Beispiel #1
0
def test_make_eeg_layout():
    """Test creation of EEG layout."""
    tempdir = _TempDir()
    tmp_name = 'foo'
    lout_name = 'test_raw'
    lout_orig = read_layout(kind=lout_name, path=lout_path)
    info = read_info(fif_fname)
    info['bads'].append(info['ch_names'][360])
    layout = make_eeg_layout(info, exclude=[])
    assert_array_equal(
        len(layout.names),
        len([ch for ch in info['ch_names'] if ch.startswith('EE')]))
    layout.save(op.join(tempdir, tmp_name + '.lout'))
    lout_new = read_layout(kind=tmp_name, path=tempdir, scale=False)
    assert_array_equal(lout_new.kind, tmp_name)
    assert_allclose(layout.pos, lout_new.pos, atol=0.1)
    assert_array_equal(lout_orig.names, lout_new.names)

    # Test input validation
    pytest.raises(ValueError, make_eeg_layout, info, radius=-0.1)
    pytest.raises(ValueError, make_eeg_layout, info, radius=0.6)
    pytest.raises(ValueError, make_eeg_layout, info, width=-0.1)
    pytest.raises(ValueError, make_eeg_layout, info, width=1.1)
    pytest.raises(ValueError, make_eeg_layout, info, height=-0.1)
    pytest.raises(ValueError, make_eeg_layout, info, height=1.1)
Beispiel #2
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def test_make_eeg_layout():
    """Test creation of EEG layout"""
    tempdir = _TempDir()
    tmp_name = 'foo'
    lout_name = 'test_raw'
    lout_orig = read_layout(kind=lout_name, path=lout_path)
    info = Raw(fif_fname).info
    layout = make_eeg_layout(info)
    layout.save(op.join(tempdir, tmp_name + '.lout'))
    lout_new = read_layout(kind=tmp_name, path=tempdir, scale=False)
    assert_array_equal(lout_new.kind, tmp_name)
    assert_allclose(layout.pos, lout_new.pos, atol=0.1)
    assert_array_equal(lout_orig.names, lout_new.names)

    # Test input validation
    assert_raises(ValueError, make_eeg_layout, info, radius=-0.1)
    assert_raises(ValueError, make_eeg_layout, info, radius=0.6)
    assert_raises(ValueError, make_eeg_layout, info, width=-0.1)
    assert_raises(ValueError, make_eeg_layout, info, width=1.1)
    assert_raises(ValueError, make_eeg_layout, info, height=-0.1)
    assert_raises(ValueError, make_eeg_layout, info, height=1.1)
Beispiel #3
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def test_make_eeg_layout():
    """Test creation of EEG layout"""
    tempdir = _TempDir()
    tmp_name = "foo"
    lout_name = "test_raw"
    lout_orig = read_layout(kind=lout_name, path=lout_path)
    info = Raw(fif_fname).info
    info["bads"].append(info["ch_names"][360])
    layout = make_eeg_layout(info, exclude=[])
    assert_array_equal(len(layout.names), len([ch for ch in info["ch_names"] if ch.startswith("EE")]))
    layout.save(op.join(tempdir, tmp_name + ".lout"))
    lout_new = read_layout(kind=tmp_name, path=tempdir, scale=False)
    assert_array_equal(lout_new.kind, tmp_name)
    assert_allclose(layout.pos, lout_new.pos, atol=0.1)
    assert_array_equal(lout_orig.names, lout_new.names)

    # Test input validation
    assert_raises(ValueError, make_eeg_layout, info, radius=-0.1)
    assert_raises(ValueError, make_eeg_layout, info, radius=0.6)
    assert_raises(ValueError, make_eeg_layout, info, width=-0.1)
    assert_raises(ValueError, make_eeg_layout, info, width=1.1)
    assert_raises(ValueError, make_eeg_layout, info, height=-0.1)
    assert_raises(ValueError, make_eeg_layout, info, height=1.1)
Beispiel #4
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def test_make_eeg_layout():
    """Test creation of EEG layout."""
    tempdir = _TempDir()
    tmp_name = 'foo'
    lout_name = 'test_raw'
    lout_orig = read_layout(kind=lout_name, path=lout_path)
    info = read_info(fif_fname)
    info['bads'].append(info['ch_names'][360])
    layout = make_eeg_layout(info, exclude=[])
    assert_array_equal(len(layout.names), len([ch for ch in info['ch_names']
                                               if ch.startswith('EE')]))
    layout.save(op.join(tempdir, tmp_name + '.lout'))
    lout_new = read_layout(kind=tmp_name, path=tempdir, scale=False)
    assert_array_equal(lout_new.kind, tmp_name)
    assert_allclose(layout.pos, lout_new.pos, atol=0.1)
    assert_array_equal(lout_orig.names, lout_new.names)

    # Test input validation
    pytest.raises(ValueError, make_eeg_layout, info, radius=-0.1)
    pytest.raises(ValueError, make_eeg_layout, info, radius=0.6)
    pytest.raises(ValueError, make_eeg_layout, info, width=-0.1)
    pytest.raises(ValueError, make_eeg_layout, info, width=1.1)
    pytest.raises(ValueError, make_eeg_layout, info, height=-0.1)
    pytest.raises(ValueError, make_eeg_layout, info, height=1.1)
Beispiel #5
0
def test_plot_topomap():
    """Test topomap plotting."""
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle
    # evoked
    warnings.simplefilter('always')
    res = 8
    fast_test = {"res": res, "contours": 0, "sensors": False}
    evoked = read_evokeds(evoked_fname, 'Left Auditory', baseline=(None, 0))

    # Test animation
    _, anim = evoked.animate_topomap(ch_type='grad',
                                     times=[0, 0.1],
                                     butterfly=False)
    anim._func(1)  # _animate has to be tested separately on 'Agg' backend.
    plt.close('all')

    ev_bad = evoked.copy().pick_types(meg=False, eeg=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    plt_topomap = partial(ev_bad.plot_topomap, **fast_test)
    plt_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, plots EEG
    assert_raises(ValueError, plt_topomap, ch_type='mag')
    assert_raises(TypeError, plt_topomap, head_pos='foo')
    assert_raises(KeyError, plt_topomap, head_pos=dict(foo='bar'))
    assert_raises(ValueError, plt_topomap, head_pos=dict(center=0))
    assert_raises(ValueError, plt_topomap, times=[-100])  # bad time
    assert_raises(ValueError, plt_topomap, times=[[0]])  # bad time

    evoked.plot_topomap([0.1],
                        ch_type='eeg',
                        scalings=1,
                        res=res,
                        contours=[-100, 0, 100])
    plt_topomap = partial(evoked.plot_topomap, **fast_test)
    plt_topomap(0.1, layout=layout, scalings=dict(mag=0.1))
    plt.close('all')
    axes = [plt.subplot(221), plt.subplot(222)]
    plt_topomap(axes=axes, colorbar=False)
    plt.close('all')
    plt_topomap(times=[-0.1, 0.2])
    plt.close('all')
    evoked_grad = evoked.copy().crop(0, 0).pick_types(meg='grad')
    mask = np.zeros((204, 1), bool)
    mask[[0, 3, 5, 6]] = True
    names = []

