Python tfr.AverageTFR类代码示例

def test_add_channels():
    """Test tfr splitting / re-appending channel types
    """
    data = np.zeros((6, 2, 3))
    times = np.array([0.1, 0.2, 0.3])
    freqs = np.array([0.10, 0.20])
    info = mne.create_info(
        ["MEG 001", "MEG 002", "MEG 003", "EEG 001", "EEG 002", "STIM 001"],
        1000.0,
        ["mag", "mag", "mag", "eeg", "eeg", "stim"],
    )
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs, nave=20, comment="test", method="crazy-tfr")
    tfr_eeg = tfr.pick_types(meg=False, eeg=True, copy=True)
    tfr_meg = tfr.pick_types(meg=True, copy=True)
    tfr_stim = tfr.pick_types(meg=False, stim=True, copy=True)
    tfr_eeg_meg = tfr.pick_types(meg=True, eeg=True, copy=True)
    tfr_new = tfr_meg.add_channels([tfr_eeg, tfr_stim], copy=True)
    assert_true(all(ch in tfr_new.ch_names for ch in tfr_stim.ch_names + tfr_meg.ch_names))
    tfr_new = tfr_meg.add_channels([tfr_eeg], copy=True)

    assert_true(ch in tfr_new.ch_names for ch in tfr.ch_names)
    assert_array_equal(tfr_new.data, tfr_eeg_meg.data)
    assert_true(all(ch not in tfr_new.ch_names for ch in tfr_stim.ch_names))

    # Now test errors
    tfr_badsf = tfr_eeg.copy()
    tfr_badsf.info["sfreq"] = 3.1415927
    tfr_eeg = tfr_eeg.crop(-0.1, 0.1)

    assert_raises(RuntimeError, tfr_meg.add_channels, [tfr_badsf])
    assert_raises(AssertionError, tfr_meg.add_channels, [tfr_eeg])
    assert_raises(ValueError, tfr_meg.add_channels, [tfr_meg])
    assert_raises(AssertionError, tfr_meg.add_channels, tfr_badsf)

def test_add_channels():
    """Test tfr splitting / re-appending channel types."""
    data = np.zeros((6, 2, 3))
    times = np.array([.1, .2, .3])
    freqs = np.array([.10, .20])
    info = mne.create_info(
        ['MEG 001', 'MEG 002', 'MEG 003', 'EEG 001', 'EEG 002', 'STIM 001'],
        1000., ['mag', 'mag', 'mag', 'eeg', 'eeg', 'stim'])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
                     nave=20, comment='test', method='crazy-tfr')
    tfr_eeg = tfr.copy().pick_types(meg=False, eeg=True)
    tfr_meg = tfr.copy().pick_types(meg=True)
    tfr_stim = tfr.copy().pick_types(meg=False, stim=True)
    tfr_eeg_meg = tfr.copy().pick_types(meg=True, eeg=True)
    tfr_new = tfr_meg.copy().add_channels([tfr_eeg, tfr_stim])
    assert all(ch in tfr_new.ch_names
               for ch in tfr_stim.ch_names + tfr_meg.ch_names)
    tfr_new = tfr_meg.copy().add_channels([tfr_eeg])

    assert all(ch in tfr_new.ch_names
               for ch in tfr.ch_names if ch != 'STIM 001')
    assert_array_equal(tfr_new.data, tfr_eeg_meg.data)
    assert all(ch not in tfr_new.ch_names for ch in tfr_stim.ch_names)

    # Now test errors
    tfr_badsf = tfr_eeg.copy()
    tfr_badsf.info['sfreq'] = 3.1415927
    tfr_eeg = tfr_eeg.crop(-.1, .1)

    pytest.raises(RuntimeError, tfr_meg.add_channels, [tfr_badsf])
    pytest.raises(AssertionError, tfr_meg.add_channels, [tfr_eeg])
    pytest.raises(ValueError, tfr_meg.add_channels, [tfr_meg])
    pytest.raises(TypeError, tfr_meg.add_channels, tfr_badsf)

def test_plot_tfr_topomap():
    """Test plotting of TFR data
    """
    import matplotlib as mpl
    import matplotlib.pyplot as plt

