def test_ch_loc():
    """Test raw kit loc
    """
    raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<')
    raw_bin = Raw(op.join(data_dir, 'test_bin_raw.fif'))

    ch_py = raw_py._sqd_params['sensor_locs'][:, :5]
    # ch locs stored as m, not mm
    ch_py[:, :3] *= 1e3
    ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
    assert_array_almost_equal(ch_py, ch_sns, 2)

    assert_array_almost_equal(raw_py.info['dev_head_t']['trans'],
                              raw_bin.info['dev_head_t']['trans'], 4)
    for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
        if bin_ch['ch_name'].startswith('MEG'):
            # the stored ch locs have more precision than the sns.txt
            assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)
            assert_array_almost_equal(py_ch['coil_trans'],
                                      bin_ch['coil_trans'],
                                      decimal=2)

    # test when more than one marker file provided
    mrks = [mrk_path, mrk2_path, mrk3_path]
    read_raw_kit(sqd_path, mrks, elp_path, hsp_path, preload=False)

def test_ch_loc():
    """Test raw kit loc."""
    raw_py = read_raw_kit(sqd_path, mrk_path, elp_txt_path, hsp_txt_path,
                          stim='<')
    raw_bin = read_raw_fif(op.join(data_dir, 'test_bin_raw.fif'))

    ch_py = np.array([ch['loc'] for ch in
                      raw_py._raw_extras[0]['channels'][:160]])
    # ch locs stored as m, not mm
    ch_py[:, :3] *= 1e3
    ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
    assert_array_almost_equal(ch_py, ch_sns, 2)

    assert_array_almost_equal(raw_py.info['dev_head_t']['trans'],
                              raw_bin.info['dev_head_t']['trans'], 4)
    for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
        if bin_ch['ch_name'].startswith('MEG'):
            # the stored ch locs have more precision than the sns.txt
            assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)

    # test when more than one marker file provided
    mrks = [mrk_path, mrk2_path, mrk3_path]
    read_raw_kit(sqd_path, mrks, elp_txt_path, hsp_txt_path, preload=False)
    # this dataset does not have the equivalent set of points :(
    raw_bin.info['dig'] = raw_bin.info['dig'][:8]
    raw_py.info['dig'] = raw_py.info['dig'][:8]
    assert_dig_allclose(raw_py.info, raw_bin.info)

def test_raw_events():
    """Test creating stim channel from raw SQD file."""
    def evts(a, b, c, d, e, f=None):
        out = [[269, a, b], [281, b, c], [1552, c, d], [1564, d, e]]
        if f is not None:
            out.append([2000, e, f])
        return out

    raw = read_raw_kit(sqd_path)
    assert_array_equal(find_events(raw, output='step', consecutive=True),
                       evts(255, 254, 255, 254, 255, 0))

    raw = read_raw_kit(sqd_path, slope='+')
    assert_array_equal(find_events(raw, output='step', consecutive=True),
                       evts(0, 1, 0, 1, 0))

    raw = read_raw_kit(sqd_path, stim='<', slope='+')
    assert_array_equal(find_events(raw, output='step', consecutive=True),
                       evts(0, 128, 0, 128, 0))

    raw = read_raw_kit(sqd_path, stim='<', slope='+', stim_code='channel')
    assert_array_equal(find_events(raw, output='step', consecutive=True),
                       evts(0, 160, 0, 160, 0))

    raw = read_raw_kit(sqd_path, stim=range(160, 162), slope='+',
                       stim_code='channel')
    assert_array_equal(find_events(raw, output='step', consecutive=True),
                       evts(0, 160, 0, 160, 0))

def test_read_segment():
    """Test writing raw kit files when preload is False
    """
    tempdir = _TempDir()
    raw1 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=False)
    raw1_file = op.join(tempdir, 'test1-raw.fif')
    raw1.save(raw1_file, buffer_size_sec=.1, overwrite=True)
    raw2 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=True)
    raw2_file = op.join(tempdir, 'test2-raw.fif')
    raw2.save(raw2_file, buffer_size_sec=.1, overwrite=True)
    data1, times1 = raw1[0, 0:1]

