Plot Recruitment Deviations

Plot Recruitment Deviations

plot_recruitment_deviations(
  dat,
  module = NULL,
  era = "time",
  interactive = TRUE,
  make_rda = FALSE,
  figures_dir = getwd(),
  ...
)

Arguments

dat

A tibble or named list of tibbles (input as `list()`) returned from convert_output.

If inputting a list of tibbles, the first tibble's reference point defined in `ref_line` is used to plot a reference line or calculate relative spawning biomass.

module

(Optional) A string indicating the module_name found in `dat`.

Default: NULL

If the interactive and >1 module_name is found, user will select the module_name in the console. @seealso [filter_data()]

era

A string naming the era of data.

Default: "time"

Options: "early", "time", "fore" (forecast), or NULL (all data)

interactive

A logical value indicating if the environment is interactive.

Default: `FALSE`

make_rda

A logical value indicating whether to save the object and make an automated caption and alternative text in the form of an `rda` object. If TRUE, the rda will be exported to the folder indicated in the argument "figures_dir".

Default: `FALSE`.

figures_dir

A string indicating a path to the "figures" folder.

Default: `getwd()`

The folder is created within the path if it does not exist.

...

Arguments called from geom_line or geom_point

Value

Plot recruitment deviations relative to one over time from an assessment model output file translated to a standardized output (convert_output). There are options to return a `ggplot2` object or export an .rda object containing associated caption and alternative text for the figure.

Examples

plot_recruitment_deviations(
  dat = stockplotr:::example_data,
  interactive = FALSE,
  size = 1.5
)
#> ! Multiple module names found in data. 
#> ℹ Environment not interactive. Selecting PARAMETERS.
#> Ignoring unknown labels:
#> • colour : "Model"

plot_recruitment_deviations(
  dat = stockplotr:::example_data,
  era = "early",
  interactive = FALSE,
  shape = 2
)
#> ! Multiple module names found in data. 
#> ℹ Environment not interactive. Selecting PARAMETERS.
#> Ignoring unknown labels:
#> • colour : "Model"