    def proc_names(x):
        names.append(x)
        return x[4:]

    evoked_grad.plot_topomap(ch_type='grad',
                             times=[0],
                             mask=mask,
                             show_names=proc_names,
                             **fast_test)
    assert_equal(sorted(names),
                 ['MEG 011x', 'MEG 012x', 'MEG 013x', 'MEG 014x'])
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    plt_topomap(ch_type='mag', outlines=None)
    times = [0.1]
    plt_topomap(times, ch_type='grad', mask=mask)
    plt_topomap(times, ch_type='planar1')
    plt_topomap(times, ch_type='planar2')
    plt_topomap(times,
                ch_type='grad',
                mask=mask,
                show_names=True,
                mask_params={'marker': 'x'})
    plt.close('all')
    assert_raises(ValueError, plt_topomap, times, ch_type='eeg', average=-1e3)
    assert_raises(ValueError, plt_topomap, times, ch_type='eeg', average='x')

    p = plt_topomap(times,
                    ch_type='grad',
                    image_interp='bilinear',
                    show_names=lambda x: x.replace('MEG', ''))
    subplot = [
        x for x in p.get_children() if isinstance(x, matplotlib.axes.Subplot)
    ][0]
    assert_true(
        all('MEG' not in x.get_text() for x in subplot.get_children()
            if isinstance(x, matplotlib.text.Text)))

    # Plot array
    for ch_type in ('mag', 'grad'):
        evoked_ = evoked.copy().pick_types(eeg=False, meg=ch_type)
        plot_topomap(evoked_.data[:, 0], evoked_.info, **fast_test)
    # fail with multiple channel types
    assert_raises(ValueError, plot_topomap, evoked.data[0, :], evoked.info)

    # Test title
    def get_texts(p):
        return [
            x.get_text() for x in p.get_children()
            if isinstance(x, matplotlib.text.Text)
        ]

    p = plt_topomap(times, ch_type='eeg', average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = plt_topomap(times, ch_type='eeg', title='Custom')
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], 'Custom')
    plt.close('all')

    # delaunay triangulation warning
    with warnings.catch_warnings(record=True):  # can't show
        warnings.simplefilter('always')
        plt_topomap(times, ch_type='mag', layout=None)
    assert_raises(RuntimeError,
                  plot_evoked_topomap,
                  evoked,
                  0.1,
                  'mag',
                  proj='interactive')  # projs have already been applied

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname,
                          'Left Auditory',
                          baseline=(None, 0),
                          proj=False)
    with warnings.catch_warnings(record=True):
        warnings.simplefilter('always')
        fig1 = evoked.plot_topomap('interactive',
                                   'mag',
                                   proj='interactive',
                                   **fast_test)
        _fake_click(fig1, fig1.axes[1], (0.5, 0.5))  # click slider
    data_max = np.max(fig1.axes[0].images[0]._A)
    fig2 = plt.gcf()
    _fake_click(fig2, fig2.axes[0], (0.075, 0.775))  # toggle projector
    # make sure projector gets toggled
    assert_true(np.max(fig1.axes[0].images[0]._A) != data_max)

    assert_raises(RuntimeError, plot_evoked_topomap, evoked, np.repeat(.1, 50))
    assert_raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6])

    for ch in evoked.info['chs']:
        if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
            ch['loc'].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info['dig'][85]

    pos = make_eeg_layout(evoked.info).pos[:, :2]
    pos, outlines = _check_outlines(pos, 'head')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.5)

    pos, outlines = _check_outlines(pos, 'skirt')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(not outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.625)

    pos, outlines = _check_outlines(pos,
                                    'skirt',
                                    head_pos={'scale': [1.2, 1.2]})
    assert_array_equal(outlines['clip_radius'], 0.75)

    # Plot skirt
    evoked.plot_topomap(times, ch_type='eeg', outlines='skirt', **fast_test)

    # Pass custom outlines without patch
    evoked.plot_topomap(times, ch_type='eeg', outlines=outlines, **fast_test)
    plt.close('all')

    # Test interactive cmap
    fig = plot_evoked_topomap(evoked,
                              times=[0., 0.1],
                              ch_type='eeg',
                              cmap=('Reds', True),
                              title='title',
                              **fast_test)
    fig.canvas.key_press_event('up')
    fig.canvas.key_press_event(' ')
    fig.canvas.key_press_event('down')
    cbar = fig.get_axes()[0].CB  # Fake dragging with mouse.
    ax = cbar.cbar.ax
    _fake_click(fig, ax, (0.1, 0.1))
    _fake_click(fig, ax, (0.1, 0.2), kind='motion')
    _fake_click(fig, ax, (0.1, 0.3), kind='release')

    _fake_click(fig, ax, (0.1, 0.1), button=3)
    _fake_click(fig, ax, (0.1, 0.2), button=3, kind='motion')
    _fake_click(fig, ax, (0.1, 0.3), kind='release')

    fig.canvas.scroll_event(0.5, 0.5, -0.5)  # scroll down
    fig.canvas.scroll_event(0.5, 0.5, 0.5)  # scroll up

    plt.close('all')

    # Pass custom outlines with patch callable
    def patch():
        return Circle((0.5, 0.4687),
                      radius=.46,
                      clip_on=True,
                      transform=plt.gca().transAxes)

    outlines['patch'] = patch
    plot_evoked_topomap(evoked,
                        times,
                        ch_type='eeg',
                        outlines=outlines,
                        **fast_test)

    # Remove digitization points. Now topomap should fail
    evoked.info['dig'] = None
    assert_raises(RuntimeError,
                  plot_evoked_topomap,
                  evoked,
                  times,
                  ch_type='eeg')
    plt.close('all')

    # Error for missing names
    n_channels = len(pos)
    data = np.ones(n_channels)
    assert_raises(ValueError, plot_topomap, data, pos, show_names=True)

    # Test error messages for invalid pos parameter
    pos_1d = np.zeros(n_channels)
    pos_3d = np.zeros((n_channels, 2, 2))
    assert_raises(ValueError, plot_topomap, data, pos_1d)
    assert_raises(ValueError, plot_topomap, data, pos_3d)
    assert_raises(ValueError, plot_topomap, data, pos[:3, :])

    pos_x = pos[:, :1]
    pos_xyz = np.c_[pos, np.zeros(n_channels)[:, np.newaxis]]
    assert_raises(ValueError, plot_topomap, data, pos_x)
    assert_raises(ValueError, plot_topomap, data, pos_xyz)

    # An #channels x 4 matrix should work though. In this case (x, y, width,
    # height) is assumed.
    pos_xywh = np.c_[pos, np.zeros((n_channels, 2))]
    plot_topomap(data, pos_xywh)
    plt.close('all')

