[Mne_analysis] shifting time-scale in RAW data

[Martin Luessi]

On 04/29/14 05:54, Stephen Politzer-Ahles wrote:
> Hi Lau,
> 
> I thought there was a function for this on raw data but I can no longer
> find it (so I too would be interested to hear what others have to say).
> But it should be possible to do this in sort of a hack-ish way by just
> shifting the times of the events in the event table. For example:
> 
> # Get the event list events = mne.find_events( raw, min_duration = .002 )
> 
> # Adjust the trigger latencies
> events[:,0] = [ x + 25 for x in events[:,0] ]

Note that the first column in "events" contains the time in samples, not
milliseconds. So this will be incorrect unless your sampling frequency
is 1kHz. To shift it by 25ms I would use

import numpy as np

events[:,0] += np.round(25e-3 * raw.info['sfreq'])

Best,

Martin

> 
> Alternatively, I suppose you could just pull out bigger epochs (e.g., 25
> ms longer than you intend) in the beginning, then use evoked.shift_time
> later, and make sure to leave off the first 25 ms of the epoch in your
> plotting and analysis. But yes, it would be great if there is a cleaner
> way to do this.
> 
> Best,
> Steve
> 
> 
> 
> Stephen Politzer-Ahles
> New York University, Abu Dhabi
> Neuroscience of Language Lab
> http://www.nyu.edu/projects/politzer-ahles/
> 
> 
> On Tue, Apr 29, 2014 at 1:34 PM, Lau Møller Andersen
> <lau.andersen at cnru.dk <mailto:lau.andersen at cnru.dk>> wrote:
> 
>     Dear list
> 
>     I am aware of how to shift the time-scale in evoked files:
>     http://martinos.org/mne/stable/auto_examples/plot_shift_evoked.html#example-plot-shift-evoked-py
> 
>     But is it possible to do it already on the raw file? (I have a
>     trigger delay of 25 msec.)
> 
>     The reason for this being preferable in my view is that if you do it
>     after having epoched, you effectively include 25 msec of data before
>     the epoch that does not belong to the epoch. Furthermore, you
>     exclude 25 msec of data at the end of the epoch that does belong in
>     the epoch.
> 
>     Best Wishes
> 
>     Lau
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