def test_ch_loc():
"""Test raw kit loc
"""
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<')
raw_bin = Raw(op.join(data_dir, 'test_bin.fif'))
ch_py = raw_py._sqd_params['sensor_locs'][:, :5]
# ch locs stored as m, not mm
ch_py[:, :3] *= 1e3
ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
assert_array_almost_equal(ch_py, ch_sns, 2)
assert_array_almost_equal(raw_py.info['dev_head_t']['trans'],
raw_bin.info['dev_head_t']['trans'], 4)
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the stored ch locs have more precision than the sns.txt
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)
assert_array_almost_equal(py_ch['coil_trans'],
bin_ch['coil_trans'],
decimal=2)
# test when more than one marker file provided
mrks = [mrk_path, mrk2_path, mrk3_path]
_ = read_raw_kit(sqd_path, mrks, elp_path, hsp_path, preload=False)
def test_read_segment():
"""Test writing raw kit files when preload is False
"""
raw1 = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1), preload=False)
raw1_file = op.join(tempdir, 'raw1.fif')
raw1.save(raw1_file, buffer_size_sec=.1, overwrite=True)
raw2 = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1), preload=True)
raw2_file = op.join(tempdir, 'raw2.fif')
raw2.save(raw2_file, buffer_size_sec=.1, overwrite=True)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
raw3 = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1), preload=True)
assert_array_almost_equal(raw1._data, raw3._data)
def test_read_segment():
"""Test writing raw kit files when preload is False
"""
raw1 = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1),
preload=False)
raw1_file = op.join(tempdir, 'raw1.fif')
raw1.save(raw1_file, buffer_size_sec=.1, overwrite=True)
raw2 = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1),
preload=True)
raw2_file = op.join(tempdir, 'raw2.fif')
raw2.save(raw2_file, buffer_size_sec=.1, overwrite=True)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
raw3 = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1),
preload=True)
assert_array_almost_equal(raw1._data, raw3._data)
def test_ch_loc():
"""Test raw kit loc
"""
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<')
raw_bin = Raw(op.join(data_dir, 'test_bin.fif'))
ch_py = raw_py._sqd_params['sensor_locs'][:, :5]
# ch locs stored as m, not mm
ch_py[:, :3] *= 1e3
ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
assert_array_almost_equal(ch_py, ch_sns, 2)
assert_array_almost_equal(raw_py.info['dev_head_t']['trans'],
raw_bin.info['dev_head_t']['trans'], 4)
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the stored ch locs have more precision than the sns.txt
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)
assert_array_almost_equal(py_ch['coil_trans'],
bin_ch['coil_trans'],
decimal=2)
# test when more than one marker file provided
mrks = [mrk_path, mrk2_path, mrk3_path]
_ = read_raw_kit(sqd_path, mrks, elp_path, hsp_path, preload=False)
def test_read_segment():
"""Test writing raw kit files when preload is False
"""
raw1 = read_raw_kit(sqd_path,
mrk_path,
elp_path,
hsp_path,
stim='<',
preload=False)
raw1_file = op.join(tempdir, 'raw1.fif')
raw1.save(raw1_file, buffer_size_sec=.1, overwrite=True)
raw2 = read_raw_kit(sqd_path,
mrk_path,
elp_path,
hsp_path,
stim='<',
preload=True)
raw2_file = op.join(tempdir, 'raw2.fif')
raw2.save(raw2_file, buffer_size_sec=.1, overwrite=True)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
raw3 = read_raw_kit(sqd_path,
mrk_path,
elp_path,
hsp_path,
stim='<',
preload=True)
assert_array_almost_equal(raw1._data, raw3._data)
def test_data():
"""Test reading raw kit files
"""
raw_py = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1), stimthresh=1,
preload=True)
# Binary file only stores the sensor channels
py_picks = pick_types(raw_py.info, exclude='bads')
raw_bin = op.join(data_dir, 'test_bin.fif')
raw_bin = Raw(raw_bin, preload=True)
bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
data_bin, _ = raw_bin[bin_picks]
data_py, _ = raw_py[py_picks]
# this .mat was generated using the Yokogawa MEG Reader
data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
