def test_compute_proj_epochs():
"""Test SSP computation on epochs"""
event_id, tmin, tmax = 1, -0.2, 0.3
raw = Raw(raw_fname, preload=True)
events = read_events(event_fname)
bad_ch = 'MEG 2443'
picks = pick_types(raw.info, meg=True, eeg=False, stim=False, eog=False,
exclude=[])
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
baseline=None, proj=False)
evoked = epochs.average()
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1)
write_proj(op.join(tempdir, 'proj.fif.gz'), projs)
for p_fname in [proj_fname, proj_gz_fname,
op.join(tempdir, 'proj.fif.gz')]:
projs2 = read_proj(p_fname)
assert_true(len(projs) == len(projs2))
for p1, p2 in zip(projs, projs2):
assert_true(p1['desc'] == p2['desc'])
assert_true(p1['data']['col_names'] == p2['data']['col_names'])
assert_true(p1['active'] == p2['active'])
# compare with sign invariance
p1_data = p1['data']['data'] * np.sign(p1['data']['data'][0, 0])
p2_data = p2['data']['data'] * np.sign(p2['data']['data'][0, 0])
if bad_ch in p1['data']['col_names']:
bad = p1['data']['col_names'].index('MEG 2443')
mask = np.ones(p1_data.size, dtype=np.bool)
mask[bad] = False
p1_data = p1_data[:, mask]
p2_data = p2_data[:, mask]
corr = np.corrcoef(p1_data, p2_data)[0, 1]
assert_array_almost_equal(corr, 1.0, 5)
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert_true(nproj == 2)
assert_true(U.shape[1] == 2)
# test that you can save them
epochs.info['projs'] += projs
evoked = epochs.average()
evoked.save(op.join(tempdir, 'foo.fif'))
projs = read_proj(proj_fname)
projs_evoked = compute_proj_evoked(evoked, n_grad=1, n_mag=1, n_eeg=0)
assert_true(len(projs_evoked) == 2)
# XXX : test something
# test parallelization
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=2)
projs = activate_proj(projs)
proj_par, _, _ = make_projector(projs, epochs.ch_names, bads=[])
assert_allclose(proj, proj_par, rtol=1e-8, atol=1e-16)
def test_compute_proj_epochs(tmp_path):
"""Test SSP computation on epochs."""
tempdir = str(tmp_path)
event_id, tmin, tmax = 1, -0.2, 0.3
raw = read_raw_fif(raw_fname, preload=True)
events = read_events(event_fname)
bad_ch = 'MEG 2443'
picks = pick_types(raw.info,
meg=True,
eeg=False,
stim=False,
eog=False,
exclude=[])
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
baseline=None,
proj=False)
evoked = epochs.average()
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1)
write_proj(op.join(tempdir, 'test-proj.fif.gz'), projs)
for p_fname in [
proj_fname, proj_gz_fname,
op.join(tempdir, 'test-proj.fif.gz')
]:
projs2 = read_proj(p_fname)
assert len(projs) == len(projs2)
for p1, p2 in zip(projs, projs2):
assert p1['desc'] == p2['desc']
assert p1['data']['col_names'] == p2['data']['col_names']
assert p1['active'] == p2['active']
# compare with sign invariance
p1_data = p1['data']['data'] * np.sign(p1['data']['data'][0, 0])
p2_data = p2['data']['data'] * np.sign(p2['data']['data'][0, 0])
if bad_ch in p1['data']['col_names']:
bad = p1['data']['col_names'].index('MEG 2443')
mask = np.ones(p1_data.size, dtype=bool)
mask[bad] = False
p1_data = p1_data[:, mask]
p2_data = p2_data[:, mask]
corr = np.corrcoef(p1_data, p2_data)[0, 1]
assert_array_almost_equal(corr, 1.0, 5)
if p2['explained_var']:
assert_array_almost_equal(p1['explained_var'],
p2['explained_var'])
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert nproj == 2
assert U.shape[1] == 2
# test that you can save them
with epochs.info._unlock():
epochs.info['projs'] += projs
evoked = epochs.average()
evoked.save(op.join(tempdir, 'foo-ave.fif'))