    raw1 = Raw(raw1_file, preload=True)
    raw2 = Raw(raw2_file, preload=True)
    assert_array_equal(raw1._data, raw2._data)
    data2, times2 = raw2[0, 0:1]
    assert_array_almost_equal(data1, data2)
    assert_array_almost_equal(times1, times2)
    raw3 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=True)
    assert_array_almost_equal(raw1._data, raw3._data)
    raw4 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=False)
    raw4.load_data()
    buffer_fname = op.join(tempdir, 'buffer')
    assert_array_almost_equal(raw1._data, raw4._data)
    raw5 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=buffer_fname)
    assert_array_almost_equal(raw1._data, raw5._data)

def test_data():
    """Test reading raw kit files
    """
    assert_raises(TypeError, read_raw_kit, epochs_path)
    assert_raises(TypeError, read_epochs_kit, sqd_path)
    assert_raises(ValueError, read_raw_kit, sqd_path, mrk_path, elp_path)
    assert_raises(ValueError, read_raw_kit, sqd_path, None, None, None,
                  list(range(200, 190, -1)))
    assert_raises(ValueError, read_raw_kit, sqd_path, None, None, None,
                  list(range(167, 159, -1)), '*', 1, True)
    # check functionality
    raw_mrk = read_raw_kit(sqd_path, [mrk2_path, mrk3_path], elp_path,
                           hsp_path)
    raw_py = _test_raw_reader(read_raw_kit,
                              input_fname=sqd_path, mrk=mrk_path, elp=elp_path,
                              hsp=hsp_path, stim=list(range(167, 159, -1)),
                              slope='+', stimthresh=1)
    assert_true('RawKIT' in repr(raw_py))
    assert_equal(raw_mrk.info['kit_system_id'], KIT.SYSTEM_NYU_2010)
    assert_true(KIT_CONSTANTS[raw_mrk.info['kit_system_id']] is KIT_NY)

    # Test stim channel
    raw_stim = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                            preload=False)
    for raw in [raw_py, raw_stim, raw_mrk]:
        stim_pick = pick_types(raw.info, meg=False, ref_meg=False,
                               stim=True, exclude='bads')
        stim1, _ = raw[stim_pick]
        stim2 = np.array(raw.read_stim_ch(), ndmin=2)
        assert_array_equal(stim1, stim2)

    # Binary file only stores the sensor channels
    py_picks = pick_types(raw_py.info, exclude='bads')
    raw_bin = op.join(data_dir, 'test_bin_raw.fif')
    raw_bin = Raw(raw_bin, preload=True)
    bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
    data_bin, _ = raw_bin[bin_picks]
    data_py, _ = raw_py[py_picks]

    # this .mat was generated using the Yokogawa MEG Reader
    data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
    data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
    data_Ykgw = data_Ykgw[py_picks]

    assert_array_almost_equal(data_py, data_Ykgw)

    py_picks = pick_types(raw_py.info, stim=True, ref_meg=False,
                          exclude='bads')
    data_py, _ = raw_py[py_picks]
    assert_array_almost_equal(data_py, data_bin)

    # KIT-UMD data
    _test_raw_reader(read_raw_kit, input_fname=sqd_umd_path)
    raw = read_raw_kit(sqd_umd_path)
    assert_equal(raw.info['kit_system_id'], KIT.SYSTEM_UMD_2014_12)
    assert_true(KIT_CONSTANTS[raw.info['kit_system_id']] is KIT_UMD_2014)

def test_data():
    """Test reading raw kit files
    """
    raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path,
                          stim=list(range(167, 159, -1)), slope='+',
                          stimthresh=1, preload=True)
    print(repr(raw_py))

    # Binary file only stores the sensor channels
    py_picks = pick_types(raw_py.info, exclude='bads')
    raw_bin = op.join(data_dir, 'test_bin_raw.fif')
    raw_bin = Raw(raw_bin, preload=True)
    bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
    data_bin, _ = raw_bin[bin_picks]
    data_py, _ = raw_py[py_picks]

    # this .mat was generated using the Yokogawa MEG Reader
    data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
    data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
    data_Ykgw = data_Ykgw[py_picks]

    assert_array_almost_equal(data_py, data_Ykgw)

    py_picks = pick_types(raw_py.info, stim=True, ref_meg=False,
                          exclude='bads')
    data_py, _ = raw_py[py_picks]
    assert_array_almost_equal(data_py, data_bin)

    # Make sure concatenation works
    raw_concat = concatenate_raws([raw_py.copy(), raw_py])
    assert_equal(raw_concat.n_times, 2 * raw_py.n_times)

def test_decimate(tmpdir):
    """Test decimation of digitizer headshapes with too many points."""
    # load headshape and convert to meters
    hsp_mm = _get_ico_surface(5)['rr'] * 100
    hsp_m = hsp_mm / 1000.