    # Test peak finder
    axes = [plt.subplot(131), plt.subplot(132)]
    with warnings.catch_warnings(record=True):  # rightmost column
        evoked.plot_topomap(times='peaks', axes=axes, **fast_test)
    plt.close('all')
    evoked.data = np.zeros(evoked.data.shape)
    evoked.data[50][1] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[1])
    evoked.data[80][100] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 100]])
    evoked.data[2][95] = 2
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 95]])
    assert_array_equal(_find_peaks(evoked, 1), evoked.times[95])

    # Test excluding bads channels
    evoked_grad.info['bads'] += [evoked_grad.info['ch_names'][0]]
    orig_bads = evoked_grad.info['bads']
    evoked_grad.plot_topomap(ch_type='grad', times=[0])
    assert_array_equal(evoked_grad.info['bads'], orig_bads)
    plt.close('all')
Beispiel #6
0
def test_plot_topomap():
    """Test topomap plotting
    """
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle

    # evoked
    warnings.simplefilter("always")
    res = 16
    evoked = read_evokeds(evoked_fname, "Left Auditory", baseline=(None, 0))
    # Test animation
    _, anim = evoked.animate_topomap(ch_type="grad", times=[0, 0.1], butterfly=False)
    anim._func(1)  # _animate has to be tested separately on 'Agg' backend.
    plt.close("all")

    ev_bad = evoked.pick_types(meg=False, eeg=True, copy=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    ev_bad.plot_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, plots EEG
    assert_raises(ValueError, ev_bad.plot_topomap, ch_type="mag")
    assert_raises(TypeError, ev_bad.plot_topomap, head_pos="foo")
    assert_raises(KeyError, ev_bad.plot_topomap, head_pos=dict(foo="bar"))
    assert_raises(ValueError, ev_bad.plot_topomap, head_pos=dict(center=0))
    assert_raises(ValueError, ev_bad.plot_topomap, times=[-100])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time

    evoked.plot_topomap(0.1, layout=layout, scale=dict(mag=0.1))
    plt.close("all")
    axes = [plt.subplot(221), plt.subplot(222)]
    evoked.plot_topomap(axes=axes, colorbar=False)
    plt.close("all")
    evoked.plot_topomap(times=[-0.1, 0.2])
    plt.close("all")
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    evoked.plot_topomap(ch_type="mag", outlines=None)
    times = [0.1]
    evoked.plot_topomap(times, ch_type="eeg", res=res, scale=1)
    evoked.plot_topomap(times, ch_type="grad", mask=mask, res=res)
    evoked.plot_topomap(times, ch_type="planar1", res=res)
    evoked.plot_topomap(times, ch_type="planar2", res=res)
    evoked.plot_topomap(times, ch_type="grad", mask=mask, res=res, show_names=True, mask_params={"marker": "x"})
    plt.close("all")
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type="eeg", res=res, average=-1000)
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type="eeg", res=res, average="hahahahah")

    p = evoked.plot_topomap(
        times, ch_type="grad", res=res, show_names=lambda x: x.replace("MEG", ""), image_interp="bilinear"
    )
    subplot = [x for x in p.get_children() if isinstance(x, matplotlib.axes.Subplot)][0]
    assert_true(all("MEG" not in x.get_text() for x in subplot.get_children() if isinstance(x, matplotlib.text.Text)))

    # Test title
    def get_texts(p):
        return [x.get_text() for x in p.get_children() if isinstance(x, matplotlib.text.Text)]

    p = evoked.plot_topomap(times, ch_type="eeg", res=res, average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = evoked.plot_topomap(times, ch_type="eeg", title="Custom", res=res)
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], "Custom")
    plt.close("all")

    # delaunay triangulation warning
    with warnings.catch_warnings(record=True):  # can't show
        warnings.simplefilter("always")
        evoked.plot_topomap(times, ch_type="mag", layout=None, res=res)
    assert_raises(
        RuntimeError, plot_evoked_topomap, evoked, 0.1, "mag", proj="interactive"
    )  # projs have already been applied

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname, "Left Auditory", baseline=(None, 0), proj=False)
    with warnings.catch_warnings(record=True):
        warnings.simplefilter("always")
        evoked.plot_topomap(0.1, "mag", proj="interactive", res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked, np.repeat(0.1, 50))
    assert_raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6])

    with warnings.catch_warnings(record=True):  # file conventions
        warnings.simplefilter("always")
        projs = read_proj(ecg_fname)
    projs = [pp for pp in projs if pp["desc"].lower().find("eeg") < 0]
    plot_projs_topomap(projs, res=res)
    plt.close("all")
    ax = plt.subplot(111)
    plot_projs_topomap([projs[0]], res=res, axes=ax)  # test axes param
    plt.close("all")
    for ch in evoked.info["chs"]:
        if ch["coil_type"] == FIFF.FIFFV_COIL_EEG:
            ch["loc"].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info["dig"][85]

    pos = make_eeg_layout(evoked.info).pos[:, :2]
    pos, outlines = _check_outlines(pos, "head")
    assert_true("head" in outlines.keys())
    assert_true("nose" in outlines.keys())
    assert_true("ear_left" in outlines.keys())
    assert_true("ear_right" in outlines.keys())
    assert_true("autoshrink" in outlines.keys())
    assert_true(outlines["autoshrink"])
    assert_true("clip_radius" in outlines.keys())
    assert_array_equal(outlines["clip_radius"], 0.5)

    pos, outlines = _check_outlines(pos, "skirt")
    assert_true("head" in outlines.keys())
    assert_true("nose" in outlines.keys())
    assert_true("ear_left" in outlines.keys())
    assert_true("ear_right" in outlines.keys())
    assert_true("autoshrink" in outlines.keys())
    assert_true(not outlines["autoshrink"])
    assert_true("clip_radius" in outlines.keys())
    assert_array_equal(outlines["clip_radius"], 0.625)

    pos, outlines = _check_outlines(pos, "skirt", head_pos={"scale": [1.2, 1.2]})
    assert_array_equal(outlines["clip_radius"], 0.75)

    # Plot skirt
    evoked.plot_topomap(times, ch_type="eeg", outlines="skirt")

    # Pass custom outlines without patch
    evoked.plot_topomap(times, ch_type="eeg", outlines=outlines)
    plt.close("all")

    # Pass custom outlines with patch callable
    def patch():
        return Circle((0.5, 0.4687), radius=0.46, clip_on=True, transform=plt.gca().transAxes)

    outlines["patch"] = patch
    plot_evoked_topomap(evoked, times, ch_type="eeg", outlines=outlines)

    # Remove digitization points. Now topomap should fail
    evoked.info["dig"] = None
    assert_raises(RuntimeError, plot_evoked_topomap, evoked, times, ch_type="eeg")
    plt.close("all")

    # Error for missing names
    n_channels = len(pos)
    data = np.ones(n_channels)
    assert_raises(ValueError, plot_topomap, data, pos, show_names=True)

    # Test error messages for invalid pos parameter
    pos_1d = np.zeros(n_channels)
    pos_3d = np.zeros((n_channels, 2, 2))
    assert_raises(ValueError, plot_topomap, data, pos_1d)
    assert_raises(ValueError, plot_topomap, data, pos_3d)
    assert_raises(ValueError, plot_topomap, data, pos[:3, :])

    pos_x = pos[:, :1]
    pos_xyz = np.c_[pos, np.zeros(n_channels)[:, np.newaxis]]
    assert_raises(ValueError, plot_topomap, data, pos_x)
    assert_raises(ValueError, plot_topomap, data, pos_xyz)