data_Ykgw = data_Ykgw[py_picks]
assert_array_almost_equal(data_py, data_Ykgw)
py_picks = pick_types(raw_py.info, stim=True, exclude='bads')
data_py, _ = raw_py[py_picks]
assert_array_almost_equal(data_py, data_bin)
def test_data():
"""Test reading raw kit files
"""
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path,
stim=list(range(167, 159, -1)), slope='+',
stimthresh=1, preload=True)
print(repr(raw_py))
# Binary file only stores the sensor channels
py_picks = pick_types(raw_py.info, exclude='bads')
raw_bin = op.join(data_dir, 'test_bin.fif')
raw_bin = Raw(raw_bin, preload=True)
bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
data_bin, _ = raw_bin[bin_picks]
data_py, _ = raw_py[py_picks]
# this .mat was generated using the Yokogawa MEG Reader
data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
data_Ykgw = data_Ykgw[py_picks]
assert_array_almost_equal(data_py, data_Ykgw)
py_picks = pick_types(raw_py.info, stim=True, ref_meg=False,
exclude='bads')
data_py, _ = raw_py[py_picks]
assert_array_almost_equal(data_py, data_bin)
def test_data():
"""Test reading raw kit files
"""
raw_py = read_raw_kit(sqd_path,
mrk_path,
elp_path,
hsp_path,
stim=list(range(167, 159, -1)),
slope='+',
stimthresh=1,
preload=True)
print(repr(raw_py))
# Binary file only stores the sensor channels
py_picks = pick_types(raw_py.info, exclude='bads')
raw_bin = op.join(data_dir, 'test_bin.fif')
raw_bin = Raw(raw_bin, preload=True)
bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
data_bin, _ = raw_bin[bin_picks]
data_py, _ = raw_py[py_picks]
# this .mat was generated using the Yokogawa MEG Reader
data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
data_Ykgw = data_Ykgw[py_picks]
assert_array_almost_equal(data_py, data_Ykgw)
py_picks = pick_types(raw_py.info,
stim=True,
ref_meg=False,
exclude='bads')
data_py, _ = raw_py[py_picks]
assert_array_almost_equal(data_py, data_bin)
def test_data():
"""Test reading raw kit files
"""
raw_py = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1),
stimthresh=1,
preload=True)
# Binary file only stores the sensor channels
py_picks = pick_types(raw_py.info, exclude='bads')
raw_bin = op.join(data_dir, 'test_bin.fif')
raw_bin = Raw(raw_bin, preload=True)
bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
data_bin, _ = raw_bin[bin_picks]
data_py, _ = raw_py[py_picks]
# this .mat was generated using the Yokogawa MEG Reader
data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
data_Ykgw = data_Ykgw[py_picks]
assert_array_almost_equal(data_py, data_Ykgw)
py_picks = pick_types(raw_py.info, stim=True, exclude='bads')
data_py, _ = raw_py[py_picks]
assert_array_almost_equal(data_py, data_bin)
def test_read_segment():
"""Test writing raw kit files when preload is False
"""
raw1 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
preload=False)
raw1_file = op.join(tempdir, 'raw1.fif')
raw1.save(raw1_file, buffer_size_sec=.1, overwrite=True)
raw2 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
preload=True)
raw2_file = op.join(tempdir, 'raw2.fif')
raw2.save(raw2_file, buffer_size_sec=.1, overwrite=True)
raw1 = Raw(raw1_file, preload=True)
raw2 = Raw(raw2_file, preload=True)
assert_array_equal(raw1._data, raw2._data)
raw3 = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
preload=True)
assert_array_almost_equal(raw1._data, raw3._data)
def test_stim_ch():
"""Test raw kit stim ch
"""
raw = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<',
slope='+', preload=True)
stim_pick = pick_types(raw.info, meg=False, stim=True, exclude='bads')
stim1, _ = raw[stim_pick]
stim2 = np.array(raw.read_stim_ch(), ndmin=2)
assert_array_equal(stim1, stim2)
def test_ch_loc():
raw_py = kit.read_raw_kit(input_fname=os.path.join(data_dir, 'test.sqd'),
mrk_fname=os.path.join(data_dir, 'test_mrk.sqd'),
elp_fname=os.path.join(data_dir, 'test_elp.txt'),
hsp_fname=os.path.join(data_dir, 'test_hsp.txt'),
sns_fname=os.path.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1))
raw_bin = Raw(os.path.join(data_dir, 'test_bin.fif'))
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the mne_kit2fiff_bin has a different representation of pi.
