def test_directed_transfer_function():
c = Connectivity(fourier_coefficients=np.empty((1, )))
type(c)._transfer_function = PropertyMock(
return_value=np.arange(1, 5).reshape((2, 2)))
dtf = c.directed_transfer_function()
assert np.allclose(dtf.sum(axis=-1), 1.0)
assert np.all((dtf >= 0.0) & (dtf <= 1.0))
def test_partial_directed_coherence():
c = Connectivity(fourier_coefficients=np.empty((1, )))
type(c)._MVAR_Fourier_coefficients = PropertyMock(
return_value=np.arange(1, 5).reshape((2, 2)))
pdc = c.partial_directed_coherence()
assert np.allclose(pdc.sum(axis=-2), 1.0)
assert np.all((pdc >= 0.0) & (pdc <= 1.0))
def test_pairwise_phase_consistency():
'''Test that incoherent signals are set to zero or below
and that differences in power are ignored.'''
np.random.seed(0)
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 200, 5,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
magnitude1 = np.random.uniform(
0.5, 3, (n_time_samples, n_trials, n_tapers, n_fft_samples))
angles1 = np.random.uniform(
0, 2 * np.pi, (n_time_samples, n_trials, n_tapers, n_fft_samples))
magnitude2 = np.random.uniform(
0.5, 3, (n_time_samples, n_trials, n_tapers, n_fft_samples))
angles2 = np.random.uniform(
0, 2 * np.pi, (n_time_samples, n_trials, n_tapers, n_fft_samples))
fourier_coefficients[..., 0] = magnitude1 * np.exp(1j * angles1)
fourier_coefficients[..., 1] = magnitude2 * np.exp(1j * angles2)
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
ppc = this_Conn.pairwise_phase_consistency()
# set diagonal to zero because its always 1
diagonal_ind = np.arange(0, n_signals)
ppc[..., diagonal_ind, diagonal_ind] = 0
assert np.all(ppc < np.finfo(float).eps)
def test_weighted_phase_lag_index_sets_zero_phase_signals_to_zero():
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 30, 1,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
fourier_coefficients[..., :] = [2 * np.exp(1j * 0), 3 * np.exp(1j * 0)]
expected_phase_lag_index = np.zeros((2, 2))
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(this_Conn.weighted_phase_lag_index().squeeze(),
expected_phase_lag_index)
def test_weighted_phase_lag_index_is_same_as_phase_lag_index():
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 30, 1,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
fourier_coefficients[..., :] = [
1 * np.exp(1j * 3 * np.pi / 4), 1 * np.exp(1j * 5 * np.pi / 4)
]
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(this_Conn.phase_lag_index(),
this_Conn.weighted_phase_lag_index())
def test_imaginary_coherence():
'''Test that imaginary coherence sets signals with the same phase
to zero.'''
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 30, 1,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
fourier_coefficients[..., :] = [2 * np.exp(1j * 0), 3 * np.exp(1j * 0)]
expected_imaginary_coherence = np.zeros((2, 2))
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(this_Conn.imaginary_coherence().squeeze(),
expected_imaginary_coherence)
def test_phase_locking_value():
'''Make sure phase locking value ignores magnitudes.'''
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 30, 1,
1, 2)
fourier_coefficients = (np.random.uniform(
0, 2, (n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals)) *
np.exp(1j * np.pi / 2))
expected_phase_locking_value_magnitude = np.ones(
fourier_coefficients.shape)
expected_phase_locking_value_angle = np.zeros(fourier_coefficients.shape)
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(np.abs(this_Conn.phase_locking_value()),
expected_phase_locking_value_magnitude)
assert np.allclose(np.angle(this_Conn.phase_locking_value()),
expected_phase_locking_value_angle)
def test_cross_spectrum(axis):
'''Test that the cross spectrum is correct for each dimension.'''
