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test_maxwell.py
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test_maxwell.py
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# Author: Mark Wronkiewicz <wronk@uw.edu>
#
# License: BSD (3-clause)
from contextlib import contextmanager
import os.path as op
import pathlib
import re
import numpy as np
from numpy.testing import assert_allclose, assert_array_equal
import pytest
from scipy import sparse
from scipy.special import sph_harm
import mne
from mne import compute_raw_covariance, pick_types, concatenate_raws, pick_info
from mne.annotations import _annotations_starts_stops
from mne.chpi import read_head_pos, filter_chpi
from mne.forward import _prep_meg_channels
from mne.datasets import testing
from mne.forward import use_coil_def
from mne.io import (read_raw_fif, read_info, read_raw_bti, read_raw_kit,
BaseRaw, read_raw_ctf)
from mne.io.constants import FIFF
from mne.preprocessing.maxwell import (
maxwell_filter, _get_n_moments, _sss_basis_basic, _sh_complex_to_real,
_sh_real_to_complex, _sh_negate, _bases_complex_to_real, _trans_sss_basis,
_bases_real_to_complex, _prep_mf_coils, find_bad_channels_maxwell)
from mne.rank import _get_rank_sss, _compute_rank_int
from mne.utils import (assert_meg_snr, run_tests_if_main, catch_logging,
object_diff, buggy_mkl_svd, use_log_level)
data_path = testing.data_path(download=False)
sss_path = op.join(data_path, 'SSS')
pre = op.join(sss_path, 'test_move_anon_')
raw_fname = pre + 'raw.fif'
sss_std_fname = pre + 'stdOrigin_raw_sss.fif'
sss_nonstd_fname = pre + 'nonStdOrigin_raw_sss.fif'
sss_bad_recon_fname = pre + 'badRecon_raw_sss.fif'
sss_reg_in_fname = pre + 'regIn_raw_sss.fif'
sss_fine_cal_fname = pre + 'fineCal_raw_sss.fif'
sss_ctc_fname = pre + 'crossTalk_raw_sss.fif'
sss_trans_default_fname = pre + 'transDefault_raw_sss.fif'
sss_trans_sample_fname = pre + 'transSample_raw_sss.fif'
sss_st1FineCalCrossTalkRegIn_fname = \
pre + 'st1FineCalCrossTalkRegIn_raw_sss.fif'
sss_st1FineCalCrossTalkRegInTransSample_fname = \
pre + 'st1FineCalCrossTalkRegInTransSample_raw_sss.fif'
sss_movecomp_fname = pre + 'movecomp_raw_sss.fif'
sss_movecomp_reg_in_fname = pre + 'movecomp_regIn_raw_sss.fif'
sss_movecomp_reg_in_st4s_fname = pre + 'movecomp_regIn_st4s_raw_sss.fif'
skip_fname = op.join(data_path, 'misc', 'intervalrecording_raw.fif')
erm_fname = pre + 'erm_raw.fif'
sss_erm_std_fname = pre + 'erm_devOrigin_raw_sss.fif'
sss_erm_reg_in_fname = pre + 'erm_regIn_raw_sss.fif'
sss_erm_fine_cal_fname = pre + 'erm_fineCal_raw_sss.fif'
sss_erm_ctc_fname = pre + 'erm_crossTalk_raw_sss.fif'
sss_erm_st_fname = pre + 'erm_st1_raw_sss.fif'
sss_erm_st1FineCalCrossTalk_fname = pre + 'erm_st1FineCalCrossTalk_raw_sss.fif'
sss_erm_st1FineCalCrossTalkRegIn_fname = \
pre + 'erm_st1FineCalCrossTalkRegIn_raw_sss.fif'
sample_fname = op.join(
data_path, 'MEG', 'sample', 'sample_audvis_trunc_raw.fif')
sss_samp_reg_in_fname = op.join(data_path, 'SSS',
'sample_audvis_trunc_regIn_raw_sss.fif')
sss_samp_fname = op.join(data_path, 'SSS', 'sample_audvis_trunc_raw_sss.fif')
pos_fname = op.join(data_path, 'SSS', 'test_move_anon_raw.pos')
bases_fname = op.join(sss_path, 'sss_data.mat')
fine_cal_fname = op.join(sss_path, 'sss_cal_3053.dat')
fine_cal_fname_3d = op.join(sss_path, 'sss_cal_3053_3d.dat')
ctc_fname = op.join(sss_path, 'ct_sparse.fif')
fine_cal_mgh_fname = op.join(sss_path, 'sss_cal_mgh.dat')
ctc_mgh_fname = op.join(sss_path, 'ct_sparse_mgh.fif')
triux_path = op.join(data_path, 'SSS', 'TRIUX')
tri_fname = op.join(triux_path, 'triux_bmlhus_erm_raw.fif')
tri_sss_fname = op.join(triux_path, 'triux_bmlhus_erm_raw_sss.fif')
tri_sss_reg_fname = op.join(triux_path, 'triux_bmlhus_erm_regIn_raw_sss.fif')
tri_sss_st4_fname = op.join(triux_path, 'triux_bmlhus_erm_st4_raw_sss.fif')
tri_sss_ctc_fname = op.join(triux_path, 'triux_bmlhus_erm_ctc_raw_sss.fif')
tri_sss_cal_fname = op.join(triux_path, 'triux_bmlhus_erm_cal_raw_sss.fif')
tri_sss_ctc_cal_fname = op.join(
triux_path, 'triux_bmlhus_erm_ctc_cal_raw_sss.fif')
tri_sss_ctc_cal_reg_in_fname = op.join(
triux_path, 'triux_bmlhus_erm_ctc_cal_regIn_raw_sss.fif')
tri_ctc_fname = op.join(triux_path, 'ct_sparse_BMLHUS.fif')
tri_cal_fname = op.join(triux_path, 'sss_cal_BMLHUS.dat')
io_dir = op.join(op.dirname(__file__), '..', '..', 'io')
fname_ctf_raw = op.join(io_dir, 'tests', 'data', 'test_ctf_comp_raw.fif')
ctf_fname_continuous = op.join(data_path, 'CTF', 'testdata_ctf.ds')
# In some of the tests, use identical coil defs to what is used in
# MaxFilter
elekta_def_fname = op.join(op.dirname(mne.__file__), 'data',
'coil_def_Elekta.dat')
int_order, ext_order = 8, 3
mf_head_origin = (0., 0., 0.04)
mf_meg_origin = (0., 0.013, -0.006)
# 30 random bad MEG channels (20 grad, 10 mag) that were used in generation
bads = ['MEG0912', 'MEG1722', 'MEG2213', 'MEG0132', 'MEG1312', 'MEG0432',
'MEG2433', 'MEG1022', 'MEG0442', 'MEG2332', 'MEG0633', 'MEG1043',
'MEG1713', 'MEG0422', 'MEG0932', 'MEG1622', 'MEG1343', 'MEG0943',
'MEG0643', 'MEG0143', 'MEG2142', 'MEG0813', 'MEG2143', 'MEG1323',
'MEG0522', 'MEG1123', 'MEG0423', 'MEG2122', 'MEG2532', 'MEG0812']
def _assert_n_free(raw_sss, lower, upper=None):
"""Check the DOF."""
