def test_simulate_stc_labels_overlap():
"""Test generation of source estimate, overlapping labels."""
fwd = read_forward_solution_meg(fname_fwd, force_fixed=True, use_cps=True)
labels = [read_label(op.join(data_path, 'MEG', 'sample', 'labels',
'%s.label' % label)) for label in label_names]
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
# Adding the last label twice
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(mylabels), n_times))
# Test false
with pytest.raises(RuntimeError, match='must be non-overlapping'):
simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep,
allow_overlap=False)
# test True
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep,
allow_overlap=True)
assert_equal(stc.subject, 'sample')
assert (stc.data.shape[1] == n_times)
# Some of the elements should be equal to 2 since we have duplicate labels
assert (2 in stc.data)
def test_simulate_stc_labels_overlap(_get_fwd_labels):
"""Test generation of source estimate, overlapping labels."""
fwd, labels = _get_fwd_labels
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
# Adding the last label twice
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(mylabels), n_times))
# Test false
with pytest.raises(RuntimeError, match='must be non-overlapping'):
simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep,
allow_overlap=False)
# test True
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep,
allow_overlap=True)
assert_equal(stc.subject, 'sample')
assert (stc.data.shape[1] == n_times)
# Some of the elements should be equal to 2 since we have duplicate labels
assert (2 in stc.data)
def test_simulate_stc_labels_overlap(_get_fwd_labels):
"""Test generation of source estimate, overlapping labels."""
fwd, labels = _get_fwd_labels
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
# Adding the last label twice
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(mylabels), n_times))
# Test false
with pytest.raises(RuntimeError, match='must be non-overlapping'):
simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep,
allow_overlap=False)
# test True
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep,
allow_overlap=True)
assert_equal(stc.subject, 'sample')
assert (stc.data.shape[1] == n_times)
# Some of the elements should be equal to 2 since we have duplicate labels
assert (2 in stc.data)
def test_simulate_stc():
""" Test generation of source estimate """
fwd = read_forward_solution_meg(fname_fwd, force_fixed=True)
labels = [read_label(op.join(data_path, "MEG", "sample", "labels", "%s.label" % label)) for label in label_names]
mylabels = []
for i, label in enumerate(labels):
new_label = Label(
vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment,
)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels), n_times))
stc = simulate_stc(fwd["src"], mylabels, stc_data, tmin, tstep)
for label in labels:
if label.hemi == "lh":
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
assert_true(np.all(stc.data[idx] == 1.0))
assert_true(stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd["src"], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels):
if label.hemi == "lh":
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2.0 * i) ** 2.0) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
def test_generate_stc_single_hemi():
"""Test generation of source estimate, single hemi."""
fwd = read_forward_solution_meg(fname_fwd, force_fixed=True, use_cps=True)
labels_single_hemi = [read_label(op.join(data_path, 'MEG', 'sample',
'labels', '%s.label' % label))
for label in label_names_single_hemi]
mylabels = []
for i, label in enumerate(labels_single_hemi):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels_single_hemi), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
for label in labels_single_hemi:
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels_single_hemi):
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2. * i) ** 2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
def test_generate_stc_single_hemi():
"""Test generation of source estimate, single hemi."""
fwd = read_forward_solution_meg(fname_fwd, force_fixed=True, use_cps=True)
labels_single_hemi = [read_label(op.join(data_path, 'MEG', 'sample',
'labels', '%s.label' % label))
for label in label_names_single_hemi]
mylabels = []
for i, label in enumerate(labels_single_hemi):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels_single_hemi), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
for label in labels_single_hemi:
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels_single_hemi):
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2. * i) ** 2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
def test_simulate_stc(_get_fwd_labels):
"""Test generation of source estimate."""
fwd, labels = _get_fwd_labels
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
assert_equal(stc.subject, 'sample')
for label in labels:
idx = _get_idx_label_stc(label, stc)
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x**2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels):
idx = _get_idx_label_stc(label, stc)
res = ((2. * i)**2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
# degenerate conditions
label_subset = mylabels[:2]
data_subset = stc_data[:2]
stc = simulate_stc(fwd['src'], label_subset, data_subset, tmin, tstep, fun)
pytest.raises(ValueError, simulate_stc, fwd['src'], label_subset,
data_subset[:-1], tmin, tstep, fun)
pytest.raises(RuntimeError, simulate_stc, fwd['src'], label_subset * 2,
np.concatenate([data_subset] * 2, axis=0), tmin, tstep, fun)
i = np.where(fwd['src'][0]['inuse'] == 0)[0][0]
label_single_vert = Label(vertices=[i],
pos=fwd['src'][0]['rr'][i:i + 1, :],
hemi='lh')
stc = simulate_stc(fwd['src'], [label_single_vert], stc_data[:1], tmin,
tstep)
assert_equal(len(stc.lh_vertno), 1)
def test_generate_stc_single_hemi(_get_fwd_labels):
"""Test generation of source estimate, single hemi."""
