Tool helping psychologists and other behavioural scientists to analyze mouse movement (and other 2D trajectory) data. Bundles together several functions computing spatial measures (maximum absolute deviation, area under the curve, sample entropy) or providing a shorthand for oftenused procedures.
Installation
You can install mousetRajectory from CRAN with
install.packages("mousetRajectory")
Alternatively, you can keep up to date and install the latest development version of mousetRajectory from github.com/mcschaaf/mousetRajectory with:
if(!require("devtools")){install.packages("devtools")}
devtools::install_github("mcschaaf/mousetRajectory")
Function Overview
Currently, the following functions are featured:
 Preprocessing:

is_monotonic()
checks whether your timestamps make sense and warns you if they don’t. 
is_monotonic_along_ideal()
checks whether your trajectories make sense and warns you if they don’t. 
time_circle_left()
tells you the time at which the starting area was left. 
time_circle_entered()
tells you the time at which the end area was entered. 
point_crosses()
tells you how often a certain value on the x or y axis is crossed. 
direction_changes()
tells you how often the direction along the x or y axis changes.

interp1()
directs you to the interpolation function from the awesomesignal
package. Thus, you do not have to calllibrary("signal")
. Such timesaving, much wow. Also, not having to attach thesignal
package avoids ambiguity betweensignal::filter()
anddplyr::filter()
in your search path. 
interp2()
is a convenience wrapper tointerp1()
that rescales the time for you.

 Spatial measures:

starting_angle()
computes (not only starting) angles. 
auc()
computes the (signed) Area Under the Curve (AUC). 
max_ad()
computes the (signed) Maximum Absolute Deviation (MAD). 
curvature()
computes the curvature. 
index_max_velocity()
computes the time to peak velocity, assuming equidistant times between data points. 
index_max_acceleration()
computes the time to peak acceleration, assuming equidistant times between data points.

 Other measures

sampen()
computes the sample entropy.

Documentation
You can find an example application as well as the full documentation at mcschaaf.github.io/mousetRajectory/.
Bug Reports
Please report bugs to github.com/mcschaaf/mousetRajectory/issues.