[Mne_analysis] how to extract compute_energy_freq_bands features per channel

[Alexandre Gramfort]

        External Email - Use Caution        

hi,

your question concerns mne-features :
https://github.com/mne-tools/mne-features
not mne-python.

you can open an issue here :
https://github.com/mne-tools/mne-features/issues

Alex

On Wed, Feb 27, 2019 at 7:18 PM Ben Ighoyota Ajenaghughrure <ighoyota at tlu.ee>
wrote:

>         External Email - Use Caution
>
> Hello All,
>
> I am having a problem extracting "compute_energy_freq_bands" features from
> myEEG data.
>
> When i use the python mne function "compute_energy_freq_bands"  , the
> resulting feature extracted per channel is more than expected,  for example
> if i want to extract the energy frequency band for 4.5 to7hz, having
> recorded with 8channel electrode, i get for each channel, say  CZ as
> channel 1 in my eeg data, will become
> ch1_energy_freq_band0
> ch1_energy_freq_band1
> ch1_energy_freq_band2
> ch1_energy_freq_band3
> ch1_energy_freq_band4
> ch1_energy_freq_band5
> This is the same set I get for all other channels. I do not need all
> these, i only need
> Ch1_energy_freq_band,
> CH2_energy_freq_band.
>
> I have gone through the python mne website and try to understand the
> parameters, but I still have a problem, is a there a way to get around this
> problem? especially restricting the feature outcome to a single channel and
> not splitting them into several bands per channel?
>
> Here is my example code.
> selected_funcs1 = {'pow_freq_bands'}
> X_new1 = extract_features(data, raw.info['sfreq'],
> selected_funcs=selected_funcs1, return_as_df=True)
>
>
> A. Ighoyota ben
> Junior Researcher HCI (PhD in-view)
> Tallinn University, Estonia
> School of digital Technologies.
> mobile:+372582 <+372%205832%206393>78794
> skype: ighoyota-ben
>
>
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