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import os
import os.path as op
import warnings
from nose.tools import assert_true, assert_raises
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_equal,
assert_array_equal, assert_allclose)
from mne.datasets import sample
from mne.io import Raw
from mne import (read_forward_solution, apply_forward, apply_forward_raw,
average_forward_solutions, write_forward_solution,
convert_forward_solution)
from mne import SourceEstimate, pick_types_forward, read_evokeds
from mne.label import read_label
from mne.utils import requires_mne, run_subprocess, _TempDir
from mne.forward import (restrict_forward_to_stc, restrict_forward_to_label,
Forward)
data_path = sample.data_path(download=False)
fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis-meg-oct-6-fwd.fif')
fname_meeg = op.join(data_path, 'MEG', 'sample',
'sample_audvis-meg-eeg-oct-6-fwd.fif')
fname_raw = op.join(op.dirname(__file__), '..', '..', 'io', 'tests', 'data',
'test_raw.fif')
fname_evoked = op.join(op.dirname(__file__), '..', '..', 'io', 'tests',
'data', 'test-ave.fif')
fname_mri = op.join(data_path, 'MEG', 'sample', 'sample_audvis_raw-trans.fif')
subjects_dir = os.path.join(data_path, 'subjects')
fname_src = op.join(subjects_dir, 'sample', 'bem', 'sample-oct-6-src.fif')
temp_dir = _TempDir()
# make a file that exists with some data in it
existing_file = op.join(temp_dir, 'test.fif')
with open(existing_file, 'w') as fid:
fid.write('aoeu')
def compare_forwards(f1, f2):
"""Helper to compare two potentially converted forward solutions"""
assert_allclose(f1['sol']['data'], f2['sol']['data'])
assert_equal(f1['sol']['ncol'], f2['sol']['ncol'])
assert_allclose(f1['source_nn'], f2['source_nn'])
if f1['sol_grad'] is not None:
assert_allclose(f1['sol_grad']['data'], f2['sol_grad']['data'])
assert_equal(f1['sol_grad']['ncol'], f2['sol_grad']['ncol'])
else:
assert_equal(f2['sol_grad'], None)
assert_equal(f1['source_ori'], f2['source_ori'])
assert_equal(f1['surf_ori'], f2['surf_ori'])
@sample.requires_sample_data
def test_convert_forward():
"""Test converting forward solution between different representations
"""
fwd = read_forward_solution(fname_meeg)
print(fwd) # __repr__
assert_true(isinstance(fwd, Forward))
# look at surface orientation
fwd_surf = convert_forward_solution(fwd, surf_ori=True)
fwd_surf_io = read_forward_solution(fname_meeg, surf_ori=True)
compare_forwards(fwd_surf, fwd_surf_io)
# go back
fwd_new = convert_forward_solution(fwd_surf, surf_ori=False)
print(fwd_new)
assert_true(isinstance(fwd, Forward))
compare_forwards(fwd, fwd_new)
# now go to fixed
fwd_fixed = convert_forward_solution(fwd_surf, surf_ori=False,
force_fixed=True)
print(fwd_fixed)
assert_true(isinstance(fwd_fixed, Forward))
fwd_fixed_io = read_forward_solution(fname_meeg, surf_ori=False,
force_fixed=True)
compare_forwards(fwd_fixed, fwd_fixed_io)
# now go back to cartesian (original condition)
fwd_new = convert_forward_solution(fwd_fixed)
print(fwd_new)
assert_true(isinstance(fwd_new, Forward))
compare_forwards(fwd, fwd_new)
@sample.requires_sample_data
def test_io_forward():
"""Test IO for forward solutions
"""
# test M/EEG
fwd_meeg = read_forward_solution(fname_meeg)
assert_true(isinstance(fwd_meeg, Forward))
leadfield = fwd_meeg['sol']['data']
assert_equal(leadfield.shape, (366, 22494))
assert_equal(len(fwd_meeg['sol']['row_names']), 366)
fname_temp = op.join(temp_dir, 'test-fwd.fif')
write_forward_solution(fname_temp, fwd_meeg, overwrite=True)
fwd_meeg = read_forward_solution(fname_temp)
assert_allclose(leadfield, fwd_meeg['sol']['data'])
assert_equal(len(fwd_meeg['sol']['row_names']), 366)
# now do extensive tests with MEG
fwd = read_forward_solution(fname)
fwd = read_forward_solution(fname, surf_ori=True)
leadfield = fwd['sol']['data']
assert_equal(leadfield.shape, (306, 22494))
