Description Usage Arguments Details Value See Also
Clips all trials to identical start and stop times, and issues a warning if there are any missing samples.
1 | clip_trials(data, trial, time, start, stop)
|
data |
Data frame containing all of your time series data and metadata. |
trial |
Name of the variable containing the trial label. |
time |
Name of the variable containing the time stamp. |
start |
Value for start time. Times earlier than this will be discarded. |
stop |
Value for stop time. Times later than this will be discarded. |
Due to a variety of factors, trials in an eye-tracking experiment end up
being somewhat variable in length. clip_trials
is useful for trimming
multiple trials down to identical lengths, issuing a warning if your data
contain trials that are shorter than the standard length you have specified.
Note that unlike most of the other functions in this package,
clip_trials
operates on an entire data frame (not individual vectors).
The data frame must contain a column specifying trial number and a column
specifying time. The names of these columns should be passed, without quotes,
to the trial
and time
parameters, respectively.
If you did not include a trial number label in your eye-tracking output, you
can use label_trials
to construct one based on the sample
index. Importantly, you must first use the zero_trials
function
to synchronize the time
variable of each trial such that the 0 time
point of each trial corresponds to the onset of the experimental event. The
times in start
and stop
should be expressed in units relative
to this event, e.g., if the time scale is in milliseconds, arguments of
start = -1000
and stop = 6000
will standardize all trials to
begin 1 second before the event and end 6 seconds after the event.
See the vignette on cleaning pupil data (browseVignettes("itrak")
) for
an example of how to use this function.
Copy of data frame reduced to the range of times given by
start
and stop
.
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