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Samu validation
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| from __future__ import print_function | |
| import sys | |
| from os import path as op | |
| import numpy as np | |
| from scipy.io import loadmat | |
| from mne.io import read_info | |
| from mne import pick_types, pick_info | |
| from mne.preprocessing.maxwell import (_concatenate_sph_coils, _sh_negate, | |
| _bases_real_to_complex, _deg_order_idx, | |
| _sph_to_cart_partials, _sph_harm_norm, | |
| _sph_harm, _alegendre_deriv, | |
| _cart_to_sph, _sss_basis) | |
| from mne.datasets import testing | |
| from mne.forward._make_forward import _prep_meg_channels | |
| ############################################################################### | |
| # Validate Sin | |
| mu0 = 1.25664e-6 # Permeability of vacuum | |
| def Sin_vsh_enm(info, origin, magscale, Lin): | |
| coils = _prep_meg_channels(info, True, [], True, True, True, False)[0] | |
| Sin = np.empty((len(info['chs']), Lin * (Lin + 2)), np.complex128) | |
| rs, ws, ezs, bins = _concatenate_sph_coils(coils) | |
| rs -= origin | |
| rad, az, pol = _cart_to_sph(rs).T | |
| for degree in range(1, Lin + 1): | |
| for order in range(degree + 1): | |
| sph_norm = _sph_harm_norm(order, degree) | |
| sph = _sph_harm(order, degree, az, pol, norm=False) | |
| sph *= sph_norm | |
| az_factor = 1j * order * sph / np.sin(np.maximum(pol, 1e-16)) | |
| pol_factor = (-sph_norm * np.sin(pol) * np.exp(1j * order * az) * | |
| _alegendre_deriv(order, degree, np.cos(pol))) | |
| in_norm = rad ** -(degree + 2) | |
| g_rad = in_norm * -(degree + 1) * sph | |
| g_az = in_norm * az_factor | |
| g_pol = in_norm * pol_factor | |
| V = _sph_to_cart_partials(az, pol, g_rad, g_az, g_pol) | |
| V = np.einsum('ij,ij,i->i', V, ezs, ws) | |
| x = (np.bincount(bins, V.real, minlength=len(coils)) + | |
| 1j * np.bincount(bins, V.imag, minlength=len(coils))) | |
| Sin[:, _deg_order_idx(degree, order)] = -mu0 * x | |
| if order > 0: | |
| Sin[:, _deg_order_idx(degree, -order)] = \ | |
| -mu0 * _sh_negate(x, order) | |
| Sin[pick_types(info, meg='mag')] *= magscale | |
| SNin = Sin / np.linalg.norm(Sin, axis=0)[np.newaxis, :] | |
| return Sin, SNin | |
| data_path = testing.data_path() | |
| fname_mat = op.join(data_path, 'SSS', 'sss_data.mat') | |
| fname_raw = op.join(data_path, 'SSS', 'test_move_anon_raw.fif') | |
| data = loadmat(fname_mat) | |
| origin = np.array([0., 0., 0.04]) | |
| info = read_info(fname_raw) | |
| info_meg = pick_info(info, pick_types(info, meg=True, exclude=[])) | |
| print('Validating bases (S_in)...', end='') | |
| sys.stdout.flush() | |
| Sin_mat, SNin_mat = data['Sin0040'], data['SNin0040'] | |
| Sin, SNin = Sin_vsh_enm(info_meg, origin, 100., 8) | |
| np.testing.assert_allclose(Sin, Sin_mat, rtol=1e-6, atol=1e-9) | |
| np.testing.assert_allclose(SNin, SNin_mat, rtol=1e-6, atol=1e-9) | |
| print(' [Done]') | |
| sys.stdout.flush() | |
| print('Validating mne bases (S_in)...', end='') | |
| coils = _prep_meg_channels(info_meg, accurate=True, elekta_defs=True, | |
| head_frame=True, verbose=False)[0] | |
| Sin, SNin = Sin_vsh_enm(info_meg, origin, 100., 8) | |
| Sin_py = _bases_real_to_complex(_sss_basis(origin, coils, 8, 0, 100., | |
| method='alternative'), 8, 0) | |
| Sin_py *= mu0 | |
| np.testing.assert_allclose(Sin, Sin_py, rtol=1e-6, atol=1e-9) | |
| print(' [Done]') | |
| sys.stdout.flush() |
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