def test_make_forward_solution_kit():
"""Test making fwd using KIT, BTI, and CTF (compensated) files."""
kit_dir = op.join(op.dirname(__file__), '..', '..', 'io', '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')
trans_path = op.join(kit_dir, 'trans-sample.fif')
fname_kit_raw = op.join(kit_dir, 'test_bin_raw.fif')
bti_dir = op.join(op.dirname(__file__), '..', '..', 'io', '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_raw.fif')
fname_ctf_raw = op.join(op.dirname(__file__), '..', '..', 'io', 'tests',
'data', 'test_ctf_comp_raw.fif')
# first set up a small testing source space
temp_dir = _TempDir()
fname_src_small = op.join(temp_dir, 'sample-oct-2-src.fif')
src = setup_source_space('sample', 'oct2', subjects_dir=subjects_dir,
add_dist=False)
write_source_spaces(fname_src_small, src) # to enable working with MNE-C
n_src = 108 # this is the resulting # of verts in fwd
# first use mne-C: convert file, make forward solution
fwd = _do_forward_solution('sample', fname_kit_raw, src=fname_src_small,
bem=fname_bem_meg, mri=trans_path,
eeg=False, meg=True, subjects_dir=subjects_dir)
assert (isinstance(fwd, Forward))
# now let's use python with the same raw file
fwd_py = make_forward_solution(fname_kit_raw, trans_path, src,
fname_bem_meg, eeg=False, meg=True)
_compare_forwards(fwd, fwd_py, 157, n_src)
assert (isinstance(fwd_py, Forward))
# 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:
pytest.raises(NotImplementedError, make_forward_solution, raw_py.info,
src=src, eeg=False, meg=True,
bem=fname_bem_meg, trans=trans_path)
# check that asking for eeg channels (even if they don't exist) is handled
meg_only_info = pick_info(raw_py.info, pick_types(raw_py.info, meg=True,
eeg=False))
fwd_py = make_forward_solution(meg_only_info, src=src, meg=True, eeg=True,
bem=fname_bem_meg, trans=trans_path,
ignore_ref=True)
_compare_forwards(fwd, fwd_py, 157, n_src,
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_small,
bem=fname_bem_meg, mri=trans_path,
eeg=False, meg=True, subjects_dir=subjects_dir)
raw_py = read_raw_bti(bti_pdf, bti_config, bti_hs, preload=False)
fwd_py = make_forward_solution(raw_py.info, src=src, eeg=False, meg=True,
bem=fname_bem_meg, trans=trans_path)
_compare_forwards(fwd, fwd_py, 248, n_src)
# now let's test CTF w/compensation
fwd_py = make_forward_solution(fname_ctf_raw, fname_trans, src,
fname_bem_meg, eeg=False, meg=True)
fwd = _do_forward_solution('sample', fname_ctf_raw, mri=fname_trans,
src=fname_src_small, bem=fname_bem_meg,
eeg=False, meg=True, subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, n_src)
# CTF with compensation changed in python
ctf_raw = read_raw_fif(fname_ctf_raw)
ctf_raw.info['bads'] = ['MRO24-2908'] # test that it works with some bads
ctf_raw.apply_gradient_compensation(2)
fwd_py = make_forward_solution(ctf_raw.info, fname_trans, src,
fname_bem_meg, eeg=False, meg=True)
fwd = _do_forward_solution('sample', ctf_raw, mri=fname_trans,
src=fname_src_small, bem=fname_bem_meg,
eeg=False, meg=True,
subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, n_src)
temp_dir = _TempDir()
fname_temp = op.join(temp_dir, 'test-ctf-fwd.fif')
write_forward_solution(fname_temp, fwd_py)
fwd_py2 = read_forward_solution(fname_temp)
_compare_forwards(fwd_py, fwd_py2, 274, n_src)
repr(fwd_py)
def test_make_forward_solution_kit():
"""Test making fwd using KIT, BTI, and CTF (compensated) files."""
