A data object of class "mousetrap" with example data created by importing mt_example_raw and applying basic post-processing.



A mousetrap data object is a list containing at least the following objects:

  • data: a 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. The rownames of data correspond to the trial identifier. For convenience, the trial identifier is also stored in an additional column called "mt_id".

  • trajectories: an array containing the raw mouse-tracking trajectories. The first dimension represents the different trials and the dimension names (which can be accessed using rownames) correspond to the trial identifier (the same identifier that is used as the rownames in data). The second dimension corresponds to the samples taken over time which are included in chronological order. The third dimension corresponds to the different mouse-tracking variables (timestamps, x-positions, y-positions) which are usually called timestamps, xpos, and ypos.

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_derivatives adds distance, velocity, and acceleration to an existing dataset). Finally mt_measures adds an additional data.frame with mouse-tracking measures to it.


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).