def test_saving_picked():
"""Test saving picked CTF instances."""
temp_dir = _TempDir()
out_fname = op.join(temp_dir, 'test_py_raw.fif')
raw = read_raw_ctf(op.join(ctf_dir, ctf_fname_1_trial))
raw.crop(0, 1).load_data()
assert raw.compensation_grade == get_current_comp(raw.info) == 0
assert len(raw.info['comps']) == 5
pick_kwargs = dict(meg=True, ref_meg=False, verbose=True)
for comp_grade in [0, 1]:
raw.apply_gradient_compensation(comp_grade)
with catch_logging() as log:
raw_pick = raw.copy().pick_types(**pick_kwargs)
assert len(raw.info['comps']) == 5
assert len(raw_pick.info['comps']) == 0
log = log.getvalue()
assert 'Removing 5 compensators' in log
raw_pick.save(out_fname, overwrite=True) # should work
raw2 = read_raw_fif(out_fname)
assert (raw_pick.ch_names == raw2.ch_names)
assert_array_equal(raw_pick.times, raw2.times)
assert_allclose(raw2[0:20][0], raw_pick[0:20][0], rtol=1e-6,
atol=1e-20) # atol is very small but > 0
raw2 = read_raw_fif(out_fname, preload=True)
assert (raw_pick.ch_names == raw2.ch_names)
assert_array_equal(raw_pick.times, raw2.times)
assert_allclose(raw2[0:20][0], raw_pick[0:20][0], rtol=1e-6,
atol=1e-20) # atol is very small but > 0
def test_compensation():
"""Test compensation."""
tempdir = _TempDir()
raw = read_raw_fif(ctf_comp_fname, compensation=None, add_eeg_ref=False)
assert_equal(get_current_comp(raw.info), 3)
comp1 = make_compensator(raw.info, 3, 1, exclude_comp_chs=False)
assert_true(comp1.shape == (340, 340))
comp2 = make_compensator(raw.info, 3, 1, exclude_comp_chs=True)
assert_true(comp2.shape == (311, 340))
# round-trip
desired = np.eye(340)
for from_ in range(3):
for to in range(3):
if from_ == to:
continue
comp1 = make_compensator(raw.info, from_, to)
comp2 = make_compensator(raw.info, to, from_)
# To get 1e-12 here (instead of 1e-6) we must use the linalg.inv
# method mentioned in compensator.py
assert_allclose(np.dot(comp1, comp2), desired, atol=1e-12)
assert_allclose(np.dot(comp2, comp1), desired, atol=1e-12)
# make sure that changing the comp doesn't modify the original data
raw2 = read_raw_fif(ctf_comp_fname, add_eeg_ref=False)
raw2.apply_gradient_compensation(2)
assert_equal(get_current_comp(raw2.info), 2)
fname = op.join(tempdir, 'ctf-raw.fif')
raw2.save(fname)
raw2 = read_raw_fif(fname, add_eeg_ref=False)
assert_equal(raw2.compensation_grade, 2)
raw2.apply_gradient_compensation(3)
assert_equal(raw2.compensation_grade, 3)
data, _ = raw[:, :]
data2, _ = raw2[:, :]
# channels have norm ~1e-12
assert_allclose(data, data2, rtol=1e-9, atol=1e-18)
for ch1, ch2 in zip(raw.info['chs'], raw2.info['chs']):
assert_true(ch1['coil_type'] == ch2['coil_type'])
def test_saving_picked(tmpdir, comp_grade):
"""Test saving picked CTF instances."""
temp_dir = str(tmpdir)
out_fname = op.join(temp_dir, 'test_py_raw.fif')
raw = read_raw_ctf(op.join(ctf_dir, ctf_fname_1_trial))
raw.crop(0, 1).load_data()
assert raw.compensation_grade == get_current_comp(raw.info) == 0
assert len(raw.info['comps']) == 5
pick_kwargs = dict(meg=True, ref_meg=False, verbose=True)
raw.apply_gradient_compensation(comp_grade)
with catch_logging() as log:
raw_pick = raw.copy().pick_types(**pick_kwargs)
assert len(raw.info['comps']) == 5
assert len(raw_pick.info['comps']) == 0
log = log.getvalue()
assert 'Removing 5 compensators' in log
raw_pick.save(out_fname, overwrite=True) # should work
raw2 = read_raw_fif(out_fname)
assert (raw_pick.ch_names == raw2.ch_names)
assert_array_equal(raw_pick.times, raw2.times)
assert_allclose(raw2[0:20][0], raw_pick[0:20][0], rtol=1e-6,
atol=1e-20) # atol is very small but > 0
raw2 = read_raw_fif(out_fname, preload=True)
assert (raw_pick.ch_names == raw2.ch_names)
assert_array_equal(raw_pick.times, raw2.times)
assert_allclose(raw2[0:20][0], raw_pick[0:20][0], rtol=1e-6,
atol=1e-20) # atol is very small but > 0
def test_compensation_apply(tmp_path, preload, pick):
"""Test applying compensation."""