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=5)
def test_stim_ch():
"""Test raw kit stim ch
"""
raw = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1), preload=True)
stim_pick = pick_types(raw.info, meg=False, stim=True, exclude='bads')
stim1, _ = raw[stim_pick]
stim2 = np.array(raw.read_stim_ch(), ndmin=2)
assert_array_equal(stim1, stim2)
def test_stim_ch():
"""Test raw kit stim ch
"""
raw = read_raw_kit(sqd_path,
mrk_path,
elp_path,
hsp_path,
stim='<',
slope='+',
preload=True)
stim_pick = pick_types(raw.info, meg=False, stim=True, exclude='bads')
stim1, _ = raw[stim_pick]
stim2 = np.array(raw.read_stim_ch(), ndmin=2)
assert_array_equal(stim1, stim2)
def test_stim_ch():
"""Test raw kit stim ch
"""
raw = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1),
preload=True)
stim_pick = pick_types(raw.info, meg=False, stim=True, exclude='bads')
stim1, _ = raw[stim_pick]
stim2 = np.array(raw.read_stim_ch(), ndmin=2)
assert_array_equal(stim1, stim2)
def test_ch_loc():
"""Test raw kit loc
"""
raw_py = kit.read_raw_kit(input_fname=op.join(data_dir, 'test.sqd'),
mrk_fname=op.join(data_dir, 'test_mrk.sqd'),
elp_fname=op.join(data_dir, 'test_elp.txt'),
hsp_fname=op.join(data_dir, 'test_hsp.txt'),
sns_fname=op.join(data_dir, 'sns.txt'),
stim=range(167, 159, -1))
raw_bin = Raw(op.join(data_dir, 'test_bin.fif'))
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the mne_kit2fiff_bin has a different representation of pi.
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=5)
def test_ch_loc():
"""Test raw kit loc
"""
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<')
raw_bin = Raw(op.join(data_dir, 'test_bin.fif'))
ch_py = raw_py._sqd_params['sensor_locs'][:, :5]
# ch locs stored as m, not mm
ch_py[:, :3] *= 1e3
ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
assert_array_almost_equal(ch_py, ch_sns, 2)
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the stored ch locs have more precision than the sns.txt
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)
def test_ch_loc():
"""Test raw kit loc
"""
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path, stim='<')
raw_bin = Raw(op.join(data_dir, 'test_bin.fif'))
ch_py = raw_py._sqd_params['sensor_locs'][:, :5]
# ch locs stored as m, not mm
ch_py[:, :3] *= 1e3
ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
assert_array_almost_equal(ch_py, ch_sns, 2)
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the stored ch locs have more precision than the sns.txt
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)
input_fname = options.input_fname
if input_fname is None:
parser.print_help()
sys.exit(-1)
sns_fname = options.sns_fname
hsp_fname = options.hsp_fname
elp_fname = options.elp_fname
mrk_fname = options.mrk_fname
stim = options.stim
stimthresh = options.stimthresh
out_fname = options.out_fname
if isinstance(stim, str):
stim = stim.split(":")
raw = read_raw_kit(
input_fname=input_fname,
mrk_fname=mrk_fname,
elp_fname=elp_fname,
hsp_fname=hsp_fname,
sns_fname=sns_fname,
stim=stim,
stimthresh=stimthresh,
)
raw.save(out_fname)
raw.close()
sys.exit(0)
options, args = parser.parse_args()
input_fname = options.input_fname
if input_fname is None:
parser.print_help()
sys.exit(-1)