upper = lower if upper is None else upper
n_free = raw_sss.info['proc_history'][0]['max_info']['sss_info']['nfree']
assert lower <= n_free <= upper, \
'nfree fail: %s <= %s <= %s' % (lower, n_free, upper)
def _assert_mag_coil_type(info, coil_type):
__tracebackhide__ = True
picks = pick_types(info, meg='mag', exclude=())
coil_types = set(info['chs'][pick]['coil_type'] for pick in picks)
assert coil_types == {coil_type}
def read_crop(fname, lims=(0, None)):
"""Read and crop."""
return read_raw_fif(fname, allow_maxshield='yes').crop(*lims)
@pytest.mark.slowtest
@testing.requires_testing_data
def test_movement_compensation(tmpdir):
"""Test movement compensation."""
temp_dir = str(tmpdir)
lims = (0, 4)
raw = read_crop(raw_fname, lims).load_data()
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
_assert_mag_coil_type(raw.info, FIFF.FIFFV_COIL_VV_MAG_T3)
assert_allclose(raw.info['chs'][2]['cal'], 4.14e-11, rtol=1e-6)
raw.info['chs'][2]['coil_type'] = FIFF.FIFFV_COIL_VV_MAG_T2
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
_assert_mag_coil_type(raw_sss.info, FIFF.FIFFV_COIL_VV_MAG_T3)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_fname, lims),
4.6, 12.4, chpi_med_tol=58)
# IO
temp_fname = op.join(temp_dir, 'test_raw_sss.fif')
raw_sss.save(temp_fname)
raw_sss = read_crop(temp_fname)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_fname, lims),
4.6, 12.4, chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_reg_in_fname, lims),
0.5, 1.9, chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy(), t_window=0.2)
with pytest.warns(RuntimeWarning, match='untested'):
raw_sss_mv = maxwell_filter(raw_nohpi, head_pos=head_pos,
st_duration=4., origin=mf_head_origin,
st_fixed=False)
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv, read_crop(sss_movecomp_reg_in_st4s_fname, lims),
0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv, read_crop(tSSS_fname, lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(read_crop(sss_movecomp_reg_in_st4s_fname),
read_crop(tSSS_fname), 0.8, 1.0, chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi, head_pos=head_pos, st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc, read_crop(tSSS_fname, lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
raw_erm = read_crop(erm_fname)
with pytest.raises(ValueError, match='positions can only be used'):
maxwell_filter(raw_erm, coord_frame='meg',
head_pos=head_pos)
with pytest.raises(ValueError, match=r'of shape \(N, 10\)'):
maxwell_filter(raw, head_pos=head_pos[:, :9])
with pytest.raises(TypeError, match='instance of ndarray'):
maxwell_filter(raw, head_pos='foo')
with pytest.raises(ValueError, match='ascending'):
maxwell_filter(raw, head_pos=head_pos[::-1])
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw._first_time - 1e-2
with pytest.raises(ValueError, match='greater than'):
maxwell_filter(raw, head_pos=head_pos_bad)
head_pos_bad = head_pos.copy()
head_pos_bad[0, 4] = 1. # off by more than 1 m
with pytest.warns(RuntimeWarning, match='greater than 1 m'):
maxwell_filter(raw.copy().crop(0, 0.1), head_pos=head_pos_bad,
bad_condition='ignore')
# make sure numerical error doesn't screw it up, though
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw._first_time - 5e-4
raw_sss_tweak = maxwell_filter(
raw.copy().crop(0, 0.05), head_pos=head_pos_bad, origin=mf_head_origin)
assert_meg_snr(raw_sss_tweak, raw_sss.copy().crop(0, 0.05), 1.4, 8.,
chpi_med_tol=5)
@pytest.mark.slowtest
def test_other_systems():
"""Test Maxwell filtering on KIT, BTI, and CTF files."""