projs = read_proj(proj_fname)
projs_evoked = compute_proj_evoked(evoked, n_grad=1, n_mag=1, n_eeg=0)
assert len(projs_evoked) == 2
# XXX : test something
# test parallelization
projs = compute_proj_epochs(epochs,
n_grad=1,
n_mag=1,
n_eeg=0,
n_jobs=1,
desc_prefix='foobar')
assert all('foobar' in x['desc'] for x in projs)
projs = activate_proj(projs)
proj_par, _, _ = make_projector(projs, epochs.ch_names, bads=[])
assert_allclose(proj, proj_par, rtol=1e-8, atol=1e-16)
# test warnings on bad filenames
proj_badname = op.join(tempdir, 'test-bad-name.fif.gz')
with pytest.warns(RuntimeWarning, match='-proj.fif'):
write_proj(proj_badname, projs)
with pytest.warns(RuntimeWarning, match='-proj.fif'):
read_proj(proj_badname)
# bad inputs
fname = op.join(tempdir, 'out-proj.fif')
with pytest.raises(TypeError, match='projs'):
write_proj(fname, 'foo')
with pytest.raises(TypeError, match=r'projs\[0\] must be .*'):
write_proj(fname, ['foo'])
def test_compute_proj_epochs():
"""Test SSP computation on epochs."""
tempdir = _TempDir()
event_id, tmin, tmax = 1, -0.2, 0.3
raw = read_raw_fif(raw_fname, preload=True)
events = read_events(event_fname)
bad_ch = "MEG 2443"
picks = pick_types(raw.info, meg=True, eeg=False, stim=False, eog=False, exclude=[])
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks, baseline=None, proj=False)
evoked = epochs.average()
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1)
write_proj(op.join(tempdir, "test-proj.fif.gz"), projs)
for p_fname in [proj_fname, proj_gz_fname, op.join(tempdir, "test-proj.fif.gz")]:
projs2 = read_proj(p_fname)
assert_true(len(projs) == len(projs2))
for p1, p2 in zip(projs, projs2):
assert_true(p1["desc"] == p2["desc"])
assert_true(p1["data"]["col_names"] == p2["data"]["col_names"])
assert_true(p1["active"] == p2["active"])
# compare with sign invariance
p1_data = p1["data"]["data"] * np.sign(p1["data"]["data"][0, 0])
p2_data = p2["data"]["data"] * np.sign(p2["data"]["data"][0, 0])
if bad_ch in p1["data"]["col_names"]:
bad = p1["data"]["col_names"].index("MEG 2443")
mask = np.ones(p1_data.size, dtype=np.bool)
mask[bad] = False
p1_data = p1_data[:, mask]
p2_data = p2_data[:, mask]
corr = np.corrcoef(p1_data, p2_data)[0, 1]
assert_array_almost_equal(corr, 1.0, 5)
if p2["explained_var"]:
assert_array_almost_equal(p1["explained_var"], p2["explained_var"])
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert_true(nproj == 2)
assert_true(U.shape[1] == 2)
# test that you can save them
epochs.info["projs"] += projs
evoked = epochs.average()
evoked.save(op.join(tempdir, "foo-ave.fif"))
projs = read_proj(proj_fname)
projs_evoked = compute_proj_evoked(evoked, n_grad=1, n_mag=1, n_eeg=0)
assert_true(len(projs_evoked) == 2)
# XXX : test something
# test parallelization
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=2, desc_prefix="foobar")
assert_true(all("foobar" in x["desc"] for x in projs))
projs = activate_proj(projs)
proj_par, _, _ = make_projector(projs, epochs.ch_names, bads=[])
assert_allclose(proj, proj_par, rtol=1e-8, atol=1e-16)
# test warnings on bad filenames
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
proj_badname = op.join(tempdir, "test-bad-name.fif.gz")
write_proj(proj_badname, projs)
read_proj(proj_badname)
assert_naming(w, "test_proj.py", 2)
def test_compute_proj_epochs():
"""Test SSP computation on epochs"""
tempdir = _TempDir()
event_id, tmin, tmax = 1, -0.2, 0.3
raw = Raw(raw_fname, preload=True)
events = read_events(event_fname)
bad_ch = 'MEG 2443'
picks = pick_types(raw.info,
meg=True,
