本文整理汇总了Python中mne.preprocessing.ICA._check_n_pca_components方法的典型用法代码示例。如果您正苦于以下问题：Python ICA._check_n_pca_components方法的具体用法？Python ICA._check_n_pca_components怎么用？Python ICA._check_n_pca_components使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mne.preprocessing.ICA的用法示例。
在下文中一共展示了ICA._check_n_pca_components方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_ica_additional
# 需要导入模块: from mne.preprocessing import ICA [as 别名]
# 或者: from mne.preprocessing.ICA import _check_n_pca_components [as 别名]
#.........这里部分代码省略.........
continue
scores = ica.score_sources(raw, target='EOG 061', score_func=func,
start=0, stop=10)
assert_true(ica.n_components_ == len(scores))
# check univariate stats
scores = ica.score_sources(raw, score_func=stats.skew)
# check exception handling
assert_raises(ValueError, ica.score_sources, raw,
target=np.arange(1))
params = []
params += [(None, -1, slice(2), [0, 1])] # varicance, kurtosis idx params
params += [(None, 'MEG 1531')] # ECG / EOG channel params
for idx, ch_name in product(*params):
ica.detect_artifacts(raw, start_find=0, stop_find=50, ecg_ch=ch_name,
eog_ch=ch_name, skew_criterion=idx,
var_criterion=idx, kurt_criterion=idx)
with warnings.catch_warnings(record=True):
idx, scores = ica.find_bads_ecg(raw, method='ctps')
assert_equal(len(scores), ica.n_components_)
idx, scores = ica.find_bads_ecg(raw, method='correlation')
assert_equal(len(scores), ica.n_components_)
idx, scores = ica.find_bads_ecg(epochs, method='ctps')
assert_equal(len(scores), ica.n_components_)
assert_raises(ValueError, ica.find_bads_ecg, epochs.average(),
method='ctps')
assert_raises(ValueError, ica.find_bads_ecg, raw,
method='crazy-coupling')
idx, scores = ica.find_bads_eog(raw)
assert_equal(len(scores), ica.n_components_)
raw.info['chs'][raw.ch_names.index('EOG 061') - 1]['kind'] = 202
idx, scores = ica.find_bads_eog(raw)
assert_true(isinstance(scores, list))
assert_equal(len(scores[0]), ica.n_components_)
# check score funcs
for name, func in get_score_funcs().items():
if name in score_funcs_unsuited:
continue
scores = ica.score_sources(epochs_eog, target='EOG 061',
score_func=func)
assert_true(ica.n_components_ == len(scores))
# check univariate stats
scores = ica.score_sources(epochs, score_func=stats.skew)
# check exception handling
assert_raises(ValueError, ica.score_sources, epochs,
target=np.arange(1))
# ecg functionality
ecg_scores = ica.score_sources(raw, target='MEG 1531',
score_func='pearsonr')
with warnings.catch_warnings(record=True): # filter attenuation warning
ecg_events = ica_find_ecg_events(raw,
sources[np.abs(ecg_scores).argmax()])
assert_true(ecg_events.ndim == 2)
# eog functionality
eog_scores = ica.score_sources(raw, target='EOG 061',
score_func='pearsonr')
with warnings.catch_warnings(record=True): # filter attenuation warning
eog_events = ica_find_eog_events(raw,
sources[np.abs(eog_scores).argmax()])
assert_true(eog_events.ndim == 2)
# Test ica fiff export
ica_raw = ica.get_sources(raw, start=0, stop=100)
assert_true(ica_raw.last_samp - ica_raw.first_samp == 100)
assert_true(len(ica_raw._filenames) == 0) # API consistency
ica_chans = [ch for ch in ica_raw.ch_names if 'ICA' in ch]
assert_true(ica.n_components_ == len(ica_chans))
test_ica_fname = op.join(op.abspath(op.curdir), 'test-ica_raw.fif')
ica.n_components = np.int32(ica.n_components)
ica_raw.save(test_ica_fname, overwrite=True)
ica_raw2 = Raw(test_ica_fname, preload=True)
assert_allclose(ica_raw._data, ica_raw2._data, rtol=1e-5, atol=1e-4)
ica_raw2.close()
os.remove(test_ica_fname)
# Test ica epochs export
ica_epochs = ica.get_sources(epochs)
assert_true(ica_epochs.events.shape == epochs.events.shape)
ica_chans = [ch for ch in ica_epochs.ch_names if 'ICA' in ch]
assert_true(ica.n_components_ == len(ica_chans))
assert_true(ica.n_components_ == ica_epochs.get_data().shape[1])
assert_true(ica_epochs._raw is None)
assert_true(ica_epochs.preload is True)
# test float n pca components
ica.pca_explained_variance_ = np.array([0.2] * 5)
ica.n_components_ = 0
for ncomps, expected in [[0.3, 1], [0.9, 4], [1, 1]]:
ncomps_ = ica._check_n_pca_components(ncomps)
assert_true(ncomps_ == expected)示例2: test_ica_additional
# 需要导入模块: from mne.preprocessing import ICA [as 别名]
# 或者: from mne.preprocessing.ICA import _check_n_pca_components [as 别名]
#.........这里部分代码省略.........
