Test: util_lapply

Ivan Jacob Agaloos Pesigan

2021-01-15

library(testthat)
library(jeksterslabRutils)
context("Test util_lapply.")

Parameters

FUN <- rnorm
n <- 10000
mu <- 100
sigma <- 15
args <- list(
  n = rep(
    x = n,
    times = 10000
  ),
  mean = mu,
  sd = sigma
)
par <- FALSE
ncores <- NULL
Variable <- c(
  "`FUN`",
  "`n`",
  "`mu` named as `mean` in `args`.",
  "`sigma` named as `sd` in `args`."
)
Description <- c(
  "Function.",
  "Number of observations.",
  "Population mean $\\left( \\mu \\right)$.",
  "Standard deviation $\\left( \\sigma \\right)$."
)
Value <- c(
  "`rnorm`",
  n,
  mu,
  sigma
)
knitr::kable(
  x = data.frame(
    Variable,
    Description,
    Value
  ),
  row.names = FALSE
)

Variable	Description	Value
FUN	Function.	rnorm
n	Number of observations.	10000
mu named as mean in args.	Population mean \(\left( \mu \right)\).	100
sigma named as sd in args.	Standard deviation \(\left( \sigma \right)\).	15

Run test

sample <- util_lapply(
  FUN = FUN,
  args = args,
  par = par,
  ncores = ncores
)
sample_means <- unlist(
  util_lapply(
    FUN = mean,
    args = c(x = sample),
    par = par,
    ncores = ncores
  )
)
mean_of_means <- mean(sample_means)
mean_of_ns <- mean(
  lengths(sample)
)

Results

Description <- c(
  "Sample size.",
  "Mean of means."
)
Parameter <- c(
  n,
  mu
)
Result <- c(
  mean_of_ns,
  mean_of_means
)
knitr::kable(
  x = data.frame(
    Description,
    Parameter,
    Result
  ),
  row.names = FALSE
)

Description	Parameter	Result
Sample size.	10000	10000.00000
Mean of means.	100	99.74345

test_that("sample size used is correct", {
  expect_equivalent(
    mean_of_ns,
    n
  )
})
#> Test passed 🥳

test_that("the mean of means converges to the population mean", {
  expect_equivalent(
    round(
      x = mean_of_means,
      digits = 0
    ),
    mu,
  )
})
#> Test passed 🥇