trim_tunnel_outliers: Trim out artifacts and other outliers from the extremes of...

View source: R/utility_functions.R

trim_tunnel_outliersR Documentation

Trim out artifacts and other outliers from the extremes of the tunnel

Description

The user provides estimates of min and max values of data. This function then trims out anything beyond these estimates.

Usage

trim_tunnel_outliers(
  obj_name,
  lengths_min = 0,
  lengths_max = 3,
  widths_min = -0.4,
  widths_max = 0.8,
  heights_min = -0.2,
  heights_max = 0.5,
  ...
)

Arguments

obj_name

The input viewr object; a tibble or data.frame with attribute pathviewr_steps that includes "viewr" that has been passed through relabel_viewr_axes() and gather_tunnel_data() (or is structured as though it has been passed through those functions).

lengths_min

Minimum length

lengths_max

Maximum length

widths_min

Minimum width

widths_max

Maximum width

heights_min

Minimum height

heights_max

Maximum height

...

Additional arguments passed to/from other pathviewr functions

Details

Anything supplied to _min or _max arguments should be single numeric values.

Value

A viewr object (tibble or data.frame with attribute pathviewr_steps that includes "viewr") in which data outside the specified ranges has been excluded.

Author(s)

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(), visualize_frame_gap_choice()

Examples

## 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
## "gather" step before running trim_tunnel_outliers().
motive_gathered <-
  motive_data %>%
  relabel_viewr_axes() %>%
  gather_tunnel_data()

## Now trim outliers using default values
motive_trimmed <-
  motive_gathered %>%
  trim_tunnel_outliers(lengths_min = 0,
                       lengths_max = 3,
                       widths_min = -0.4,
                       widths_max = 0.8,
                       heights_min = -0.2,
                       heights_max = 0.5)

pathviewr documentation built on Nov. 10, 2022, 5:07 p.m.