sns_fname = options.sns_fname
hsp_fname = options.hsp_fname
elp_fname = options.elp_fname
mrk_fname = options.mrk_fname
stim = options.stim
stimthresh = options.stimthresh
out_fname = options.out_fname
if isinstance(stim, str):
stim = stim.split(':')
raw = read_raw_kit(input_fname=input_fname,
mrk_fname=mrk_fname,
elp_fname=elp_fname,
hsp_fname=hsp_fname,
sns_fname=sns_fname,
stim=stim,
stimthresh=stimthresh)
raw.save(out_fname)
raw.close()
sys.exit(0)
def test_find_layout():
"""Test finding layout"""
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
find_layout(chs=test_info['chs'])
assert_true(w[0].category == DeprecationWarning)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
find_layout(test_info['chs'])
assert_true(w[0].category == DeprecationWarning)
assert_raises(ValueError, find_layout, dict())
assert_raises(ValueError, find_layout, test_info, ch_type='meep')
sample_info = Raw(fif_fname).info
grads = pick_types(sample_info, meg='grad')
sample_info2 = pick_info(sample_info, grads)
mags = pick_types(sample_info, meg='mag')
sample_info3 = pick_info(sample_info, mags)
# mock new convention
sample_info4 = copy.deepcopy(sample_info)
for ii, name in enumerate(sample_info4['ch_names']):
new = name.replace(' ', '')
sample_info4['ch_names'][ii] = new
sample_info4['chs'][ii]['ch_name'] = new
mags = pick_types(sample_info, meg=False, eeg=True)
sample_info5 = pick_info(sample_info, mags)
lout = find_layout(sample_info, ch_type=None)
assert_true(lout.kind == 'Vectorview-all')
assert_true(all(' ' in k for k in lout.names))
lout = find_layout(sample_info2, ch_type='meg')
assert_true(lout.kind == 'Vectorview-all')
# test new vector-view
lout = find_layout(sample_info4, ch_type=None)
assert_true(lout.kind == 'Vectorview-all')
assert_true(all(not ' ' in k for k in lout.names))
lout = find_layout(sample_info, ch_type='grad')
assert_true(lout.kind == 'Vectorview-grad')
lout = find_layout(sample_info2)
assert_true(lout.kind == 'Vectorview-grad')
lout = find_layout(sample_info2, ch_type='grad')
assert_true(lout.kind == 'Vectorview-grad')
lout = find_layout(sample_info2, ch_type='meg')
assert_true(lout.kind == 'Vectorview-all')
lout = find_layout(sample_info, ch_type='mag')
assert_true(lout.kind == 'Vectorview-mag')
lout = find_layout(sample_info3)
assert_true(lout.kind == 'Vectorview-mag')
lout = find_layout(sample_info3, ch_type='mag')
assert_true(lout.kind == 'Vectorview-mag')
lout = find_layout(sample_info3, ch_type='meg')
assert_true(lout.kind == 'Vectorview-all')
#
lout = find_layout(sample_info, ch_type='eeg')
assert_true(lout.kind == 'EEG')
lout = find_layout(sample_info5)
assert_true(lout.kind == 'EEG')
lout = find_layout(sample_info5, ch_type='eeg')
assert_true(lout.kind == 'EEG')
# no common layout, 'meg' option not supported
fname_bti_raw = op.join(bti_dir, 'exported4D_linux.fif')
lout = find_layout(Raw(fname_bti_raw).info)
assert_true(lout.kind == 'magnesWH3600')
lout = find_layout(Raw(fname_ctf_raw).info)
assert_true(lout.kind == 'CTF-275')
lout = find_layout(read_raw_kit(fname_kit_157).info)
assert_true(lout.kind == 'KIT-157')
sample_info5['dig'] = []
assert_raises(RuntimeError, find_layout, sample_info5)
def test_make_forward_solution_kit():
