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')