = FramedSignal(sig_1d, frame_size=4, hop_size=2)
result = energy(frames)
self.assertTrue(np.allclose(result, [0, 1, 2, 1, 1]))
result = energy(np.zeros(100))
self.assertTrue(np.allclose(result, 0))
# multi-channel signals
frames = FramedSignal(sig_2d, frame_size=4, hop_size=2)
result = energy(frames)
self.assertTrue(np.allclose(result, [1, 3, 4, 3, 3]))
result = energy(np.zeros(100).reshape(-1, 2))
self.assertTrue(np.allclose(result, 0))
class TestRootMeanSquareFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = root_mean_square(sig_1d)
self.assertIsInstance(result, float)
# multi-channel signals
result = root_mean_square(sig_2d)
self.assertIsInstance(result, float)
def test_values(self):
# mono signals
result = root_mean_square(sig_1d)
self.assertTrue(np.allclose(result, 0.57735026919))
result = root_mean_square(np.zeros(100))
self.assertTrue(np.allclose(result, 0))
# multi-channel signals
result = root_mean_square(sig_2d)
self.assertTrue(np.allclose(result, 2. / 3))
result = root_mean_square(np.zeros(100).reshape(-1, 2))
self.assertTrue(np.allclose(result, 0))
def test_frames(self):
# mono signals
frames = FramedSignal(sig_1d, frame_size=4, hop_size=2)
result = root_mean_square(frames)
self.assertTrue(np.allclose(result, [0, 0.5, 0.70710678, 0.5, 0.5]))
result = root_mean_square(np.zeros(100))
self.assertTrue(np.allclose(result, 0))
# multi-channel signals
frames = FramedSignal(sig_2d, frame_size=4, hop_size=2)
result = root_mean_square(frames)
self.assertTrue(np.allclose(result, [0.35355339, 0.61237244,
0.70710678, 0.61237244,
0.61237244]))
result = root_mean_square(np.zeros(100).reshape(-1, 2))
self.assertTrue(np.allclose(result, 0))
class TestSoundPressureLevelFunction(unittest.TestCase):
def test_types(self):
# mono signals
result = sound_pressure_level(sig_1d)
self.assertIsInstance(result, float)
# multi-channel signals
result = sound_pressure_level(sig_2d)
self.assertIsInstance(result, float)
def test_values(self):
# mono signals
result = sound_pressure_level(sig_1d)
self.assertTrue(np.allclose(result, -4.7712125472))
# silence
result = sound_pressure_level(np.zeros(100))
self.assertTrue(np.allclose(result, -np.finfo(float).max))
# maximum float amplitude, alternating between -1 and 1
sinus = np.cos(np.linspace(0, 2 * np.pi * 100, 2 * 100 + 1))
result = sound_pressure_level(sinus)
self.assertTrue(np.allclose(result, 0.))
# maximum int16 amplitude, alternating between -1 and 1
sinus_int16 = (sinus * np.iinfo(np.int16).max).astype(np.int16)
result = sound_pressure_level(sinus_int16)
self.assertTrue(np.allclose(result, 0.))
# multi-channel signals
result = sound_pressure_level(sig_2d)
self.assertTrue(np.allclose(result, -3.52182518111))
# silence
result = sound_pressure_level(np.zeros(100).reshape(-1, 2))
self.assertTrue(np.allclose(result, -np.finfo(float).max))
# maximum float amplitude, alternating between -1 and 1
sig = remix(sinus, 2)
result = sound_pressure_level(sig)
self.assertTrue(np.allclose(result, 0.))