eeg=False,
stim=False,
eog=False,
exclude=[])
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
baseline=None,
proj=False)
evoked = epochs.average()
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1)
write_proj(op.join(tempdir, 'test-proj.fif.gz'), projs)
for p_fname in [
proj_fname, proj_gz_fname,
op.join(tempdir, 'test-proj.fif.gz')
]:
projs2 = read_proj(p_fname)
assert_true(len(projs) == len(projs2))
for p1, p2 in zip(projs, projs2):
assert_true(p1['desc'] == p2['desc'])
assert_true(p1['data']['col_names'] == p2['data']['col_names'])
assert_true(p1['active'] == p2['active'])
# compare with sign invariance
p1_data = p1['data']['data'] * np.sign(p1['data']['data'][0, 0])
p2_data = p2['data']['data'] * np.sign(p2['data']['data'][0, 0])
if bad_ch in p1['data']['col_names']:
bad = p1['data']['col_names'].index('MEG 2443')
mask = np.ones(p1_data.size, dtype=np.bool)
mask[bad] = False
p1_data = p1_data[:, mask]
p2_data = p2_data[:, mask]
corr = np.corrcoef(p1_data, p2_data)[0, 1]
assert_array_almost_equal(corr, 1.0, 5)
if p2['explained_var']:
assert_array_almost_equal(p1['explained_var'],
p2['explained_var'])
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert_true(nproj == 2)
assert_true(U.shape[1] == 2)
# test that you can save them
epochs.info['projs'] += projs
evoked = epochs.average()
evoked.save(op.join(tempdir, 'foo-ave.fif'))
projs = read_proj(proj_fname)
projs_evoked = compute_proj_evoked(evoked, n_grad=1, n_mag=1, n_eeg=0)
assert_true(len(projs_evoked) == 2)
# XXX : test something
# test parallelization
projs = compute_proj_epochs(epochs,
n_grad=1,
n_mag=1,
n_eeg=0,
n_jobs=2,
desc_prefix='foobar')
assert_true(all('foobar' in x['desc'] for x in projs))
projs = activate_proj(projs)
proj_par, _, _ = make_projector(projs, epochs.ch_names, bads=[])
assert_allclose(proj, proj_par, rtol=1e-8, atol=1e-16)
# test warnings on bad filenames
clean_warning_registry()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
proj_badname = op.join(tempdir, 'test-bad-name.fif.gz')
write_proj(proj_badname, projs)
read_proj(proj_badname)
print([ww.message for ww in w])
assert_equal(len(w), 2)
def test_compute_proj_epochs():
"""Test SSP computation on epochs."""
tempdir = _TempDir()
event_id, tmin, tmax = 1, -0.2, 0.3
raw = read_raw_fif(raw_fname, preload=True)
events = read_events(event_fname)
bad_ch = 'MEG 2443'
picks = pick_types(raw.info, meg=True, eeg=False, stim=False, eog=False,
exclude=[])
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
baseline=None, proj=False)
evoked = epochs.average()
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1)
write_proj(op.join(tempdir, 'test-proj.fif.gz'), projs)
for p_fname in [proj_fname, proj_gz_fname,
op.join(tempdir, 'test-proj.fif.gz')]:
projs2 = read_proj(p_fname)
assert len(projs) == len(projs2)
for p1, p2 in zip(projs, projs2):
assert p1['desc'] == p2['desc']
assert p1['data']['col_names'] == p2['data']['col_names']
assert p1['active'] == p2['active']
# compare with sign invariance
p1_data = p1['data']['data'] * np.sign(p1['data']['data'][0, 0])
p2_data = p2['data']['data'] * np.sign(p2['data']['data'][0, 0])
if bad_ch in p1['data']['col_names']:
bad = p1['data']['col_names'].index('MEG 2443')
mask = np.ones(p1_data.size, dtype=np.bool)
mask[bad] = False
p1_data = p1_data[:, mask]
p2_data = p2_data[:, mask]
corr = np.corrcoef(p1_data, p2_data)[0, 1]
assert_array_almost_equal(corr, 1.0, 5)
if p2['explained_var']:
assert_array_almost_equal(p1['explained_var'],
p2['explained_var'])