assert_equal(len(fwd['sol']['row_names']), 306)
fname_temp = op.join(temp_dir, 'test-fwd.fif')
write_forward_solution(fname_temp, fwd, overwrite=True)
fwd = read_forward_solution(fname, surf_ori=True)
fwd_read = read_forward_solution(fname_temp, surf_ori=True)
leadfield = fwd_read['sol']['data']
assert_equal(leadfield.shape, (306, 22494))
assert_equal(len(fwd_read['sol']['row_names']), 306)
assert_equal(len(fwd_read['info']['chs']), 306)
assert_true('dev_head_t' in fwd_read['info'])
assert_true('mri_head_t' in fwd_read)
assert_array_almost_equal(fwd['sol']['data'], fwd_read['sol']['data'])
fwd = read_forward_solution(fname, force_fixed=True)
leadfield = fwd['sol']['data']
assert_equal(leadfield.shape, (306, 22494 / 3))
assert_equal(len(fwd['sol']['row_names']), 306)
assert_equal(len(fwd['info']['chs']), 306)
assert_true('dev_head_t' in fwd['info'])
assert_true('mri_head_t' in fwd)
assert_true(fwd['surf_ori'])
# test warnings on bad filenames
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
fwd_badname = op.join(temp_dir, 'test-bad-name.fif.gz')
write_forward_solution(fwd_badname, fwd_meeg)
read_forward_solution(fwd_badname)
assert_true(len(w) == 2)
@sample.requires_sample_data
def test_apply_forward():
"""Test projection of source space data to sensor space
"""
start = 0
stop = 5
n_times = stop - start - 1
sfreq = 10.0
t_start = 0.123
fwd = read_forward_solution(fname, force_fixed=True)
fwd = pick_types_forward(fwd, meg=True)
assert_true(isinstance(fwd, Forward))
vertno = [fwd['src'][0]['vertno'], fwd['src'][1]['vertno']]
stc_data = np.ones((len(vertno[0]) + len(vertno[1]), n_times))
stc = SourceEstimate(stc_data, vertno, tmin=t_start, tstep=1.0 / sfreq)
gain_sum = np.sum(fwd['sol']['data'], axis=1)
# Evoked
with warnings.catch_warnings(record=True) as w:
evoked = read_evokeds(fname_evoked, condition=0)
evoked = apply_forward(fwd, stc, evoked, start=start, stop=stop)
assert_equal(len(w), 2)
data = evoked.data
times = evoked.times
# do some tests
assert_array_almost_equal(evoked.info['sfreq'], sfreq)
assert_array_almost_equal(np.sum(data, axis=1), n_times * gain_sum)
assert_array_almost_equal(times[0], t_start)
assert_array_almost_equal(times[-1], t_start + (n_times - 1) / sfreq)
# Raw
raw = Raw(fname_raw)
raw_proj = apply_forward_raw(fwd, stc, raw, start=start, stop=stop)
data, times = raw_proj[:, :]
# do some tests
assert_array_almost_equal(raw_proj.info['sfreq'], sfreq)
assert_array_almost_equal(np.sum(data, axis=1), n_times * gain_sum)
assert_array_almost_equal(times[0], t_start)
assert_array_almost_equal(times[-1], t_start + (n_times - 1) / sfreq)
@sample.requires_sample_data
def test_restrict_forward_to_stc():
"""Test restriction of source space to source SourceEstimate
"""
start = 0
stop = 5
n_times = stop - start - 1
sfreq = 10.0
t_start = 0.123
fwd = read_forward_solution(fname, force_fixed=True)
fwd = pick_types_forward(fwd, meg=True)
vertno = [fwd['src'][0]['vertno'][0:15], fwd['src'][1]['vertno'][0:5]]
stc_data = np.ones((len(vertno[0]) + len(vertno[1]), n_times))
stc = SourceEstimate(stc_data, vertno, tmin=t_start, tstep=1.0 / sfreq)
fwd_out = restrict_forward_to_stc(fwd, stc)
assert_true(isinstance(fwd_out, Forward))
assert_equal(fwd_out['sol']['ncol'], 20)
assert_equal(fwd_out['src'][0]['nuse'], 15)
assert_equal(fwd_out['src'][1]['nuse'], 5)
assert_equal(fwd_out['src'][0]['vertno'], fwd['src'][0]['vertno'][0:15])
assert_equal(fwd_out['src'][1]['vertno'], fwd['src'][1]['vertno'][0:5])
fwd = read_forward_solution(fname, force_fixed=False)
fwd = pick_types_forward(fwd, meg=True)
vertno = [fwd['src'][0]['vertno'][0:15], fwd['src'][1]['vertno'][0:5]]
stc_data = np.ones((len(vertno[0]) + len(vertno[1]), n_times))
stc = SourceEstimate(stc_data, vertno, tmin=t_start, tstep=1.0 / sfreq)
fwd_out = restrict_forward_to_stc(fwd, stc)
assert_equal(fwd_out['sol']['ncol'], 60)
