def plot_components(A, raw, picks, **kwargs):
p, q = A.shape
ica = ICA_(n_components=q, method='fastica', random_state=0,
fit_params=dict(max_iter=1))
ica.info = pick_info(raw.info, picks)
if ica.info['comps']:
ica.info['comps'] = []
ica.ch_names = ica.info['ch_names']
ica.mixing_matrix_ = A
ica.pca_components_ = np.eye(p)
ica.pca_mean_ = None
ica.unmixing_matrix_ = np.linalg.pinv(A)
ica.n_components_ = p
ica._update_ica_names()
ica.plot_components(**kwargs)
def transfer_to_mne(A, raw, picks):
'''
Hack to use the MNE ICA class providing the estimated mixing matrix A.
'''
p, q = A.shape
ica = ICA_(n_components=q, method='fastica', random_state=0,
fit_params=dict(max_iter=1))
ica.info = pick_info(raw.info, picks)
if ica.info['comps']:
ica.info['comps'] = []
ica.ch_names = ica.info['ch_names']
ica.mixing_matrix_ = A
ica.pca_components_ = np.eye(p)
ica.pca_mean_ = None
ica.unmixing_matrix_ = np.linalg.pinv(A)
ica.n_components_ = p
ica._update_ica_names()
return ica