# KIT
kit_dir = op.join(io_dir, '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')
raw_kit = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path)
with pytest.warns(RuntimeWarning, match='fit'):
pytest.raises(RuntimeError, maxwell_filter, raw_kit)
with catch_logging() as log:
raw_sss = maxwell_filter(raw_kit, origin=(0., 0., 0.04),
ignore_ref=True, verbose=True)
assert '12/15 out' in log.getvalue() # homogeneous fields removed
_assert_n_free(raw_sss, 65, 65)
raw_sss_auto = maxwell_filter(raw_kit, origin=(0., 0., 0.04),
ignore_ref=True, mag_scale='auto')
assert_allclose(raw_sss._data, raw_sss_auto._data)
# XXX this KIT origin fit is terrible! Eventually we should get a
# corrected HSP file with proper coverage
with pytest.warns(RuntimeWarning, match='more than 20 mm'):
with catch_logging() as log:
pytest.raises(RuntimeError, maxwell_filter, raw_kit,
ignore_ref=True, regularize=None) # bad condition
raw_sss = maxwell_filter(raw_kit, origin='auto',
ignore_ref=True, bad_condition='info',
verbose=True)
log = log.getvalue()
assert 'badly conditioned' in log
assert 'more than 20 mm from' in log
# fits can differ slightly based on scipy version, so be lenient here
_assert_n_free(raw_sss, 28, 34) # bad origin == brutal reg
# Let's set the origin
with catch_logging() as log:
raw_sss = maxwell_filter(raw_kit, origin=(0., 0., 0.04),
ignore_ref=True, bad_condition='info',
regularize=None, verbose=True)
log = log.getvalue()
assert 'badly conditioned' in log
assert '80/80 in, 12/15 out' in log
_assert_n_free(raw_sss, 80)
# Now with reg
with catch_logging() as log:
raw_sss = maxwell_filter(raw_kit, origin=(0., 0., 0.04),
ignore_ref=True, verbose=True)
log = log.getvalue()
assert 'badly conditioned' not in log
assert '12/15 out' in log
_assert_n_free(raw_sss, 65)
# BTi
bti_dir = op.join(io_dir, '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')
raw_bti = read_raw_bti(bti_pdf, bti_config, bti_hs, preload=False)
picks = pick_types(raw_bti.info, meg='mag', exclude=())
power = np.sqrt(np.sum(raw_bti[picks][0] ** 2))
raw_sss = maxwell_filter(raw_bti)
_assert_n_free(raw_sss, 70)
_assert_shielding(raw_sss, power, 0.5)
raw_sss_auto = maxwell_filter(raw_bti, mag_scale='auto', verbose=True)
_assert_shielding(raw_sss_auto, power, 0.7)
# CTF
raw_ctf = read_crop(fname_ctf_raw)
assert raw_ctf.compensation_grade == 3
with pytest.raises(RuntimeError, match='compensated'):
maxwell_filter(raw_ctf)
raw_ctf.apply_gradient_compensation(0)
with pytest.raises(ValueError, match='digitization points'):
maxwell_filter(raw_ctf)
raw_sss = maxwell_filter(raw_ctf, origin=(0., 0., 0.04))
_assert_n_free(raw_sss, 68)
_assert_shielding(raw_sss, raw_ctf, 1.8)
with catch_logging() as log:
raw_sss = maxwell_filter(raw_ctf, origin=(0., 0., 0.04),
ignore_ref=True, verbose=True)
assert ', 12/15 out' in log.getvalue() # homogeneous fields removed
_assert_n_free(raw_sss, 70)
_assert_shielding(raw_sss, raw_ctf, 12)
raw_sss_auto = maxwell_filter(raw_ctf, origin=(0., 0., 0.04),
ignore_ref=True, mag_scale='auto')
assert_allclose(raw_sss._data, raw_sss_auto._data)
with catch_logging() as log:
maxwell_filter(raw_ctf, origin=(0., 0., 0.04), regularize=None,
ignore_ref=True, verbose=True)
assert '80/80 in, 12/15 out' in log.getvalue() # homogeneous fields
def test_spherical_conversions():
"""Test spherical harmonic conversions."""
# Test our real<->complex conversion functions
az, pol = np.meshgrid(np.linspace(0, 2 * np.pi, 30),
np.linspace(0, np.pi, 20))
for degree in range(1, int_order):
for order in range(0, degree + 1):
sph = sph_harm(order, degree, az, pol)
# ensure that we satisfy the conjugation property
assert_allclose(_sh_negate(sph, order),
sph_harm(-order, degree, az, pol))
# ensure our conversion functions work
sph_real_pos = _sh_complex_to_real(sph, order)
sph_real_neg = _sh_complex_to_real(sph, -order)
sph_2 = _sh_real_to_complex([sph_real_pos, sph_real_neg], order)
assert_allclose(sph, sph_2, atol=1e-7)
@testing.requires_testing_data
def test_multipolar_bases():
"""Test multipolar moment basis calculation using sensor information."""