# maximum int16 amplitude, alternating between -1 and 1
sig = remix(sinus_int16, 2)
result = sound_pressure_level(sig)
self.assertTrue(np.allclose(result, 0.))
def test_frames(self):
# mono signals
frames = FramedSignal(sig_1d, frame_size=4, hop_size=2)
result = sound_pressure_level(frames)
self.assertTrue(np.allclose(result, [-np.finfo(float).max, -6.0206,
-3.0103, -6.0206, -6.0206]))
result = sound_pressure_level(np.zeros(100))
self.assertTrue(np.allclose(result, -np.finfo(float).max))
# multi-channel signals
frames = FramedSignal(sig_2d, frame_size=4, hop_size=2)
result = sound_pressure_level(frames)
self.assertTrue(np.allclose(result, [-9.03089987, -4.25968732,
-3.01029996, -4.25968732,
-4.25968732]))
result = sound_pressure_level(np.zeros(100).reshape(-1, 2))
self.assertTrue(np.allclose(result, -np.finfo(float).max))
class TestLoadWaveFileFunction(unittest.TestCase):
def test_types(self):
signal, sample_rate = load_wave_file(sample_file)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
def test_file_handle(self):
# open file handle
file_handle = open(sample_file, 'rb')
signal, sample_rate = load_wave_file(file_handle)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
def test_values(self):
# test wave loader
signal, sample_rate = load_wave_file(sample_file)
self.assertTrue(np.allclose(signal[:5],
[-2494, -2510, -2484, -2678, -2833]))
self.assertTrue(len(signal) == 123481)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (123481,))
# stereo
signal, sample_rate = load_wave_file(stereo_sample_file)
self.assertTrue(np.allclose(signal[:4],
[[33, 38], [35, 36], [29, 34], [36, 31]]))
self.assertTrue(len(signal) == 182919)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (182919, 2))
def test_start_stop(self):
# test wave loader
signal, sample_rate = load_wave_file(sample_file, start=1. / 44100,
stop=5. / 44100)
self.assertTrue(np.allclose(signal, [-2510, -2484, -2678, -2833]))
self.assertTrue(len(signal) == 4)
self.assertTrue(sample_rate == 44100)
def test_downmix(self):
# test wave loader
signal, sample_rate = load_wave_file(stereo_sample_file,
num_channels=1)
self.assertTrue(np.allclose(signal[:5], [35, 35, 31, 33, 33]))
self.assertTrue(len(signal) == 182919)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (182919, ))
def test_upmix(self):
signal, sample_rate = load_wave_file(sample_file, num_channels=2)
self.assertTrue(np.allclose(signal[:5],
[[-2494, -2494], [-2510, -2510],
[-2484, -2484], [-2678, -2678],
[-2833, -2833]]))
self.assertTrue(len(signal) == 123481)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (123481, 2))
def test_errors(self):
# resampling of wav not supported
with self.assertRaises(ValueError):
load_wave_file(sample_file, sample_rate=22050)
# resampling of wav not supported
with self.assertRaises(ValueError):
load_wave_file(sample_file, dtype=np.float)
# file not found
with self.assertRaises(IOError):
load_wave_file(pj(AUDIO_PATH, 'foo_bar.wav'))
# not an audio file
with self.assertRaises(ValueError):
load_wave_file(pj(DATA_PATH, 'README'))
# closed file handle
with self.assertRaises(ValueError):
file_handle = open(sample_file, 'rb')
file_handle.close()
load_wave_file(file_handle)
class TestWriteWaveFileFunction(unittest.TestCase):
def setUp(self):
self.signal = Signal(sample_file)
write_wave_file(self.signal, tmp_file)
self.result = Signal(sample_file)
def test_types(self):
self.assertIsInstance(self.result, Signal)
self.assertIsInstance(self.result, np.ndarray)
self.assertTrue(self.result.dtype == np.int16)
self.assertTrue(type(self.result.sample_rate) == int)
def test_values(self):
# test wave loader
self.assertTrue(np.allclose(self.signal, self.result))
self.assertTrue(self.result.sample_rate == 44100)