    # An #channels x 4 matrix should work though. In this case (x, y, width,
    # height) is assumed.
    pos_xywh = np.c_[pos, np.zeros((n_channels, 2))]
    plot_topomap(data, pos_xywh)
    plt.close("all")

    # Test peak finder
    axes = [plt.subplot(131), plt.subplot(132)]
    with warnings.catch_warnings(record=True):  # rightmost column
        evoked.plot_topomap(times="peaks", axes=axes)
    plt.close("all")
    evoked.data = np.zeros(evoked.data.shape)
    evoked.data[50][1] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[1])
    evoked.data[80][100] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 100]])
    evoked.data[2][95] = 2
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 95]])
    assert_array_equal(_find_peaks(evoked, 1), evoked.times[95])
Beispiel #7
0
def test_plot_topomap():
    """Test topomap plotting
    """
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle
    # evoked
    warnings.simplefilter('always')
    res = 16
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0))
    ev_bad = evoked.pick_types(meg=False, eeg=True, copy=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    ev_bad.plot_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, should plot EEG
    assert_raises(ValueError, ev_bad.plot_topomap, ch_type='mag')
    assert_raises(TypeError, ev_bad.plot_topomap, head_pos='foo')
    assert_raises(KeyError, ev_bad.plot_topomap, head_pos=dict(foo='bar'))
    assert_raises(ValueError, ev_bad.plot_topomap, head_pos=dict(center=0))
    assert_raises(ValueError, ev_bad.plot_topomap, times=[-100])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time

    evoked.plot_topomap(0.1, layout=layout, scale=dict(mag=0.1))
    plt.close('all')
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    evoked.plot_topomap(None, ch_type='mag', outlines=None)
    times = [0.1]
    evoked.plot_topomap(times, ch_type='eeg', res=res, scale=1)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res)
    evoked.plot_topomap(times, ch_type='planar1', res=res)
    evoked.plot_topomap(times, ch_type='planar2', res=res)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res,
                        show_names=True, mask_params={'marker': 'x'})
    plt.close('all')
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type='eeg',
                  res=res, average=-1000)
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type='eeg',
                  res=res, average='hahahahah')

    p = evoked.plot_topomap(times, ch_type='grad', res=res,
                            show_names=lambda x: x.replace('MEG', ''),
                            image_interp='bilinear')
    subplot = [x for x in p.get_children() if
               isinstance(x, matplotlib.axes.Subplot)][0]
    assert_true(all('MEG' not in x.get_text()
                    for x in subplot.get_children()
                    if isinstance(x, matplotlib.text.Text)))

    # Test title
    def get_texts(p):
        return [x.get_text() for x in p.get_children() if
                isinstance(x, matplotlib.text.Text)]

    p = evoked.plot_topomap(times, ch_type='eeg', res=res, average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = evoked.plot_topomap(times, ch_type='eeg', title='Custom', res=res)
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], 'Custom')
    plt.close('all')

    # delaunay triangulation warning
    with warnings.catch_warnings(record=True):  # can't show
        warnings.simplefilter('always')
        evoked.plot_topomap(times, ch_type='mag', layout=None, res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked, 0.1, 'mag',
                  proj='interactive')  # projs have already been applied

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0), proj=False)
    with warnings.catch_warnings(record=True):
        warnings.simplefilter('always')
        evoked.plot_topomap(0.1, 'mag', proj='interactive', res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked,
                  np.repeat(.1, 50))
    assert_raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6])

    with warnings.catch_warnings(record=True):  # file conventions
        warnings.simplefilter('always')
        projs = read_proj(ecg_fname)
    projs = [pp for pp in projs if pp['desc'].lower().find('eeg') < 0]
    plot_projs_topomap(projs, res=res)
    plt.close('all')
    for ch in evoked.info['chs']:
        if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
            if ch['eeg_loc'] is not None:
                ch['eeg_loc'].fill(0)
            ch['loc'].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info['dig'][85]

    pos = make_eeg_layout(evoked.info).pos
    pos, outlines = _check_outlines(pos, 'head')
    # test 1: pass custom outlines without patch

    def patch():
        return Circle((0.5, 0.4687), radius=.46,
                      clip_on=True, transform=plt.gca().transAxes)

    # test 2: pass custom outlines with patch callable
    outlines['patch'] = patch
    plot_evoked_topomap(evoked, times, ch_type='eeg', outlines='head')
    # Remove digitization points. Now topomap should fail
    evoked.info['dig'] = None
    assert_raises(RuntimeError, plot_evoked_topomap, evoked,
                  times, ch_type='eeg')
    plt.close('all')
Beispiel #8
0
def test_plot_topomap():
    """Test topomap plotting."""
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle
    # evoked
    res = 8
    fast_test = dict(res=res, contours=0, sensors=False, time_unit='s')
    fast_test_noscale = dict(res=res, contours=0, sensors=False)
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0))

    # Test animation
    _, anim = evoked.animate_topomap(ch_type='grad', times=[0, 0.1],
                                     butterfly=False, time_unit='s')
    anim._func(1)  # _animate has to be tested separately on 'Agg' backend.
    plt.close('all')

    ev_bad = evoked.copy().pick_types(meg=False, eeg=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    plt_topomap = partial(ev_bad.plot_topomap, **fast_test)
    plt_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, plots EEG
    pytest.raises(ValueError, plt_topomap, ch_type='mag')
    pytest.raises(TypeError, plt_topomap, head_pos='foo')
    pytest.raises(KeyError, plt_topomap, head_pos=dict(foo='bar'))
    pytest.raises(ValueError, plt_topomap, head_pos=dict(center=0))
    pytest.raises(ValueError, plt_topomap, times=[-100])  # bad time
    pytest.raises(ValueError, plt_topomap, times=[[0]])  # bad time

    evoked.plot_topomap([0.1], ch_type='eeg', scalings=1, res=res,
                        contours=[-100, 0, 100], time_unit='ms')
    plt_topomap = partial(evoked.plot_topomap, **fast_test)
    plt_topomap(0.1, layout=layout, scalings=dict(mag=0.1))
    plt.close('all')
    axes = [plt.subplot(221), plt.subplot(222)]
    plt_topomap(axes=axes, colorbar=False)
    plt.close('all')
    plt_topomap(times=[-0.1, 0.2])
    plt.close('all')
    evoked_grad = evoked.copy().crop(0, 0).pick_types(meg='grad')
    mask = np.zeros((204, 1), bool)
    mask[[0, 3, 5, 6]] = True
    names = []

    def proc_names(x):
        names.append(x)
        return x[4:]