assert_equal(len(scores), ica.n_components_)
pytest.raises(ValueError, ica.find_bads_ecg, epochs.average(),
method='ctps')
pytest.raises(ValueError, ica.find_bads_ecg, raw,
method='crazy-coupling')
with pytest.warns(RuntimeWarning, match='longer'):
idx, scores = ica.find_bads_eog(raw)
assert_equal(len(scores), ica.n_components_)
raw.info['chs'][raw.ch_names.index('EOG 061') - 1]['kind'] = 202
with pytest.warns(RuntimeWarning, match='longer'):
idx, scores = ica.find_bads_eog(raw)
assert (isinstance(scores, list))
assert_equal(len(scores[0]), ica.n_components_)
idx, scores = ica.find_bads_eog(evoked, ch_name='MEG 1441')
assert_equal(len(scores), ica.n_components_)
idx, scores = ica.find_bads_ecg(evoked, method='correlation')
assert_equal(len(scores), ica.n_components_)
assert_array_equal(raw_data, raw[:][0])
assert_array_equal(epochs_data, epochs.get_data())
assert_array_equal(evoked_data, evoked.data)
# check score funcs
for name, func in get_score_funcs().items():
if name in score_funcs_unsuited:
continue
scores = ica.score_sources(epochs_eog, target='EOG 061',
score_func=func)
assert (ica.n_components_ == len(scores))
# check univariate stats
scores = ica.score_sources(epochs, score_func=stats.skew)
# check exception handling
pytest.raises(ValueError, ica.score_sources, epochs,
target=np.arange(1))
# ecg functionality
ecg_scores = ica.score_sources(raw, target='MEG 1531',
score_func='pearsonr')
with pytest.warns(RuntimeWarning, match='longer'):
ecg_events = ica_find_ecg_events(
raw, sources[np.abs(ecg_scores).argmax()])
assert (ecg_events.ndim == 2)
# eog functionality
eog_scores = ica.score_sources(raw, target='EOG 061',
score_func='pearsonr')
with pytest.warns(RuntimeWarning, match='longer'):
eog_events = ica_find_eog_events(
raw, sources[np.abs(eog_scores).argmax()])
assert (eog_events.ndim == 2)
# Test ica fiff export
ica_raw = ica.get_sources(raw, start=0, stop=100)
assert (ica_raw.last_samp - ica_raw.first_samp == 100)
assert_equal(len(ica_raw._filenames), 1) # API consistency
ica_chans = [ch for ch in ica_raw.ch_names if 'ICA' in ch]
assert (ica.n_components_ == len(ica_chans))
test_ica_fname = op.join(op.abspath(op.curdir), 'test-ica_raw.fif')
ica.n_components = np.int32(ica.n_components)
ica_raw.save(test_ica_fname, overwrite=True)
ica_raw2 = read_raw_fif(test_ica_fname, preload=True)
assert_allclose(ica_raw._data, ica_raw2._data, rtol=1e-5, atol=1e-4)
ica_raw2.close()
os.remove(test_ica_fname)
# Test ica epochs export
ica_epochs = ica.get_sources(epochs)
assert (ica_epochs.events.shape == epochs.events.shape)
ica_chans = [ch for ch in ica_epochs.ch_names if 'ICA' in ch]
assert (ica.n_components_ == len(ica_chans))
assert (ica.n_components_ == ica_epochs.get_data().shape[1])
assert (ica_epochs._raw is None)
assert (ica_epochs.preload is True)
# test float n pca components
ica.pca_explained_variance_ = np.array([0.2] * 5)
ica.n_components_ = 0
for ncomps, expected in [[0.3, 1], [0.9, 4], [1, 1]]:
ncomps_ = ica._check_n_pca_components(ncomps)
assert (ncomps_ == expected)
ica = ICA(method=method)
with pytest.warns(None): # sometimes does not converge
ica.fit(raw, picks=picks[:5])
with pytest.warns(RuntimeWarning, match='longer'):
ica.find_bads_ecg(raw)
ica.find_bads_eog(epochs, ch_name='MEG 0121')
assert_array_equal(raw_data, raw[:][0])
raw.drop_channels(['MEG 0122'])
pytest.raises(RuntimeError, ica.find_bads_eog, raw)
with pytest.warns(RuntimeWarning, match='longer'):
pytest.raises(RuntimeError, ica.find_bads_ecg, raw)