[Mne_analysis] ICA, hyperbolic tangent (tanh) and component filtering

[Alexandre Gramfort]

        External Email - Use Caution        

ica = ICA(n_components=20, method='fastica', fit_params=dict(fun='cube'),
random_state=0)
ica.fit(raw, picks=picks, reject=reject)

works fine. To use a callable please read the doc at:

https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.FastICA.html

""""
You can also provide your own function. It should return a tuple containing
the value of the function, and of its derivative, in the point. Example:

def my_g(x):
    return x ** 3, (3 * x ** 2).mean(axis=-1)
"""

Alex
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