[Mne_analysis] INCORRECT VALUES PRODUCED WHEN EPOCHING A CONTINOUS DISCRETE SIGNAL USING MNE EPOCH FUNCTION

Dan McCloy dan.mccloy at gmail.com
Sat Oct 26 12:58:29 EDT 2019
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mne.Epochs defaults to tmin=-0.2 and tmax=0.5.  So you are not getting
20-second long epochs, you are getting 700ms epochs.  You need to set, for
example, tmin=0 and tmax=20, or tmin=-5 and tmax=15, etc.

On Sat, Oct 26, 2019 at 6:47 AM RODNEY PETRUS BALANDONG <
rodney.petrus_g03291 at utp.edu.my> wrote:

>         External Email - Use Caution
>
> Dear All,
>
>
>
> The idea was to epoch the continuous EEG data of 386.936 s long into non
> overlapping epoch window, of size 20 s. With a sampling frequency 250 Hz,
> theoretically each epochs should contain 5000 data points per epoch.
>
>
>
> To achieve the objective, the following code was utilised,
>
>
>
> *epochs = mne.Epochs(raw, events=events, event_id=event_id,
> baseline=None, verbose=True)*
>
> *MneApproach=epochs.to_data_frame()*
>
>
>
>
>
> To confirm whether the value return from the mne.Epoch  was correct or
> not, I had created a script that can performed the epoching manually. The
> output from the script has been validated visually and was working as
> intended.
>
> However, I noticed there were different between the script output and the
> value from dataframe MneApproach. Apart from different values, the
> MneApproach contained only 176 datasets per epoch.
>
>
>
> May I know what did I do wrong while inputting the mne.Epoch function.
>
>
>
> The above problem can be reproduced from the following ipynb
> <https://colab.research.google.com/github/balandongiv/Downsample/blob/master/helpMne.ipynb>
> via Google Colab
>
>
>
>
>
> Really appreciate for any feedback and help.
>
>
>
> Regards
>
> Rpb
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