Simulate data from discrete power law distribution in parallel

simulate_power_distributed_discrete.R

library(xfun)
pkg_attach2("tidyverse", "poweRlaw", "furrr")
plan(multiprocess)


# Simulate from a discrete power law
# @param counter numeric, to enable mapping
# @param n integer, number of draws
# @param xmin numeric, minimum value subject to power law
# @param alpha, scaling parameter
#
# @importFrom poweRlaw rpldis

pwrdis_counter <- function(counter = 1, n = 1e4, xmin = 2, alpha = 3,
                           drop_box_outliers = FALSE,
                           drop_99p_outliers = FALSE) {
    x <- rpldis(n, xmin = xmin, alpha = alpha)
    if (isTRUE(drop_box_outliers)) 
        x <- x[!x %in% boxplot.stats(x)$out]
    if (isTRUE(drop_99p_outliers))
        x <- x[x < quantile(x = x, probs = 0.99)]
    return(x)    
}

# Simulate in parallel
# @param n integer, number of simulations
#
# @importFrom furrr future_map future_map_dbl
sim_many <- function(n, ...) {
    ndraws %>%
        future_map(pwrdis_counter, ...) %>%
        future_map_dbl(mean)
}