def test_coil_trans():
    """Test loc<->coil_trans functions"""
    rng = np.random.RandomState(0)
    x = rng.randn(4, 4)
    x[3] = [0, 0, 0, 1]
    assert_allclose(_loc_to_coil_trans(_coil_trans_to_loc(x)), x)
    x = rng.randn(12)
    assert_allclose(_coil_trans_to_loc(_loc_to_coil_trans(x)), x)
Beispiel #2
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def test_coil_trans():
    """Test loc<->coil_trans functions."""
    rng = np.random.RandomState(0)
    x = rng.randn(4, 4)
    x[3] = [0, 0, 0, 1]
    assert_allclose(_loc_to_coil_trans(_coil_trans_to_loc(x)), x)
    x = rng.randn(12)
    assert_allclose(_coil_trans_to_loc(_loc_to_coil_trans(x)), x)
def _create_meg_coil(coilset, ch, acc, do_es):
    """Create a coil definition using templates, transform if necessary."""
    # Also change the coordinate frame if so desired
    if ch['kind'] not in [FIFF.FIFFV_MEG_CH, FIFF.FIFFV_REF_MEG_CH]:
        raise RuntimeError('%s is not a MEG channel' % ch['ch_name'])

    # Simple linear search from the coil definitions
    for coil in coilset:
        if coil['coil_type'] == (ch['coil_type'] & 0xFFFF) and \
                coil['accuracy'] == acc:
            break
    else:
        raise RuntimeError('Desired coil definition not found '
                           '(type = %d acc = %d)' % (ch['coil_type'], acc))
    # Apply a coordinate transformation if so desired
    coil_trans = _loc_to_coil_trans(ch['loc'])

    # Create the result

    #print(coil['coil_type'], coil['accuracy'])
    res = dict(chname=ch['ch_name'],
               coil_class=coil['coil_class'],
               accuracy=coil['accuracy'],
               base=coil['base'],
               size=coil['size'],
               type=ch['coil_type'],
               w=coil['w'],
               desc=coil['desc'],
               coord_frame=FIFF.FIFFV_COORD_DEVICE,
               rmag_orig=coil['rmag'],
               cosmag_orig=coil['cosmag'],
               coil_trans_orig=coil_trans,
               r0=coil_trans[:3, 3],
               rmag=apply_trans(coil_trans, coil['rmag']),
               cosmag=apply_trans(coil_trans, coil['cosmag'], False))

    if do_es:
        r0_exey = (np.dot(coil['rmag'][:, :2], coil_trans[:3, :2].T) +
                   coil_trans[:3, 3])
        res.update(ex=coil_trans[:3, 0],
                   ey=coil_trans[:3, 1],
                   ez=coil_trans[:3, 2],
                   r0_exey=r0_exey)
    return res
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def _check_infos_trans(infos):
    """XXX this goes to tests later, currently not used"""
    chan_max_idx = np.argmax([c['nchan'] for c in infos])
    chan_template = infos[chan_max_idx]['ch_names']
    channels = [c['ch_names'] for c in infos]
    common_channels = set(chan_template).intersection(*channels)

    common_chs = [[c['chs'][c['ch_names'].index(ch)] for ch in common_channels]
                  for c in infos]
    dev_ctf_trans = [i['dev_ctf_t']['trans'] for i in infos]
    cns = [[c['ch_name'] for c in cc] for cc in common_chs]
    for cn1, cn2 in itt.combinations(cns, 2):
        assert cn1 == cn2
    # BTI stores data in head coords, as a consequence the coordinates
    # change across run, we apply the ctf->ctf_head transform here
    # to check that all transforms are correct.
    cts = [np.array([linalg.inv(_loc_to_coil_trans(c['loc'])).dot(t)
                    for c in cc])
           for t, cc in zip(dev_ctf_trans, common_chs)]
    for ct1, ct2 in itt.combinations(cts, 2):
        np.testing.assert_array_almost_equal(ct1, ct2, 12)
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def _check_infos_trans(infos):
    """XXX this goes to tests later, currently not used"""
    chan_max_idx = np.argmax([c['nchan'] for c in infos])
    chan_template = infos[chan_max_idx]['ch_names']
    channels = [c['ch_names'] for c in infos]
    common_channels = set(chan_template).intersection(*channels)