    evoked_grad.plot_topomap(ch_type='grad', times=[0], mask=mask,
                             show_names=proc_names, **fast_test)
    assert_equal(sorted(names),
                 ['MEG 011x', 'MEG 012x', 'MEG 013x', 'MEG 014x'])
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    plt_topomap(ch_type='mag', outlines=None)
    times = [0.1]
    plt_topomap(times, ch_type='grad', mask=mask)
    plt_topomap(times, ch_type='planar1')
    plt_topomap(times, ch_type='planar2')
    plt_topomap(times, ch_type='grad', mask=mask, show_names=True,
                mask_params={'marker': 'x'})
    plt.close('all')
    pytest.raises(ValueError, plt_topomap, times, ch_type='eeg', average=-1e3)
    pytest.raises(ValueError, plt_topomap, times, ch_type='eeg', average='x')

    p = plt_topomap(times, ch_type='grad', image_interp='bilinear',
                    show_names=lambda x: x.replace('MEG', ''))
    subplot = [x for x in p.get_children() if 'Subplot' in str(type(x))]
    assert len(subplot) >= 1, [type(x) for x in p.get_children()]
    subplot = subplot[0]
    assert (all('MEG' not in x.get_text()
                for x in subplot.get_children()
                if isinstance(x, matplotlib.text.Text)))

    # Plot array
    for ch_type in ('mag', 'grad'):
        evoked_ = evoked.copy().pick_types(eeg=False, meg=ch_type)
        plot_topomap(evoked_.data[:, 0], evoked_.info, **fast_test_noscale)
    # fail with multiple channel types
    pytest.raises(ValueError, plot_topomap, evoked.data[0, :], evoked.info)

    # Test title
    def get_texts(p):
        return [x.get_text() for x in p.get_children() if
                isinstance(x, matplotlib.text.Text)]

    p = plt_topomap(times, ch_type='eeg', average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = plt_topomap(times, ch_type='eeg', title='Custom')
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], 'Custom')
    plt.close('all')

    # delaunay triangulation warning
    plt_topomap(times, ch_type='mag', layout=None)
    # projs have already been applied
    pytest.raises(RuntimeError, plot_evoked_topomap, evoked, 0.1, 'mag',
                  proj='interactive', time_unit='s')

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0), proj=False)
    fig1 = evoked.plot_topomap('interactive', 'mag', proj='interactive',
                               **fast_test)
    _fake_click(fig1, fig1.axes[1], (0.5, 0.5))  # click slider
    data_max = np.max(fig1.axes[0].images[0]._A)
    fig2 = plt.gcf()
    _fake_click(fig2, fig2.axes[0], (0.075, 0.775))  # toggle projector
    # make sure projector gets toggled
    assert (np.max(fig1.axes[0].images[0]._A) != data_max)

    pytest.raises(RuntimeError, plot_evoked_topomap, evoked,
                  np.repeat(.1, 50), time_unit='s')
    pytest.raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6],
                  time_unit='s')

    for ch in evoked.info['chs']:
        if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
            ch['loc'].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info['dig'][85]

    pos = make_eeg_layout(evoked.info).pos[:, :2]
    pos, outlines = _check_outlines(pos, 'head')
    assert ('head' in outlines.keys())
    assert ('nose' in outlines.keys())
    assert ('ear_left' in outlines.keys())
    assert ('ear_right' in outlines.keys())
    assert ('autoshrink' in outlines.keys())
    assert (outlines['autoshrink'])
    assert ('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.5)

    pos, outlines = _check_outlines(pos, 'skirt')
    assert ('head' in outlines.keys())
    assert ('nose' in outlines.keys())
    assert ('ear_left' in outlines.keys())
    assert ('ear_right' in outlines.keys())
    assert ('autoshrink' in outlines.keys())
    assert (not outlines['autoshrink'])
    assert ('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.625)

    pos, outlines = _check_outlines(pos, 'skirt',
                                    head_pos={'scale': [1.2, 1.2]})
    assert_array_equal(outlines['clip_radius'], 0.75)

    # Plot skirt
    evoked.plot_topomap(times, ch_type='eeg', outlines='skirt', **fast_test)

    # Pass custom outlines without patch
    evoked.plot_topomap(times, ch_type='eeg', outlines=outlines, **fast_test)
    plt.close('all')

    # Test interactive cmap
    fig = plot_evoked_topomap(evoked, times=[0., 0.1], ch_type='eeg',
                              cmap=('Reds', True), title='title', **fast_test)
    fig.canvas.key_press_event('up')
    fig.canvas.key_press_event(' ')
    fig.canvas.key_press_event('down')
    cbar = fig.get_axes()[0].CB  # Fake dragging with mouse.
    ax = cbar.cbar.ax
    _fake_click(fig, ax, (0.1, 0.1))
    _fake_click(fig, ax, (0.1, 0.2), kind='motion')
    _fake_click(fig, ax, (0.1, 0.3), kind='release')

    _fake_click(fig, ax, (0.1, 0.1), button=3)
    _fake_click(fig, ax, (0.1, 0.2), button=3, kind='motion')
    _fake_click(fig, ax, (0.1, 0.3), kind='release')

    fig.canvas.scroll_event(0.5, 0.5, -0.5)  # scroll down
    fig.canvas.scroll_event(0.5, 0.5, 0.5)  # scroll up

    plt.close('all')

    # Pass custom outlines with patch callable
    def patch():
        return Circle((0.5, 0.4687), radius=.46,
                      clip_on=True, transform=plt.gca().transAxes)
    outlines['patch'] = patch
    plot_evoked_topomap(evoked, times, ch_type='eeg', outlines=outlines,
                        **fast_test)

    # Remove digitization points. Now topomap should fail
    evoked.info['dig'] = None
    pytest.raises(RuntimeError, plot_evoked_topomap, evoked,
                  times, ch_type='eeg', time_unit='s')
    plt.close('all')

    # Error for missing names
    n_channels = len(pos)
    data = np.ones(n_channels)
    pytest.raises(ValueError, plot_topomap, data, pos, show_names=True)

    # Test error messages for invalid pos parameter
    pos_1d = np.zeros(n_channels)
    pos_3d = np.zeros((n_channels, 2, 2))
    pytest.raises(ValueError, plot_topomap, data, pos_1d)
    pytest.raises(ValueError, plot_topomap, data, pos_3d)
    pytest.raises(ValueError, plot_topomap, data, pos[:3, :])

    pos_x = pos[:, :1]
    pos_xyz = np.c_[pos, np.zeros(n_channels)[:, np.newaxis]]
    pytest.raises(ValueError, plot_topomap, data, pos_x)
    pytest.raises(ValueError, plot_topomap, data, pos_xyz)

    # An #channels x 4 matrix should work though. In this case (x, y, width,
    # height) is assumed.
    pos_xywh = np.c_[pos, np.zeros((n_channels, 2))]
    plot_topomap(data, pos_xywh)
    plt.close('all')

    # Test peak finder
    axes = [plt.subplot(131), plt.subplot(132)]
    evoked.plot_topomap(times='peaks', axes=axes, **fast_test)
    plt.close('all')
    evoked.data = np.zeros(evoked.data.shape)
    evoked.data[50][1] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[1])
    evoked.data[80][100] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 100]])
    evoked.data[2][95] = 2
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 95]])
    assert_array_equal(_find_peaks(evoked, 1), evoked.times[95])