    # save headshape to a file in mm in temporary directory
    tempdir = str(tmpdir)
    sphere_hsp_path = op.join(tempdir, 'test_sphere.txt')
    np.savetxt(sphere_hsp_path, hsp_mm)

    # read in raw data using spherical hsp, and extract new hsp
    with pytest.warns(RuntimeWarning,
                      match='was automatically downsampled .* FastScan'):
        raw = read_raw_kit(sqd_path, mrk_path, elp_txt_path, sphere_hsp_path)
    # collect headshape from raw (should now be in m)
    hsp_dec = np.array([dig['r'] for dig in raw.info['dig']])[8:]

    # with 10242 points and _decimate_points set to resolution of 5 mm, hsp_dec
    # should be a bit over 5000 points. If not, something is wrong or
    # decimation resolution has been purposefully changed
    assert len(hsp_dec) > 5000

    # should have similar size, distance from center
    dist = np.sqrt(np.sum((hsp_m - np.mean(hsp_m, axis=0))**2, axis=1))
    dist_dec = np.sqrt(np.sum((hsp_dec - np.mean(hsp_dec, axis=0))**2, axis=1))
    hsp_rad = np.mean(dist)
    hsp_dec_rad = np.mean(dist_dec)
    assert_array_almost_equal(hsp_rad, hsp_dec_rad, decimal=3)

def test_plot_trans():
    """Test plotting of -trans.fif files and MEG sensor layouts
    """
    evoked = read_evokeds(evoked_fname)[0]
    with warnings.catch_warnings(record=True):  # 4D weight tables
        bti = read_raw_bti(pdf_fname, config_fname, hs_fname, convert=True,
                           preload=False).info
    infos = dict(
        Neuromag=evoked.info,
        CTF=read_raw_ctf(ctf_fname).info,
        BTi=bti,
        KIT=read_raw_kit(sqd_fname).info,
    )
    for system, info in infos.items():
        ref_meg = False if system == 'KIT' else True
        plot_trans(info, trans_fname, subject='sample', meg_sensors=True,
                   subjects_dir=subjects_dir, ref_meg=ref_meg)
    # KIT ref sensor coil def not defined
    assert_raises(RuntimeError, plot_trans, infos['KIT'], None,
                  meg_sensors=True, ref_meg=True)
    info = infos['Neuromag']
    assert_raises(ValueError, plot_trans, info, trans_fname,
                  subject='sample', subjects_dir=subjects_dir,
                  ch_type='bad-chtype')
    assert_raises(TypeError, plot_trans, 'foo', trans_fname,
                  subject='sample', subjects_dir=subjects_dir)
    # no-head version
    plot_trans(info, None, meg_sensors=True, dig=True, coord_frame='head')
    # EEG only with strange options
    with warnings.catch_warnings(record=True) as w:
        plot_trans(evoked.copy().pick_types(meg=False, eeg=True).info,
                   trans=trans_fname, meg_sensors=True)
    assert_true(['Cannot plot MEG' in str(ww.message) for ww in w])

def test_decimate():
    """Test decimation of digitizer headshapes with too many points."""
    # load headshape and convert to meters
    hsp_mm = _get_ico_surface(5)['rr'] * 100
    hsp_m = hsp_mm / 1000.