    common_chs = [[c['chs'][c['ch_names'].index(ch)] for ch in common_channels]
                  for c in infos]
    dev_ctf_trans = [i['dev_ctf_t']['trans'] for i in infos]
    cns = [[c['ch_name'] for c in cc] for cc in common_chs]
    for cn1, cn2 in itt.combinations(cns, 2):
        assert cn1 == cn2
    # BTI stores data in head coords, as a consequence the coordinates
    # change across run, we apply the ctf->ctf_head transform here
    # to check that all transforms are correct.
    cts = [np.array([linalg.inv(_loc_to_coil_trans(c['loc'])).dot(t)
                    for c in cc])
           for t, cc in zip(dev_ctf_trans, common_chs)]
    for ct1, ct2 in itt.combinations(cts, 2):
        np.testing.assert_array_almost_equal(ct1, ct2, 12)
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def test_read_raw_curry_rfDC(fname, tol, mock_dev_head_t, tmpdir):
    """Test reading CURRY files."""
    if mock_dev_head_t:
        if 'Curry 7' in fname:  # not supported yet
            return
        # copy files to tmpdir
        base = op.splitext(fname)[0]
        for ext in ('.cdt', '.cdt.dpa'):
            src = base + ext
            dst = op.join(tmpdir, op.basename(base) + ext)
            copyfile(src, dst)
            if ext == '.cdt.dpa':
                with open(dst, 'a') as fid:
                    fid.write(LM_CONTENT)
        fname = op.join(tmpdir, op.basename(fname))
        with open(fname + '.hpi', 'w') as fid:
            fid.write(HPI_CONTENT)

    # check data
    bti_rfDC = read_raw_bti(pdf_fname=bti_rfDC_file, head_shape_fname=None)
    with catch_logging() as log:
        raw = read_raw_curry(fname, verbose=True)
    log = log.getvalue()
    if mock_dev_head_t:
        assert 'Composing device' in log
    else:
        assert 'Leaving device' in log
        assert 'no landmark' in log

    # test on the eeg chans, since these were not renamed by curry
    eeg_names = [
        ch["ch_name"] for ch in raw.info["chs"]
        if ch["kind"] == FIFF.FIFFV_EEG_CH
    ]

    assert_allclose(raw.get_data(eeg_names),
                    bti_rfDC.get_data(eeg_names),
                    rtol=tol)
    assert bti_rfDC.info['dev_head_t'] is not None  # XXX probably a BTI bug
    if mock_dev_head_t:
        assert raw.info['dev_head_t'] is not None
        assert_allclose(raw.info['dev_head_t']['trans'], WANT_TRANS, atol=1e-5)
    else:
        assert raw.info['dev_head_t'] is None

    # check that most MEG sensors are approximately oriented outward from
    # the device origin
    n_meg = n_eeg = n_other = 0
    pos = list()
    nn = list()
    for ch in raw.info['chs']:
        if ch['kind'] == FIFF.FIFFV_MEG_CH:
            assert ch['coil_type'] == FIFF.FIFFV_COIL_CTF_GRAD
            t = _loc_to_coil_trans(ch['loc'])
            pos.append(t[:3, 3])
            nn.append(t[:3, 2])
            assert_allclose(np.linalg.norm(nn[-1]), 1.)
            n_meg += 1
        elif ch['kind'] == FIFF.FIFFV_EEG_CH:
            assert ch['coil_type'] == FIFF.FIFFV_COIL_EEG
            n_eeg += 1
        else:
            assert ch['coil_type'] == FIFF.FIFFV_COIL_NONE
            n_other += 1
    assert n_meg == 148
    assert n_eeg == 31
    assert n_other == 15
    pos = np.array(pos)
    nn = np.array(nn)
    rad, origin = _fit_sphere(pos, disp=False)
    assert 0.11 < rad < 0.13
    pos -= origin
    pos /= np.linalg.norm(pos, axis=1, keepdims=True)
    angles = np.abs(np.rad2deg(np.arccos((pos * nn).sum(-1))))
    assert (angles < 20).sum() > 100