self.assertTrue(self.result.shape == (123481,))
class TestLoadAudioFileFunction(unittest.TestCase):
# this tests both the madmom.audio.signal.load_wave_file() and the
# madmom.audio.ffmpeg.load_ffmpeg_file() functions via the universal
# load_audio_file() function
def test_types(self):
# test wave loader
signal, sample_rate = load_audio_file(sample_file)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
# test ffmpeg loader
signal, sample_rate = load_audio_file(stereo_sample_file)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
if sys.version_info[0] == 2:
# test unicode string type (Python 2 only)
signal, sample_rate = load_audio_file(unicode(sample_file))
def test_file_handle(self):
# test wave loader
file_handle = open(sample_file)
signal, sample_rate = load_audio_file(file_handle)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
file_handle.close()
# closed file handle
signal, sample_rate = load_audio_file(file_handle)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
# test ffmpeg loader
file_handle = open(sample_file)
signal, sample_rate = load_audio_file(file_handle)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
file_handle.close()
# closed file handle
signal, sample_rate = load_audio_file(file_handle)
self.assertIsInstance(signal, np.ndarray)
self.assertTrue(signal.dtype == np.int16)
self.assertTrue(type(sample_rate) == int)
def test_values(self):
# test wave loader
signal, sample_rate = load_audio_file(sample_file)
self.assertTrue(np.allclose(signal[:5],
[-2494, -2510, -2484, -2678, -2833]))
self.assertTrue(len(signal) == 123481)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (123481,))
# stereo
signal, sample_rate = load_audio_file(stereo_sample_file)
self.assertTrue(np.allclose(signal[:4],
[[33, 38], [35, 36], [29, 34], [36, 31]]))
self.assertTrue(len(signal) == 182919)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (182919, 2))
# test ffmpeg loader
signal, sample_rate = load_audio_file(stereo_sample_file)
self.assertTrue(np.allclose(signal[:4],
[[33, 38], [35, 36], [29, 34], [36, 31]]))
self.assertTrue(len(signal) == 182919)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (182919, 2))
def test_start_stop(self):
# test wave loader
signal, sample_rate = load_audio_file(sample_file, start=1. / 44100,
stop=5. / 44100)
self.assertTrue(np.allclose(signal, [-2510, -2484, -2678, -2833]))
self.assertTrue(len(signal) == 4)
self.assertTrue(sample_rate == 44100)
# test ffmpeg loader
signal, sample_rate = load_audio_file(stereo_sample_file,
start=1. / 44100,
stop=4. / 44100)
self.assertTrue(np.allclose(signal, [[35, 36], [29, 34], [36, 31]]))
self.assertTrue(len(signal) == 3)
self.assertTrue(sample_rate == 44100)
def test_downmix(self):
# test wave loader
signal, sample_rate = load_audio_file(stereo_sample_file,
num_channels=1)
self.assertTrue(np.allclose(signal[:5],
[35, 35, 31, 33, 33]))
self.assertTrue(len(signal) == 182919)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (182919, ))
# test ffmpeg loader
signal, sample_rate = load_audio_file(stereo_sample_file,
num_channels=1)
# results are rounded differently, thus allow atol=1
self.assertTrue(np.allclose(signal[:5], [35, 35, 31, 33, 33], atol=1))
# avconv results in a different length of 182909 samples
self.assertTrue(np.allclose(len(signal), 182919, atol=10))
self.assertTrue(sample_rate == 44100)
# test clipping
f = pj(AUDIO_PATH, 'stereo_chirp.wav')
signal, _ = load_audio_file(f, num_channels=1)
signal_stereo, _ = load_audio_file(f)
# sanity checks
self.assertTrue(np.allclose(signal_stereo[:, 0], signal_stereo[:, 1]))
self.assertTrue(np.allclose(signal_stereo.mean(axis=1),
signal_stereo[:, 0]))
# check clipping
self.assertTrue(np.allclose(signal, signal_stereo[:, 1]))