    # save headshape to a file in mm in temporary directory
    tempdir = _TempDir()
    sphere_hsp_path = op.join(tempdir, 'test_sphere.txt')
    np.savetxt(sphere_hsp_path, hsp_mm)

    # read in raw data using spherical hsp, and extract new hsp
    with warnings.catch_warnings(record=True) as w:
        raw = read_raw_kit(sqd_path, mrk_path, elp_txt_path, sphere_hsp_path)
    assert_true(any('more than' in str(ww.message) for ww in w))
    # collect headshape from raw (should now be in m)
    hsp_dec = np.array([dig['r'] for dig in raw.info['dig']])[8:]

    # with 10242 points and _decimate_points set to resolution of 5 mm, hsp_dec
    # should be a bit over 5000 points. If not, something is wrong or
    # decimation resolution has been purposefully changed
    assert_true(len(hsp_dec) > 5000)

    # should have similar size, distance from center
    dist = np.sqrt(np.sum((hsp_m - np.mean(hsp_m, axis=0))**2, axis=1))
    dist_dec = np.sqrt(np.sum((hsp_dec - np.mean(hsp_dec, axis=0))**2, axis=1))
    hsp_rad = np.mean(dist)
    hsp_dec_rad = np.mean(dist_dec)
    assert_almost_equal(hsp_rad, hsp_dec_rad, places=3)

def test_epochs():
    raw = read_raw_kit(sqd_path, stim=None)
    events = read_events(events_path)
    raw_epochs = Epochs(raw, events, None, tmin=0, tmax=.099, baseline=None)
    data1 = raw_epochs.get_data()
    epochs = read_epochs_kit(epochs_path, events_path)
    data11 = epochs.get_data()
    assert_array_equal(data1, data11)

def test_read_segment():
    """Test writing raw kit files when preload is False
    """
    raw1 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=False)
    raw1_file = op.join(tempdir, 'test1-raw.fif')
    raw1.save(raw1_file, buffer_size_sec=.1, overwrite=True)
    raw2 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=True)
    raw2_file = op.join(tempdir, 'test2-raw.fif')
    raw2.save(raw2_file, buffer_size_sec=.1, overwrite=True)
    raw1 = Raw(raw1_file, preload=True)
    raw2 = Raw(raw2_file, preload=True)
    assert_array_equal(raw1._data, raw2._data)
    raw3 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                        preload=True)
    assert_array_almost_equal(raw1._data, raw3._data)

def run():
    """Run command."""
    from mne.commands.utils import get_optparser

    parser = get_optparser(__file__)

    parser.add_option('--input', dest='input_fname',
                      help='Input data file name', metavar='filename')
    parser.add_option('--mrk', dest='mrk_fname',
                      help='MEG Marker file name', metavar='filename')
    parser.add_option('--elp', dest='elp_fname',
                      help='Headshape points file name', metavar='filename')
    parser.add_option('--hsp', dest='hsp_fname',
                      help='Headshape file name', metavar='filename')
    parser.add_option('--stim', dest='stim',
                      help='Colon Separated Stimulus Trigger Channels',
                      metavar='chs')
    parser.add_option('--slope', dest='slope', help='Slope direction',
                      metavar='slope')
    parser.add_option('--stimthresh', dest='stimthresh', default=1,
                      help='Threshold value for trigger channels',
                      metavar='value')
    parser.add_option('--output', dest='out_fname',
                      help='Name of the resulting fiff file',
                      metavar='filename')
    parser.add_option('--debug', dest='debug', action='store_true',
                      default=False,
                      help='Set logging level for terminal output to debug')

    options, args = parser.parse_args()

    if options.debug:
        mne.set_log_level('debug')

    input_fname = options.input_fname
    if input_fname is None:
        with ETSContext():
            mne.gui.kit2fiff()
        sys.exit(0)

    hsp_fname = options.hsp_fname
    elp_fname = options.elp_fname
    mrk_fname = options.mrk_fname
    stim = options.stim
    slope = options.slope
    stimthresh = options.stimthresh
    out_fname = options.out_fname

    if isinstance(stim, str):
        stim = map(int, stim.split(':'))

    raw = read_raw_kit(input_fname=input_fname, mrk=mrk_fname, elp=elp_fname,
                       hsp=hsp_fname, stim=stim, slope=slope,
                       stimthresh=stimthresh)

    raw.save(out_fname)
    raw.close()
    sys.exit(0)

