def test_ica_core():
"""Test ICA on raw and epochs
"""
# setup parameter
# XXX. The None cases helped revealing bugs but are time consuming.
noise_cov = [None, test_cov]
# removed None cases to speed up...
n_components = [3, 1.0] # for future dbg add cases
max_n_components = [4]
picks_ = [picks]
iter_ica_params = product(noise_cov, n_components, max_n_components,
picks_)
# test init catchers
assert_raises(ValueError, ICA, n_components=3, max_n_components=2)
assert_raises(ValueError, ICA, n_components=1.3, max_n_components=2)
# test essential core functionality
for n_cov, n_comp, max_n, pcks in iter_ica_params:
# Test ICA raw
ica = ICA(noise_cov=n_cov,
n_components=n_comp,
max_n_components=max_n,
random_state=0)
print ica # to test repr
# test fit checker
assert_raises(RuntimeError, ica.get_sources_raw, raw)
assert_raises(RuntimeError, ica.get_sources_epochs, epochs)
# test decomposition
ica.decompose_raw(raw, picks=pcks, start=start, stop=stop)
# test re-init exception
assert_raises(RuntimeError, ica.decompose_raw, raw, picks=picks)
sources = ica.get_sources_raw(raw)
assert_true(sources.shape[0] == ica.n_components)
# test preload filter
raw3 = raw.copy()
raw3._preloaded = False
assert_raises(ValueError,
ica.pick_sources_raw,
raw3,
include=[1, 2],
n_pca_components=ica.n_components)
for excl, incl in (([], []), ([], [1, 2]), ([1, 2], [])):
raw2 = ica.pick_sources_raw(raw,
exclude=excl,
include=incl,
copy=True,
n_pca_components=ica.n_components)
assert_array_almost_equal(raw2[:, :][1], raw[:, :][1])
#######################################################################
# test epochs decomposition
# test re-init exception
assert_raises(RuntimeError, ica.decompose_epochs, epochs, picks=picks)
ica = ICA(noise_cov=n_cov,
n_components=n_comp,
max_n_components=max_n,
random_state=0)
ica.decompose_epochs(epochs, picks=picks)
# test pick block after epochs fit
assert_raises(ValueError,
ica.pick_sources_raw,
raw,
n_pca_components=ica.n_components)
sources = ica.get_sources_epochs(epochs)
assert_true(sources.shape[1] == ica.n_components)
assert_raises(ValueError,
ica.find_sources_epochs,
epochs,
target=np.arange(1))
# test preload filter
epochs3 = epochs.copy()
epochs3.preload = False
assert_raises(ValueError,
ica.pick_sources_epochs,
epochs3,
include=[1, 2],
n_pca_components=ica.n_components)
# test source picking
for excl, incl in (([], []), ([], [1, 2]), ([1, 2], [])):
epochs2 = ica.pick_sources_epochs(
epochs,
exclude=excl,
include=incl,
copy=True,
n_pca_components=ica.n_components)
assert_array_almost_equal(epochs2.get_data(), epochs.get_data())
def test_ica_core():
"""Test ICA on raw and epochs
"""
# setup parameter
# XXX. The None cases helped revealing bugs but are time consuming.
noise_cov = [None, test_cov]
