[Mne_analysis] [mne-python] tfr_morlet to return single epochs

[Mads Jensen]

hi Alex,

thanks for the reply. I afraid cannot make it work, I get the following 
error:

Traceback (most recent call last):

   File "<ipython-input-9-1e05100b604d>", line 30, in <module>
     return_itc=True, decim=3, n_jobs=1)

   File 
"/home/mje/Toolboxes/anaconda/lib/python2.7/site-packages/mne-0.9.git-py2.7.egg/mne/time_frequency/tfr.py", 
line 892, in tfr_morlet
     data = data[:, picks, :]

IndexError: too many indice


I just used to the code from the example 
"time_frequency/plot_time_frequency_sensors.py" and changed the:
power, itc = tfr_morlet(epochs, freqs=freqs, n_cycles=n_cycles, 
use_fft=False,
to:
power, itc = tfr_morlet(epochs[0], freqs=freqs, n_cycles=n_cycles, 
use_fft=False,
                         return_itc=True, decim=3, n_jobs=1) 
            return_itc=True, decim=3, n_jobs=1)

the full code is below,

any thoughts?
best regards,
mads

***
import numpy as np
import mne
from mne import io
from mne.time_frequency import tfr_morlet
from mne.datasets import somato

###############################################################################
# Set parameters
data_path = somato.data_path()
raw_fname = data_path + '/MEG/somato/sef_raw_sss.fif'
event_id, tmin, tmax = 1, -1., 3.

# Setup for reading the raw data
raw = io.Raw(raw_fname)
baseline = (None, 0)
events = mne.find_events(raw, stim_channel='STI 014')

# picks MEG gradiometers
picks = mne.pick_types(raw.info, meg='grad', eeg=False, eog=True, 
stim=False)

epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                     baseline=baseline, reject=dict(grad=4000e-13, 
eog=350e-6))

###############################################################################
# Calculate power and intertrial coherence

freqs = np.arange(6, 30, 3)  # define frequencies of interest
n_cycles = freqs / 2.  # different number of cycle per frequency
power, itc = tfr_morlet(epochs[0], freqs=freqs, n_cycles=n_cycles, 
use_fft=False,
                         return_itc=True, decim=3, n_jobs=1)
***


On 29/08/14 18:32, Alexandre Gramfort wrote:
> hi Mads,
>
> yes you can. Just call tfr_morlet on epochs[k] to compute it on one epochs.
>
> You can index epochs like arrays with MNE-Python
>
> Alex
>
>
>
> On Fri, Aug 29, 2014 at 1:41 PM, Mads Jensen <mje.mads at gmail.com> wrote:
>> Dear mne-list,
>>
>> I would like to make a morlet wavelet on single epochs but as I
>> understand the tfr_morlet, it returns the average power for all the
>> epochs. If this is correct is there a way to make tfr_morlet return the
>> single epochs or is there another function that can?
>>
>> thanks,
>> mads
>>
>>
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