Function test_ssd_epoched_data

mne/decoding/tests/test_ssd.py:279–329

Test Common Spatial Patterns algorithm on epoched data. Compare the outputs when raw data is used.

()

def test_ssd_epoched_data():
    """Test Common Spatial Patterns algorithm on epoched data.

    Compare the outputs when raw data is used.
    """
    X, A, S = simulate_data(n_trials=100, n_channels=20, n_samples=500)
    sf = 250
    n_channels = X.shape[0]
    info = create_info(ch_names=n_channels, sfreq=sf, ch_types="eeg")
    n_components_true = 5

    # Build epochs as sliding windows over the continuous raw file

    # Epoch length is 1 second
    X_e = np.reshape(X, (100, 20, 500))

    # Fit
    filt_params_signal = dict(
        l_freq=freqs_sig[0],
        h_freq=freqs_sig[1],
        l_trans_bandwidth=4,
        h_trans_bandwidth=4,
    )
    filt_params_noise = dict(
        l_freq=freqs_noise[0],
        h_freq=freqs_noise[1],
        l_trans_bandwidth=4,
        h_trans_bandwidth=4,
    )

    # ssd on epochs
    ssd_e = SSD(info, filt_params_signal, filt_params_noise)
    ssd_e.fit(X_e)
    # ssd on raw
    ssd = SSD(info, filt_params_signal, filt_params_noise)
    ssd.fit(X)

    # Check if the 5 first 5 components are the same for both
    _, sorter_spec_e = _get_spectral_ratio(
        ssd_e.transform(X_e),
        ssd_e.sfreq_,
        ssd_e.n_fft_,
        ssd_e.freqs_signal_,
        ssd_e.freqs_noise_,
    )
    _, sorter_spec = _get_spectral_ratio(
        ssd.transform(X), ssd.sfreq_, ssd.n_fft_, ssd.freqs_signal_, ssd.freqs_noise_
    )
    assert_array_equal(
        sorter_spec_e[:n_components_true], sorter_spec[:n_components_true]
    )


def test_ssd_pipeline():