# make sure that changing the comp doesn't modify the original data
raw = read_raw_fif(ctf_comp_fname, preload=preload)
assert raw._comp is None
raw2 = raw.copy()
raw2.apply_gradient_compensation(2)
if pick:
raw2.pick([0] + list(range(2, len(raw.ch_names))))
raw.pick([0] + list(range(2, len(raw.ch_names))))
assert get_current_comp(raw2.info) == 2
if preload:
assert raw2._comp is None
else:
assert raw2._comp.shape == (len(raw2.ch_names), ) * 2
fname = op.join(tmp_path, 'ctf-raw.fif')
raw2.save(fname)
raw2 = read_raw_fif(fname)
assert raw2.compensation_grade == 2
raw2.apply_gradient_compensation(3)
assert raw2.compensation_grade == 3
data, _ = raw[:, :]
data2, _ = raw2[:, :]
# channels have norm ~1e-12
assert_allclose(data, data2, rtol=1e-9, atol=1e-18)
for ch1, ch2 in zip(raw.info['chs'], raw2.info['chs']):
assert ch1['coil_type'] == ch2['coil_type']
def test_ctf_plotting():
"""Test CTF topomap plotting."""
raw = read_raw_fif(ctf_fname, preload=True)
events = make_fixed_length_events(raw, duration=0.01)
assert len(events) > 10
evoked = Epochs(raw, events, tmin=0, tmax=0.01, baseline=None).average()
assert get_current_comp(evoked.info) == 3
evoked.plot_topomap() # smoke test that compensation does not matter
def test_ctf_plotting():
"""Test CTF topomap plotting."""
raw = read_raw_fif(ctf_fname, preload=True)
events = make_fixed_length_events(raw, duration=0.01)
assert len(events) > 10
evoked = Epochs(raw, events, tmin=0, tmax=0.01, baseline=None).average()
assert get_current_comp(evoked.info) == 3
# smoke test that compensation does not matter
evoked.plot_topomap(time_unit='s')
def test_ctf_plotting():
"""Test CTF topomap plotting."""
raw = read_raw_fif(ctf_fname, preload=True)
assert raw.compensation_grade == 3
events = make_fixed_length_events(raw, duration=0.01)
assert len(events) > 10
evoked = Epochs(raw, events, tmin=0, tmax=0.01, baseline=None).average()
assert get_current_comp(evoked.info) == 3
# smoke test that compensation does not matter
evoked.plot_topomap(time_unit='s')
# better test that topomaps can still be used without plotting ref
evoked.pick_types(meg=True, ref_meg=False)
evoked.plot_topomap()
def test_ctf_plotting():
"""Test CTF topomap plotting."""
raw = read_raw_fif(ctf_fname, preload=True)
assert raw.compensation_grade == 3
events = make_fixed_length_events(raw, duration=0.01)
assert len(events) > 10
evoked = Epochs(raw, events, tmin=0, tmax=0.01, baseline=None).average()
assert get_current_comp(evoked.info) == 3
# smoke test that compensation does not matter
evoked.plot_topomap(time_unit='s')
# better test that topomaps can still be used without plotting ref
evoked.pick_types(meg=True, ref_meg=False)
evoked.plot_topomap()
def test_saving_picked():
"""Test saving picked CTF instances."""
temp_dir = _TempDir()
out_fname = op.join(temp_dir, 'test_py_raw.fif')
raw = read_raw_ctf(op.join(ctf_dir, ctf_fname_1_trial))
raw.crop(0, 1).load_data()
assert raw.compensation_grade == get_current_comp(raw.info) == 0
assert len(raw.info['comps']) == 5
pick_kwargs = dict(meg=True, ref_meg=False, verbose=True)
with catch_logging() as log:
raw_pick = raw.copy().pick_types(**pick_kwargs)
assert len(raw.info['comps']) == 5
assert len(raw_pick.info['comps']) == 0
log = log.getvalue()
assert 'Removing 5 compensators' in log
raw_pick.save(out_fname) # should work
read_raw_fif(out_fname)
read_raw_fif(out_fname, preload=True)
# If comp is applied, picking should error
raw.apply_gradient_compensation(1)
assert raw.compensation_grade == get_current_comp(raw.info) == 1
with pytest.raises(RuntimeError, match='Compensation grade 1 has been'):
raw.copy().pick_types(**pick_kwargs)
def test_saving_picked():
"""Test saving picked CTF instances."""
