[Mne_analysis] Mne_analysis Digest, Vol 55, Issue 16

[Kambiz Tavabi]

Greetings,
I am trying to filter raw data before extracting epochs and computing 
contrasts.
I am using:
     raw = fiff.Raw(f, preload=True) #Setup for reading the raw data
     events = mne.find_events(raw, stim_channel='STI101')
Up to this point I get 7 events, which is correct.

     raw.filter(None, 40.0, picks=None, filter_length=4096, 
h_trans_bandwidth=0.5, verbose=5, n_jobs=8) # filter raw
This command works without error.

     tmin, tmax = -0.1, 0.5
     reject = dict(grad=3000e-13)
     epochs = mne.Epochs(raw, events, 1, tmin, tmax, baseline=(None, 0), 
reject=reject) #extract epochs
I get an output with ~300 epochs, also correct.

     evoked = epochs.average()  # average epochs and get an Evoked dataset.
If I don't include the mne.filter command I get an unfiltered evoked 
dataset which I can visualize with plot_evoked(evoked).
If I include the mne.filter command I get the following error during 
averaging:
/usr/local/mne-python/mne/epochs.py:424: RuntimeWarning: invalid value 
encountered in divide data /= n_events. And no evoked dataset.
Assuming this procedure is incorrect, how else can I filter raw data on 
the fly (i.e., without saving), and average epochs?

Thanks in advance
Kambiz