gather_tunnel_data: Gather data columns into key-value pairs

In pathviewr: Wrangle, Analyze, and Visualize Animal Movement Data

Gather data columns into key-value pairs

Description

Reformat viewr data into a "tidy" format so that every row corresponds to the position (and potentially rotation) of a single subject during an observed frame and time.

Usage

gather_tunnel_data(obj_name, NA_drop = TRUE, ...)

Arguments

obj_name	The input viewr object; a tibble or data.frame with attribute pathviewr_steps that includes "viewr"
NA_drop	Should rows with NAs be dropped? Defaults to TRUE
...	Additional arguments that can be passed to other pathviewr functions such as relabel_viewr_axes() or read_motive_csv()

Details

The tibble or data.frame that is fed in must have variables that have subject names and axis names separated by underscores. Axis names must be one of the following: position_length, position_width, or position_height. Each of these three dimensions must be present in the data. Collectively, this means that names like bird01_position_length or larry_position_height are acceptable, but bird01_x or bird01_length are not.

Value

A tibble in "tidy" format which is formatted to have every row correspond to the position (and potentially rotation) of a single subject during an observed frame and time. Subjects' names are automatically parsed from original variable names (e.g. subject1_rotation_width extracts "subject1" as the subject name) and stored in a Subjects column in the returned tibble.

Author(s)

Vikram B. Baliga

See Also

Other data cleaning functions: get_full_trajectories(), quick_separate_trajectories(), redefine_tunnel_center(), relabel_viewr_axes(), rename_viewr_characters(), rotate_tunnel(), select_x_percent(), separate_trajectories(), standardize_tunnel(), trim_tunnel_outliers(), visualize_frame_gap_choice()

Examples

library(pathviewr)

## Import the Motive example data included in the package
motive_data <-
  read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv",
                             package = 'pathviewr'))

## First use relabel_viewr_axes() to rename these variables using _length,
## _width, and _height instead
motive_data_relabeled <- relabel_viewr_axes(motive_data)

## Now use gather_tunnel_data() to gather colums into tidy format
motive_data_gathered <- gather_tunnel_data(motive_data_relabeled)

## Column names reflect the way in which data were reformatted:
names(motive_data_gathered)

pathviewr documentation built on March 31, 2023, 5:47 p.m.