tests/testthat/helper-data.R

In infer: Tidy Statistical Inference

set.seed(4242)

expect_doppelganger <- function(title, fig, ...) {
  testthat::skip_if_not_installed("vdiffr")
  vdiffr::expect_doppelganger(title, fig, ...)
}

eps <- if (capabilities("long.double")) {
  sqrt(.Machine$double.eps)
} else {
  0.01
}

gss_tbl <- tibble::as_tibble(gss) |>
  dplyr::filter(!(is.na(sex) | is.na(college))) |>
  dplyr::mutate(partyid = as.character(partyid)) |>
  dplyr::filter(partyid %in% c("ind", "rep", "dem"))

gss_calc <- gss_tbl |>
  specify(college ~ sex, success = "no degree") |>
  hypothesize(null = "independence") |>
  generate(reps = 1000, type = "permute") |>
  calculate(stat = "diff in props", order = c("female", "male"))

mtcars_df <- mtcars |>
  dplyr::mutate(
    cyl = factor(cyl),
    vs = factor(vs),
    am = factor(am),
    gear = factor(gear),
    carb = factor(carb)
  )

obs_diff <- gss_tbl |>
  specify(college ~ sex, success = "no degree") |>
  calculate(stat = "diff in props", order = c("female", "male"))

set.seed(2018)
test_df <- tibble::tibble(stat = rnorm(100))

# Data for visualization tests

gss_permute <- gss_tbl |>
  specify(college ~ sex, success = "no degree") |>
  hypothesize(null = "independence") |>
  generate(reps = 100, type = "permute") |>
  calculate(stat = "z", order = c("female", "male"))

gss_viz_sim <- gss_permute |> visualize(method = "simulation")

# Warnings are about checking conditions for the theoretical method.
gss_viz_theor <- suppressWarnings(suppressMessages(
  gss_permute |> visualize(method = "theoretical")
))
gss_viz_both <- suppressWarnings(
  gss_permute |> visualize(method = "both")
)