"""Test making fwd using KIT, BTI, and CTF (compensated) files
"""
fname_bem = op.join(subjects_dir, 'sample', 'bem',
'sample-5120-bem-sol.fif')
kit_dir = op.join(op.dirname(__file__), '..', '..', 'fiff', 'kit',
'tests', 'data')
sqd_path = op.join(kit_dir, 'test.sqd')
mrk_path = op.join(kit_dir, 'test_mrk.sqd')
elp_path = op.join(kit_dir, 'test_elp.txt')
hsp_path = op.join(kit_dir, 'test_hsp.txt')
mri_path = op.join(kit_dir, 'trans-sample.fif')
fname_kit_raw = op.join(kit_dir, 'test_bin.fif')
bti_dir = op.join(op.dirname(__file__), '..', '..', 'fiff', 'bti',
'tests', 'data')
bti_pdf = op.join(bti_dir, 'test_pdf_linux')
bti_config = op.join(bti_dir, 'test_config_linux')
bti_hs = op.join(bti_dir, 'test_hs_linux')
fname_bti_raw = op.join(bti_dir, 'exported4D_linux.fif')
fname_ctf_raw = op.join(op.dirname(__file__), '..', '..', 'fiff', 'tests',
'data', 'test_ctf_comp_raw.fif')
# first set up a testing source space
fname_src = op.join(temp_dir, 'oct2-src.fif')
src = setup_source_space('sample', fname_src, 'oct2',
subjects_dir=subjects_dir)
# first use mne-C: convert file, make forward solution
fwd = do_forward_solution('sample', fname_kit_raw, src=fname_src,
mindist=0.0, bem=fname_bem, mri=mri_path,
eeg=False, meg=True, subjects_dir=subjects_dir)
# now let's use python with the same raw file
fwd_py = make_forward_solution(fname_kit_raw, mindist=0.0,
src=src, eeg=False, meg=True,
bem=fname_bem, mri=mri_path)
_compare_forwards(fwd, fwd_py, 157, 108)
# now let's use mne-python all the way
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path)
# without ignore_ref=True, this should throw an error:
assert_raises(NotImplementedError, make_forward_solution, raw_py.info,
mindist=0.0, src=src, eeg=False, meg=True,
bem=fname_bem, mri=mri_path)
fwd_py = make_forward_solution(raw_py.info, mindist=0.0,
src=src, eeg=False, meg=True,
bem=fname_bem, mri=mri_path,
ignore_ref=True)
_compare_forwards(fwd, fwd_py, 157, 108,
meg_rtol=1e-3, meg_atol=1e-7)
# BTI python end-to-end versus C
fwd = do_forward_solution('sample', fname_bti_raw, src=fname_src,
mindist=0.0, bem=fname_bem, mri=mri_path,
eeg=False, meg=True, subjects_dir=subjects_dir)
raw_py = read_raw_bti(bti_pdf, bti_config, bti_hs)
fwd_py = make_forward_solution(raw_py.info, mindist=0.0,
src=src, eeg=False, meg=True,
bem=fname_bem, mri=mri_path)
_compare_forwards(fwd, fwd_py, 248, 108)
# now let's test CTF w/compensation
fwd_py = make_forward_solution(fname_ctf_raw, mindist=0.0,
src=src, eeg=False, meg=True,
bem=fname_bem, mri=fname_mri)
fwd = do_forward_solution('sample', fname_ctf_raw, src=fname_src,
mindist=0.0, bem=fname_bem, mri=fname_mri,
eeg=False, meg=True, subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, 108)
# CTF with compensation changed in python
ctf_raw = Raw(fname_ctf_raw, compensation=2)
fwd_py = make_forward_solution(ctf_raw.info, mindist=0.0,
src=src, eeg=False, meg=True,
bem=fname_bem, mri=fname_mri)
fwd = do_forward_solution('sample', ctf_raw, src=fname_src,
mindist=0.0, bem=fname_bem, mri=fname_mri,
eeg=False, meg=True, subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, 108)
def mne_raw(path=None, proj=False, **kwargs):
"""
Returns a mne.fiff.Raw object with added projections if appropriate.
