

@testing.requires_testing_data
def test_apply_mne_inverse_raw():
    'Test MNE with precomputed inverse operator on Raw\n    '
    start = 3
    stop = 10
    raw = Raw(fname_raw)
    label_lh = read_label((fname_label % 'Aud-lh'))
    (_, times) = raw[0, start:stop]
    inverse_operator = read_inverse_operator(fname_full)
    inverse_operator = prepare_inverse_operator(inverse_operator, nave=1, lambda2=lambda2, method='dSPM')
    for pick_ori in [None, 'normal']:
        stc = apply_inverse_raw(raw, inverse_operator, lambda2, 'dSPM', label=label_lh, start=start, stop=stop, nave=1, pick_ori=pick_ori, buffer_size=None, prepared=True)
        stc2 = apply_inverse_raw(raw, inverse_operator, lambda2, 'dSPM', label=label_lh, start=start, stop=stop, nave=1, pick_ori=pick_ori, buffer_size=3, prepared=True)
        if (pick_ori is None):
            assert_true(np.all((stc.data > 0)))
            assert_true(np.all((stc2.data > 0)))
        assert_true((stc.subject == 'sample'))
        assert_true((stc2.subject == 'sample'))
        assert_array_almost_equal(stc.times, times)
        assert_array_almost_equal(stc2.times, times)
        assert_array_almost_equal(stc.data, stc2.data)

dataset/ETHPy150Open mne-tools/mne-python/mne/minimum_norm/tests/test_inverse.py test_apply_mne_inverse_raw/original