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert nproj == 2
assert U.shape[1] == 2
# test that you can save them
epochs.info['projs'] += projs
evoked = epochs.average()
evoked.save(op.join(tempdir, 'foo-ave.fif'))
projs = read_proj(proj_fname)
projs_evoked = compute_proj_evoked(evoked, n_grad=1, n_mag=1, n_eeg=0)
assert len(projs_evoked) == 2
# XXX : test something
# test parallelization
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1,
desc_prefix='foobar')
assert all('foobar' in x['desc'] for x in projs)
projs = activate_proj(projs)
proj_par, _, _ = make_projector(projs, epochs.ch_names, bads=[])
assert_allclose(proj, proj_par, rtol=1e-8, atol=1e-16)
# test warnings on bad filenames
proj_badname = op.join(tempdir, 'test-bad-name.fif.gz')
with pytest.warns(RuntimeWarning, match='-proj.fif'):
write_proj(proj_badname, projs)
with pytest.warns(RuntimeWarning, match='-proj.fif'):
read_proj(proj_badname)
def test_compute_proj():
"""Test SSP computation"""
event_id, tmin, tmax = 1, -0.2, 0.3
raw = Raw(raw_fname, preload=True)
events = read_events(event_fname)
exclude = []
bad_ch = 'MEG 2443'
picks = pick_types(raw.info, meg=True, eeg=False, stim=False, eog=False,
exclude=exclude)
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
baseline=None, proj=False)
evoked = epochs.average()
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=1)
write_proj('proj.fif.gz', projs)
for p_fname in [proj_fname, proj_gz_fname, 'proj.fif.gz']:
projs2 = read_proj(p_fname)
assert_true(len(projs) == len(projs2))
for p1, p2 in zip(projs, projs2):
assert_true(p1['desc'] == p2['desc'])
assert_true(p1['data']['col_names'] == p2['data']['col_names'])
assert_true(p1['active'] == p2['active'])
# compare with sign invariance
p1_data = p1['data']['data'] * np.sign(p1['data']['data'][0, 0])
p2_data = p2['data']['data'] * np.sign(p2['data']['data'][0, 0])
if bad_ch in p1['data']['col_names']:
bad = p1['data']['col_names'].index('MEG 2443')
mask = np.ones(p1_data.size, dtype=np.bool)
mask[bad] = False
p1_data = p1_data[:, mask]
p2_data = p2_data[:, mask]
corr = np.corrcoef(p1_data, p2_data)[0, 1]
assert_array_almost_equal(corr, 1.0, 5)
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert_true(nproj == 2)
assert_true(U.shape[1] == 2)
# test that you can save them
epochs.info['projs'] += projs
evoked = epochs.average()
evoked.save('foo.fif')
projs = read_proj(proj_fname)
projs_evoked = compute_proj_evoked(evoked, n_grad=1, n_mag=1, n_eeg=0)
# XXX : test something
# test parallelization
projs = compute_proj_epochs(epochs, n_grad=1, n_mag=1, n_eeg=0, n_jobs=2)
projs = activate_proj(projs)
proj_par, _, _ = make_projector(projs, epochs.ch_names, bads=[])
assert_array_equal(proj, proj_par)
# Test that the raw projectors work
for ii in (1, 2, 4, 8, 12, 24):
raw = Raw(raw_fname)
projs = compute_proj_raw(raw, duration=ii-0.1, n_grad=1, n_mag=1,
n_eeg=0)
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert_true(nproj == 2)
assert_true(U.shape[1] == 2)
# test that you can save them
raw.info['projs'] += projs
raw.save('foo_%d_raw.fif' % ii)
# Test that purely continuous (no duration) raw projection works
raw = Raw(raw_fname)
projs = compute_proj_raw(raw, duration=None, n_grad=1, n_mag=1, n_eeg=0)
# test that you can compute the projection matrix
projs = activate_proj(projs)
proj, nproj, U = make_projector(projs, epochs.ch_names, bads=[])
assert_true(nproj == 2)
assert_true(U.shape[1] == 2)
# test that you can save them
raw.info['projs'] += projs
raw.save('foo_rawproj_continuous_raw.fif')