Parameters
----------
path : None | str(path)
path to the raw fiff file. If ``None``, a file can be chosen form a
file dialog.
proj : bool | str(path)
Add projections from a separate file to the Raw object.
**``False``**: No proj file will be added.
**``True``**: ``'{raw}*proj.fif'`` will be used.
``'{raw}'`` will be replaced with the raw file's path minus '_raw.fif',
and '*' will be expanded using fnmatch. If multiple files match the
pattern, a ValueError will be raised.
**``str``**: A custom path template can be provided, ``'{raw}'`` and
``'*'`` will be treated as with ``True``.
kwargs
Additional keyword arguments are forwarded to mne.fiff.Raw
initialization.
"""
if path is None:
path = ui.ask_file("Pick a Raw Fiff File", "Pick a Raw Fiff File",
[('Functional image file (*.fif)', '*.fif'),
('KIT Raw File (*.sqd,*.con', '*.sqd;*.con')])
if not path:
return
if not os.path.isfile(path):
raise IOError("%r is not a file" % path)
if isinstance(path, basestring):
_, ext = os.path.splitext(path)
if ext.startswith('.fif'):
raw = mne.fiff.Raw(path, **kwargs)
elif ext in ('.sqd', '.con'):
from mne.fiff.kit import read_raw_kit
raw = read_raw_kit(path, **kwargs)
else:
raise ValueError("Unknown extension: %r" % ext)
else:
raw = mne.fiff.Raw(path, **kwargs)
if proj:
if proj == True:
proj = '{raw}*proj.fif'
if '{raw}' in proj:
raw_file = raw.info['filename']
raw_root, _ = os.path.splitext(raw_file)
raw_root = raw_root.rstrip('raw')
proj = proj.format(raw=raw_root)
if '*' in proj:
head, tail = os.path.split(proj)
names = fnmatch.filter(os.listdir(head), tail)
if len(names) == 1:
proj = os.path.join(head, names[0])
else:
if len(names) == 0:
err = "No file matching %r"
else:
err = "Multiple files matching %r"
raise ValueError(err % proj)
# add the projections to the raw file
proj = mne.read_proj(proj)
raw.add_proj(proj, remove_existing=True)
return raw
def test_make_forward_solution_kit():
"""Test making fwd using KIT, BTI, and CTF (compensated) files
"""
fname_bem = op.join(subjects_dir, 'sample', 'bem',
'sample-5120-bem-sol.fif')
kit_dir = op.join(op.dirname(__file__), '..', '..', 'fiff', 'kit', 'tests',
'data')
sqd_path = op.join(kit_dir, 'test.sqd')
mrk_path = op.join(kit_dir, 'test_mrk.sqd')
elp_path = op.join(kit_dir, 'test_elp.txt')
hsp_path = op.join(kit_dir, 'test_hsp.txt')
mri_path = op.join(kit_dir, 'trans-sample.fif')
fname_kit_raw = op.join(kit_dir, 'test_bin.fif')
bti_dir = op.join(op.dirname(__file__), '..', '..', 'fiff', 'bti', 'tests',
'data')
bti_pdf = op.join(bti_dir, 'test_pdf_linux')
bti_config = op.join(bti_dir, 'test_config_linux')
bti_hs = op.join(bti_dir, 'test_hs_linux')
fname_bti_raw = op.join(bti_dir, 'exported4D_linux.fif')
fname_ctf_raw = op.join(op.dirname(__file__), '..', '..', 'fiff', 'tests',
'data', 'test_ctf_comp_raw.fif')
