visualize_frame_gap_choice {pathviewr}

Visualize the consequence of using various max_frame_gap values

Description

Run separate_trajectories() with many different frame gaps to help determine what value to use

Usage

visualize_frame_gap_choice(obj_name, loops = 20, ...)

Arguments

obj_name

The input viewr object; a tibble or data.frame with attribute pathviewr_steps that includes "viewr"

loops

How many total frame gap entries to consider. Each loop will increase the max_fram_gap argument in separate_trajectories by 1.

...

Additional arguments

Details

The input viewr object (obj_name) should likely be an object that has passed through the select_x_percent() step.

Value

A plot and a tibble, each of which shows the total number of trajectories that result from using the specified range of max_frame_gap values.

Author(s)

Melissa S. Armstrong and Vikram B. Baliga

See Also

Other data cleaning functions: gather_tunnel_data(), 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()

Other plotting functions: plot_by_subject(), plot_viewr_trajectories()

Other functions that define or clean trajectories: get_full_trajectories(), quick_separate_trajectories(), separate_trajectories()

Examples

library(pathviewr)

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

motive_selected <-
  motive_data %>%
  relabel_viewr_axes() %>%
  gather_tunnel_data() %>%
  trim_tunnel_outliers() %>%
  rotate_tunnel() %>%
  get_velocity() %>%
  select_x_percent(desired_percent = 50)

visualize_frame_gap_choice(motive_selected, loops = 10)