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Tidy Simulation Output from simmar

Source: R/process_marlin.R
process_marlin.Rd

Converts the nested list output of simmar into two tidy tibbles: one for population state ($fauna) and one for fleet outcomes ($fleets). This is the primary post-processing step before plotting or analysis.

Usage

process_marlin(sim, steps_to_keep = NULL, time_step = NULL, keep_age = TRUE)

Arguments

sim

Named list returned by simmar. Step names should follow the "year_season" convention (with optional "step_" prefix, which is automatically stripped).

steps_to_keep

Character or integer vector of step names / indices to include in the output. Useful for reducing memory use when only the final years are needed. Default NULL keeps all steps.

time_step

Numeric. Fraction of a year per step (e.g. 0.25 for quarterly seasons). When NULL, inferred from the step names in sim (requires at least two steps).

keep_age

Logical. If TRUE (default), return age-structured output. If FALSE, aggregate across all ages before returning.

Value

A named list with two elements:

fauna

Tibble of population state; see Details.

fleets

Tibble of fleet outcomes; see Details.

Details

Output columns

$fauna — one row per critter × patch × age × step:

  • critter: species name

  • patch: patch index

  • x, y: spatial coordinates

  • age: age class (numeric)

  • mean_length: mean length at age (from life history)

  • step: decimal year (e.g. 5.75 = year 5, season 4 of 4)

  • n: numbers at age

  • b: biomass at age

  • ssb: spawning stock biomass at age

  • c: catch in numbers at age

$fleets — one row per critter × patch × age × fleet × step:

  • critter, patch, x, y, age, fleet, step, mean_length: as above

  • catch: catch in numbers

  • revenue: revenue

  • effort: effort units

  • cpue: catch per unit effort (NA where effort = 0)

When keep_age = FALSE, age classes are summed and a single age = "all" row is returned per spatial unit per step.

See also

simmar, plot_marlin

Examples

if (FALSE) { # \dontrun{
sim <- simmar(fauna = fauna, fleets = fleets, years = 50)

# Full output (all steps, all ages)
proc <- process_marlin(sim, time_step = 1)

# Last 10 years only, aggregated across ages
last_steps <- tail(names(sim), 10)
proc_last  <- process_marlin(sim,
                             steps_to_keep = last_steps,
                             time_step     = 1,
                             keep_age      = FALSE)

# Plot SSB over time
plot_marlin(proc, plot_var = "ssb", plot_type = "time")
} # }