PopulationResults: R6 class representing population simulator results.

In poems: Pattern-Oriented Ensemble Modeling System

R6 class representing population simulator results.

Description

R6 class encapsulating and dynamically generating spatially-explicit population_simulator results, as well as optional re-generated Generator outputs.

Super classes

poems::GenericClass -> poems::GenericModel -> poems::SpatialModel -> poems::SimulationResults -> PopulationResults

Public fields

attached

A list of dynamically attached attributes (name-value pairs).

Active bindings

model_attributes

A vector of model attribute names.

region

A Region (or inherited class) object specifying the study region.

coordinates

Data frame (or matrix) of X-Y population (WGS84) coordinates in longitude (degrees West) and latitude (degrees North) (get and set), or distance-based coordinates dynamically returned by region raster (get only).

time_steps

Number of simulation time steps.

burn_in_steps

Optional number of initial 'burn-in' time steps to be ignored.

occupancy_mask

Optional binary mask array (matrix), data frame, or raster (stack) for each cell at each time-step of the simulation including burn-in.

trend_interval

Optional time-step range (indices) for trend calculations (assumes indices begin after the burn-in when utilized).

abundance

Population abundance across simulation time-steps (summary list or replicate array).

abundance_stages

Population abundance for combined stages across simulation time-steps (list of summary lists or replicate arrays for each combined stage).

abundance_trend

Trend or average Sen's slope of abundance (optionally across a time-step interval).

ema

Array of population expected minimum abundance (EMA) across simulation time-steps.

extirpation

Array of population extirpation times.

extinction_location

The weighted centroid of cells occupied in the time-step prior to the extirpation of all populations (if it occurred).

harvested

Number of animals harvested from each population across simulation time-steps (summary list or replicate array).

harvested_stages

Number of animals harvested from each population for combined stages across simulation time-steps (list of summary lists or replicate arrays for each combined stage).

occupancy

Array of the number of populations occupied at each time-step.

all

Nested simulation results for all cells.

parent

Parent simulation results for individual cells.

default

Default value/attribute utilized when applying primitive metric functions (e.g. max) to the results.

attribute_aliases

A list of alternative alias names for model attributes (form: alias = "attribute") to be used with the set and get attributes methods.

error_messages

A vector of error messages encountered when setting model attributes.

warning_messages

A vector of warning messages encountered when setting model attributes.

Methods

Public methods

• PopulationResults$clone()

Inherited methods

• poems::GenericModel$get_attribute()
• poems::GenericModel$get_attribute_aliases()
• poems::SimulationResults$get_attribute_names()
• poems::SimulationResults$get_attributes()
• poems::SimulationResults$initialize()
• poems::SimulationResults$new_clone()
• poems::SimulationResults$set_attributes()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PopulationResults$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# 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")
# Sample results occupancy (ignore cell 2 in last 5 time steps)
occupancy_raster <- region$raster_from_values(array(1, c(7, 13)))
occupancy_raster[region$region_indices][2, 9:13] <- 0
occupancy_raster[region$region_indices]
# Population simulation example results
example_results <- list(abundance = t(apply(matrix(11:17), 1, function(n)  {
  c(rep(n, 3), round(n*exp(-(0:9)/2)))}
)))
example_results$harvested <- round(example_results$abundance*0.3)
example_results
# Population results object
pop_results <- PopulationResults$new(region = region,
                                     time_steps = 13,
                                     burn_in_steps = 3,
                                     occupancy_mask = occupancy_raster,
                                     trend_interval = 1:5)
pop_results$get_attribute_names(all = TRUE)
# Clone (for each population simulation results)
results_clone <- pop_results$new_clone(results = example_results)
results_clone$all$get_attribute("abundance")
results_clone$get_attributes(c("abundance", "all$abundance",
                               "abundance_trend", "all$abundance_trend",
                               "all$ema", # only defined for all
                               "extirpation", "all$extirpation",
                               "all$extinction_location", # only defined for all
                               "harvested", "all$harvested",
                               "occupancy", "all$occupancy"))

poems documentation built on Oct. 7, 2023, 9:06 a.m.