def test_pick_refs():
    """Test picking of reference sensors
    """
    infos = list()
    # KIT
    kit_dir = op.join(io_dir, 'kit', 'tests', 'data')
    sqd_path = op.join(kit_dir, 'test.sqd')
    mrk_path = op.join(kit_dir, 'test_mrk.sqd')
    elp_path = op.join(kit_dir, 'test_elp.txt')
    hsp_path = op.join(kit_dir, 'test_hsp.txt')
    raw_kit = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path)
    infos.append(raw_kit.info)
    # BTi
    bti_dir = op.join(io_dir, 'bti', 'tests', 'data')
    bti_pdf = op.join(bti_dir, 'test_pdf_linux')
    bti_config = op.join(bti_dir, 'test_config_linux')
    bti_hs = op.join(bti_dir, 'test_hs_linux')
    with warnings.catch_warnings(record=True):  # weight tables
        raw_bti = read_raw_bti(bti_pdf, bti_config, bti_hs, preload=False)
    infos.append(raw_bti.info)
    # CTF
    fname_ctf_raw = op.join(io_dir, 'tests', 'data', 'test_ctf_comp_raw.fif')
    raw_ctf = read_raw_fif(fname_ctf_raw, add_eeg_ref=False)
    raw_ctf.apply_gradient_compensation(2)
    infos.append(raw_ctf.info)
    for info in infos:
        info['bads'] = []
        assert_raises(ValueError, pick_types, info, meg='foo')
        assert_raises(ValueError, pick_types, info, ref_meg='foo')
        picks_meg_ref = pick_types(info, meg=True, ref_meg=True)
        picks_meg = pick_types(info, meg=True, ref_meg=False)
        picks_ref = pick_types(info, meg=False, ref_meg=True)
        assert_array_equal(picks_meg_ref,
                           np.sort(np.concatenate([picks_meg, picks_ref])))
        picks_grad = pick_types(info, meg='grad', ref_meg=False)
        picks_ref_grad = pick_types(info, meg=False, ref_meg='grad')
        picks_meg_ref_grad = pick_types(info, meg='grad', ref_meg='grad')
        assert_array_equal(picks_meg_ref_grad,
                           np.sort(np.concatenate([picks_grad,
                                                   picks_ref_grad])))
        picks_mag = pick_types(info, meg='mag', ref_meg=False)
        picks_ref_mag = pick_types(info, meg=False, ref_meg='mag')
        picks_meg_ref_mag = pick_types(info, meg='mag', ref_meg='mag')
        assert_array_equal(picks_meg_ref_mag,
                           np.sort(np.concatenate([picks_mag,
                                                   picks_ref_mag])))
        assert_array_equal(picks_meg,
                           np.sort(np.concatenate([picks_mag, picks_grad])))
        assert_array_equal(picks_ref,
                           np.sort(np.concatenate([picks_ref_mag,
                                                   picks_ref_grad])))
        assert_array_equal(picks_meg_ref, np.sort(np.concatenate(
            [picks_grad, picks_mag, picks_ref_grad, picks_ref_mag])))
        for pick in (picks_meg_ref, picks_meg, picks_ref,
                     picks_grad, picks_ref_grad, picks_meg_ref_grad,
                     picks_mag, picks_ref_mag, picks_meg_ref_mag):
            if len(pick) > 0:
                pick_info(info, pick)

def test_stim_ch():
    """Test raw kit stim ch
    """
    raw = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
                       slope='+', preload=True)
    stim_pick = pick_types(raw.info, meg=False, ref_meg=False,
                           stim=True, exclude='bads')
    stim1, _ = raw[stim_pick]
    stim2 = np.array(raw.read_stim_ch(), ndmin=2)
    assert_array_equal(stim1, stim2)

def test_hsp_elp():
    """Test KIT usage of *.elp and *.hsp files against *.txt files."""
    raw_txt = read_raw_kit(sqd_path, mrk_path, elp_txt_path, hsp_txt_path)
    raw_elp = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path)

    # head points
    pts_txt = np.array([dig_point['r'] for dig_point in raw_txt.info['dig']])
    pts_elp = np.array([dig_point['r'] for dig_point in raw_elp.info['dig']])
    assert_array_almost_equal(pts_elp, pts_txt, decimal=5)

    # transforms
    trans_txt = raw_txt.info['dev_head_t']['trans']
    trans_elp = raw_elp.info['dev_head_t']['trans']
    assert_array_almost_equal(trans_elp, trans_txt, decimal=5)

