def test_sine_func_multi_channel():
"""Test generation of sine data, multiple channels.
"""
sampling_rate = 12
n_samples = 12
fft_norm = 'none'
cshape = (2, 2)
frequency_truth = np.array([[1, 2], [3, 4]])
sq3_2 = np.sqrt(3) / 2
time_truth = np.array(
[[[0, 0.5, sq3_2, 1, sq3_2, 0.5, 0, -0.5, -sq3_2, -1, -sq3_2, -0.5],
[
0, sq3_2, sq3_2, 0, -sq3_2, -sq3_2, 0, sq3_2, sq3_2, 0, -sq3_2,
-sq3_2
]],
[[0, 1, 0, -1, 0, 1, 0, -1, 0, 1, 0, -1],
[
0, sq3_2, -sq3_2, 0, sq3_2, -sq3_2, 0, sq3_2, -sq3_2, 0, sq3_2,
-sq3_2
]]])
freq_truth = np.array([[[0, -6j, 0, 0, 0, 0, 0], [0, 0, -6j, 0, 0, 0, 0]],
[[0, 0, 0, -6j, 0, 0, 0], [0, 0, 0, 0, -6j, 0, 0]]],
dtype=complex)
time, freq, frequency = stub_utils.sine_func(frequency_truth,
sampling_rate, n_samples,
fft_norm, cshape)
npt.assert_allclose(time,
time_truth,
rtol=1e-10,
atol=10 * np.finfo(float).eps)
npt.assert_allclose(freq, freq_truth, rtol=1e-10)
npt.assert_allclose(frequency, frequency_truth, rtol=1e-10)
def test_sine_func_value_error():
"""Test generation of sine data, value errors.
"""
n_samples = 4
fft_norm = 'none'
# Sampling theorem
cshape = (1, )
sampling_rate = 4
frequency_in = 2
with pytest.raises(ValueError):
stub_utils.sine_func(frequency_in, sampling_rate, n_samples, fft_norm,
cshape)
# Inconsistent input shape
cshape = (2, 2)
sampling_rate = 4
frequency_in = [1, 1]
with pytest.raises(ValueError):
stub_utils.sine_func(frequency_in, sampling_rate, n_samples, fft_norm,
cshape)
def test_sine_func_rms():
"""Test generation of sine,
RMS FFT normalization.
"""
n_samples = 4
sampling_rate = 4
fft_norm = 'rms'
cshape = (1, )
frequency_truth = 1
freq_truth = np.array([[0, -2j * np.sqrt(2) / n_samples, 0]],
dtype=complex)
_, freq, _ = stub_utils.sine_func(frequency_truth, sampling_rate,
n_samples, fft_norm, cshape)
npt.assert_allclose(freq, freq_truth, rtol=1e-10)
def sine():
"""Sine signal stub.
Returns
-------
signal : Signal
Stub of sine signal
"""
frequency = 441
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (1,)
time, freq, frequency = stub_utils.sine_func(
frequency, sampling_rate, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
def sine_two_by_two_channel():
"""2-by-2 channel sine signal stub.
Returns
-------
signal : Signal
Stub of sine signal
"""
frequency = np.array([[1, 2], [3, 4]]) * 441
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (2, 2)
time, freq, frequency = stub_utils.sine_func(
frequency, sampling_rate, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
def test_sine_func_frequency_adjustment():
"""Test generation of sine data, adjusted frequency.
"""
n_samples = 4
sampling_rate = 4
fft_norm = 'none'
cshape = (1, )
frequency_in = 1.5
frequency_truth = 1.
time_truth = np.array([[0, 1, 0, -1]])
freq_truth = np.array([[0, -2.j, 0]], dtype=complex)
time, freq, frequency = stub_utils.sine_func(frequency_in, sampling_rate,
n_samples, fft_norm, cshape)
npt.assert_allclose(time,
time_truth,
rtol=1e-10,
atol=10 * np.finfo(float).eps)
npt.assert_allclose(freq, freq_truth, rtol=1e-10)
assert frequency == frequency_truth
def sine_stub_odd():
"""Sine signal stub, odd number of samples
To be used in cases, when a dependence on the Signal class is prohibited,
but a correct, fixed relation of the time signal and the spectrum is
needed.
Returns
-------
signal : Signal
Stub of sine signal
"""
frequency = 441
sampling_rate = 44100
n_samples = 9999
fft_norm = 'rms'
cshape = (1, )
time, freq, frequency = stub_utils.sine_func(frequency, sampling_rate,
n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(time, freq, sampling_rate, fft_norm)
return signal
def sine_short():
"""Short sine signal stub where the first frequency is > 20 Hz.
This is used for testing plot._line._lower_frequency_limit.
Returns
-------
signal : Signal
Stub of sine signal
"""
frequency = 441
sampling_rate = 44100
n_samples = 100
fft_norm = 'none'
cshape = (1,)
time, freq, frequency = stub_utils.sine_func(
frequency, sampling_rate, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
def sine_odd_rms():
"""Sine signal stub,
odd number of samples,
RMS FFT-normalization
Returns
-------
signal : Signal
Stub of sine signal
"""
frequency = 441
sampling_rate = 44100
n_samples = 9999
fft_norm = 'rms'
cshape = (1,)
time, freq, frequency = stub_utils.sine_func(
frequency, sampling_rate, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
def sine_plus_impulse():
"""Combined sine and delta impulse signal stub.
Returns
-------
signal : Signal
Stub of sine signal
"""
frequency = 441
delay = 100
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (1,)
time_sine, freq_sine, frequency = stub_utils.sine_func(
frequency, sampling_rate, n_samples, fft_norm, cshape)
time_imp, freq_imp = stub_utils.impulse_func(
delay, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time_sine + time_imp, freq_sine + freq_imp, sampling_rate, fft_norm)
return signal
