nivlink.fht.epoching_fht¶

nivlink.fht.epoching_fht(raw, info, events, template='Start of Run%s')[source]¶

Epoch the raw eyetracking data.

Parameters:

Parameters:	raw : array, shape (n_times, 3) Raw eyetracking data. The first column contains the event messages. The second and third columns contain the eye positions in the x- and y-dimensions, respectively. info : instance of ScreenInfo Eyetracking acquisition information. events : array, shape (n_trials, 3) Events data. Each row represents a trial. The first column denotes the block. The second column denotes the trial onset relative to the block. The third column denotes the trial length. template : str Template for block start note as found in the EyeLink output file.
Returns:	epochs : array, shape (n_trials, n_times, 2) Epoched eyetracking timeseries data. Last dimension is the spatial dimension of the eyetracker (xdim, ydim).

raw : array, shape (n_times, 3): Raw eyetracking data. The first column contains the event messages. The second and third columns contain the eye positions in the x- and y-dimensions, respectively.
info : instance of ScreenInfo: Eyetracking acquisition information.
events : array, shape (n_trials, 3): Events data. Each row represents a trial. The first column denotes the block. The second column denotes the trial onset relative to the block. The third column denotes the trial length.
template : str: Template for block start note as found in the EyeLink output file.

Returns:

epochs : array, shape (n_trials, n_times, 2): Epoched eyetracking timeseries data. Last dimension is the spatial dimension of the eyetracker (xdim, ydim).

Notes

Designed for the FHTconfidence dimensions task dataset collected by Angela Radulescu & Julie Newman. Key assumption is that each “Start of Run message” is aligned to the first stimulus onset within that run/block.