    # Test excluding bads channels
    evoked_grad.info['bads'] += [evoked_grad.info['ch_names'][0]]
    orig_bads = evoked_grad.info['bads']
    evoked_grad.plot_topomap(ch_type='grad', times=[0], time_unit='ms')
    assert_array_equal(evoked_grad.info['bads'], orig_bads)
    plt.close('all')
from udgan.io import convert_mat_structure

data_path = 'data/2010-02-16_0009'

# Events management
raw, events, event_id = convert_mat_structure(data_path)
mne.viz.plot_events(events=events, event_id=event_id,
                    sfreq=raw.info['sfreq'])
event_id = {'Boop': 1, 'Beep': 2, 'Motor response': 6}

# Check raw signals
raw.plot()

# Generate topographic layout
from mne.channels import make_eeg_layout
layout = make_eeg_layout(raw.info, exclude=['MOh','MOb'])

# Generate evoked potentials
tmin, tmax = -0.2, 0.5
include = []
picks = mne.pick_types(raw.info, meg=True, eeg=True, stim=False, eog=True,
                       include=include, exclude='bads')
epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                    baseline=(None, 0), preload=True)
epochs.plot(trellis=False, title='Auditory odd ball')

# Visualization of neural repsonses for differ
import matplotlib.pyplot as plt
from mne.viz import plot_topomap
import numpy as np
res=16
Beispiel #10
0
def test_plot_topomap():
    """Test topomap plotting
    """
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle
    # evoked
    warnings.simplefilter('always')
    res = 16
    evoked = read_evokeds(evoked_fname, 'Left Auditory', baseline=(None, 0))

    # Test animation
    _, anim = evoked.animate_topomap(ch_type='grad',
                                     times=[0, 0.1],
                                     butterfly=False)
    anim._func(1)  # _animate has to be tested separately on 'Agg' backend.
    plt.close('all')

    ev_bad = evoked.copy().pick_types(meg=False, eeg=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    ev_bad.plot_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, plots EEG
    assert_raises(ValueError, ev_bad.plot_topomap, ch_type='mag')
    assert_raises(TypeError, ev_bad.plot_topomap, head_pos='foo')
    assert_raises(KeyError, ev_bad.plot_topomap, head_pos=dict(foo='bar'))
    assert_raises(ValueError, ev_bad.plot_topomap, head_pos=dict(center=0))
    assert_raises(ValueError, ev_bad.plot_topomap, times=[-100])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time

    evoked.plot_topomap(0.1, layout=layout, scale=dict(mag=0.1))
    plt.close('all')
    axes = [plt.subplot(221), plt.subplot(222)]
    evoked.plot_topomap(axes=axes, colorbar=False)
    plt.close('all')
    evoked.plot_topomap(times=[-0.1, 0.2])
    plt.close('all')
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    evoked.plot_topomap(ch_type='mag', outlines=None)
    times = [0.1]
    evoked.plot_topomap(times, ch_type='eeg', res=res, scale=1)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res)
    evoked.plot_topomap(times, ch_type='planar1', res=res)
    evoked.plot_topomap(times, ch_type='planar2', res=res)
    evoked.plot_topomap(times,
                        ch_type='grad',
                        mask=mask,
                        res=res,
                        show_names=True,
                        mask_params={'marker': 'x'})
    plt.close('all')
    assert_raises(ValueError,
                  evoked.plot_topomap,
                  times,
                  ch_type='eeg',
                  res=res,
                  average=-1000)
    assert_raises(ValueError,
                  evoked.plot_topomap,
                  times,
                  ch_type='eeg',
                  res=res,
                  average='hahahahah')

    p = evoked.plot_topomap(times,
                            ch_type='grad',
                            res=res,
                            show_names=lambda x: x.replace('MEG', ''),
                            image_interp='bilinear')
    subplot = [
        x for x in p.get_children() if isinstance(x, matplotlib.axes.Subplot)
    ][0]
    assert_true(
        all('MEG' not in x.get_text() for x in subplot.get_children()
            if isinstance(x, matplotlib.text.Text)))

    # Plot array
    for ch_type in ('mag', 'grad'):
        evoked_ = evoked.copy().pick_types(eeg=False, meg=ch_type)
        plot_topomap(evoked_.data[:, 0], evoked_.info)
    # fail with multiple channel types
    assert_raises(ValueError, plot_topomap, evoked.data[0, :], evoked.info)

    # Test title
    def get_texts(p):
        return [
            x.get_text() for x in p.get_children()
            if isinstance(x, matplotlib.text.Text)
        ]

    p = evoked.plot_topomap(times, ch_type='eeg', res=res, average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = evoked.plot_topomap(times, ch_type='eeg', title='Custom', res=res)
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], 'Custom')
    plt.close('all')

    # delaunay triangulation warning
    with warnings.catch_warnings(record=True):  # can't show
        warnings.simplefilter('always')
        evoked.plot_topomap(times, ch_type='mag', layout=None, res=res)
    assert_raises(RuntimeError,
                  plot_evoked_topomap,
                  evoked,
                  0.1,
                  'mag',
                  proj='interactive')  # projs have already been applied

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname,
                          'Left Auditory',
                          baseline=(None, 0),
                          proj=False)
    with warnings.catch_warnings(record=True):
        warnings.simplefilter('always')
        evoked.plot_topomap(0.1, 'mag', proj='interactive', res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked, np.repeat(.1, 50))
    assert_raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6])

    with warnings.catch_warnings(record=True):  # file conventions
        warnings.simplefilter('always')
        projs = read_proj(ecg_fname)
    projs = [pp for pp in projs if pp['desc'].lower().find('eeg') < 0]
    plot_projs_topomap(projs, res=res)
    plt.close('all')
    ax = plt.subplot(111)
    plot_projs_topomap([projs[0]], res=res, axes=ax)  # test axes param
    plt.close('all')
    for ch in evoked.info['chs']:
        if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
            ch['loc'].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info['dig'][85]

    pos = make_eeg_layout(evoked.info).pos[:, :2]
    pos, outlines = _check_outlines(pos, 'head')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.5)

    pos, outlines = _check_outlines(pos, 'skirt')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(not outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.625)

    pos, outlines = _check_outlines(pos,
                                    'skirt',
                                    head_pos={'scale': [1.2, 1.2]})
    assert_array_equal(outlines['clip_radius'], 0.75)

    # Plot skirt
    evoked.plot_topomap(times, ch_type='eeg', outlines='skirt')

    # Pass custom outlines without patch
    evoked.plot_topomap(times, ch_type='eeg', outlines=outlines)
    plt.close('all')

    # Pass custom outlines with patch callable
    def patch():
        return Circle((0.5, 0.4687),
                      radius=.46,
                      clip_on=True,
                      transform=plt.gca().transAxes)

    outlines['patch'] = patch
    plot_evoked_topomap(evoked, times, ch_type='eeg', outlines=outlines)

