Get instantaneous velocity for subjectsSource:
Velocity (both overall and per-axis) is computed for each row in the data (see Details)
get_velocity( obj_name, time_col = "time_sec", length_col = "position_length", width_col = "position_width", height_col = "position_height", add_to_viewr = TRUE, velocity_min = NA, velocity_max = NA, ... )
The input viewr object; a tibble or data.frame with attribute
Name of the column containing time
Name of the column containing length dimension
Name of the column containing width dimension
Name of the column containing height dimension
Default TRUE; should velocity data be added as new columns or should this function create a new simpler object?
Should data below a certain velocity be filtered out of the object? If so, enter a numeric. If not, keep NA.
Should data above a certain velocity be filtered out of the object? If so, enter a numeric. If not, keep NA.
Additional arguments passed to or from other pathviewr functions.
TRUE, additional columns are
appended to the input viewr object. If
FALSE, a standalone tibble is
created. Either way, an "instantaneous" velocity is computed as the
difference in position divided by the difference in time as each successive
row is encountered. Additionally, velocities along each of the three
position axes are computed and provided as additional columns.
Instantaneous velocity is not truly "instantaneous" but rather is approximated as the change in distance divided by change in time from one observation (row) to the previous observation (row). Each component of velocity is computed (i.e. per axis) along with the overall velocity of the subject.
Other mathematical functions:
## Import the example Motive data included in the package motive_data <- read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv", package = 'pathviewr')) ## Clean the file. It is generally recommended to clean up to the ## "standarization" step before running get_velocity(). motive_cleaned <- motive_data %>% relabel_viewr_axes() %>% gather_tunnel_data() %>% trim_tunnel_outliers() %>% rotate_tunnel() ## Now compute velocity and add as columns motive_velocity_added <- motive_cleaned %>% get_velocity(add_to_viewr = TRUE) ## Or set add_to_viewr to FALSE for a standalone object motive_velocity_standalone <- motive_cleaned %>% get_velocity(add_to_viewr = TRUE)