tests/testthat/test-count.r

In hadley/plyr: Tools for Splitting, Applying and Combining Data

library(testthat)
context("Count")

count_f <- function(...) count(...)$freq
table_f <- function(...) {
  x <- unname(as.numeric(table(rev(...))))
  x[x != 0]
}

test_that("count matches table", {
  data <- list(
    mtcars["cyl"],
    mtcars["mpg"],
    mtcars[c("cyl", "vs")])

  for (datum in data) {
    expect_that(count_f(datum), equals(table_f(datum)))
  }

})

test_that("random order doesn't affect count", {
  usual <- count(mtcars, "cyl")

  for (i in 1:5) {
    mtcars_r <- mtcars[sample(1:nrow(mtcars)), ]
    expect_that(count(mtcars_r, "cyl"), equals(usual))
  }

})

test_that("weighted count matches xtab", {
  xt1 <- as.data.frame(xtabs(g ~ id, data = baseball), responseName = "freq")
  xt1$id <- as.character(xt1$id)
  ct1 <- count(baseball, "id", "g")

  expect_that(ct1, equals(xt1))

  xt2 <- as.data.frame(xtabs(g ~ year + team, data = baseball),
    responseName = "freq")
  xt2 <- subset(xt2, freq > 0)
  xt2$year <- as.numeric(as.character(xt2$year))
  xt2$team <- as.character(xt2$team)
  xt2 <- arrange(xt2, year, team)
  ct2 <- count(baseball, c("year", "team"), "g")

  expect_that(ct2, equals(xt2))

})

test_that("count works with factors and dates", {
  genders <- c("Female", "Male")
  n <- c(5, 10)
  gender_data <- factor(rep.int(genders, n))

  expect_equal(
    count(gender_data),
    data.frame(x = genders, freq = n, stringsAsFactors = TRUE)
  )

  this_week <- seq(Sys.Date(), Sys.Date() + 6, "1 day")
  n2 <- 1:7
  day_data <- rep(this_week, n2)

  expect_equal(count(day_data), data.frame(x = this_week, freq = n2))
})

test_that("vaggregate corner cases", {
  res <- vaggregate(1:99, rep(1:11, 9), sum)
  expect_equal(res, vaggregate(1:99, expand.grid(1:11, 1:9)[,1,drop=FALSE], sum))
  expect_equal(res, vaggregate(1:99, rep(0.5 + (1:11), 9), sum, .default = 1))
})