assert_equal(fwd_out['src'][0]['nuse'], 15)
assert_equal(fwd_out['src'][1]['nuse'], 5)
assert_equal(fwd_out['src'][0]['vertno'], fwd['src'][0]['vertno'][0:15])
assert_equal(fwd_out['src'][1]['vertno'], fwd['src'][1]['vertno'][0:5])
@sample.requires_sample_data
def test_restrict_forward_to_label():
"""Test restriction of source space to label
"""
fwd = read_forward_solution(fname, force_fixed=True)
fwd = pick_types_forward(fwd, meg=True)
label_path = op.join(data_path, 'MEG', 'sample', 'labels')
labels = ['Aud-lh', 'Vis-rh']
label_lh = read_label(op.join(label_path, labels[0] + '.label'))
label_rh = read_label(op.join(label_path, labels[1] + '.label'))
fwd_out = restrict_forward_to_label(fwd, [label_lh, label_rh])
src_sel_lh = np.intersect1d(fwd['src'][0]['vertno'], label_lh.vertices)
src_sel_lh = np.searchsorted(fwd['src'][0]['vertno'], src_sel_lh)
src_sel_rh = np.intersect1d(fwd['src'][1]['vertno'], label_rh.vertices)
src_sel_rh = (np.searchsorted(fwd['src'][1]['vertno'], src_sel_rh)
+ len(fwd['src'][0]['vertno']))
assert_equal(fwd_out['sol']['ncol'], len(src_sel_lh) + len(src_sel_rh))
assert_equal(fwd_out['src'][0]['nuse'], len(src_sel_lh))
assert_equal(fwd_out['src'][1]['nuse'], len(src_sel_rh))
assert_equal(fwd_out['src'][0]['vertno'], src_sel_lh)
assert_equal(fwd_out['src'][1]['vertno'], src_sel_rh)
fwd = read_forward_solution(fname, force_fixed=False)
fwd = pick_types_forward(fwd, meg=True)
label_path = op.join(data_path, 'MEG', 'sample', 'labels')
labels = ['Aud-lh', 'Vis-rh']
label_lh = read_label(op.join(label_path, labels[0] + '.label'))
label_rh = read_label(op.join(label_path, labels[1] + '.label'))
fwd_out = restrict_forward_to_label(fwd, [label_lh, label_rh])
src_sel_lh = np.intersect1d(fwd['src'][0]['vertno'], label_lh.vertices)
src_sel_lh = np.searchsorted(fwd['src'][0]['vertno'], src_sel_lh)
src_sel_rh = np.intersect1d(fwd['src'][1]['vertno'], label_rh.vertices)
src_sel_rh = (np.searchsorted(fwd['src'][1]['vertno'], src_sel_rh)
+ len(fwd['src'][0]['vertno']))
assert_equal(fwd_out['sol']['ncol'],
3 * (len(src_sel_lh) + len(src_sel_rh)))
assert_equal(fwd_out['src'][0]['nuse'], len(src_sel_lh))
assert_equal(fwd_out['src'][1]['nuse'], len(src_sel_rh))
assert_equal(fwd_out['src'][0]['vertno'], src_sel_lh)
assert_equal(fwd_out['src'][1]['vertno'], src_sel_rh)
@sample.requires_sample_data
@requires_mne
def test_average_forward_solution():
"""Test averaging forward solutions
"""
fwd = read_forward_solution(fname)
# input not a list
assert_raises(TypeError, average_forward_solutions, 1)
# list is too short
assert_raises(ValueError, average_forward_solutions, [])
# negative weights
assert_raises(ValueError, average_forward_solutions, [fwd, fwd], [-1, 0])
# all zero weights
assert_raises(ValueError, average_forward_solutions, [fwd, fwd], [0, 0])
# weights not same length
assert_raises(ValueError, average_forward_solutions, [fwd, fwd], [0, 0, 0])
# list does not only have all dict()
assert_raises(TypeError, average_forward_solutions, [1, fwd])
# try an easy case
fwd_copy = average_forward_solutions([fwd])
assert_true(isinstance(fwd_copy, Forward))
assert_array_equal(fwd['sol']['data'], fwd_copy['sol']['data'])
# modify a fwd solution, save it, use MNE to average with old one
fwd_copy['sol']['data'] *= 0.5
fname_copy = op.join(temp_dir, 'copy-fwd.fif')
write_forward_solution(fname_copy, fwd_copy, overwrite=True)
cmd = ('mne_average_forward_solutions', '--fwd', fname, '--fwd',
fname_copy, '--out', fname_copy)
run_subprocess(cmd)
# now let's actually do it, with one filename and one fwd
fwd_ave = average_forward_solutions([fwd, fwd_copy])
assert_array_equal(0.75 * fwd['sol']['data'], fwd_ave['sol']['data'])
# fwd_ave_mne = read_forward_solution(fname_copy)
# assert_array_equal(fwd_ave_mne['sol']['data'], fwd_ave['sol']['data'])
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