本文整理汇总了Python中mne.EpochsArray.get_data方法的典型用法代码示例。如果您正苦于以下问题：Python EpochsArray.get_data方法的具体用法？Python EpochsArray.get_data怎么用？Python EpochsArray.get_data使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mne.EpochsArray的用法示例。
在下文中一共展示了EpochsArray.get_data方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_decim
# 需要导入模块: from mne import EpochsArray [as 别名]
# 或者: from mne.EpochsArray import get_data [as 别名]
def test_decim():
"""Test evoked decimation."""
rng = np.random.RandomState(0)
n_epochs, n_channels, n_times = 5, 10, 20
dec_1, dec_2 = 2, 3
decim = dec_1 * dec_2
sfreq = 1000.
sfreq_new = sfreq / decim
data = rng.randn(n_epochs, n_channels, n_times)
events = np.array([np.arange(n_epochs), [0] * n_epochs, [1] * n_epochs]).T
info = create_info(n_channels, sfreq, 'eeg')
info['lowpass'] = sfreq_new / float(decim)
epochs = EpochsArray(data, info, events)
data_epochs = epochs.copy().decimate(decim).get_data()
data_epochs_2 = epochs.copy().decimate(decim, offset=1).get_data()
data_epochs_3 = epochs.decimate(dec_1).decimate(dec_2).get_data()
assert_array_equal(data_epochs, data[:, :, ::decim])
assert_array_equal(data_epochs_2, data[:, :, 1::decim])
assert_array_equal(data_epochs, data_epochs_3)
# Now let's do it with some real data
raw = read_raw_fif(raw_fname, add_eeg_ref=False)
events = read_events(event_name)
sfreq_new = raw.info['sfreq'] / decim
raw.info['lowpass'] = sfreq_new / 4. # suppress aliasing warnings
picks = pick_types(raw.info, meg=True, eeg=True, exclude=())
epochs = Epochs(raw, events, 1, -0.2, 0.5, picks=picks, preload=True,
add_eeg_ref=False)
for offset in (0, 1):
ev_ep_decim = epochs.copy().decimate(decim, offset).average()
ev_decim = epochs.average().decimate(decim, offset)
expected_times = epochs.times[offset::decim]
assert_allclose(ev_decim.times, expected_times)
assert_allclose(ev_ep_decim.times, expected_times)
expected_data = epochs.get_data()[:, :, offset::decim].mean(axis=0)
assert_allclose(ev_decim.data, expected_data)
assert_allclose(ev_ep_decim.data, expected_data)
assert_equal(ev_decim.info['sfreq'], sfreq_new)
assert_array_equal(ev_decim.times, expected_times)示例2: tfr_morlet
# 需要导入模块: from mne import EpochsArray [as 别名]
# 或者: from mne.EpochsArray import get_data [as 别名]
power = tfr_morlet(epochs, freqs=freqs,
n_cycles=n_cycles, return_itc=False, average=False)
print(type(power))
avgpower = power.average()
avgpower.plot([0], baseline=(0., 0.1), mode='mean', vmin=vmin, vmax=vmax,
title='Using Morlet wavelets and EpochsTFR', show=False)
###############################################################################
# Operating on arrays
# -------------------
#
# MNE also has versions of the functions above which operate on numpy arrays
# instead of MNE objects. They expect inputs of the shape
# ``(n_epochs, n_channels, n_times)``. They will also return a numpy array
# of shape ``(n_epochs, n_channels, n_frequencies, n_times)``.
power = tfr_array_morlet(epochs.get_data(), sfreq=epochs.info['sfreq'],
frequencies=freqs, n_cycles=n_cycles,
output='avg_power')
# Baseline the output
rescale(power, epochs.times, (0., 0.1), mode='mean', copy=False)
fig, ax = plt.subplots()
mesh = ax.pcolormesh(epochs.times * 1000, freqs, power[0],
cmap='RdBu_r', vmin=vmin, vmax=vmax)
ax.set_title('TFR calculated on a numpy array')
ax.set(ylim=freqs[[0, -1]], xlabel='Time (ms)')
fig.colorbar(mesh)
plt.tight_layout()
plt.show()