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Dear MNE team and users,
I currently working on testing MNE ICA algorithms for different case ( noise level, sample length)
I would like to extract the mixing matrix M used by ica.apply to go back from ica source space to recording space such as
Recordings = M * Sources
I ended with this formula :
M = pre_whitener_ * (pca_components_) -1 * mixing [1]
And implemented it with python using:
pre_whitener_ = getattr(ica, "pre_whitener_" )
whitenning_matrix = np.eye(len(pre_whitener_))*pre_whitener_
mixing = getattr(ica, "mixing_matrix_" )
pca_components_ = getattr(ica, "pca_components_" )
M = np.dot (whitenning_matrix, np.dot(np.linalg.inv(pca_components_), mixing ) )
But I weren?t able to successfully reconstruct the signal by using the following line:
Records_from_ica = np.dot(M, ica.get_sources(Raw).get_data())
It?s probably a problem in the formula [1] , but I can?t find any solution
Do you have any idea on how to get the mixing matrix used by the ica.apply function ? I looked up the code, but it didn?t completely understand it
Thanks for your help,
Victor
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