R6 class representing a simulation manager.
R6 class to represent a manager for running multiple model
simulations and saving results.
# U Island example region coordinates <- data.frame(x = rep(seq(177.01, 177.05, 0.01), 5), y = rep(seq(-18.01, -18.05, -0.01), each = 5)) template_raster <- Region$new(coordinates = coordinates)$region_raster # full extent template_raster[][-c(7, 9, 12, 14, 17:19)] <- NA # make U Island region <- Region$new(template_raster = template_raster) raster::plot(region$region_raster, main = "Example region (indices)", xlab = "Longitude (degrees)", ylab = "Latitude (degrees)", colNA = "blue") # Example population model template model_template <- PopulationModel$new(region = region, time_steps = 10, # years populations = region$region_cells, # 7 stage_matrix = 1) # Example generators for initial abundance and carrying capacity hs_matrix <- c(0.5, 0.3, 0.7, 0.9, 0.6, 0.7, 0.8) initial_gen <- Generator$new(description = "initial abundance", region = region, hs_matrix = hs_matrix, # template attached inputs = c("initial_n"), outputs = c("initial_abundance")) initial_gen$add_generative_requirements(list(initial_abundance = "function")) initial_gen$add_function_template("initial_abundance", function_def = function(params) stats::rmultinom(1, size = params$initial_n, prob = params$hs_matrix)[, 1] , call_params = c("initial_n", "hs_matrix")) capacity_gen <- Generator$new(description = "carrying capacity", region = region, hs_matrix = hs_matrix, # template attached inputs = c("density_max"), outputs = c("carrying_capacity")) capacity_gen$add_generative_requirements(list(carrying_capacity = "function")) capacity_gen$add_function_template("carrying_capacity", function_def = function(params) round(params$density_max*params$hs_matrix) , call_params = c("density_max", "hs_matrix")) # Sample input parameters sample_data <- data.frame(initial_n = c(40, 60, 80), density_max = c(15, 20, 25)) # Simulation manager sim_manager <- SimulationManager$new(sample_data = sample_data, model_template = model_template, generators = list(initial_gen, capacity_gen), parallel_cores = 2, results_dir = tempdir()) run_output <- sim_manager$run() run_output$summary dir(tempdir(), "*.RData") # includes 3 result files for (i in 1:3) print(paste("Run", i, "results:")) file_name <- paste0(sim_manager$get_results_filename(i), ".RData") print(readRDS(file.path(tempdir(), file_name))) dir(tempdir(), "*.txt") # plus simulation log
poems::GenericClass -> poems::GenericManager -> SimulationManager
attachedA list of dynamically attached attributes (name-value pairs).
sample_dataA data frame of sampled parameters for each simulation/result.
model_templateA SimulationModel (or inherited class) object with parameters common to all simulations.
nested_modelA SimulationModel (or inherited class) object with empty sample parameters and a nested model template common to all simulations.
generatorsA list of generators (Generator or inherited class) objects for generating simulation model values.
model_simulatorA ModelSimulator (or inherited class) object for running the simulations.
parallel_coresNumber of cores for running the simulations in parallel.
results_dirResults directory path.
results_extResult file extension (default is .RData).
results_filename_attributesA vector of: prefix (optional); attribute names (from the sample data frame); postfix (optional); utilized to construct results filenames.
error_messagesA vector of error messages encountered when setting model attributes.
warning_messagesA vector of warning messages encountered when setting model attributes.
new()
Initialization method sets any included attributes (sample_data, model_template, generators, model_simulator, parallel_cores, results_dir, results_filename_attributes) and attaches other attributes individually listed.
SimulationManager$new(model_template = NULL, ...)
model_templateA SimulationModel (or inherited class) object with parameters common to all simulations.
...Parameters listed individually.
run()
Runs the multiple population simulations (via the set function), stores the results, and creates/writes a simulation log.
SimulationManager$run(results_dir = NULL)
results_dirResults directory path (must be present if not already set within manager class object).
Simulator log as a list.
set_model_sample()
Sets the model sample attributes via the sample data frame and the generators.
SimulationManager$set_model_sample(model, sample_index)
modelSimulationModel (or inherited class) object (clone) to receive sample attributes.
sample_indexIndex of sample from data frame.
log_simulation()
Summarizes the simulation log generated within the run method and writes it to a text file in the results directory.
SimulationManager$log_simulation(simulation_log)
simulation_logNested list of simulation log entries generated via the run method.
clone()
The objects of this class are cloneable with this method.
SimulationManager$clone(deep = FALSE)
deepWhether to make a deep clone.
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.