# removed None cases to speed up...
n_components = [3, 1.0] # for future dbg add cases
max_n_components = [4]
picks_ = [picks]
iter_ica_params = product(noise_cov, n_components, max_n_components,
picks_)
# test init catchers
assert_raises(ValueError, ICA, n_components=3, max_n_components=2)
assert_raises(ValueError, ICA, n_components=1.3, max_n_components=2)
# test essential core functionality
for n_cov, n_comp, max_n, pcks in iter_ica_params:
# Test ICA raw
ica = ICA(noise_cov=n_cov, n_components=n_comp, max_n_components=max_n,
random_state=0)
print ica # to test repr
# test fit checker
assert_raises(RuntimeError, ica.get_sources_raw, raw)
assert_raises(RuntimeError, ica.get_sources_epochs, epochs)
# test decomposition
ica.decompose_raw(raw, picks=pcks, start=start, stop=stop)
# test re-init exception
assert_raises(RuntimeError, ica.decompose_raw, raw, picks=picks)
sources = ica.get_sources_raw(raw)
assert_true(sources.shape[0] == ica.n_components)
# test preload filter
raw3 = raw.copy()
raw3._preloaded = False
assert_raises(ValueError, ica.pick_sources_raw, raw3,
include=[1, 2], n_pca_components=ica.n_components)
for excl, incl in (([], []), ([], [1, 2]), ([1, 2], [])):
raw2 = ica.pick_sources_raw(raw, exclude=excl, include=incl,
copy=True,
n_pca_components=ica.n_components)
assert_array_almost_equal(raw2[:, :][1], raw[:, :][1])
#######################################################################
# test epochs decomposition
# test re-init exception
assert_raises(RuntimeError, ica.decompose_epochs, epochs, picks=picks)
ica = ICA(noise_cov=n_cov, n_components=n_comp, max_n_components=max_n,
random_state=0)
ica.decompose_epochs(epochs, picks=picks)
# test pick block after epochs fit
assert_raises(ValueError, ica.pick_sources_raw, raw,
n_pca_components=ica.n_components)
sources = ica.get_sources_epochs(epochs)
assert_true(sources.shape[1] == ica.n_components)
assert_raises(ValueError, ica.find_sources_epochs, epochs,
target=np.arange(1))
# test preload filter
epochs3 = epochs.copy()
epochs3.preload = False
assert_raises(ValueError, ica.pick_sources_epochs, epochs3,
include=[1, 2], n_pca_components=ica.n_components)
# test source picking
for excl, incl in (([], []), ([], [1, 2]), ([1, 2], [])):
epochs2 = ica.pick_sources_epochs(epochs, exclude=excl,
include=incl, copy=True,
n_pca_components=ica.n_components)
assert_array_almost_equal(epochs2.get_data(),
epochs.get_data())
def test_ica_additional():
# Test additional functionality
stop2 = 500
ica = ICA(n_components=3, max_n_components=4)
ica.decompose_raw(raw, picks=None, start=start, stop=stop2)
# epochs extraction from raw fit
assert_raises(RuntimeError, ica.get_sources_epochs, epochs)
ica = ICA(n_components=3, max_n_components=4)
ica.decompose_raw(raw, picks=picks, start=start, stop=stop2)
sources = ica.get_sources_epochs(epochs)
assert_true(sources.shape[1] == ica.n_components)
sources = ica.get_sources_raw(raw)
# score funcs raw
sfunc_test = [
ica.find_sources_raw(raw,
target='EOG 061',
score_func=n,
start=0,
stop=10) for n, f in score_funcs.items()
]
# check lenght of scores
[assert_true(ica.n_components == len(scores)) for scores in sfunc_test]
# check univariate stats
scores = ica.find_sources_raw(raw, score_func=stats.skew)
# check exception handling
assert_raises(ValueError, ica.find_sources_raw, raw, target=np.arange(1))
## score funcs epochs ##
# check lenght of scores
sfunc_test = [
ica.find_sources_epochs(epochs_eog, target='EOG 061', score_func=n)
for n, f in score_funcs.items()
]
# check lenght of scores
[assert_true(ica.n_components == len(scores)) for scores in sfunc_test]
# check univariat stats
scores = ica.find_sources_epochs(epochs, score_func=stats.skew)