    # head points in device space
    pts_txt_in_dev = apply_trans(linalg.inv(trans_txt), pts_txt)
    pts_elp_in_dev = apply_trans(linalg.inv(trans_elp), pts_elp)
    assert_array_almost_equal(pts_elp_in_dev, pts_txt_in_dev, decimal=5)

def test_epochs():
    """Test reading epoched SQD file."""
    raw = read_raw_kit(sqd_path, stim=None)
    events = read_events(events_path)
    raw_epochs = Epochs(raw, events, None, tmin=0, tmax=.099, baseline=None,
                        add_eeg_ref=False)
    data1 = raw_epochs.get_data()
    epochs = read_epochs_kit(epochs_path, events_path)
    data11 = epochs.get_data()
    assert_array_equal(data1, data11)

def test_data():
    """Test reading raw kit files
    """
    assert_raises(TypeError, read_raw_kit, epochs_path)
    assert_raises(TypeError, read_epochs_kit, sqd_path)
    assert_raises(ValueError, read_raw_kit, sqd_path, mrk_path, elp_path)
    assert_raises(ValueError, read_raw_kit, sqd_path, None, None, None,
                  list(range(200, 190, -1)))
    assert_raises(ValueError, read_raw_kit, sqd_path, None, None, None,
                  list(range(167, 159, -1)), '*', 1, True)
    # check functionality
    _ = read_raw_kit(sqd_path, [mrk2_path, mrk3_path], elp_path,
                     hsp_path)
    raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path,
                          stim=list(range(167, 159, -1)), slope='+',
                          stimthresh=1, preload=True)
    assert_true('RawKIT' in repr(raw_py))

    # Binary file only stores the sensor channels
    py_picks = pick_types(raw_py.info, exclude='bads')
    raw_bin = op.join(data_dir, 'test_bin_raw.fif')
    raw_bin = Raw(raw_bin, preload=True)
    bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
    data_bin, _ = raw_bin[bin_picks]
    data_py, _ = raw_py[py_picks]

    # this .mat was generated using the Yokogawa MEG Reader
    data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
    data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
    data_Ykgw = data_Ykgw[py_picks]

    assert_array_almost_equal(data_py, data_Ykgw)

    py_picks = pick_types(raw_py.info, stim=True, ref_meg=False,
                          exclude='bads')
    data_py, _ = raw_py[py_picks]
    assert_array_almost_equal(data_py, data_bin)

    # Make sure concatenation works
    raw_concat = concatenate_raws([raw_py.copy(), raw_py])
    assert_equal(raw_concat.n_times, 2 * raw_py.n_times)

def run():
    from mne.commands.utils import get_optparser

    parser = get_optparser(__file__)

    parser.add_option('--input', dest='input_fname',
                      help='Input data file name', metavar='filename')
    parser.add_option('--mrk', dest='mrk_fname',
                      help='MEG Marker file name', metavar='filename')
    parser.add_option('--elp', dest='elp_fname',
                      help='Headshape points file name', metavar='filename')
    parser.add_option('--hsp', dest='hsp_fname',
                      help='Headshape file name', metavar='filename')
    parser.add_option('--stim', dest='stim',
                      help='Colon Separated Stimulus Trigger Channels',
                      metavar='chs')
    parser.add_option('--slope', dest='slope', help='Slope direction',
                      metavar='slope')
    parser.add_option('--stimthresh', dest='stimthresh', default=1,
                      help='Threshold value for trigger channels',
                      metavar='value')
    parser.add_option('--output', dest='out_fname',
                      help='Name of the resulting fiff file',
                      metavar='filename')

    options, args = parser.parse_args()

    input_fname = options.input_fname
    if input_fname is None:
        os.environ['ETS_TOOLKIT'] = 'qt4'
        mne.gui.kit2fiff()
        sys.exit(0)

    hsp_fname = options.hsp_fname
    elp_fname = options.elp_fname
    mrk_fname = options.mrk_fname
    stim = options.stim
    slope = options.slope
    stimthresh = options.stimthresh
    out_fname = options.out_fname

    if isinstance(stim, str):
        stim = stim.split(':')

    raw = read_raw_kit(input_fname=input_fname, mrk=mrk_fname, elp=elp_fname,
                       hsp=hsp_fname, stim=stim, slope=slope,
                       stimthresh=stimthresh)

    raw.save(out_fname)
    raw.close()
    sys.exit(0)