from scipy.io import loadmat
# Test our basis calculations
info = read_info(raw_fname)
with use_coil_def(elekta_def_fname):
coils = _prep_meg_channels(info, accurate=True, do_es=True)[0]
# Check against a known benchmark
sss_data = loadmat(bases_fname)
exp = dict(int_order=int_order, ext_order=ext_order)
for origin in ((0, 0, 0.04), (0, 0.02, 0.02)):
o_str = ''.join('%d' % (1000 * n) for n in origin)
exp.update(origin=origin)
S_tot = _sss_basis_basic(exp, coils, method='alternative')
# Test our real<->complex conversion functions
S_tot_complex = _bases_real_to_complex(S_tot, int_order, ext_order)
S_tot_round = _bases_complex_to_real(S_tot_complex,
int_order, ext_order)
assert_allclose(S_tot, S_tot_round, atol=1e-7)
S_tot_mat = np.concatenate([sss_data['Sin' + o_str],
sss_data['Sout' + o_str]], axis=1)
S_tot_mat_real = _bases_complex_to_real(S_tot_mat,
int_order, ext_order)
S_tot_mat_round = _bases_real_to_complex(S_tot_mat_real,
int_order, ext_order)
assert_allclose(S_tot_mat, S_tot_mat_round, atol=1e-7)
assert_allclose(S_tot_complex, S_tot_mat, rtol=1e-4, atol=1e-8)
assert_allclose(S_tot, S_tot_mat_real, rtol=1e-4, atol=1e-8)
# Now normalize our columns
S_tot /= np.sqrt(np.sum(S_tot * S_tot, axis=0))[np.newaxis]
S_tot_complex /= np.sqrt(np.sum(
(S_tot_complex * S_tot_complex.conj()).real, axis=0))[np.newaxis]
# Check against a known benchmark
S_tot_mat = np.concatenate([sss_data['SNin' + o_str],
sss_data['SNout' + o_str]], axis=1)
# Check this roundtrip
S_tot_mat_real = _bases_complex_to_real(S_tot_mat,
int_order, ext_order)
S_tot_mat_round = _bases_real_to_complex(S_tot_mat_real,
int_order, ext_order)
assert_allclose(S_tot_mat, S_tot_mat_round, atol=1e-7)
assert_allclose(S_tot_complex, S_tot_mat, rtol=1e-4, atol=1e-8)
# Now test our optimized version
S_tot = _sss_basis_basic(exp, coils)
with use_coil_def(elekta_def_fname):
S_tot_fast = _trans_sss_basis(
exp, all_coils=_prep_mf_coils(info), trans=info['dev_head_t'])
# there are some sign differences for columns (order/degrees)
# in here, likely due to Condon-Shortley. Here we use a
# Magnetometer channel to figure out the flips because the
# gradiometer channels have effectively zero values for first three
# external components (i.e., S_tot[grad_picks, 80:83])
flips = (np.sign(S_tot_fast[2]) != np.sign(S_tot[2]))
flips = 1 - 2 * flips
assert_allclose(S_tot, S_tot_fast * flips, atol=1e-16)
@testing.requires_testing_data
def test_basic():
"""Test Maxwell filter basic version."""
# Load testing data (raw, SSS std origin, SSS non-standard origin)
raw = read_crop(raw_fname, (0., 1.))
raw_err = read_crop(raw_fname).apply_proj()
raw_erm = read_crop(erm_fname)
with pytest.raises(RuntimeError, match='cannot be applied'):
maxwell_filter(raw_err)
with pytest.raises(TypeError, match='instance of BaseRaw'):
maxwell_filter(1.)
with pytest.raises(ValueError, match='Number of requested bases'):
maxwell_filter(raw, int_order=20) # too many
n_int_bases = int_order ** 2 + 2 * int_order
n_ext_bases = ext_order ** 2 + 2 * ext_order
nbases = n_int_bases + n_ext_bases
# Check number of bases computed correctly
assert _get_n_moments([int_order, ext_order]).sum() == nbases
# Test SSS computation at the standard head origin
assert len(raw.info['projs']) == 12 # 11 MEG projs + 1 AVG EEG
with use_coil_def(elekta_def_fname):
raw_sss = maxwell_filter(raw, origin=mf_head_origin, regularize=None,
bad_condition='ignore')
assert len(raw_sss.info['projs']) == 1 # avg EEG
assert raw_sss.info['projs'][0]['desc'] == 'Average EEG reference'
assert_meg_snr(raw_sss, read_crop(sss_std_fname), 200., 1000.)
py_cal = raw_sss.info['proc_history'][0]['max_info']['sss_cal']
assert len(py_cal) == 0
py_ctc = raw_sss.info['proc_history'][0]['max_info']['sss_ctc']
assert len(py_ctc) == 0
py_st = raw_sss.info['proc_history'][0]['max_info']['max_st']
assert len(py_st) == 0
with pytest.raises(RuntimeError, match='cannot reapply'):
maxwell_filter(raw_sss)
# Test SSS computation at non-standard head origin
with use_coil_def(elekta_def_fname):
raw_sss = maxwell_filter(raw, origin=[0., 0.02, 0.02], regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss, read_crop(sss_nonstd_fname), 250., 700.)
# Test SSS computation at device origin
sss_erm_std = read_crop(sss_erm_std_fname)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg',
origin=mf_meg_origin, regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss, sss_erm_std, 70., 260.)
for key in ('job', 'frame'):
vals = [x.info['proc_history'][0]['max_info']['sss_info'][key]
for x in [raw_sss, sss_erm_std]]
assert vals[0] == vals[1]
# Two equivalent things: at device origin in device coords (0., 0., 0.)
# and at device origin at head coords info['dev_head_t'][:3, 3]
raw_sss_meg = maxwell_filter(
raw, coord_frame='meg', origin=(0., 0., 0.))
raw_sss_head = maxwell_filter(
raw, origin=raw.info['dev_head_t']['trans'][:3, 3])
assert_meg_snr(raw_sss_meg, raw_sss_head, 100., 900.)
# Check against SSS functions from proc_history
assert _get_n_moments(int_order) == _get_rank_sss(raw_sss)
# Degenerate cases
with pytest.raises(ValueError, match='Invalid value'):
maxwell_filter(raw, coord_frame='foo')
with pytest.raises(ValueError, match='numerical array'):
maxwell_filter(raw, origin='foo')
with pytest.raises(ValueError, match='3-element array'):
maxwell_filter(raw, origin=[0] * 4)
with pytest.raises(ValueError, match='must be a float'):
maxwell_filter(raw, mag_scale='foo')
raw_missing = raw.copy().load_data()
raw_missing.info['bads'] = ['MEG0111']
raw_missing.pick_types(meg=True) # will be missing the bad
maxwell_filter(raw_missing)
with pytest.warns(RuntimeWarning, match='not in data'):
maxwell_filter(raw_missing, calibration=fine_cal_fname)
@testing.requires_testing_data
def test_maxwell_filter_additional(tmpdir):
"""Test processing of Maxwell filtered data."""