    raw = _get_raw()
    times = np.linspace(-0.1, 0.1, 200)
    n_freqs = 3
    nave = 1
    rng = np.random.RandomState(42)
    data = rng.randn(len(raw.ch_names), n_freqs, len(times))
    tfr = AverageTFR(raw.info, data, times, np.arange(n_freqs), nave)
    tfr.plot_topomap(ch_type="mag", tmin=0.05, tmax=0.150, fmin=0, fmax=10, res=16)

    eclick = mpl.backend_bases.MouseEvent("button_press_event", plt.gcf().canvas, 0, 0, 1)
    eclick.xdata = 0.1
    eclick.ydata = 0.1
    eclick.inaxes = plt.gca()
    erelease = mpl.backend_bases.MouseEvent("button_release_event", plt.gcf().canvas, 0.9, 0.9, 1)
    erelease.xdata = 0.3
    erelease.ydata = 0.2
    pos = [[0.11, 0.11], [0.25, 0.5], [0.0, 0.2], [0.2, 0.39]]
    _onselect(eclick, erelease, tfr, pos, "mag", 1, 3, 1, 3, "RdBu_r", list())
    tfr._onselect(eclick, erelease, None, "mean", None)
    plt.close("all")

def test_crop():
    """Test TFR cropping"""
    data = np.zeros((3, 2, 3))
    times = np.array([0.1, 0.2, 0.3])
    freqs = np.array([0.10, 0.20])
    info = mne.create_info(["MEG 001", "MEG 002", "MEG 003"], 1000.0, ["mag", "mag", "mag"])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs, nave=20, comment="test", method="crazy-tfr")
    tfr.crop(0.2, 0.3)
    assert_array_equal(tfr.times, [0.2, 0.3])
    assert_equal(tfr.data.shape[-1], 2)

def test_plot_tfr_topo():
    """Test plotting of TFR data
    """
    epochs = _get_epochs()
    n_freqs = 3
    nave = 1
    data = np.random.randn(len(epochs.ch_names), n_freqs, len(epochs.times))
    tfr = AverageTFR(epochs.info, data, epochs.times, np.arange(n_freqs), nave)
    tfr.plot_topo(baseline=(None, 0), mode="ratio", title="Average power", vmin=0.0, vmax=14.0)
    tfr.plot([4], baseline=(None, 0), mode="ratio")

def test_plot_tfr_topo():
    """Test plotting of TFR data."""
    epochs = _get_epochs()
    n_freqs = 3
    nave = 1
    data = np.random.RandomState(0).randn(len(epochs.ch_names),
                                          n_freqs, len(epochs.times))
    tfr = AverageTFR(epochs.info, data, epochs.times, np.arange(n_freqs), nave)
    tfr.plot_topo(baseline=(None, 0), mode='ratio', title='Average power',
                  vmin=0., vmax=14., show=False)
    tfr.plot([4], baseline=(None, 0), mode='ratio', show=False, title='foo')

def test_plot_tfr_topomap():
    """Test plotting of TFR data
    """
    raw = _get_raw()
    times = np.linspace(-0.1, 0.1, 200)
    n_freqs = 3
    nave = 1
    rng = np.random.RandomState(42)
    data = rng.randn(len(raw.ch_names), n_freqs, len(times))
    tfr = AverageTFR(raw.info, data, times, np.arange(n_freqs), nave)
    tfr.plot_topomap(ch_type="mag", tmin=0.05, tmax=0.150, fmin=0, fmax=10, res=16)

def test_crop():
    """Test TFR cropping."""
    data = np.zeros((3, 2, 3))
    times = np.array([.1, .2, .3])
    freqs = np.array([.10, .20])
    info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
                           ['mag', 'mag', 'mag'])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
                     nave=20, comment='test', method='crazy-tfr')
    tfr.crop(0.2, 0.3)
    assert_array_equal(tfr.times, [0.2, 0.3])
    assert_equal(tfr.data.shape[-1], 2)

def test_plot_tfr_topo():
    """Test plotting of TFR data."""
    import matplotlib.pyplot as plt

    epochs = _get_epochs()
    n_freqs = 3
    nave = 1
    data = np.random.RandomState(0).randn(len(epochs.ch_names),
                                          n_freqs, len(epochs.times))
    tfr = AverageTFR(epochs.info, data, epochs.times, np.arange(n_freqs), nave)
    plt.close('all')
    fig = tfr.plot_topo(baseline=(None, 0), mode='ratio',
                        title='Average power', vmin=0., vmax=14.)