# first set up a testing source space
fname_src = op.join(temp_dir, 'oct2-src.fif')
src = setup_source_space('sample',
fname_src,
'oct2',
subjects_dir=subjects_dir)
# first use mne-C: convert file, make forward solution
fwd = do_forward_solution('sample',
fname_kit_raw,
src=fname_src,
mindist=0.0,
bem=fname_bem,
mri=mri_path,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
# now let's use python with the same raw file
fwd_py = make_forward_solution(fname_kit_raw,
mindist=0.0,
src=src,
eeg=False,
meg=True,
bem=fname_bem,
mri=mri_path)
_compare_forwards(fwd, fwd_py, 157, 108)
# now let's use mne-python all the way
raw_py = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path)
# without ignore_ref=True, this should throw an error:
assert_raises(NotImplementedError,
make_forward_solution,
raw_py.info,
mindist=0.0,
src=src,
eeg=False,
meg=True,
bem=fname_bem,
mri=mri_path)
fwd_py = make_forward_solution(raw_py.info,
mindist=0.0,
src=src,
eeg=False,
meg=True,
bem=fname_bem,
mri=mri_path,
ignore_ref=True)
_compare_forwards(fwd, fwd_py, 157, 108, meg_rtol=1e-3, meg_atol=1e-7)
# BTI python end-to-end versus C
fwd = do_forward_solution('sample',
fname_bti_raw,
src=fname_src,
mindist=0.0,
bem=fname_bem,
mri=mri_path,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
raw_py = read_raw_bti(bti_pdf, bti_config, bti_hs)
fwd_py = make_forward_solution(raw_py.info,
mindist=0.0,
src=src,
eeg=False,
meg=True,
bem=fname_bem,
mri=mri_path)
_compare_forwards(fwd, fwd_py, 248, 108)
# now let's test CTF w/compensation
fwd_py = make_forward_solution(fname_ctf_raw,
mindist=0.0,
src=src,
eeg=False,
meg=True,
bem=fname_bem,
mri=fname_mri)
fwd = do_forward_solution('sample',
fname_ctf_raw,
src=fname_src,
mindist=0.0,
bem=fname_bem,
mri=fname_mri,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, 108)
# CTF with compensation changed in python
ctf_raw = Raw(fname_ctf_raw, compensation=2)
fwd_py = make_forward_solution(ctf_raw.info,
mindist=0.0,
src=src,
eeg=False,
meg=True,
bem=fname_bem,
mri=fname_mri)
fwd = do_forward_solution('sample',
ctf_raw,
src=fname_src,
mindist=0.0,
bem=fname_bem,
mri=fname_mri,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, 108)
metavar='value')
parser.add_option('--output', dest='out_fname',
help='Name of the resulting fiff file',
metavar='filename')
options, args = parser.parse_args()
input_fname = options.input_fname
if input_fname is None:
parser.print_help()
sys.exit(1)
hsp_fname = options.hsp_fname
elp_fname = options.elp_fname
mrk_fname = options.mrk_fname
stim = options.stim
slope = options.slope
stimthresh = options.stimthresh
out_fname = options.out_fname
if isinstance(stim, str):
stim = stim.split(':')
raw = read_raw_kit(input_fname=input_fname, mrk=mrk_fname, elp=elp_fname,
hsp=hsp_fname, stim=stim, slope=slope,
stimthresh=stimthresh)
raw.save(out_fname)
raw.close()
sys.exit(0)