def run():
    from mne.commands.utils import get_optparser

    parser = get_optparser(__file__)

    parser.add_option("--input", dest="input_fname", help="Input data file name", metavar="filename")
    parser.add_option("--mrk", dest="mrk_fname", help="MEG Marker file name", metavar="filename")
    parser.add_option("--elp", dest="elp_fname", help="Headshape points file name", metavar="filename")
    parser.add_option("--hsp", dest="hsp_fname", help="Headshape file name", metavar="filename")
    parser.add_option("--stim", dest="stim", help="Colon Separated Stimulus Trigger Channels", metavar="chs")
    parser.add_option("--slope", dest="slope", help="Slope direction", metavar="slope")
    parser.add_option(
        "--stimthresh", dest="stimthresh", default=1, help="Threshold value for trigger channels", metavar="value"
    )
    parser.add_option("--output", dest="out_fname", help="Name of the resulting fiff file", metavar="filename")

    options, args = parser.parse_args()

    input_fname = options.input_fname
    if input_fname is None:
        os.environ["ETS_TOOLKIT"] = "qt4"
        mne.gui.kit2fiff()
        sys.exit(0)

    hsp_fname = options.hsp_fname
    elp_fname = options.elp_fname
    mrk_fname = options.mrk_fname
    stim = options.stim
    slope = options.slope
    stimthresh = options.stimthresh
    out_fname = options.out_fname

    if isinstance(stim, str):
        stim = map(int, stim.split(":"))

    raw = read_raw_kit(
        input_fname=input_fname,
        mrk=mrk_fname,
        elp=elp_fname,
        hsp=hsp_fname,
        stim=stim,
        slope=slope,
        stimthresh=stimthresh,
    )

    raw.save(out_fname)
    raw.close()
    sys.exit(0)

def test_plot_trans():
    """Test plotting of -trans.fif files and MEG sensor layouts."""
    from mayavi import mlab
    evoked = read_evokeds(evoked_fname)[0]
    with warnings.catch_warnings(record=True):  # 4D weight tables
        bti = read_raw_bti(pdf_fname, config_fname, hs_fname, convert=True,
                           preload=False).info
    infos = dict(
        Neuromag=evoked.info,
        CTF=read_raw_ctf(ctf_fname).info,
        BTi=bti,
        KIT=read_raw_kit(sqd_fname).info,
    )
    for system, info in infos.items():
        ref_meg = False if system == 'KIT' else True
        plot_trans(info, trans_fname, subject='sample', meg_sensors=True,
                   subjects_dir=subjects_dir, ref_meg=ref_meg)
        mlab.close(all=True)
    # KIT ref sensor coil def is defined
    plot_trans(infos['KIT'], None, meg_sensors=True, ref_meg=True)
    mlab.close(all=True)
    info = infos['Neuromag']
    assert_raises(ValueError, plot_trans, info, trans_fname,
                  subject='sample', subjects_dir=subjects_dir,
                  ch_type='bad-chtype')
    assert_raises(TypeError, plot_trans, 'foo', trans_fname,
                  subject='sample', subjects_dir=subjects_dir)
    # no-head version
    plot_trans(info, None, meg_sensors=True, dig=True, coord_frame='head')
    mlab.close(all=True)
    # all coord frames
    for coord_frame in ('meg', 'head', 'mri'):
        plot_trans(info, meg_sensors=True, dig=True, coord_frame=coord_frame,
                   trans=trans_fname, subject='sample',
                   subjects_dir=subjects_dir)
        mlab.close(all=True)
    # EEG only with strange options
    evoked_eeg_ecog = evoked.copy().pick_types(meg=False, eeg=True)
    evoked_eeg_ecog.info['projs'] = []  # "remove" avg proj
    evoked_eeg_ecog.set_channel_types({'EEG 001': 'ecog'})
    with warnings.catch_warnings(record=True) as w:
        plot_trans(evoked_eeg_ecog.info, subject='sample', trans=trans_fname,
                   source='outer_skin', meg_sensors=True, skull=True,
                   eeg_sensors=['original', 'projected'], ecog_sensors=True,
                   brain='white', head=True, subjects_dir=subjects_dir)
    mlab.close(all=True)
    assert_true(['Cannot plot MEG' in str(ww.message) for ww in w])