# check exception handling
assert_raises(ValueError,
ica.find_sources_epochs,
epochs,
target=np.arange(1))
# ecg functionality
ecg_scores = ica.find_sources_raw(raw,
target='MEG 1531',
score_func='pearsonr')
ecg_events = ica_find_ecg_events(raw, sources[np.abs(ecg_scores).argmax()])
assert_true(ecg_events.ndim == 2)
# eog functionality
eog_scores = ica.find_sources_raw(raw,
target='EOG 061',
score_func='pearsonr')
eog_events = ica_find_eog_events(raw, sources[np.abs(eog_scores).argmax()])
assert_true(eog_events.ndim == 2)
# Test ica fiff export
raw3 = raw.copy()
raw3._preloaded = False
assert_raises(ValueError, ica.export_sources, raw3, start=0, stop=100)
ica_raw = ica.export_sources(raw, start=0, stop=100)
assert_true(ica_raw.last_samp - ica_raw.first_samp == 100)
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.fif')
ica_raw.save(test_ica_fname)
ica_raw2 = fiff.Raw(test_ica_fname, preload=True)
assert_array_almost_equal(ica_raw._data, ica_raw2._data)
os.remove(test_ica_fname)
# regression test for plot method
assert_raises(ValueError, ica.plot_sources_raw, raw, order=np.arange(50))
assert_raises(ValueError,
ica.plot_sources_epochs,
epochs,
order=np.arange(50))
def test_ica_additional():
# Test additional functionality
stop2 = 500
ica = ICA(n_components=3, max_n_components=4)
ica.decompose_raw(raw, picks=None, start=start, stop=stop2)
# epochs extraction from raw fit
assert_raises(RuntimeError, ica.get_sources_epochs, epochs)
ica = ICA(n_components=3, max_n_components=4)
ica.decompose_raw(raw, picks=picks, start=start, stop=stop2)
sources = ica.get_sources_epochs(epochs)
assert_true(sources.shape[1] == ica.n_components)
sources = ica.get_sources_raw(raw)
# score funcs raw
sfunc_test = [ica.find_sources_raw(raw, target='EOG 061', score_func=n,
start=0, stop=10) for n, f in score_funcs.items()]
# check lenght of scores
[assert_true(ica.n_components == len(scores)) for scores in sfunc_test]
# check univariate stats
scores = ica.find_sources_raw(raw, score_func=stats.skew)
# check exception handling
assert_raises(ValueError, ica.find_sources_raw, raw,
target=np.arange(1))
## score funcs epochs ##
# check lenght of scores
sfunc_test = [ica.find_sources_epochs(epochs_eog, target='EOG 061',
score_func=n) for n, f in score_funcs.items()]
# check lenght of scores
[assert_true(ica.n_components == len(scores)) for scores in sfunc_test]
# check univariat stats
scores = ica.find_sources_epochs(epochs, score_func=stats.skew)
# check exception handling
assert_raises(ValueError, ica.find_sources_epochs, epochs,
target=np.arange(1))
# ecg functionality
ecg_scores = ica.find_sources_raw(raw, target='MEG 1531',
score_func='pearsonr')
ecg_events = ica_find_ecg_events(raw, sources[np.abs(ecg_scores).argmax()])
assert_true(ecg_events.ndim == 2)
# eog functionality
eog_scores = ica.find_sources_raw(raw, target='EOG 061',
score_func='pearsonr')
eog_events = ica_find_eog_events(raw, sources[np.abs(eog_scores).argmax()])
assert_true(eog_events.ndim == 2)
# Test ica fiff export
raw3 = raw.copy()
raw3._preloaded = False
assert_raises(ValueError, ica.export_sources, raw3, start=0, stop=100)
ica_raw = ica.export_sources(raw, start=0, stop=100)
assert_true(ica_raw.last_samp - ica_raw.first_samp == 100)
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.fif')
ica_raw.save(test_ica_fname)
ica_raw2 = fiff.Raw(test_ica_fname, preload=True)
assert_array_almost_equal(ica_raw._data, ica_raw2._data)
os.remove(test_ica_fname)
# regression test for plot method
assert_raises(ValueError, ica.plot_sources_raw, raw,
order=np.arange(50))
assert_raises(ValueError, ica.plot_sources_epochs, epochs,
order=np.arange(50))