    # test opening tfr by clicking
    num_figures_before = len(plt.get_fignums())
    # could use np.reshape(fig.axes[-1].images[0].get_extent(), (2, 2)).mean(1)
    with pytest.warns(None):  # on old mpl there is a warning
        _fake_click(fig, fig.axes[0], (0.08, 0.65))
    assert num_figures_before + 1 == len(plt.get_fignums())
    plt.close('all')

    tfr.plot([4], baseline=(None, 0), mode='ratio', show=False, title='foo')
    pytest.raises(ValueError, tfr.plot, [4], yscale='lin', show=False)

    # nonuniform freqs
    freqs = np.logspace(*np.log10([3, 10]), num=3)
    tfr = AverageTFR(epochs.info, data, epochs.times, freqs, nave)
    fig = tfr.plot([4], baseline=(None, 0), mode='mean', vmax=14., show=False)
    assert fig.axes[0].get_yaxis().get_scale() == 'log'

    # one timesample
    tfr = AverageTFR(epochs.info, data[:, :, [0]], epochs.times[[1]],
                     freqs, nave)
    with pytest.warns(None):  # matplotlib equal left/right
        tfr.plot([4], baseline=None, vmax=14., show=False, yscale='linear')

    # one frequency bin, log scale required: as it doesn't make sense
    # to plot log scale for one value, we test whether yscale is set to linear
    vmin, vmax = 0., 2.
    fig, ax = plt.subplots()
    tmin, tmax = epochs.times[0], epochs.times[-1]
    with pytest.warns(RuntimeWarning, match='not masking'):
        _imshow_tfr(ax, 3, tmin, tmax, vmin, vmax, None, tfr=data[:, [0], :],
                    freq=freqs[[-1]], x_label=None, y_label=None,
                    colorbar=False, cmap=('RdBu_r', True), yscale='log')
    fig = plt.gcf()
    assert fig.axes[0].get_yaxis().get_scale() == 'linear'

    # ValueError when freq[0] == 0 and yscale == 'log'
    these_freqs = freqs[:3].copy()
    these_freqs[0] = 0
    with pytest.warns(RuntimeWarning, match='not masking'):
        pytest.raises(ValueError, _imshow_tfr, ax, 3, tmin, tmax, vmin, vmax,
                      None, tfr=data[:, :3, :], freq=these_freqs, x_label=None,
                      y_label=None, colorbar=False, cmap=('RdBu_r', True),
                      yscale='log')

def test_io():
    """Test TFR IO capacities."""

    tempdir = _TempDir()
    fname = op.join(tempdir, 'test-tfr.h5')
    data = np.zeros((3, 2, 3))
    times = np.array([.1, .2, .3])
    freqs = np.array([.10, .20])

    info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
                           ['mag', 'mag', 'mag'])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
                     nave=20, comment='test', method='crazy-tfr')
    tfr.save(fname)
    tfr2 = read_tfrs(fname, condition='test')

    assert_array_equal(tfr.data, tfr2.data)
    assert_array_equal(tfr.times, tfr2.times)
    assert_array_equal(tfr.freqs, tfr2.freqs)
    assert_equal(tfr.comment, tfr2.comment)
    assert_equal(tfr.nave, tfr2.nave)

    assert_raises(IOError, tfr.save, fname)

    tfr.comment = None
    tfr.save(fname, overwrite=True)
    assert_equal(read_tfrs(fname, condition=0).comment, tfr.comment)
    tfr.comment = 'test-A'
    tfr2.comment = 'test-B'

    fname = op.join(tempdir, 'test2-tfr.h5')
    write_tfrs(fname, [tfr, tfr2])
    tfr3 = read_tfrs(fname, condition='test-A')
    assert_equal(tfr.comment, tfr3.comment)

    assert_true(isinstance(tfr.info, mne.Info))

    tfrs = read_tfrs(fname, condition=None)
    assert_equal(len(tfrs), 2)
    tfr4 = tfrs[1]
    assert_equal(tfr2.comment, tfr4.comment)

    assert_raises(ValueError, read_tfrs, fname, condition='nonono')

