User-defined feature functions made easy

[jbschiratti]

1. I think that _embed, _filt, _wavelet_coefs (in utils.py) should not be private functions and should be added (along with power_spectrum) to MNE-features' API. The reason for that is that those functions are "building blocks" for user-defined feature functions. For instance, it would be great if they could do:

from mne_features.utils import power_spectrum
from mne_features.feature_extraction import extract_features

def myspectralfeature(sfreq, data):
    psd, _ = power_spectrum(sfreq, data)
    ...
    return ...

selected_funcs = ['mean', 'variance', ('myfunc', myspectralfeature)]
features = extract_features(epochs_data, sfreq, selected_funcs)

2. It is implicit that, for any feature function, if sfreq is one of the parameters, then it should be placed first because unless feature_funcs[alias] = partial(func, sfreq) (in _get_feature_funcs) will not work as expected. This should be mentioned in the doc... Or partial(func, sfreq) should be changed for partial(func, **{'sfreq': sfreq}).

[agramfort]

no objection