def test_brainvision_data():
"""Test reading raw Brain Vision files
"""
raw_py = read_raw_brainvision(vhdr_path, elp_path, elp_names, preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True, exclude='bads')
data_py, times_py = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# compare with a file that was generated using MNE-C
raw_bin = Raw(eeg_bin, preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True, exclude='bads')
data_bin, times_bin = raw_bin[picks]
assert_array_almost_equal(data_py, data_bin)
assert_array_almost_equal(times_py, times_bin)
# Make sure EOG channels are marked correctly
raw_py = read_raw_brainvision(vhdr_path,
elp_path,
elp_names,
eog=eog,
preload=True)
for ch in raw_py.info['chs']:
if ch['ch_name'] in eog:
assert_equal(ch['kind'], FIFF.FIFFV_EOG_CH)
elif ch['ch_name'] in elp_names:
assert_equal(ch['kind'], FIFF.FIFFV_EEG_CH)
elif ch['ch_name'] == 'STI 014':
assert_equal(ch['kind'], FIFF.FIFFV_STIM_CH)
else:
raise RuntimeError("Unknown Channel: %s" % ch['ch_name'])
def test_brainvision_data():
"""Test reading raw Brain Vision files
"""
raw_py = read_raw_brainvision(vhdr_path, elp_path, elp_names, preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True, exclude='bads')
data_py, times_py = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# compare with a file that was generated using MNE-C
raw_bin = Raw(eeg_bin, preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True, exclude='bads')
data_bin, times_bin = raw_bin[picks]
assert_array_almost_equal(data_py, data_bin)
assert_array_almost_equal(times_py, times_bin)
# Make sure EOG channels are marked correctly
raw_py = read_raw_brainvision(vhdr_path, elp_path, elp_names, eog=eog,
preload=True)
for ch in raw_py.info['chs']:
if ch['ch_name'] in eog:
assert_equal(ch['kind'], FIFF.FIFFV_EOG_CH)
elif ch['ch_name'] in elp_names:
assert_equal(ch['kind'], FIFF.FIFFV_EEG_CH)
elif ch['ch_name'] == 'STI 014':
assert_equal(ch['kind'], FIFF.FIFFV_STIM_CH)
else:
raise RuntimeError("Unknown Channel: %s" % ch['ch_name'])
def test_read_segment():
"""Test writing raw eeg files when preload is False
"""
raw1 = read_raw_brainvision(vhdr_path, preload=False)
raw1_file = op.join(tempdir, 'raw1.fif')
raw1.save(raw1_file, overwrite=True)
raw11 = Raw(raw1_file, preload=True)
data1, times1 = raw1[:, :]
data11, times11 = raw11[:, :]
assert_array_almost_equal(data1, data11, 8)
assert_array_almost_equal(times1, times11)
assert_equal(sorted(raw1.info.keys()), sorted(raw11.info.keys()))
raw2 = read_raw_brainvision(vhdr_path, preload=True)
raw2_file = op.join(tempdir, 'raw2.fif')
raw2.save(raw2_file, overwrite=True)
data2, times2 = raw2[:, :]
assert_array_equal(data1, data2)
assert_array_equal(times1, times2)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
# save with buffer size smaller than file
raw3_file = op.join(tempdir, 'raw3.fif')
raw3 = read_raw_brainvision(vhdr_path)
raw3.save(raw3_file, buffer_size_sec=2)
raw3 = Raw(raw3_file, preload=True)
assert_array_equal(raw3._data, raw1._data)
# add reference channel
raw4_file = op.join(tempdir, 'raw4.fif')
raw4 = read_raw_brainvision(vhdr_path, reference='A1')
raw4.save(raw4_file, buffer_size_sec=2)
raw4 = Raw(raw4_file, preload=True)
ref_idx = raw4.ch_names.index('A1')
assert_equal(len(raw4._data), len(raw1._data) + 1)
ref_data, _ = raw4[ref_idx]
assert_array_equal(ref_data, 0)
def test_read_segment():
"""Test writing raw eeg files when preload is False
"""
raw1 = read_raw_brainvision(vhdr_path, preload=False)
raw1_file = op.join(tempdir, 'raw1.fif')
raw1.save(raw1_file, overwrite=True)
raw11 = Raw(raw1_file, preload=True)
data1, times1 = raw1[:, :]
data11, times11 = raw11[:, :]
assert_array_almost_equal(data1, data11, 8)
assert_array_almost_equal(times1, times11)
assert_equal(sorted(raw1.info.keys()), sorted(raw11.info.keys()))
raw2 = read_raw_brainvision(vhdr_path, preload=True)
raw2_file = op.join(tempdir, 'raw2.fif')
raw2.save(raw2_file, overwrite=True)
data2, times2 = raw2[:, :]
assert_array_equal(data1, data2)
assert_array_equal(times1, times2)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
# save with buffer size smaller than file
raw3_file = op.join(tempdir, 'raw3.fif')
raw3 = read_raw_brainvision(vhdr_path)
raw3.save(raw3_file, buffer_size_sec=2)
raw3 = Raw(raw3_file, preload=True)
assert_array_equal(raw3._data, raw1._data)