kit_dir = op.join(op.dirname(__file__), '..', '..', 'io', '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')
trans_path = op.join(kit_dir, 'trans-sample.fif')
fname_kit_raw = op.join(kit_dir, 'test_bin_raw.fif')
bti_dir = op.join(op.dirname(__file__), '..', '..', 'io', '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_raw.fif')
fname_ctf_raw = op.join(op.dirname(__file__), '..', '..', 'io', 'tests',
'data', 'test_ctf_comp_raw.fif')
# first set up a small testing source space
temp_dir = _TempDir()
fname_src_small = op.join(temp_dir, 'sample-oct-2-src.fif')
src = setup_source_space('sample',
'oct2',
subjects_dir=subjects_dir,
add_dist=False)
write_source_spaces(fname_src_small, src) # to enable working with MNE-C
n_src = 108 # this is the resulting # of verts in fwd
# first use mne-C: convert file, make forward solution
fwd = _do_forward_solution('sample',
fname_kit_raw,
src=fname_src_small,
bem=fname_bem_meg,
mri=trans_path,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
assert_true(isinstance(fwd, Forward))
# now let's use python with the same raw file
fwd_py = make_forward_solution(fname_kit_raw,
trans_path,
src,
fname_bem_meg,
eeg=False,
meg=True)
_compare_forwards(fwd, fwd_py, 157, n_src)
assert_true(isinstance(fwd_py, Forward))
# 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,
src=src,
eeg=False,
meg=True,
bem=fname_bem_meg,
trans=trans_path)
# check that asking for eeg channels (even if they don't exist) is handled
meg_only_info = pick_info(raw_py.info,
pick_types(raw_py.info, meg=True, eeg=False))
fwd_py = make_forward_solution(meg_only_info,
src=src,
meg=True,
eeg=True,
bem=fname_bem_meg,
trans=trans_path,
ignore_ref=True)
_compare_forwards(fwd, fwd_py, 157, n_src, 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_small,
bem=fname_bem_meg,
mri=trans_path,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
with warnings.catch_warnings(record=True): # weight tables
raw_py = read_raw_bti(bti_pdf, bti_config, bti_hs, preload=False)
fwd_py = make_forward_solution(raw_py.info,
src=src,
eeg=False,
meg=True,
bem=fname_bem_meg,
trans=trans_path)
_compare_forwards(fwd, fwd_py, 248, n_src)
# now let's test CTF w/compensation
fwd_py = make_forward_solution(fname_ctf_raw,
fname_trans,
src,
fname_bem_meg,
eeg=False,
meg=True)
fwd = _do_forward_solution('sample',
fname_ctf_raw,
mri=fname_trans,
src=fname_src_small,
bem=fname_bem_meg,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, n_src)
# CTF with compensation changed in python
ctf_raw = read_raw_fif(fname_ctf_raw)
ctf_raw.apply_gradient_compensation(2)
fwd_py = make_forward_solution(ctf_raw.info,
fname_trans,
src,
fname_bem_meg,
eeg=False,
meg=True)
with warnings.catch_warnings(record=True):
fwd = _do_forward_solution('sample',
ctf_raw,
mri=fname_trans,
src=fname_src_small,
bem=fname_bem_meg,
eeg=False,
meg=True,
subjects_dir=subjects_dir)
_compare_forwards(fwd, fwd_py, 274, n_src)
def test_make_forward_solution_kit():
"""Test making fwd using KIT, BTI, and CTF (compensated) files
"""
kit_dir = op.join(op.dirname(__file__), "..", "..", "io", "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")
trans_path = op.join(kit_dir, "trans-sample.fif")
fname_kit_raw = op.join(kit_dir, "test_bin_raw.fif")
bti_dir = op.join(op.dirname(__file__), "..", "..", "io", "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_raw.fif")
fname_ctf_raw = op.join(op.dirname(__file__), "..", "..", "io", "tests", "data", "test_ctf_comp_raw.fif")
# first set up a small testing source space
temp_dir = _TempDir()
fname_src_small = op.join(temp_dir, "sample-oct-2-src.fif")
src = setup_source_space("sample", fname_src_small, "oct2", subjects_dir=subjects_dir, add_dist=False)
n_src = 108 # this is the resulting # of verts in fwd
# first use mne-C: convert file, make forward solution
fwd = _do_forward_solution(
"sample",
fname_kit_raw,
src=fname_src_small,
bem=fname_bem_meg,
mri=trans_path,
eeg=False,
meg=True,
subjects_dir=subjects_dir,
)
assert_true(isinstance(fwd, Forward))
# now let's use python with the same raw file
fwd_py = make_forward_solution(fname_kit_raw, trans_path, src, fname_bem_meg, eeg=False, meg=True)
_compare_forwards(fwd, fwd_py, 157, n_src)
assert_true(isinstance(fwd_py, Forward))
# 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,
src=src,
eeg=False,
meg=True,
bem=fname_bem_meg,
trans=trans_path,
)
# check that asking for eeg channels (even if they don't exist) is handled
meg_only_info = pick_info(raw_py.info, pick_types(raw_py.info, meg=True, eeg=False))
fwd_py = make_forward_solution(
meg_only_info, src=src, meg=True, eeg=True, bem=fname_bem_meg, trans=trans_path, ignore_ref=True
)
_compare_forwards(fwd, fwd_py, 157, n_src, 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_small,
bem=fname_bem_meg,
mri=trans_path,
eeg=False,
meg=True,
subjects_dir=subjects_dir,
)
with warnings.catch_warnings(record=True): # weight tables
raw_py = read_raw_bti(bti_pdf, bti_config, bti_hs, preload=False)
fwd_py = make_forward_solution(raw_py.info, src=src, eeg=False, meg=True, bem=fname_bem_meg, trans=trans_path)
_compare_forwards(fwd, fwd_py, 248, n_src)
# now let's test CTF w/compensation
fwd_py = make_forward_solution(fname_ctf_raw, fname_trans, src, fname_bem_meg, eeg=False, meg=True)
fwd = _do_forward_solution(
"sample",
fname_ctf_raw,
mri=fname_trans,
src=fname_src_small,
bem=fname_bem_meg,
eeg=False,
meg=True,
subjects_dir=subjects_dir,
)
_compare_forwards(fwd, fwd_py, 274, n_src)
# CTF with compensation changed in python
ctf_raw = Raw(fname_ctf_raw, compensation=2)
fwd_py = make_forward_solution(ctf_raw.info, fname_trans, src, fname_bem_meg, eeg=False, meg=True)
with warnings.catch_warnings(record=True):
fwd = _do_forward_solution(
"sample",
ctf_raw,
mri=fname_trans,
src=fname_src_small,
bem=fname_bem_meg,
eeg=False,
meg=True,
subjects_dir=subjects_dir,
)
_compare_forwards(fwd, fwd_py, 274, n_src)
