In pratikunterwegs/kleptomove-ms: R code for the Kleptomove Simulation

Get transformed weight frequency data

These are the tanh scaled weights, and not the relative preferences.

Load libraries

# load libs
library(data.table)
library(stringr)
# load local functions in `R/`
devtools::load_all()

Get transformed cue preferences

Prepare data paths.

# read paths
paths <- list.dirs("data/", recursive = F)
paths <- paths[grep("rep_", paths)]

# make df
data = CJ(
  path = paths
)

# get replicate
data[, rep := as.numeric(
  stringr::str_extract_all(path, "rep_(\\d{3})") |> 
    stringr::str_extract_all("\\d{3}")
)]

# get sim type
data[, sim_type := stringr::str_extract(
  path, "obligate|facultative|foragers|random"
 ) 
]

data[, regrowth := as.numeric(str_extract(path, "(0\\.\\d+)"))]

# select the default scenario with regrowth == 0.01
data = data[regrowth == 0.01,]

Get frequencies of evolved cue preferences using the custom function get_sim_weight_evol, documented in R/fun_weight_evo.R

# from each simulation
temp_gen_data <- lapply(
  data$path,
  function(x) {

    # this applies a custom function to each simulation replicate
    get_sim_weight_evol(
      data_folder = x,
      generations = unique(
        c(
          seq(1, 999, 2)
        )
      ),
      which_weight = NA
    )
  }
)

# bind with parameters
data[, wt_data := temp_gen_data]

# unnest
data <- data[, unlist(wt_data, recursive = F),
  by = list(sim_type, rep, regrowth)
]

fwrite(data, file = "data/results/data_relative_preference_evolution.csv")