# add reference channel
raw4_file = op.join(tempdir, 'raw4.fif')
raw4 = read_raw_brainvision(vhdr_path, reference='A1')
raw4.save(raw4_file, buffer_size_sec=2)
raw4 = Raw(raw4_file, preload=True)
ref_idx = raw4.ch_names.index('A1')
assert_equal(len(raw4._data), len(raw1._data) + 1)
ref_data, _ = raw4[ref_idx]
assert_array_equal(ref_data, 0)
def test_read_segment():
"""Test writing raw eeg files when preload is False
"""
raw1 = read_raw_brainvision(vhdr_path, preload=False)
raw1_file = op.join(tempdir, "raw1.fif")
raw1.save(raw1_file, overwrite=True)
raw11 = Raw(raw1_file, preload=True)
data1, times1 = raw1[:, :]
data11, times11 = raw11[:, :]
assert_array_almost_equal(data1, data11, 8)
assert_array_almost_equal(times1, times11)
assert_equal(sorted(raw1.info.keys()), sorted(raw11.info.keys()))
raw2 = read_raw_brainvision(vhdr_path, preload=True)
raw2_file = op.join(tempdir, "raw2.fif")
raw2.save(raw2_file, overwrite=True)
data2, times2 = raw2[:, :]
assert_array_equal(data1, data2)
assert_array_equal(times1, times2)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
def test_brainvision_data():
"""Test reading raw Brain Vision files
"""
raw_py = read_raw_brainvision(vhdr_path, elp_fname=elp_path, ch_names=ch_names, preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True, exclude="bads")
data_py, times_py = raw_py[picks]
print(raw_py) # to test repr
print(raw_py.info) # to test Info repr
# this fif was generated using MNE-C
raw_bin = Raw(eeg_bin, preload=True)
picks = pick_types(raw_py.info, meg=False, eeg=True, exclude="bads")
data_bin, times_bin = raw_bin[picks]
assert_array_almost_equal(data_py, data_bin)
assert_array_almost_equal(times_py, times_bin)
def test_events():
"""Test reading and modifying events"""
raw = read_raw_brainvision(vhdr_path, preload=True)
# check that events are read and stim channel is synthesized correcly
events = raw.get_brainvision_events()
assert_array_equal(events, [[ 487, 1, 253],
[ 497, 1, 255],
[1770, 1, 254],
[1780, 1, 255],
[3253, 1, 254],
[3263, 1, 255],
[4936, 1, 253],
[4946, 1, 255],
[6620, 1, 254],
[6630, 1, 255]])
mne_events = mne.find_events(raw, stim_channel='STI 014')
assert_array_equal(events[:, [0, 2]], mne_events[:, [0, 2]])
# modify events and check that stim channel is updated
index = events[:, 2] == 255
events = events[index]
raw.set_brainvision_events(events)
mne_events = mne.find_events(raw, stim_channel='STI 014')
assert_array_equal(events[:, [0, 2]], mne_events[:, [0, 2]])
# remove events
nchan = raw.info['nchan']
ch_name = raw.info['chs'][-2]['ch_name']
events = np.empty((0, 3))
raw.set_brainvision_events(events)
assert_equal(raw.info['nchan'], nchan - 1)
assert_equal(len(raw._data), nchan - 1)
assert_equal(raw.info['chs'][-1]['ch_name'], ch_name)
fname = op.join(tempdir, 'raw_evt.fif')
raw.save(fname)
# add events back in
events = [[10, 1, 2]]
raw.set_brainvision_events(events)
assert_equal(raw.info['nchan'], nchan)
assert_equal(len(raw._data), nchan)
assert_equal(raw.info['chs'][-1]['ch_name'], 'STI 014')
def test_events():
"""Test reading and modifying events"""
raw = read_raw_brainvision(vhdr_path, preload=True)
# check that events are read and stim channel is synthesized correcly
events = raw.get_brainvision_events()
assert_array_equal(
events, [[487, 1, 253], [497, 1, 255], [1770, 1, 254], [1780, 1, 255],
[3253, 1, 254], [3263, 1, 255], [4936, 1, 253],
[4946, 1, 255], [6620, 1, 254], [6630, 1, 255]])
mne_events = mne.find_events(raw, stim_channel='STI 014')
assert_array_equal(events[:, [0, 2]], mne_events[:, [0, 2]])
# modify events and check that stim channel is updated
index = events[:, 2] == 255
events = events[index]
raw.set_brainvision_events(events)
mne_events = mne.find_events(raw, stim_channel='STI 014')
assert_array_equal(events[:, [0, 2]], mne_events[:, [0, 2]])
# remove events
nchan = raw.info['nchan']
ch_name = raw.info['chs'][-2]['ch_name']
events = np.empty((0, 3))
raw.set_brainvision_events(events)
assert_equal(raw.info['nchan'], nchan - 1)
assert_equal(len(raw._data), nchan - 1)
assert_equal(raw.info['chs'][-1]['ch_name'], ch_name)
fname = op.join(tempdir, 'raw_evt.fif')
raw.save(fname)
# add events back in
events = [[10, 1, 2]]
raw.set_brainvision_events(events)
assert_equal(raw.info['nchan'], nchan)
assert_equal(len(raw._data), nchan)
assert_equal(raw.info['chs'][-1]['ch_name'], 'STI 014')