# TODO: Future tests integrate with mne/io/tests/test_proc_history
# Load testing data (raw, SSS std origin, SSS non-standard origin)
data_path = op.join(testing.data_path(download=False))
file_name = 'test_move_anon'
raw_fname = op.join(data_path, 'SSS', file_name + '_raw.fif')
# Use 2.0 seconds of data to get stable cov. estimate
raw = read_crop(raw_fname, (0., 2.))
# Get MEG channels, compute Maxwell filtered data
raw.load_data()
raw.pick_types(meg=True, eeg=False)
int_order = 8
raw_sss = maxwell_filter(raw, origin=mf_head_origin, regularize=None,
bad_condition='ignore')
# Test io on processed data
tempdir = str(tmpdir)
test_outname = op.join(tempdir, 'test_raw_sss.fif')
raw_sss.save(test_outname)
raw_sss_loaded = read_crop(test_outname).load_data()
# Some numerical imprecision since save uses 'single' fmt
assert_allclose(raw_sss_loaded[:][0], raw_sss[:][0],
rtol=1e-6, atol=1e-20)
# Test rank of covariance matrices for raw and SSS processed data
cov_raw = compute_raw_covariance(raw)
cov_sss = compute_raw_covariance(raw_sss)
scalings = None
cov_raw_rank = _compute_rank_int(
cov_raw, scalings=scalings, info=raw.info, proj=False)
cov_sss_rank = _compute_rank_int(
cov_sss, scalings=scalings, info=raw_sss.info, proj=False)
assert cov_raw_rank == raw.info['nchan']
assert cov_sss_rank == _get_n_moments(int_order)
@pytest.mark.slowtest
@testing.requires_testing_data
def test_bads_reconstruction():
"""Test Maxwell filter reconstruction of bad channels."""
raw = read_crop(raw_fname, (0., 1.))
raw.info['bads'] = bads
with use_coil_def(elekta_def_fname):
raw_sss = maxwell_filter(raw, origin=mf_head_origin, regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss, read_crop(sss_bad_recon_fname), 300.)
@buggy_mkl_svd
@testing.requires_testing_data
def test_spatiotemporal():
"""Test Maxwell filter (tSSS) spatiotemporal processing."""
# Load raw testing data
raw = read_crop(raw_fname)
# Test that window is less than length of data
with pytest.raises(ValueError, match='must be'):
maxwell_filter(raw, st_duration=1000.)
# We could check both 4 and 10 seconds because Elekta handles them
# differently (to ensure that std/non-std tSSS windows are correctly
# handled), but the 4-sec case should hopefully be sufficient.
st_durations = [4.] # , 10.]
tols = [(80, 100)] # , 200.]
kwargs = dict(origin=mf_head_origin, regularize=None,
bad_condition='ignore')
for st_duration, tol in zip(st_durations, tols):
# Load tSSS data depending on st_duration and get data
tSSS_fname = op.join(sss_path,
'test_move_anon_st%0ds_raw_sss.fif' % st_duration)
tsss_bench = read_crop(tSSS_fname)
# Because Elekta's tSSS sometimes(!) lumps the tail window of data
# onto the previous buffer if it's shorter than st_duration, we have to
# crop the data here to compensate for Elekta's tSSS behavior.
# if st_duration == 10.:
# tsss_bench.crop(0, st_duration)
# raw.crop(0, st_duration)
# Test sss computation at the standard head origin. Same cropping issue
# as mentioned above.
raw_tsss = maxwell_filter(
raw, st_duration=st_duration, **kwargs)
assert _compute_rank_int(raw_tsss, proj=False) == 140
assert_meg_snr(raw_tsss, tsss_bench, *tol)
py_st = raw_tsss.info['proc_history'][0]['max_info']['max_st']
assert (len(py_st) > 0)
assert py_st['buflen'] == st_duration
assert py_st['subspcorr'] == 0.98
# Degenerate cases
with pytest.raises(ValueError, match='Need 0 < st_correlation'):
maxwell_filter(raw, st_duration=10., st_correlation=0.)
@pytest.mark.slowtest
@testing.requires_testing_data
def test_spatiotemporal_only():
"""Test tSSS-only processing."""
# Load raw testing data
tmax = 0.5
raw = read_crop(raw_fname, (0, tmax)).load_data()
picks = pick_types(raw.info, meg=True, exclude='bads')[::2]
raw.pick_channels([raw.ch_names[pick] for pick in picks])
mag_picks = pick_types(raw.info, meg='mag', exclude=())
power = np.sqrt(np.sum(raw[mag_picks][0] ** 2))
# basics
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True)
assert len(raw.info['projs']) == len(raw_tsss.info['projs'])
assert _compute_rank_int(raw_tsss, proj=False) == len(picks)
_assert_shielding(raw_tsss, power, 9)
# with movement
head_pos = read_head_pos(pos_fname)
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True,
head_pos=head_pos)
assert _compute_rank_int(raw_tsss, proj=False) == len(picks)
_assert_shielding(raw_tsss, power, 9)
with pytest.warns(RuntimeWarning, match='st_fixed'):
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True,
head_pos=head_pos, st_fixed=False)
assert _compute_rank_int(raw_tsss, proj=False) == len(picks)
_assert_shielding(raw_tsss, power, 9)
# should do nothing
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_correlation=1.,
st_only=True)
assert_allclose(raw[:][0], raw_tsss[:][0])
# degenerate
pytest.raises(ValueError, maxwell_filter, raw, st_only=True) # no ST
# two-step process equivalent to single-step process
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_only=True)
raw_tsss = maxwell_filter(raw_tsss)
raw_tsss_2 = maxwell_filter(raw, st_duration=tmax)
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
# now also with head movement, and a bad MEG channel
assert len(raw.info['bads']) == 0
bads = [raw.ch_names[0]]
raw.info['bads'] = list(bads)
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_only=True,
head_pos=head_pos)
assert raw.info['bads'] == bads
assert raw_tsss.info['bads'] == bads # don't reset
raw_tsss = maxwell_filter(raw_tsss, head_pos=head_pos)
assert raw_tsss.info['bads'] == [] # do reset MEG bads
raw_tsss_2 = maxwell_filter(raw, st_duration=tmax, head_pos=head_pos)
assert raw_tsss_2.info['bads'] == []
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
@testing.requires_testing_data
def test_fine_calibration():
"""Test Maxwell filter fine calibration."""