    # Remove digitization points. Now topomap should fail
    evoked.info['dig'] = None
    assert_raises(RuntimeError,
                  plot_evoked_topomap,
                  evoked,
                  times,
                  ch_type='eeg')
    plt.close('all')

    # Error for missing names
    n_channels = len(pos)
    data = np.ones(n_channels)
    assert_raises(ValueError, plot_topomap, data, pos, show_names=True)

    # Test error messages for invalid pos parameter
    pos_1d = np.zeros(n_channels)
    pos_3d = np.zeros((n_channels, 2, 2))
    assert_raises(ValueError, plot_topomap, data, pos_1d)
    assert_raises(ValueError, plot_topomap, data, pos_3d)
    assert_raises(ValueError, plot_topomap, data, pos[:3, :])

    pos_x = pos[:, :1]
    pos_xyz = np.c_[pos, np.zeros(n_channels)[:, np.newaxis]]
    assert_raises(ValueError, plot_topomap, data, pos_x)
    assert_raises(ValueError, plot_topomap, data, pos_xyz)

    # An #channels x 4 matrix should work though. In this case (x, y, width,
    # height) is assumed.
    pos_xywh = np.c_[pos, np.zeros((n_channels, 2))]
    plot_topomap(data, pos_xywh)
    plt.close('all')

    # Test peak finder
    axes = [plt.subplot(131), plt.subplot(132)]
    with warnings.catch_warnings(record=True):  # rightmost column
        evoked.plot_topomap(times='peaks', axes=axes)
    plt.close('all')
    evoked.data = np.zeros(evoked.data.shape)
    evoked.data[50][1] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[1])
    evoked.data[80][100] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 100]])
    evoked.data[2][95] = 2
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 95]])
    assert_array_equal(_find_peaks(evoked, 1), evoked.times[95])
Beispiel #11
0
def test_plot_topomap():
    """Test topomap plotting
    """
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle
    # evoked
    warnings.simplefilter('always')
    res = 16
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0))
    ev_bad = evoked.pick_types(meg=False, eeg=True, copy=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    ev_bad.plot_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, should plot EEG
    assert_raises(ValueError, ev_bad.plot_topomap, ch_type='mag')
    assert_raises(TypeError, ev_bad.plot_topomap, head_pos='foo')
    assert_raises(KeyError, ev_bad.plot_topomap, head_pos=dict(foo='bar'))
    assert_raises(ValueError, ev_bad.plot_topomap, head_pos=dict(center=0))
    assert_raises(ValueError, ev_bad.plot_topomap, times=[-100])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time

    evoked.plot_topomap(0.1, layout=layout, scale=dict(mag=0.1))
    plt.close('all')
    axes = [plt.subplot(221), plt.subplot(222)]
    evoked.plot_topomap(axes=axes, colorbar=False)
    plt.close('all')
    evoked.plot_topomap(times=[-0.1, 0.2])
    plt.close('all')
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    evoked.plot_topomap(ch_type='mag', outlines=None)
    times = [0.1]
    evoked.plot_topomap(times, ch_type='eeg', res=res, scale=1)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res)
    evoked.plot_topomap(times, ch_type='planar1', res=res)
    evoked.plot_topomap(times, ch_type='planar2', res=res)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res,
                        show_names=True, mask_params={'marker': 'x'})
    plt.close('all')
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type='eeg',
                  res=res, average=-1000)
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type='eeg',
                  res=res, average='hahahahah')

    p = evoked.plot_topomap(times, ch_type='grad', res=res,
                            show_names=lambda x: x.replace('MEG', ''),
                            image_interp='bilinear')
    subplot = [x for x in p.get_children() if
               isinstance(x, matplotlib.axes.Subplot)][0]
    assert_true(all('MEG' not in x.get_text()
                    for x in subplot.get_children()
                    if isinstance(x, matplotlib.text.Text)))

    # Test title
    def get_texts(p):
        return [x.get_text() for x in p.get_children() if
                isinstance(x, matplotlib.text.Text)]

    p = evoked.plot_topomap(times, ch_type='eeg', res=res, average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = evoked.plot_topomap(times, ch_type='eeg', title='Custom', res=res)
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], 'Custom')
    plt.close('all')

    # delaunay triangulation warning
    with warnings.catch_warnings(record=True):  # can't show
        warnings.simplefilter('always')
        evoked.plot_topomap(times, ch_type='mag', layout=None, res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked, 0.1, 'mag',
                  proj='interactive')  # projs have already been applied

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0), proj=False)
    with warnings.catch_warnings(record=True):
        warnings.simplefilter('always')
        evoked.plot_topomap(0.1, 'mag', proj='interactive', res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked,
                  np.repeat(.1, 50))
    assert_raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6])

    with warnings.catch_warnings(record=True):  # file conventions
        warnings.simplefilter('always')
        projs = read_proj(ecg_fname)
    projs = [pp for pp in projs if pp['desc'].lower().find('eeg') < 0]
    plot_projs_topomap(projs, res=res)
    plt.close('all')
    ax = plt.subplot(111)
    plot_projs_topomap([projs[0]], res=res, axes=ax)  # test axes param
    plt.close('all')
    for ch in evoked.info['chs']:
        if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
            ch['loc'].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info['dig'][85]

    pos = make_eeg_layout(evoked.info).pos[:, :2]
    pos, outlines = _check_outlines(pos, 'head')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.5)

    pos, outlines = _check_outlines(pos, 'skirt')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(not outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.625)

    pos, outlines = _check_outlines(pos, 'skirt',
                                    head_pos={'scale': [1.2, 1.2]})
    assert_array_equal(outlines['clip_radius'], 0.75)

    # Plot skirt
    evoked.plot_topomap(times, ch_type='eeg', outlines='skirt')

    # Pass custom outlines without patch
    evoked.plot_topomap(times, ch_type='eeg', outlines=outlines)
    plt.close('all')

    # Pass custom outlines with patch callable
    def patch():
        return Circle((0.5, 0.4687), radius=.46,
                      clip_on=True, transform=plt.gca().transAxes)
    outlines['patch'] = patch
    plot_evoked_topomap(evoked, times, ch_type='eeg', outlines=outlines)

    # Remove digitization points. Now topomap should fail
    evoked.info['dig'] = None
    assert_raises(RuntimeError, plot_evoked_topomap, evoked,
                  times, ch_type='eeg')
    plt.close('all')

    # Error for missing names
    n_channels = len(pos)
    data = np.ones(n_channels)
    assert_raises(ValueError, plot_topomap, data, pos, show_names=True)

    # Test error messages for invalid pos parameter
    pos_1d = np.zeros(n_channels)
    pos_3d = np.zeros((n_channels, 2, 2))
    assert_raises(ValueError, plot_topomap, data, pos_1d)
    assert_raises(ValueError, plot_topomap, data, pos_3d)
    assert_raises(ValueError, plot_topomap, data, pos[:3, :])

    pos_x = pos[:, :1]
    pos_xyz = np.c_[pos, np.zeros(n_channels)[:, np.newaxis]]
    assert_raises(ValueError, plot_topomap, data, pos_x)
    assert_raises(ValueError, plot_topomap, data, pos_xyz)

