View source: R/plotting_functions.R
visualize_frame_gap_choice | R Documentation |
Run separate_trajectories() with many different frame gaps to help determine what value to use
visualize_frame_gap_choice(obj_name, loops = 20, ...)
obj_name |
The input viewr object; a tibble or data.frame with attribute
|
loops |
How many total frame gap entries to consider. Each loop will
increase the |
... |
Additional arguments |
The input viewr object (obj_name
) should likely be an object
that has passed through the select_x_percent()
step.
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.
Melissa S. Armstrong and Vikram B. Baliga
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()
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)
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