Calculate central tendency and dispersion for translational and rotational kinematics.
Arguments
- data
A kinematics aniframe (output of
calculate_kinematics())- measures
Measures of central tendency and dispersion for kinematics. Options are
"median_mad"(default) and"mean_sd".- .check
Whether to validate input. Set to
FALSEwhen called fromsummarise_aniframe()to avoid redundant checks.
Value
A summarised data frame with one row per group containing central tendency and dispersion measures (prefixed with median_/mad_ or mean_/sd_)
Speed, acceleration
Angular speed, velocity, acceleration (2D only)
Heading (2D only, using circular statistics)
Examples
kin <- calculate_kinematics(
aniframe::example_aniframe(n_obs = 20, n_individuals = 1, n_keypoints = 1)
)
summarise_kinematics(kin)
#> # A tibble: 1 × 16
#> individual keypoint session trial median_speed mad_speed median_acceleration
#> <int> <fct> <int> <int> <dbl> <dbl> <dbl>
#> 1 1 centroid 1 1 1.16 0.561 0.00709
#> # ℹ 9 more variables: mad_acceleration <dbl>, median_angular_speed <dbl>,
#> # mad_angular_speed <dbl>, median_angular_velocity <dbl>,
#> # mad_angular_velocity <dbl>, median_angular_acceleration <dbl>,
#> # mad_angular_acceleration <dbl>, median_heading <dbl>, mad_heading <dbl>
# Mean and standard deviation instead of median and MAD
summarise_kinematics(kin, measures = "mean_sd")
#> # A tibble: 1 × 16
#> individual keypoint session trial mean_speed sd_speed mean_acceleration
#> <int> <fct> <int> <int> <dbl> <dbl> <dbl>
#> 1 1 centroid 1 1 1.08 0.481 0.0692
#> # ℹ 9 more variables: sd_acceleration <dbl>, mean_angular_speed <dbl>,
#> # sd_angular_speed <dbl>, mean_angular_velocity <dbl>,
#> # sd_angular_velocity <dbl>, mean_angular_acceleration <dbl>,
#> # sd_angular_acceleration <dbl>, mean_heading <dbl>, sd_heading <dbl>