kopia lustrzana https://github.com/corrscope/corrscope
69 wiersze
2.0 KiB
Python
69 wiersze
2.0 KiB
Python
import warnings
|
|
|
|
import numpy as np
|
|
|
|
import pytest
|
|
|
|
from ovgenpy.wave import Wave
|
|
|
|
|
|
prefix = 'tests/wav-formats/'
|
|
wave_paths = [
|
|
# 2000 samples, with a full-scale peak at data[1000].
|
|
'u8-impulse1000.wav',
|
|
's16-impulse1000.wav',
|
|
's32-impulse1000.wav',
|
|
'f32-impulse1000.wav',
|
|
'f64-impulse1000.wav',
|
|
]
|
|
|
|
|
|
@pytest.mark.parametrize("wave_path", wave_paths)
|
|
def test_wave(wave_path):
|
|
with warnings.catch_warnings(record=True) as w:
|
|
# Cause all warnings to always be triggered.
|
|
warnings.simplefilter("always")
|
|
|
|
wave = Wave(None, prefix + wave_path)
|
|
data = wave[:]
|
|
|
|
# Audacity dithers <=16-bit WAV files upon export, creating a few bits of noise.
|
|
# As a result, amin(data) <= 0.
|
|
assert -0.01 < np.amin(data) <= 0
|
|
assert 0.99 < np.amax(data) <= 1
|
|
|
|
# check for FutureWarning (raised when determining wavfile type)
|
|
warns = [o for o in w if issubclass(o.category, FutureWarning)]
|
|
assert not [str(w) for w in warns]
|
|
|
|
|
|
def test_wave_subsampling():
|
|
wave = Wave(None, 'tests/sine440.wav')
|
|
# period = 48000 / 440 = 109.(09)*
|
|
|
|
wave.get_around(1000, region_nsamp=501, stride=4)
|
|
# len([:region_len:subsampling]) == ceil(region_len / subsampling)
|
|
# If region_len % subsampling != 0, len() != region_len // subsampling.
|
|
|
|
stride = 4
|
|
region = 100 # diameter = region * stride
|
|
for i in [-1000, 50000]:
|
|
data = wave.get_around(i, region, stride)
|
|
assert (data == 0).all()
|
|
|
|
|
|
def test_stereo_doesnt_overflow():
|
|
""" Ensure loud stereo tracks do not overflow. """
|
|
wave = Wave(None, 'tests/stereo in-phase.wav')
|
|
|
|
samp = 100
|
|
stride = 1
|
|
data = wave.get_around(wave.nsamp // 2, samp, stride)
|
|
assert np.amax(data) > 0.99
|
|
assert np.amin(data) < -0.99
|
|
|
|
# In the absence of overflow, sine waves have no large jumps.
|
|
# In the presence of overflow, stereo sum will jump between INT_MAX and INT_MIN.
|
|
# np.mean and rescaling converts to 0.499... and -0.5, which is nearly 1.
|
|
assert np.amax(np.abs(np.diff(data))) < 0.5
|