
library(testthat)

source("user_code.R")
test_that("returns correct sign for mixed vector", {
  expect_equal(
    determine_sign(c(3, -2, 0, 7, -5)),
    c("positive", "negative", "zero", "positive", "negative"),
    info = "Should classify each element as positive, negative, or zero."
  )
})

test_that("returns correct sign for all zeros", {
  expect_equal(
    determine_sign(c(0, 0, 0)),
    c("zero", "zero", "zero"),
    info = "Should return 'zero' for all elements if all are zero."
  )
})

test_that("returns correct sign for positive and negative only", {
  expect_equal(
    determine_sign(c(-1, 1)),
    c("negative", "positive"),
    info = "Should return 'negative' for -1 and 'positive' for 1."
  )
})

test_that("returns correct sign for only positives", {
  expect_equal(
    determine_sign(c(2, 8)),
    c("positive", "positive"),
    info = "Should return 'positive' for all positive numbers."
  )
})

test_that("returns correct sign for only negatives", {
  expect_equal(
    determine_sign(c(-3, -7)),
    c("negative", "negative"),
    info = "Should return 'negative' for all negative numbers."
  )
})

test_main.R

Master the art of writing and using functions in R, from basic syntax to advanced functional programming techniques. This course guides you through creating your own functions, leveraging anonymous functions, and applying functional programming concepts to solve real-world problems in R.

Learn how to define, call, and utilize functions in R, including understanding parameters, return values, and default arguments.

Discover how to use anonymous (inline) functions for concise, on-the-fly operations, and see how they fit into R's functional programming paradigm.

Apply functional programming concepts in R to solve real-world problems, focusing on writing concise, reusable, and efficient code.

Challenge: Inline Functions with apply

Løsning

Challenge: Inline Functions with apply

Løsning