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_true(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_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(-.1, .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(TypeError, 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_joint():
"""Test TFR joint plotting."""
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):
with catch_logging() as log:
tfr.plot_joint(title='auto',
colorbar=True,
combine=combine,
topomap_args=topomap_args,
verbose='debug')
plt.close('all')
log = log.getvalue()
assert 'Plotting topomap for grad data' in log
# 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:
pytest.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 set(tfr.ch_names) == set(tfr_orig.ch_names)
assert set(tfr.times) == set(tfr_orig.times)
# test tfr with picked channels
tfr.pick_channels(tfr.ch_names[:-1])
tfr.plot_joint(title='auto', colorbar=True, topomap_args=topomap_args)
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))
def test_plot_joint():
"""Test TFR joint plotting."""
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:
pytest.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 set(tfr.ch_names) == set(tfr_orig.ch_names)
assert set(tfr.times) == set(tfr_orig.times)
# test tfr with picked channels
tfr.pick_channels(tfr.ch_names[:-1])
tfr.plot_joint(title='auto', colorbar=True, topomap_args=topomap_args)