fwd, labels = _get_fwd_labels
labels_single_hemi = labels[1:] # keep only labels in one hemisphere
mylabels = []
for i, label in enumerate(labels_single_hemi):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels_single_hemi), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
for label in labels_single_hemi:
idx = _get_idx_label_stc(label, stc)
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x**2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels_single_hemi):
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2. * i)**2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
def test_simulate_stc(_get_fwd_labels):
"""Test generation of source estimate."""
fwd, labels = _get_fwd_labels
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
assert_equal(stc.subject, 'sample')
for label in labels:
idx = _get_idx_label_stc(label, stc)
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels):
idx = _get_idx_label_stc(label, stc)
res = ((2. * i) ** 2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
# degenerate conditions
label_subset = mylabels[:2]
data_subset = stc_data[:2]
stc = simulate_stc(fwd['src'], label_subset, data_subset, tmin, tstep, fun)
pytest.raises(ValueError, simulate_stc, fwd['src'],
label_subset, data_subset[:-1], tmin, tstep, fun)
pytest.raises(RuntimeError, simulate_stc, fwd['src'], label_subset * 2,
np.concatenate([data_subset] * 2, axis=0), tmin, tstep, fun)
def test_generate_stc_single_hemi(_get_fwd_labels):
"""Test generation of source estimate, single hemi."""
fwd, labels = _get_fwd_labels
labels_single_hemi = labels[1:] # keep only labels in one hemisphere
mylabels = []
for i, label in enumerate(labels_single_hemi):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels_single_hemi), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
for label in labels_single_hemi:
idx = _get_idx_label_stc(label, stc)
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels_single_hemi):
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2. * i) ** 2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
def test_simulate_stc():
"""Test generation of source estimate."""
fwd = read_forward_solution_meg(fname_fwd, force_fixed=True, use_cps=True)
labels = [read_label(op.join(data_path, 'MEG', 'sample', 'labels',
'%s.label' % label)) for label in label_names]
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
assert_equal(stc.subject, 'sample')
for label in labels:
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels):
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2. * i) ** 2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
# degenerate conditions
label_subset = mylabels[:2]
data_subset = stc_data[:2]
stc = simulate_stc(fwd['src'], label_subset, data_subset, tmin, tstep, fun)
pytest.raises(ValueError, simulate_stc, fwd['src'],
label_subset, data_subset[:-1], tmin, tstep, fun)
pytest.raises(RuntimeError, simulate_stc, fwd['src'], label_subset * 2,
np.concatenate([data_subset] * 2, axis=0), tmin, tstep, fun)
def test_simulate_stc():
"""Test generation of source estimate."""
fwd = read_forward_solution_meg(fname_fwd, force_fixed=True, use_cps=True)
labels = [read_label(op.join(data_path, 'MEG', 'sample', 'labels',
'%s.label' % label)) for label in label_names]
mylabels = []
for i, label in enumerate(labels):
new_label = Label(vertices=label.vertices,
pos=label.pos,
values=2 * i * np.ones(len(label.values)),
hemi=label.hemi,
comment=label.comment)
mylabels.append(new_label)
n_times = 10
tmin = 0
tstep = 1e-3
stc_data = np.ones((len(labels), n_times))
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep)
assert_equal(stc.subject, 'sample')
for label in labels:
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
assert (np.all(stc.data[idx] == 1.0))
assert (stc.data[idx].shape[1] == n_times)
# test with function
def fun(x):
return x ** 2
stc = simulate_stc(fwd['src'], mylabels, stc_data, tmin, tstep, fun)
# the first label has value 0, the second value 2, the third value 6
for i, label in enumerate(labels):
if label.hemi == 'lh':
hemi_idx = 0
else:
hemi_idx = 1
idx = np.intersect1d(stc.vertices[hemi_idx], label.vertices)
idx = np.searchsorted(stc.vertices[hemi_idx], idx)
if hemi_idx == 1:
idx += len(stc.vertices[0])
res = ((2. * i) ** 2.) * np.ones((len(idx), n_times))
assert_array_almost_equal(stc.data[idx], res)
# degenerate conditions
label_subset = mylabels[:2]
data_subset = stc_data[:2]
stc = simulate_stc(fwd['src'], label_subset, data_subset, tmin, tstep, fun)
pytest.raises(ValueError, simulate_stc, fwd['src'],
label_subset, data_subset[:-1], tmin, tstep, fun)
pytest.raises(RuntimeError, simulate_stc, fwd['src'], label_subset * 2,
np.concatenate([data_subset] * 2, axis=0), tmin, tstep, fun)
