plot_factory: Make all typical plots

In pbs-assess/ggmse: Tools for Working with openMSE (Including DLMtool, MSEtool, and SAMtool)

Make all typical plots

Description

This function returns a large set of typical plots in a list object. These can then be printed to a file or included in an R Markdown document.

Usage

plot_factory(
  mse_list,
  pm,
  scenario_df,
  mp_ref,
  mp_sat,
  mp_not_sat,
  mp_not_sat2 = mp_not_sat,
  custom_pal = NULL,
  eg_scenario = scenario_df$scenario[1],
  tradeoff = pm[1:2],
  catch_breaks = NULL,
  catch_labels = catch_breaks,
  catch_ylim = NULL,
  dodge = 0.8,
  satisficed_criteria = NULL,
  skip_projections = FALSE,
  omit_index_fn = function(x) NULL,
  survey_type = c("Ind", "AddInd"),
  skip_worms = FALSE,
  french = isTRUE(getOption("french"))
)

Arguments

mse_list	A list of MSEtool MSE objects representing different scenarios. The list should be named with the scenario names.
pm	A character vector of performance metrics. These performance metrics should exist in the current workspace or via an attached package such as MSEtool.
scenario_df	A data frame with the columns scenario, scenario_human, and scenario_type. scenario_type should contain "Reference" and "Robustness" entries.
mp_ref	Reference MPs.
mp_sat	A character vector of satisficed management procedures (MPs).
mp_not_sat	MPs that were not satisfied (a giant projection plot will be made with these) for eg_scenario (see below).
mp_not_sat2	MPs that were not satisfied to highlight in a projection plot for eg_scenario (see below). I.e. probably some subset of the full not satisfied set.
custom_pal	A named character vector of colors for the MPs. Names should correspond to the MP names. Should include all satisficed and reference MPs.
eg_scenario	An example scenario (as character) that will be used for the projection plot of not-satisficed MPs.
tradeoff	Character vector of length 2 of tradeoff PMs.
catch_breaks	An optional numeric vector of y-axis breaks for the catch projection panels.
catch_labels	An optional numeric vector of y-axis labels for the catch projection panels. This can be useful, for example, if you want the labels to be in 1000 t insead of t.
catch_ylim	Optional y-axis limits for catch, e.g. c(0, 100)
dodge	The dodge width for plot_dots() etc.
satisficed_criteria	A named numeric vector designating the satisficed criteria for use in a 'tigure' plot. See plot_tigure().
skip_projections	Logical: skip the projection and worm plots for speed?
omit_index_fn	A function that indexes years in the projection period to omit from the plot. See plot_index().
survey_type	Which survey to plot. Passed to plot_index().
skip_worms	Skip the worms plot?
french	French?

Value

A named list object containing the ggplot objects.

Examples

# Fake but fast example follows:
# In reality, you might get here with something like:
# mse <- lapply(om_list, runMSE, MPs = mps)
# or
# mse <- purrr::map(om_list, runMSE, MPs = mps)
library(DLMtool)
# Instead, let's use the same example thrice:
mse <- list()
mse[[1]] <- mse_example
mse[[2]] <- mse_example
mse[[3]] <- mse_example
names(mse) <- c("sc1", "sc2", "sc3")

# Use more meaningful names than this:
scenario_df <- tibble::tribble(
  ~scenario, ~scenario_human, ~scenario_type,
  "sc1", "Scenario 1", "Reference",
  "sc2", "Scenario 2", "Reference",
  "sc3", "Scenario 3", "Robustness"
)

`LT LRP` <- ggmse::pm_factory("SBMSY", 0.4, c(36, 50))
`LT USR` <- ggmse::pm_factory("SBMSY", 0.8, c(36, 50))
STC <- ggmse::pm_factory("LTY", 0.5, c(1, 10))
LTC <- ggmse::pm_factory("LTY", 0.5, c(36, 50))
pm <- c("LT LRP", "LT USR", "STC", "LTC")

custom_pal <- c(RColorBrewer::brewer.pal(3, "Dark2"), "grey60")
names(custom_pal) <- c("CC1.0", "Itarget1", "Iratio2", "FMSYref75")

plots <- plot_factory(
  mse,
  pm = pm,
  scenario_df = scenario_df,
  mp_sat = c("Itarget1", "Iratio2", "FMSYref75"),
  mp_ref = c("FMSYref75"),
  mp_not_sat = c("CC1.0"),
  custom_pal = custom_pal,
  eg_scenario = "sc1",
  tradeoff = c("LT LRP", "STC"),
  satisficed_criteria = c("LT LRP" = 0.9, "STC" = 0.8)
)
names(plots)
plots$tigure_minimum
plots$convergence
plots$tigure_refset_avg
plots$tigure_refset
plots$worms_proj
plots$parallel_refset
plots$dot_refset
plots$radar_refset
plots$lollipops_refset
plots$projections$sc1
plots$projections_not_sat

pbs-assess/ggmse documentation built on Nov. 21, 2023, 8:06 p.m.