plot_decision_table: Decision table of performance metrics

In salmonMSE: Management Strategy Evaluation for Salmon Species

Decision table of performance metrics

Description

Generates a coloured table of a performance metric across two axes, which may be a population dynamics variable (e.g., productivity) or a management action (e.g., hatchery production levels or harvest strategy). See example at https://docs.salmonmse.com/articles/decision-table.html. More examples below.

• plot_decision_table() is a simple figure where colour range is intended to continuously transition from pink to white to green corresponding to values of 0, 0.5, and 1, respectively.

• plot_decision_table2() is converts performance metrics values into bins and provides more user control in the colour scheme

Usage

plot_decision_table(
  x,
  y,
  z,
  title,
  xlab,
  ylab,
  scenario,
  ncol = NULL,
  dir = "v"
)

plot_decision_table2(
  x,
  y,
  z,
  title,
  xlab,
  ylab,
  zlab,
  scenario,
  ncol = NULL,
  dir = "v",
  bin = c(0, 0.05, 0.25, 0.5, 0.75, 0.95),
  bin_labels = c("0-0.04", "0.05-0.24", "0.25-0.49", "0.5-0.74", "0.75-0.94", "0.95-1"),
  bin_col = c("purple4", "deeppink", "pink", "white", "green", "green4"),
  cell_border = FALSE,
  add_values = FALSE
)

Arguments

x	Atomic, vector of values for the x axis (same length as z). Will be converted to factors
y	Atomic, vector of values for the y axis (same length as z). Will be converted to factors
z	Numeric, vector of values for the performance metric
title	Character, optional title of figure
xlab	Character, optional x-axis label
ylab	Character, optional y-axis label
scenario	Atomic, vector of faceting variables (same length as z) used to generate a grid of decision tables
ncol	Integer, number of columns for decision table grid, only used if scenario is provided
dir	Character, either "h" or "v" to describe how the grid of tables should be organized (horizontally or vertically)
zlab	Character, optional color legend
bin	Numeric vector of bins to sort values of z
bin_labels	Character vector for bin names for the figure
bin_col	Character vector of colors for the bins in the figure
cell_border	Logical, whether to add borders for each cell in the figure
add_values	Logical, whether to add the values of z in the figure

Value

ggplot object

See Also

plot_statevar_ts() plot_tradeoff()

Examples

# Simple decision table
results <- data.frame(
  PNI = c(0.7, 0.23, 0.05, 0.9, 0.85, 0.74, 0.95, 0.92, 0.9),
  pNOB = rep(c(0.5, 0.75, 1), each = 3),
  ER = rep(c(0.2, 0.3, 0.4), 3),
  scenario = "High productivity"
)
plot_decision_table(
  x = results$ER,
  y = results$pNOB,
  z = results$PNI,
  title = "PNI",
  xlab = "Exploitation rate",
  ylab = "pNOB target"
)

# Multiple decision tables organized by scenario
# Continuing from above
results_low <- results
results_low$scenario <- "Low productivity"
results_low$PNI <- 0.5 * results$PNI

results_all <- rbind(results, results_low)
plot_decision_table(
  x = results_all$ER,
  y = results_all$pNOB,
  z = results_all$PNI,
  title = "PNI",
  xlab = "Exploitation rate",
  ylab = "pNOB target",
  scenario = results_all$scenario
)
# Example of binned decision table

df <- expand.grid(
  SAR = seq(0.005, 0.03, 0.005),
  ER = seq(0, 0.5, 0.1)
)
df$value <- ifelse(5 * df$SAR + 0.2 > df$ER, 0.75, 0.05)
df$value <- ifelse(df$SAR < 0.02 & df$ER > 0.4, 0.04, df$value)

plot_decision_table2(
  x = df$SAR,
  y = df$ER,
  z = df$value,
  xlab = "Marine survival",
  ylab = "Exploitation rate",
  zlab = "Probability\nof objective"
)

salmonMSE documentation built on Aug. 20, 2026, 5:09 p.m.