# Load testing data (raw, SSS std origin, SSS non-standard origin)
raw = read_crop(raw_fname, (0., 1.))
sss_fine_cal = read_crop(sss_fine_cal_fname)
# Test 1D SSS fine calibration
with use_coil_def(elekta_def_fname):
raw_sss = maxwell_filter(raw, calibration=fine_cal_fname,
origin=mf_head_origin, regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss, sss_fine_cal, 82, 611)
py_cal = raw_sss.info['proc_history'][0]['max_info']['sss_cal']
assert (py_cal is not None)
assert (len(py_cal) > 0)
mf_cal = sss_fine_cal.info['proc_history'][0]['max_info']['sss_cal']
# we identify these differently
mf_cal['cal_chans'][mf_cal['cal_chans'][:, 1] == 3022, 1] = 3024
assert_allclose(py_cal['cal_chans'], mf_cal['cal_chans'])
assert_allclose(py_cal['cal_corrs'], mf_cal['cal_corrs'],
rtol=1e-3, atol=1e-3)
# with missing channels
raw_missing = raw.copy().load_data()
raw_missing.info['bads'] = ['MEG0111', 'MEG0943'] # 1 mag, 1 grad
raw_missing.info._check_consistency()
raw_sss_bad = maxwell_filter(
raw_missing, calibration=fine_cal_fname, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
raw_missing.pick_types(meg=True) # actually remove bads
raw_sss_bad.pick_channels(raw_missing.ch_names) # remove them here, too
with pytest.warns(RuntimeWarning, match='cal channels not in data'):
raw_sss_missing = maxwell_filter(
raw_missing, calibration=fine_cal_fname, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
assert_meg_snr(raw_sss_missing, raw_sss_bad, 1000., 10000.)
# Test 3D SSS fine calibration (no equivalent func in MaxFilter yet!)
# very low SNR as proc differs, eventually we should add a better test
raw_sss_3D = maxwell_filter(raw, calibration=fine_cal_fname_3d,
origin=mf_head_origin, regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss_3D, sss_fine_cal, 1.0, 6.)
raw_ctf = read_crop(fname_ctf_raw).apply_gradient_compensation(0)
pytest.raises(RuntimeError, maxwell_filter, raw_ctf, origin=(0., 0., 0.04),
calibration=fine_cal_fname)
@pytest.mark.slowtest
@testing.requires_testing_data
def test_regularization():
"""Test Maxwell filter regularization."""
# Load testing data (raw, SSS std origin, SSS non-standard origin)
min_tols = (20., 2.6, 1.0)
med_tols = (200., 21., 3.7)
origins = ((0., 0., 0.04), (0.,) * 3, (0., 0.02, 0.02))
coord_frames = ('head', 'meg', 'head')
raw_fnames = (raw_fname, erm_fname, sample_fname)
sss_fnames = (sss_reg_in_fname, sss_erm_reg_in_fname,
sss_samp_reg_in_fname)
comp_tols = [0, 1, 4]
for ii, rf in enumerate(raw_fnames):
raw = read_crop(rf, (0., 1.))
sss_reg_in = read_crop(sss_fnames[ii])
# Test "in" regularization
raw_sss = maxwell_filter(raw, coord_frame=coord_frames[ii],
origin=origins[ii])
assert_meg_snr(raw_sss, sss_reg_in, min_tols[ii], med_tols[ii], msg=rf)
# check components match
_check_reg_match(raw_sss, sss_reg_in, comp_tols[ii])
def _check_reg_match(sss_py, sss_mf, comp_tol):
"""Check regularization."""
info_py = sss_py.info['proc_history'][0]['max_info']['sss_info']
assert (info_py is not None)
assert (len(info_py) > 0)
info_mf = sss_mf.info['proc_history'][0]['max_info']['sss_info']
n_in = None
for inf in (info_py, info_mf):
if n_in is None:
n_in = _get_n_moments(inf['in_order'])
else:
assert n_in == _get_n_moments(inf['in_order'])
assert inf['components'][:n_in].sum() == inf['nfree']
assert_allclose(info_py['nfree'], info_mf['nfree'],
atol=comp_tol, err_msg=sss_py._filenames[0])
@testing.requires_testing_data
def test_cross_talk(tmpdir):
"""Test Maxwell filter cross-talk cancellation."""
raw = read_crop(raw_fname, (0., 1.))
raw.info['bads'] = bads
sss_ctc = read_crop(sss_ctc_fname)
with use_coil_def(elekta_def_fname):
raw_sss = maxwell_filter(raw, cross_talk=pathlib.Path(ctc_fname),
origin=mf_head_origin, regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss, sss_ctc, 275.)
