def test_linear_sweep_deprecation():
with pytest.warns(PendingDeprecationWarning,
match="This function will be deprecated"):
pfs.linear_sweep(2**10, [1e3, 20e3])
if version.parse(pf.__version__) >= version.parse('0.5.0'):
with pytest.raises(AttributeError):
# remove linear_sweep() from pyfar 0.5.0!
pfs.linear_sweep(2**10, [1e3, 20e3])
def test_linear_sweep_amplitude_sampling_rate():
"""Test linear sweep with custom amplitude and sampling rate."""
sweep = pfs.linear_sweep(
2**10, [1e3, 20e3], amplitude=2, sampling_rate=48000)
assert sweep.sampling_rate == 48000
npt.assert_allclose(
np.max(np.abs(sweep.time)), np.array(2), rtol=1e-6, atol=1e-6)
def test_linear_sweep_against_reference():
"""Test linear sweep against manually verified reference."""
sweep = pfs.linear_sweep(2**10, [1e3, 20e3])
reference = np.loadtxt(os.path.join(
os.path.dirname(__file__), "references", "signals.linear_sweep.csv"))
npt.assert_allclose(sweep.time, np.atleast_2d(reference))
assert sweep.cshape == (1, )
assert sweep.n_samples == 2**10
assert sweep.sampling_rate == 44100
assert sweep.fft_norm == "rms"
assert sweep.comment == ("linear sweep between 1000.0 and 20000.0 Hz with "
"90 samples squared cosine fade-out.")
def test_linear_sweep_assertions():
"""Test assertions for linear sweep."""
with pytest.raises(ValueError, match="The sweep must be longer"):
pfs.linear_sweep(50, [1, 2])
with pytest.raises(ValueError, match="frequency_range must be an array"):
pfs.linear_sweep(100, 1)
with pytest.raises(ValueError, match="Upper frequency limit"):
pfs.linear_sweep(100, [1, 40e3])
def test_linear_sweep_float():
"""Test linear sweep with float number of samples."""
sweep = pfs.linear_sweep(100.6, [1e3, 20e3])
assert sweep.n_samples == 100
# Write linear sweep to csv for testing.
# The sweep was manually inspected.
# The time signal was inspected for smootheness and maximum amplitudes of +/-1.
# The spectrum was inspected for the ripple at the edges of the frequency range
# (typical for time domain sweep generation) and constant amplitude across
# frequency.
import numpy as np
from pyfar.signals import linear_sweep
sweep = linear_sweep(2**10, [1e3, 20e3]).time
np.savetxt("signals.linear_sweep.csv", sweep)