def test_signal_stub_times():
""" Test times vector of Signal stub.
"""
time = np.ones((1, 4))
freq = np.ones((1, 3))
sampling_rate = 1
fft_norm = 'none'
times = np.array([0., 1., 2., 3.])
signal_stub = stub_utils.signal_stub(time, freq, sampling_rate, fft_norm)
npt.assert_allclose(signal_stub.times, times, rtol=1e-10)
def test_signal_stub_frequencies_odd():
""" Test frequencies vector of Signal stub,
odd number of samples.
"""
time = np.ones((1, 5))
freq = np.ones((1, 3))
sampling_rate = 1
fft_norm = 'none'
frequencies = np.array([0., 0.2, 0.4])
signal_stub = stub_utils.signal_stub(time, freq, sampling_rate, fft_norm)
npt.assert_allclose(signal_stub.frequencies, frequencies, rtol=1e-10)
def test_signal_stub_properties():
""" Test comparing properties of Signal stub
with actual Signal implementation.
"""
time = np.ones((1, 1024))
freq = np.ones((1, 1024))
sampling_rate = 44100
fft_norm = 'none'
signal_stub = stub_utils.signal_stub(time, freq, sampling_rate, fft_norm)
stub_dir = dir(signal_stub)
signal_dir = dir(Signal(time, sampling_rate))
assert stub_dir.sort() == signal_dir.sort()
def impulse():
"""Delta impulse signal stub.
Returns
-------
signal : Signal
Stub of impulse signal
"""
delay = 0
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (1,)
time, freq = stub_utils.impulse_func(
delay, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
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 noise_two_by_two_channel():
""" 2-by-2 channel gaussian white noise signal stub.
The frequency spectrum is set to dummy value None.
Returns
-------
signal : Signal
Stub of noise signal
"""
sigma = 1
n_samples = int(1e5)
cshape = (2, 2)
sampling_rate = 44100
fft_norm = 'rms'
freq = None
time = stub_utils.noise_func(sigma, n_samples, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
def impulse_stub():
"""Delta impulse signal stub.
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 impulse signal
"""
delay = 0
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (1, )
time, freq = stub_utils.impulse_func(delay, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(time, freq, sampling_rate, fft_norm)
return signal
def noise_stub():
"""Gaussian white noise signal stub.
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 noise signal
"""
sigma = 1
n_samples = int(1e5)
cshape = (1, )
sampling_rate = 44100
fft_norm = 'rms'
time, freq = stub_utils.noise_func(sigma, n_samples, cshape)
signal = stub_utils.signal_stub(time, freq, sampling_rate, fft_norm)
return signal
def noise_two_by_three_channel():
""" 2-by-3 channel gaussian white noise signal stub.
The frequency spectrum is created with np.fft.rfft.
Returns
-------
signal : Signal
Stub of noise signal
"""
sigma = 1
n_samples = int(1e5)
cshape = (2, 3)
sampling_rate = 44100
fft_norm = 'none'
time = stub_utils.noise_func(sigma, n_samples, cshape)
freq = np.fft.rfft(time)
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_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 noise_odd():
"""Gaussian white noise signal stub,
odd number of samples.
The frequency spectrum is set to dummy value None.
Returns
-------
signal : Signal
Stub of noise signal
"""
sigma = 1
n_samples = int(1e5 - 1)
cshape = (1,)
sampling_rate = 44100
fft_norm = 'rms'
freq = None
time = stub_utils.noise_func(sigma, n_samples, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
return signal
def impulse_group_delay():
"""Delayed delta impulse signal stub with static properties.
Returns
-------
signal : Signal
Stub of impulse signal
group_delay : ndarray
Group delay of impulse signal
"""
delay = 1000
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (1,)
time, freq = stub_utils.impulse_func(
delay, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
group_delay = delay * np.ones_like(freq, dtype=float)
return signal, group_delay
def impulse_group_delay_two_by_two_channel():
"""Delayed 2-by-2 channel delta impulse signal stub with static properties.
Returns
-------
signal : Signal
Stub of impulse signal
group_delay : ndarray
Group delay of impulse signal
"""
delay = np.array([[1000, 2000], [3000, 4000]])
sampling_rate = 44100
n_samples = 10000
fft_norm = 'none'
cshape = (2, 2)
time, freq = stub_utils.impulse_func(
delay, n_samples, fft_norm, cshape)
signal = stub_utils.signal_stub(
time, freq, sampling_rate, fft_norm)
group_delay = delay[..., np.newaxis] * np.ones_like(freq, dtype=float)
return signal, group_delay
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
