poems (version 1.3.2)

population_results: Nested functions for initializing, calculating and collecting population simulator results.

Description

Modular functions for the population simulator for initializing, calculating and collecting simulator results.

Usage

population_results(
  replicates,
  time_steps,
  coordinates,
  initial_abundance,
  results_selection = NULL,
  result_stages = NULL
)

Value

List of result functions:

initialize_attributes = function())

Constructs and returns an initialized nested list for the selected result attributes.

initialize_replicate = function(results)

Initializes and returns nested result attributes at the start of each replicate.

calculate_at_timestep = function(r, tm, stage_abundance, harvested, results)

Appends and calculates (non-NULL) results and returns nested result attributes at the end of each time step (tm) within replicate (r).

finalize_attributes = function(results)

Finalizes result calculations at the end of the simulation.

Arguments

replicates

Number of replicate simulation runs.

time_steps

Number of simulation time steps.

coordinates

Data frame (or matrix) of X-Y population coordinates.

initial_abundance

Matrix of initial abundances at each stage (in rows) for each population (in columns).

results_selection

List of results selection from: "abundance" (default), "ema", "extirpation", "extinction_location", "harvested", "occupancy"; "summarize" (default) or "replicate".

result_stages

Array of booleans or numeric (0, 1, 2, ...) for each stage to indicate which stages are included/combined (each unique digit > 0; optionally named) in the results (default is 1 for all stages).

Examples

coordinates <- array(c(1:4, 4:1), c(7, 2))
initial_abundance <- matrix(c(
  7, 13, 0, 26, 0, 39, 47,
  2, 0, 6, 8, 0, 12, 13,
  0, 3, 4, 6, 0, 9, 10
), nrow = 3, ncol = 7, byrow = TRUE)
results_selection <- c("abundance", "ema", "extirpation", 
                        "extinction_location", "harvested", "occupancy")
result_functions <- population_results(
  replicates = 1, time_steps = 10, coordinates, initial_abundance,
  results_selection = results_selection, result_stages = c(0, 1, 1)
)
result_functions$initialize_attributes()