py_ctc = raw_sss.info['proc_history'][0]['max_info']['sss_ctc']
assert (len(py_ctc) > 0)
with pytest.raises(TypeError, match='path-like'):
maxwell_filter(raw, cross_talk=raw)
pytest.raises(ValueError, maxwell_filter, raw, cross_talk=raw_fname)
mf_ctc = sss_ctc.info['proc_history'][0]['max_info']['sss_ctc']
del mf_ctc['block_id'] # we don't write this
assert isinstance(py_ctc['decoupler'], sparse.csc_matrix)
assert isinstance(mf_ctc['decoupler'], sparse.csc_matrix)
assert_array_equal(py_ctc['decoupler'].toarray(),
mf_ctc['decoupler'].toarray())
# I/O roundtrip
tempdir = str(tmpdir)
fname = op.join(tempdir, 'test_sss_raw.fif')
sss_ctc.save(fname)
sss_ctc_read = read_raw_fif(fname)
mf_ctc_read = sss_ctc_read.info['proc_history'][0]['max_info']['sss_ctc']
assert isinstance(mf_ctc_read['decoupler'], sparse.csc_matrix)
assert_array_equal(mf_ctc_read['decoupler'].toarray(),
mf_ctc['decoupler'].toarray())
assert object_diff(py_ctc, mf_ctc) == ''
raw_ctf = read_crop(fname_ctf_raw).apply_gradient_compensation(0)
raw_sss = maxwell_filter(raw_ctf, origin=(0., 0., 0.04))
_assert_n_free(raw_sss, 68)
raw_sss = maxwell_filter(raw_ctf, origin=(0., 0., 0.04), ignore_ref=True)
_assert_n_free(raw_sss, 70)
raw_missing = raw.copy().crop(0, 0.1).load_data().pick_channels(
[raw.ch_names[pi] for pi in pick_types(raw.info, meg=True,
exclude=())[3:]])
with pytest.warns(RuntimeWarning, match='Not all cross-talk channels'):
maxwell_filter(raw_missing, cross_talk=ctc_fname)
# MEG channels not in cross-talk
pytest.raises(RuntimeError, maxwell_filter, raw_ctf, origin=(0., 0., 0.04),
cross_talk=ctc_fname)
@testing.requires_testing_data
def test_head_translation():
"""Test Maxwell filter head translation."""
raw = read_crop(raw_fname, (0., 1.))
# First try with an unchanged destination
with use_coil_def(elekta_def_fname):
raw_sss = maxwell_filter(raw, destination=raw_fname,
origin=mf_head_origin, regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss, read_crop(sss_std_fname, (0., 1.)), 200.)
# Now with default
with use_coil_def(elekta_def_fname):
with pytest.warns(RuntimeWarning, match='over 25 mm'):
raw_sss = maxwell_filter(raw, destination=mf_head_origin,
origin=mf_head_origin, regularize=None,
bad_condition='ignore', verbose=True)
assert_meg_snr(raw_sss, read_crop(sss_trans_default_fname), 125.)
destination = np.eye(4)
destination[2, 3] = 0.04
assert_allclose(raw_sss.info['dev_head_t']['trans'], destination)
# Now to sample's head pos
with pytest.warns(RuntimeWarning, match='= 25.6 mm'):
raw_sss = maxwell_filter(raw, destination=sample_fname,
origin=mf_head_origin, regularize=None,
bad_condition='ignore', verbose=True)
assert_meg_snr(raw_sss, read_crop(sss_trans_sample_fname), 13., 100.)
assert_allclose(raw_sss.info['dev_head_t']['trans'],
read_info(sample_fname)['dev_head_t']['trans'])
# Degenerate cases
pytest.raises(RuntimeError, maxwell_filter, raw,
destination=mf_head_origin, coord_frame='meg')
pytest.raises(ValueError, maxwell_filter, raw, destination=[0.] * 4)
# TODO: Eventually add simulation tests mirroring Taulu's original paper
# that calculates the localization error:
# http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1495874
def _assert_shielding(raw_sss, erm_power, min_factor, max_factor=np.inf,
meg='mag'):
"""Assert a minimum shielding factor using empty-room power."""
__tracebackhide__ = True
picks = pick_types(raw_sss.info, meg=meg, ref_meg=False)
if isinstance(erm_power, BaseRaw):
picks_erm = pick_types(raw_sss.info, meg=meg, ref_meg=False)
assert_allclose(picks, picks_erm)
erm_power = np.sqrt((erm_power[picks_erm][0] ** 2).sum())
sss_power = raw_sss[picks][0].ravel()
sss_power = np.sqrt(np.sum(sss_power * sss_power))
factor = erm_power / sss_power
assert min_factor <= factor < max_factor, (
'Shielding factor not %0.3f <= %0.3f < %0.3f'
% (min_factor, factor, max_factor))
@buggy_mkl_svd
@testing.requires_testing_data
@pytest.mark.parametrize('regularize', ('in', None))
@pytest.mark.parametrize('bads', ([], ['MEG0111']))
def test_esss(regularize, bads):
"""Test extended-basis SSS."""
# Make some fake "projectors" that actually contain external SSS bases
raw_erm = read_crop(erm_fname).load_data().pick_types(meg=True)
raw_erm.info['bads'] = bads
proj_sss = mne.compute_proj_raw(raw_erm, meg='combined', verbose='error',
n_mag=15, n_grad=15)
good_info = pick_info(raw_erm.info, pick_types(raw_erm.info, meg=True))
S_tot = _trans_sss_basis(
dict(int_order=0, ext_order=3, origin=(0., 0., 0.)),
all_coils=_prep_mf_coils(good_info), coil_scale=1., trans=None)
assert S_tot.shape[-1] == len(proj_sss)
for a, b in zip(proj_sss, S_tot.T):
a['data']['data'][:] = b
with catch_logging() as log:
raw_sss = maxwell_filter(raw_erm, coord_frame='meg',
regularize=regularize, verbose=True)
log = log.getvalue()
assert 'xtend' not in log
with catch_logging() as log:
raw_sss_2 = maxwell_filter(raw_erm, coord_frame='meg',
regularize=regularize, ext_order=0,
extended_proj=proj_sss, verbose=True)
log = log.getvalue()
assert 'Extending external SSS basis using 15 projection' in log
assert_allclose(raw_sss_2._data, raw_sss._data, atol=1e-20)
# Degenerate condititons
proj_sss = proj_sss[:2]
proj_sss[0]['data']['col_names'] = proj_sss[0]['data']['col_names'][:-1]
with pytest.raises(ValueError, match='do not match the good MEG'):
maxwell_filter(raw_erm, coord_frame='meg', extended_proj=proj_sss)
proj_sss[0] = 1.