def test_upmix(self):
signal, sample_rate = load_audio_file(sample_file, num_channels=2)
self.assertTrue(np.allclose(signal[:5],
[[-2494, -2494], [-2510, -2510],
[-2484, -2484], [-2678, -2678],
[-2833, -2833]]))
self.assertTrue(len(signal) == 123481)
self.assertTrue(sample_rate == 44100)
self.assertTrue(signal.shape == (123481, 2))
def test_resample(self):
# method must chose ffmpeg loader
signal, sample_rate = load_audio_file(stereo_sample_file,
sample_rate=22050)
self.assertTrue(sample_rate == 22050)
# avconv does round differently, thus allow atol=1
# result: [[33, 38], [33, 33], [36, 31], [35, 35], [32, 35]]
self.assertTrue(np.allclose(signal[:5], [[34, 38], [32, 33], [37, 31],
[35, 35], [32, 34]], atol=1))
# also downmix
signal, sample_rate = load_audio_file(stereo_sample_file,
sample_rate=22050,
num_channels=1)
self.assertTrue(np.allclose(signal[:5], [36, 33, 34, 35, 33], atol=1))
# avconv results in a different length of 91450 samples
self.assertTrue(np.allclose(len(signal), 91460, atol=10))
def test_errors(self):
# file not found
with self.assertRaises(IOError):
load_audio_file(pj(AUDIO_PATH, 'sample.flac'))
# not an audio file
with self.assertRaises(LoadAudioFileError):
load_audio_file(pj(DATA_PATH, 'README'))
# signal classes
class TestSignalClass(unittest.TestCase):
def test_types_array(self):
result = Signal(sig_1d)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.dtype == np.float)
self.assertIsInstance(result.start, type(None))
self.assertIsInstance(result.stop, type(None))
self.assertIsInstance(result.num_samples, int)
self.assertIsInstance(result.sample_rate, type(None))
self.assertIsInstance(result.num_channels, int)
self.assertIsInstance(result.length, type(None))
self.assertIsInstance(result.ndim, int)
def test_types_array_with_sample_rate(self):
result = Signal(sig_1d, 1)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.dtype == np.float)
self.assertIsInstance(result.start, type(None))
self.assertIsInstance(result.stop, type(None))
self.assertIsInstance(result.num_samples, int)
self.assertIsInstance(result.sample_rate, int)
self.assertIsInstance(result.num_channels, int)
self.assertIsInstance(result.length, float)
self.assertIsInstance(result.ndim, int)
def test_types_file(self):
result = Signal(sample_file)
self.assertIsInstance(result, Signal)
self.assertIsInstance(result, np.ndarray)
self.assertTrue(result.dtype == np.int16)
def test_values_1d(self):
result = Signal(sig_1d, 1)
self.assertTrue(np.allclose(result, sig_1d))
self.assertTrue(len(result) == 9)
self.assertTrue(result.num_samples == 9)
self.assertTrue(result.sample_rate == 1)
self.assertTrue(result.num_channels == 1)
self.assertTrue(result.length == 9)
def test_values_1d_no_sample_rate(self):
result = Signal(sig_1d)
self.assertTrue(np.allclose(result, sig_1d))
self.assertTrue(len(result) == 9)
self.assertTrue(result.num_samples == 9)
self.assertTrue(result.sample_rate is None)
self.assertTrue(result.num_channels == 1)
self.assertTrue(result.length is None)
def test_values_2d(self):
result = Signal(sig_2d, 12.3)
self.assertTrue(np.allclose(result, sig_2d))
self.assertTrue(len(result) == 9)
self.assertTrue(result.num_samples == 9)
# not officially supported, but Signal can handle float sample rates
self.assertTrue(result.sample_rate == 12.3)
self.assertTrue(result.num_channels == 2)
self.assertTrue(result.length == 9 / 12.3)
self.assertTrue(result.ndim == 2)
def test_values_file(self):
result = Signal(sample_file)
self.assertTrue(np.allclose(result[:5],
[-2494, -2510, -2484, -2678, -2833]))
self.assertTrue(len(result) == 123481)
self.assertTrue(result.num_samples == 123481)
self.assertTrue(result.sample_rate == 44100)
self.assertTrue(result.num_channels == 1)