def test_contiguity(order, shape, axis):
x = np.zeros(shape, dtype=np.float, order=order)
sr_orig = 1
sr_new = 2
y = resamcupy.resample(x, sr_orig, sr_new, axis=axis)
assert x.flags['C_CONTIGUOUS'] == y.flags['C_CONTIGUOUS']
assert x.flags['F_CONTIGUOUS'] == y.flags['F_CONTIGUOUS']
def test_shape(axis):
sr_orig = 100
sr_new = sr_orig // 2
X = np.random.randn(sr_orig, sr_orig, sr_orig)
Y = resamcupy.resample(X, sr_orig, sr_new, axis=axis)
target_shape = list(X.shape)
target_shape[axis] = target_shape[axis] * sr_new // sr_orig
assert target_shape == list(Y.shape)
def test_good_window():
sr_orig = 100
sr_new = 200
x = np.random.randn(500)
y = resamcupy.resample(x,
sr_orig,
sr_new,
filter='sinc_window',
window=scipy.signal.blackman)
assert len(y) == 2 * len(x)
def test_quality_sweep(sr_orig, sr_new, fil, rms):
FREQ = 8192
DURATION = 5.0
x = make_sweep(FREQ, sr_orig, DURATION)
y = make_sweep(FREQ, sr_new, DURATION)
y_pred = resamcupy.resample(x, sr_orig, sr_new, filter=fil)
idx = slice(sr_new // 2, -sr_new // 2)
err = np.mean(np.abs(y[idx] - y_pred[idx]))
assert err <= rms, '{:g} > {:g}'.format(err, rms)
def test_quality_sine(sr_orig, sr_new, fil, rms):
FREQ = 512.0
DURATION = 2.0
x = make_tone(FREQ, sr_orig, DURATION)
y = make_tone(FREQ, sr_new, DURATION)
y_pred = resamcupy.resample(x, sr_orig, sr_new, filter=fil)
idx = slice(sr_new // 2, -sr_new // 2)
err = cp.mean(cp.abs(y[idx] - y_pred[idx]))
assert err <= rms #, '{:g} > {:g}'.format(err, rms)
def test_short_signal():
x = np.zeros(2)
resamcupy.resample(x, 4, 1)
def test_bad_window():
x = np.zeros(100)
resamcupy.resample(x, 100, 200, filter='sinc_window', window=np.ones(50))
def test_dtype(dtype):
x = np.random.randn(100).astype(dtype)
y = resamcupy.resample(x, 100, 200)
assert x.dtype == y.dtype
def test_bad_num_zeros():
x = np.zeros(100)
resamcupy.resample(x, 100, 50, filter='sinc_window', num_zeros=0)
def test_bad_precision():
x = np.zeros(100)
resamcupy.resample(x, 100, 50, filter='sinc_window', precision=-1)
def test_bad_rolloff(rolloff):
x = np.zeros(100)
resamcupy.resample(x, 100, 50, filter='sinc_window', rolloff=rolloff)
def test_bad_sr(sr_orig, sr_new):
x = np.zeros(100)
resamcupy.resample(x, sr_orig, sr_new)