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (2, 2, 2, 2,
2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
signal_fourier_coefficient = [
2 * np.exp(1j * np.pi / 2), 3 * np.exp(1j * -np.pi / 2)
]
fourier_ind = [slice(0, 4)] * 5
fourier_ind[-1] = slice(None)
fourier_ind[axis] = slice(1, 2)
fourier_coefficients[fourier_ind] = signal_fourier_coefficient
expected_cross_spectral_matrix = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals,
n_signals),
dtype=np.complex)
expected_slice = np.array([[4, -6], [-6, 9]], dtype=np.complex)
expected_ind = [slice(0, 5)] * 6
expected_ind[-1] = slice(None)
expected_ind[-2] = slice(None)
expected_ind[axis] = slice(1, 2)
expected_cross_spectral_matrix[expected_ind] = expected_slice
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(expected_cross_spectral_matrix,
this_Conn._cross_spectral_matrix)
def test_power():
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 1, 1, 1,
2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
fourier_coefficients[..., :] = [
2 * np.exp(1j * np.pi / 2), 3 * np.exp(1j * -np.pi / 2)
]
expected_power = np.zeros((n_time_samples, n_fft_samples, n_signals))
expected_power[..., :] = [4, 9]
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(expected_power, this_Conn.power())
def test_n_observations(expectation_type, expected_n_observations):
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 2, 3, 4,
5)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
this_Conn = Connectivity(
fourier_coefficients=fourier_coefficients,
expectation_type=expectation_type,
)
assert this_Conn.n_observations == expected_n_observations
def test_debiased_squared_phase_lag_index():
'''Test that incoherent signals are set to zero or below.'''
np.random.seed(0)
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 200, 5,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
angles1 = np.random.uniform(
0, 2 * np.pi, (n_time_samples, n_trials, n_tapers, n_fft_samples))
angles2 = np.random.uniform(
0, 2 * np.pi, (n_time_samples, n_trials, n_tapers, n_fft_samples))
fourier_coefficients[..., 0] = np.exp(1j * angles1)
fourier_coefficients[..., 1] = np.exp(1j * angles2)
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.all(
this_Conn.debiased_squared_phase_lag_index() < np.finfo(float).eps)
def test_phase_lag_index_sets_angles_up_to_pi_to_same_value():
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 30, 1,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
fourier_coefficients[..., 0] = (np.random.uniform(
0.1, 2, (n_time_samples, n_trials, n_tapers, n_fft_samples)) *
np.exp(1j * np.pi / 2))
fourier_coefficients[..., 1] = (np.random.uniform(
0.1, 2, (n_time_samples, n_trials, n_tapers, n_fft_samples)) *
np.exp(1j * np.pi / 4))
expected_phase_lag_index = np.zeros((2, 2))
expected_phase_lag_index[0, 1] = 1
expected_phase_lag_index[1, 0] = -1
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
assert np.allclose(this_Conn.phase_lag_index().squeeze(),
expected_phase_lag_index)
def test_coherency():
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 30, 1,
1, 2)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
fourier_coefficients[..., :] = [
2 * np.exp(1j * np.pi / 2), 3 * np.exp(1j * -np.pi / 2)
]
this_Conn = Connectivity(fourier_coefficients=fourier_coefficients)
expected_coherence_magnitude = np.array([[np.nan, 1], [1, np.nan]])
expected_phase = np.zeros((2, 2)) * np.nan
expected_phase[0, 1] = np.pi
expected_phase[1, 0] = -np.pi
assert np.allclose(np.abs(this_Conn.coherency().squeeze()),
expected_coherence_magnitude,
equal_nan=True)
assert np.allclose(np.angle(this_Conn.coherency().squeeze()),
expected_phase,
equal_nan=True)
def test_expectation(expectation_type, expected_shape):
n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals = (1, 2, 3, 4,
5)
fourier_coefficients = np.zeros(
(n_time_samples, n_trials, n_tapers, n_fft_samples, n_signals),
dtype=np.complex)
this_Conn = Connectivity(
fourier_coefficients=fourier_coefficients,
expectation_type=expectation_type,
)
expectation_function = this_Conn._expectation
assert np.allclose(expected_shape,
expectation_function(fourier_coefficients).shape)
time_extent = (0, 1205.02733)
n_time_samples = ((time_extent[1] - time_extent[0]) * sampling_frequency) + 1
time = np.linspace(time_extent[0],
time_extent[1],
num=n_time_samples,
endpoint=True)
signals = np.array(eeg['electric_potential'])[:len(time)]
m = Multitaper(signals,
sampling_frequency=sampling_frequency,
time_halfbandwidth_product=8,
time_window_duration=0.6,
time_window_step=0.500,
start_time=time[0])
c = Connectivity(fourier_coefficients=m.fft(),
frequencies=m.frequencies,
time=m.time)
mesh = plt.pcolormesh(c.time,
c.frequencies,
c.power().squeeze().T,
vmin=0.0,
vmax=0.03,
cmap='viridis')
#axes[1, 0].set_ylim((0, 300))
plt.axvline(time[int(np.fix(n_time_samples / 2))], color='black')
# plt.tight_layout()
cb = plt.colorbar(mesh,
orientation='horizontal',
shrink=.5,