    # Test save of EpochsTFR.
    data = np.zeros((5, 3, 2, 3))
    tfr = EpochsTFR(info, data=data, times=times, freqs=freqs,
                    comment='test', method='crazy-tfr')
    tfr.save(fname, True)
    read_tfr = read_tfrs(fname)[0]
    assert_array_equal(tfr.data, read_tfr.data)

def test_crop():
    """Test TFR cropping."""
    data = np.zeros((3, 4, 5))
    times = np.array([.1, .2, .3, .4, .5])
    freqs = np.array([.10, .20, .30, .40])
    info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
                           ['mag', 'mag', 'mag'])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
                     nave=20, comment='test', method='crazy-tfr')

    tfr.crop(tmin=0.2)
    assert_array_equal(tfr.times, [0.2, 0.3, 0.4, 0.5])
    assert tfr.data.ndim == 3
    assert tfr.data.shape[-1] == 4

    tfr.crop(fmax=0.3)
    assert_array_equal(tfr.freqs, [0.1, 0.2, 0.3])
    assert tfr.data.ndim == 3
    assert tfr.data.shape[-2] == 3

    tfr.crop(tmin=0.3, tmax=0.4, fmin=0.1, fmax=0.2)
    assert_array_equal(tfr.times, [0.3, 0.4])
    assert tfr.data.ndim == 3
    assert tfr.data.shape[-1] == 2
    assert_array_equal(tfr.freqs, [0.1, 0.2])
    assert tfr.data.shape[-2] == 2

def test_plot():
    """Test TFR plotting."""
    import matplotlib.pyplot as plt

    data = np.zeros((3, 2, 3))
    times = np.array([.1, .2, .3])
    freqs = np.array([.10, .20])
    info = mne.create_info(['MEG 001', 'MEG 002', 'MEG 003'], 1000.,
                           ['mag', 'mag', 'mag'])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs,
                     nave=20, comment='test', method='crazy-tfr')
    tfr.plot([1, 2], title='title', colorbar=False,
             mask=np.ones(tfr.data.shape[1:], bool))
    plt.close('all')
    ax = plt.subplot2grid((2, 2), (0, 0))
    ax2 = plt.subplot2grid((2, 2), (1, 1))
    ax3 = plt.subplot2grid((2, 2), (0, 1))
    tfr.plot(picks=[0, 1, 2], axes=[ax, ax2, ax3])
    plt.close('all')

    tfr.plot([1, 2], title='title', colorbar=False, exclude='bads')
    plt.close('all')

    tfr.plot_topo(picks=[1, 2])
    plt.close('all')

    fig = tfr.plot(picks=[1], cmap='RdBu_r')  # interactive mode on by default
    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')

def test_plot_tfr_topomap():
    """Test plotting of TFR data."""
    import matplotlib as mpl
    import matplotlib.pyplot as plt
    raw = read_raw_fif(raw_fname)
    times = np.linspace(-0.1, 0.1, 200)
    res = 8
    n_freqs = 3
    nave = 1
    rng = np.random.RandomState(42)
    picks = [93, 94, 96, 97, 21, 22, 24, 25, 129, 130, 315, 316, 2, 5, 8, 11]
    info = pick_info(raw.info, picks)
    data = rng.randn(len(picks), n_freqs, len(times))
    tfr = AverageTFR(info, data, times, np.arange(n_freqs), nave)
    tfr.plot_topomap(ch_type='mag', tmin=0.05, tmax=0.150, fmin=0, fmax=10,
                     res=res, contours=0)