    # An #channels x 4 matrix should work though. In this case (x, y, width,
    # height) is assumed.
    pos_xywh = np.c_[pos, np.zeros((n_channels, 2))]
    plot_topomap(data, pos_xywh)
    plt.close('all')

    # Test peak finder
    axes = [plt.subplot(131), plt.subplot(132)]
    evoked.plot_topomap(times='peaks', axes=axes)
    plt.close('all')
    evoked.data = np.zeros(evoked.data.shape)
    evoked.data[50][1] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[1])
    evoked.data[80][100] = 1
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 100]])
    evoked.data[2][95] = 2
    assert_array_equal(_find_peaks(evoked, 10), evoked.times[[1, 95]])
    assert_array_equal(_find_peaks(evoked, 1), evoked.times[95])
Beispiel #12
0
def test_plot_topomap():
    """Test topomap plotting
    """
    import matplotlib.pyplot as plt
    from matplotlib.patches import Circle
    # evoked
    warnings.simplefilter('always')
    res = 16
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0))
    ev_bad = evoked.pick_types(meg=False, eeg=True, copy=True)
    ev_bad.pick_channels(ev_bad.ch_names[:2])
    ev_bad.plot_topomap(times=ev_bad.times[:2] - 1e-6)  # auto, should plot EEG
    assert_raises(ValueError, ev_bad.plot_topomap, ch_type='mag')
    assert_raises(TypeError, ev_bad.plot_topomap, head_pos='foo')
    assert_raises(KeyError, ev_bad.plot_topomap, head_pos=dict(foo='bar'))
    assert_raises(ValueError, ev_bad.plot_topomap, head_pos=dict(center=0))
    assert_raises(ValueError, ev_bad.plot_topomap, times=[-100])  # bad time
    assert_raises(ValueError, ev_bad.plot_topomap, times=[[0]])  # bad time

    evoked.plot_topomap(0.1, layout=layout, scale=dict(mag=0.1))
    plt.close('all')
    axes = [plt.subplot(221), plt.subplot(222)]
    evoked.plot_topomap(axes=axes, colorbar=False)
    plt.close('all')
    evoked.plot_topomap(times=[-0.1, 0.2])
    plt.close('all')
    mask = np.zeros_like(evoked.data, dtype=bool)
    mask[[1, 5], :] = True
    evoked.plot_topomap(None, ch_type='mag', outlines=None)
    times = [0.1]
    evoked.plot_topomap(times, ch_type='eeg', res=res, scale=1)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res)
    evoked.plot_topomap(times, ch_type='planar1', res=res)
    evoked.plot_topomap(times, ch_type='planar2', res=res)
    evoked.plot_topomap(times, ch_type='grad', mask=mask, res=res,
                        show_names=True, mask_params={'marker': 'x'})
    plt.close('all')
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type='eeg',
                  res=res, average=-1000)
    assert_raises(ValueError, evoked.plot_topomap, times, ch_type='eeg',
                  res=res, average='hahahahah')

    p = evoked.plot_topomap(times, ch_type='grad', res=res,
                            show_names=lambda x: x.replace('MEG', ''),
                            image_interp='bilinear')
    subplot = [x for x in p.get_children() if
               isinstance(x, matplotlib.axes.Subplot)][0]
    assert_true(all('MEG' not in x.get_text()
                    for x in subplot.get_children()
                    if isinstance(x, matplotlib.text.Text)))

    # Test title
    def get_texts(p):
        return [x.get_text() for x in p.get_children() if
                isinstance(x, matplotlib.text.Text)]

    p = evoked.plot_topomap(times, ch_type='eeg', res=res, average=0.01)
    assert_equal(len(get_texts(p)), 0)
    p = evoked.plot_topomap(times, ch_type='eeg', title='Custom', res=res)
    texts = get_texts(p)
    assert_equal(len(texts), 1)
    assert_equal(texts[0], 'Custom')
    plt.close('all')

    # delaunay triangulation warning
    with warnings.catch_warnings(record=True):  # can't show
        warnings.simplefilter('always')
        evoked.plot_topomap(times, ch_type='mag', layout=None, res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked, 0.1, 'mag',
                  proj='interactive')  # projs have already been applied

    # change to no-proj mode
    evoked = read_evokeds(evoked_fname, 'Left Auditory',
                          baseline=(None, 0), proj=False)
    with warnings.catch_warnings(record=True):
        warnings.simplefilter('always')
        evoked.plot_topomap(0.1, 'mag', proj='interactive', res=res)
    assert_raises(RuntimeError, plot_evoked_topomap, evoked,
                  np.repeat(.1, 50))
    assert_raises(ValueError, plot_evoked_topomap, evoked, [-3e12, 15e6])

    with warnings.catch_warnings(record=True):  # file conventions
        warnings.simplefilter('always')
        projs = read_proj(ecg_fname)
    projs = [pp for pp in projs if pp['desc'].lower().find('eeg') < 0]
    plot_projs_topomap(projs, res=res)
    plt.close('all')
    ax = plt.subplot(111)
    plot_projs_topomap([projs[0]], res=res, axes=ax)  # test axes param
    plt.close('all')
    for ch in evoked.info['chs']:
        if ch['coil_type'] == FIFF.FIFFV_COIL_EEG:
            if ch['eeg_loc'] is not None:
                ch['eeg_loc'].fill(0)
            ch['loc'].fill(0)

    # Remove extra digitization point, so EEG digitization points
    # correspond with the EEG electrodes
    del evoked.info['dig'][85]

    pos = make_eeg_layout(evoked.info).pos
    pos, outlines = _check_outlines(pos, 'head')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.5)

    pos, outlines = _check_outlines(pos, 'skirt')
    assert_true('head' in outlines.keys())
    assert_true('nose' in outlines.keys())
    assert_true('ear_left' in outlines.keys())
    assert_true('ear_right' in outlines.keys())
    assert_true('autoshrink' in outlines.keys())
    assert_true(not outlines['autoshrink'])
    assert_true('clip_radius' in outlines.keys())
    assert_array_equal(outlines['clip_radius'], 0.625)

    pos, outlines = _check_outlines(pos, 'skirt',
                                    head_pos={'scale': [1.2, 1.2]})
    assert_array_equal(outlines['clip_radius'], 0.75)

    # Plot skirt
    evoked.plot_topomap(times, ch_type='eeg', outlines='skirt')

    # Pass custom outlines without patch
    evoked.plot_topomap(times, ch_type='eeg', outlines=outlines)
    plt.close('all')

    # Pass custom outlines with patch callable
    def patch():
        return Circle((0.5, 0.4687), radius=.46,
                      clip_on=True, transform=plt.gca().transAxes)
    outlines['patch'] = patch
    plot_evoked_topomap(evoked, times, ch_type='eeg', outlines=outlines)

    # Remove digitization points. Now topomap should fail
    evoked.info['dig'] = None
    assert_raises(RuntimeError, plot_evoked_topomap, evoked,
                  times, ch_type='eeg')
    plt.close('all')