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)
coils = _prep_meg_channels(info, accurate=True, elekta_defs=True)[0]
# Check against a known benchmark
sss_data = loadmat(bases_fname)
for origin in ((0, 0, 0.04), (0, 0.02, 0.02)):
o_str = ''.join('%d' % (1000 * n) for n in origin)
S_tot = _sss_basis_basic(origin,
coils,
int_order,
ext_order,
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(origin, coils, int_order, ext_order)
S_tot_fast = _sss_basis(origin, coils, int_order, ext_order)
S_tot_fast *= _get_coil_scale(coils)
# 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)
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)
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)
coils = _prep_meg_channels(info, accurate=True, elekta_defs=True,
verbose=False)[0]
# Check against a known benchmark
sss_data = loadmat(bases_fname)
for origin in ((0, 0, 0.04), (0, 0.02, 0.02)):
o_str = ''.join('%d' % (1000 * n) for n in origin)
S_tot = _sss_basis(origin, coils, int_order, ext_order,
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)
mu0 = 4e-7 * np.pi # Permeability of vacuum
S_tot_mat /= mu0 # divide out the magnetic permeability
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)