    eclick = mpl.backend_bases.MouseEvent('button_press_event',
                                          plt.gcf().canvas, 0, 0, 1)
    eclick.xdata = eclick.ydata = 0.1
    eclick.inaxes = plt.gca()
    erelease = mpl.backend_bases.MouseEvent('button_release_event',
                                            plt.gcf().canvas, 0.9, 0.9, 1)
    erelease.xdata = 0.3
    erelease.ydata = 0.2
    pos = [[0.11, 0.11], [0.25, 0.5], [0.0, 0.2], [0.2, 0.39]]
    _onselect(eclick, erelease, tfr, pos, 'grad', 1, 3, 1, 3, 'RdBu_r', list())
    _onselect(eclick, erelease, tfr, pos, 'mag', 1, 3, 1, 3, 'RdBu_r', list())
    eclick.xdata = eclick.ydata = 0.
    erelease.xdata = erelease.ydata = 0.9
    tfr._onselect(eclick, erelease, None, 'mean', None)
    plt.close('all')

    # test plot_psds_topomap
    info = raw.info.copy()
    chan_inds = channel_indices_by_type(info)
    info = pick_info(info, chan_inds['grad'][:4])

    fig, axes = plt.subplots()
    freqs = np.arange(3., 9.5)
    bands = [(4, 8, 'Theta')]
    psd = np.random.rand(len(info['ch_names']), freqs.shape[0])
    plot_psds_topomap(psd, freqs, info, bands=bands, axes=[axes])

def test_plot():
    """Test TFR plotting."""
    import matplotlib.pyplot as plt

    data = np.zeros((3, 2, 3))
    times = np.array([0.1, 0.2, 0.3])
    freqs = np.array([0.10, 0.20])
    info = mne.create_info(["MEG 001", "MEG 002", "MEG 003"], 1000.0, ["mag", "mag", "mag"])
    tfr = AverageTFR(info, data=data, times=times, freqs=freqs, nave=20, comment="test", method="crazy-tfr")
    tfr.plot([1, 2], title="title")
    plt.close("all")
    ax = plt.subplot2grid((2, 2), (0, 0))
    ax2 = plt.subplot2grid((2, 2), (1, 1))
    ax3 = plt.subplot2grid((2, 2), (0, 1))
    tfr.plot(picks=[0, 1, 2], axes=[ax, ax2, ax3])
    plt.close("all")

    tfr.plot_topo(picks=[1, 2])
    plt.close("all")

    tfr.plot_topo(picks=[1, 2])
    plt.close("all")

def test_plot_joint():
    """Test TFR joint plotting."""
    import matplotlib.pyplot as plt

    raw = read_raw_fif(raw_fname)
    times = np.linspace(-0.1, 0.1, 200)
    n_freqs = 3
    nave = 1
    rng = np.random.RandomState(42)
    data = rng.randn(len(raw.ch_names), n_freqs, len(times))
    tfr = AverageTFR(raw.info, data, times, np.arange(n_freqs), nave)

    topomap_args = {'res': 8, 'contours': 0, 'sensors': False}

    for combine in ('mean', 'rms', None):
        tfr.plot_joint(title='auto', colorbar=True,
                       combine=combine, topomap_args=topomap_args)
        plt.close('all')

    # check various timefreqs
    for timefreqs in (
            {(tfr.times[0], tfr.freqs[1]): (0.1, 0.5),
             (tfr.times[-1], tfr.freqs[-1]): (0.2, 0.6)},
            [(tfr.times[1], tfr.freqs[1])]):
        tfr.plot_joint(timefreqs=timefreqs, topomap_args=topomap_args)
        plt.close('all')

    # test bad timefreqs
    timefreqs = ([(-100, 1)], tfr.times[1], [1],
                 [(tfr.times[1], tfr.freqs[1], tfr.freqs[1])])
    for these_timefreqs in timefreqs:
        assert_raises(ValueError, tfr.plot_joint, these_timefreqs)

    # test that the object is not internally modified
    tfr_orig = tfr.copy()
    tfr.plot_joint(baseline=(0, None), exclude=[tfr.ch_names[0]],
                   topomap_args=topomap_args)
    plt.close('all')
    assert_array_equal(tfr.data, tfr_orig.data)
    assert_true(set(tfr.ch_names) == set(tfr_orig.ch_names))
    assert_true(set(tfr.times) == set(tfr_orig.times))