mt_example: A mousetrap data object.
Description
A mousetrap data object with example data created by importing
mt_example_raw and applying basic post-processing.
Format
A mousetrap data object is a list containing at least the
following objects:
data: data.frame containing the trial data (from
which the mouse-tracking data columns have been removed). More
information about the content of the trial data in mt_example can
be found in mt_example_raw.
trajectories: array containing raw mouse-tracking
trajectories. The first dimension represents the different trials. It
uses the ID of the trial as names (this ID is by default logged under
mt_id in data). The second dimension corresponds to the
different variables (timestamps, x-positions, y-positions) with the names
as specified in mt_variable_labels (by default: timestamps,
xpos, ypos). The third dimension corresponds to the samples
taken over time, which are included in chronological order and carry
successive integers as labels.
Some functions in this package (e.g., mt_time_normalize and
mt_average) add additional trajectory arrays (e.g.,
tn_trajectories and av_trajectories) to the mousetrap data
object. Other functions modify the existing arrays (e.g.,
mt_calculate_derivatives adds distance, velocity, and acceleration
to an existing dataset). Finally mt_calculate_measures adds an
additional data.frame with mouse-tracking measures to it.Details
The raw data set was imported using mt_import_mousetrap. Trajectories
were then remapped using mt_remap_symmetric so that all trajectories
end in the top-left corner and their starting point was aligned using
mt_align_start to a common value (0,0).