with pytest.raises(TypeError, match=r'extended_proj\[0\] must be an inst'):
maxwell_filter(raw_erm, coord_frame='meg', extended_proj=proj_sss)
with pytest.raises(TypeError, match='extended_proj must be an inst'):
maxwell_filter(raw_erm, coord_frame='meg', extended_proj=1.)
@contextmanager
def get_n_projected():
"""Get the number of projected tSSS components from the log."""
count = list()
with use_log_level(True):
with catch_logging() as log:
yield count
log = log.getvalue()
assert 'Processing data using tSSS' in log
log = log.splitlines()
reg = re.compile(r'\s+Projecting\s+([0-9])+\s+intersecting tSSS .*')
for line in log:
m = reg.match(line)
if m:
count.append(int(m.group(1)))
@buggy_mkl_svd
@pytest.mark.slowtest
@testing.requires_testing_data
def test_shielding_factor(tmpdir):
"""Test Maxwell filter shielding factor using empty room."""
raw_erm = read_crop(erm_fname).load_data().pick_types(meg=True)
erm_power = raw_erm[pick_types(raw_erm.info, meg='mag')][0]
erm_power = np.sqrt(np.sum(erm_power * erm_power))
erm_power_grad = raw_erm[pick_types(raw_erm.info, meg='grad')][0]
erm_power_grad = np.sqrt(np.sum(erm_power * erm_power))
# Vanilla SSS (second value would be for meg=True instead of meg='mag')
_assert_shielding(read_crop(sss_erm_std_fname), erm_power, 10) # 1.5)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None)
_assert_shielding(raw_sss, erm_power, 12, 13) # 1.5)
_assert_shielding(raw_sss, erm_power_grad, 0.45, 0.55, 'grad') # 1.5)
# No external basis
raw_sss_0 = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
ext_order=0)
_assert_shielding(raw_sss_0, erm_power, 1.0, 1.1)
del raw_sss_0
# Regularization
_assert_shielding(read_crop(sss_erm_std_fname), erm_power, 10) # 1.5)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg')
_assert_shielding(raw_sss, erm_power, 14.5, 15.5)
#
# Extended (eSSS)
#
# Show that using empty-room projectors increase shielding factor
proj = mne.compute_proj_raw(raw_erm, meg='combined', verbose='error',
n_mag=15, n_grad=15)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
extended_proj=proj[:3])
_assert_shielding(raw_sss, erm_power, 38, 39)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
extended_proj=proj)
_assert_shielding(raw_sss, erm_power, 49, 51)
# Now with reg
raw_sss = maxwell_filter(raw_erm, coord_frame='meg',
extended_proj=proj[:3])
_assert_shielding(raw_sss, erm_power, 42, 44)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg',
extended_proj=proj)
_assert_shielding(raw_sss, erm_power, 59, 61)
#
# Different mag_scale values
#
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
mag_scale='auto')
_assert_shielding(raw_sss, erm_power, 12, 13)
_assert_shielding(raw_sss, erm_power_grad, 0.48, 0.58, 'grad')
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
mag_scale=1.) # not a good choice
_assert_shielding(raw_sss, erm_power, 7.3, 8.)
_assert_shielding(raw_sss, erm_power_grad, 0.2, 0.3, 'grad')
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
mag_scale=1000., bad_condition='ignore')
_assert_shielding(raw_sss, erm_power, 4.0, 5.0)
_assert_shielding(raw_sss, erm_power_grad, 0.1, 0.2, 'grad')
#
# Fine cal
#
_assert_shielding(read_crop(sss_erm_fine_cal_fname), erm_power, 12) # 2.0)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
origin=mf_meg_origin,
calibration=pathlib.Path(fine_cal_fname))
_assert_shielding(raw_sss, erm_power, 12, 13) # 2.0)
#
# Crosstalk
#
_assert_shielding(read_crop(sss_erm_ctc_fname), erm_power, 12) # 2.1)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
origin=mf_meg_origin,
cross_talk=ctc_fname)
_assert_shielding(raw_sss, erm_power, 12, 13) # 2.1)
# Fine cal + Crosstalk
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
calibration=fine_cal_fname,
origin=mf_meg_origin,
cross_talk=ctc_fname)
_assert_shielding(raw_sss, erm_power, 13, 14) # 2.2)
# Fine cal + Crosstalk + Extended
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
calibration=fine_cal_fname,
origin=mf_meg_origin,
cross_talk=ctc_fname, extended_proj=proj)
_assert_shielding(raw_sss, erm_power, 28, 30)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
calibration=fine_cal_fname,
origin=mf_meg_origin,
cross_talk=ctc_fname, extended_proj=proj[:3])
_assert_shielding(raw_sss, erm_power, 25, 27)
# tSSS
_assert_shielding(read_crop(sss_erm_st_fname), erm_power, 37) # 5.8)
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
origin=mf_meg_origin, st_duration=1.)
_assert_shielding(raw_sss, erm_power, 37, 38) # 5.8)
# Crosstalk + tSSS
with get_n_projected() as counts:
raw_sss = maxwell_filter(raw_erm, coord_frame='meg', regularize=None,
cross_talk=ctc_fname, origin=mf_meg_origin,