temp_dir = _TempDir()
out_fname = op.join(temp_dir, 'test_py_raw.fif')
raw = read_raw_ctf(op.join(ctf_dir, ctf_fname_1_trial))
raw.crop(0, 1).load_data()
assert raw.compensation_grade == get_current_comp(raw.info) == 0
assert len(raw.info['comps']) == 5
pick_kwargs = dict(meg=True, ref_meg=False, verbose=True)
with catch_logging() as log:
raw_pick = raw.copy().pick_types(**pick_kwargs)
assert len(raw.info['comps']) == 5
assert len(raw_pick.info['comps']) == 0
log = log.getvalue()
assert 'Removing 5 compensators' in log
raw_pick.save(out_fname) # should work
read_raw_fif(out_fname)
read_raw_fif(out_fname, preload=True)
# If comp is applied, picking should error
raw.apply_gradient_compensation(1)
assert raw.compensation_grade == get_current_comp(raw.info) == 1
with pytest.raises(RuntimeError, match='Compensation grade 1 has been'):
raw.copy().pick_types(**pick_kwargs)
def test_compensation():
"""Test compensation
"""
raw = Raw(ctf_comp_fname, compensation=None)
comp1 = make_compensator(raw.info, 3, 1, exclude_comp_chs=False)
assert_true(comp1.shape == (340, 340))
comp2 = make_compensator(raw.info, 3, 1, exclude_comp_chs=True)
assert_true(comp2.shape == (311, 340))
# make sure that changing the comp doesn't modify the original data
raw2 = Raw(ctf_comp_fname, compensation=2)
assert_true(get_current_comp(raw2.info) == 2)
fname = op.join(tempdir, 'ctf-raw.fif')
raw2.save(fname)
raw2 = Raw(fname, compensation=None)
data, _ = raw[:, :]
data2, _ = raw2[:, :]
assert_allclose(data, data2, rtol=1e-9, atol=1e-20)
for ch1, ch2 in zip(raw.info['chs'], raw2.info['chs']):
assert_true(ch1['coil_type'] == ch2['coil_type'])
def test_compensation():
"""Test compensation
"""
raw = Raw(ctf_comp_fname, compensation=None)
comp1 = make_compensator(raw.info, 3, 1, exclude_comp_chs=False)
assert_true(comp1.shape == (340, 340))
comp2 = make_compensator(raw.info, 3, 1, exclude_comp_chs=True)
assert_true(comp2.shape == (311, 340))
# make sure that changing the comp doesn't modify the original data
raw2 = Raw(ctf_comp_fname, compensation=2)
assert_true(get_current_comp(raw2.info) == 2)
fname = op.join(tempdir, 'ctf-raw.fif')
raw2.save(fname)
raw2 = Raw(fname, compensation=None)
data, _ = raw[:, :]
data2, _ = raw2[:, :]
assert_allclose(data, data2, rtol=1e-9, atol=1e-20)
for ch1, ch2 in zip(raw.info['chs'], raw2.info['chs']):
assert_true(ch1['coil_type'] == ch2['coil_type'])
def test_compensation_identity():
"""Test compensation identity."""
raw = read_raw_fif(ctf_comp_fname)
assert get_current_comp(raw.info) == 3
comp1 = make_compensator(raw.info, 3, 1, exclude_comp_chs=False)
assert comp1.shape == (340, 340)
comp2 = make_compensator(raw.info, 3, 1, exclude_comp_chs=True)
assert comp2.shape == (311, 340)
# round-trip
desired = np.eye(340)
for from_ in range(3):
for to in range(3):
if from_ == to:
continue
comp1 = make_compensator(raw.info, from_, to)
comp2 = make_compensator(raw.info, to, from_)
# To get 1e-12 here (instead of 1e-6) we must use the linalg.inv
# method mentioned in compensator.py
assert_allclose(np.dot(comp1, comp2), desired, atol=1e-12)
assert_allclose(np.dot(comp2, comp1), desired, atol=1e-12)