Merge pull request #56 from mayer79/test-convert-revert

Add unit test, some formatting

R/missRanger.R

@@ -375,8 +375,14 @@ convert <- function(X, check = FALSE) {
  stopifnot(is.data.frame(X))
 
  if (!ncol(X)) {
- return(list(X = X, bad = character(0), vars = character(0), 
- types = character(0), classes = character(0)))
+ out <- list(
+ X = X, 
+ bad = character(0), 
+ vars = character(0), 
+ types = character(0), 
+ classes = character(0)
+ )
+ return(out)
  }
 
  types <- vapply(X, typeof2, FUN.VALUE = "")

R/pmm.R

@@ -22,12 +22,14 @@
 #' pmm(xtrain = c("A", "A", "B"), xtest = "A", ytrain = c(2, 2, 4), k = 2) # 2
 #' pmm(xtrain = factor(c("A", "B")), xtest = factor("C"), ytrain = 1:2) # 2
 pmm <- function(xtrain, xtest, ytrain, k = 1L, seed = NULL) {
- stopifnot(length(xtrain) == length(ytrain), 
- sum(ok <- !is.na(xtrain) & !is.na(ytrain)) >= 1L,
- (nt <- length(xtest)) >= 1L, !anyNA(xtest),
- mode(xtrain) %in% c("logical", "numeric", "character"),
- mode(xtrain) == mode(xtest),
- k >= 1L)
+ stopifnot(
+ length(xtrain) == length(ytrain), 
+ sum(ok <- !is.na(xtrain) & !is.na(ytrain)) >= 1L,
+ (nt <- length(xtest)) >= 1L, !anyNA(xtest),
+ mode(xtrain) %in% c("logical", "numeric", "character"),
+ mode(xtrain) == mode(xtest),
+ k >= 1L
+ )
 
  xtrain <- xtrain[ok]
  ytrain <- ytrain[ok]

tests/testthat/test-missRanger.R

@@ -208,3 +208,26 @@ test_that("Extremely wide datasets are handled", {
  data[5L, 5L] <- NA
  expect_no_error(missRanger(as.data.frame(data), num.trees = 3L, verbose = 0L))
 })
+
+test_that("Convert and revert do what they should", {
+ n <- 20L
+ X <- data.frame(
+ x1 = seq_len(n), 
+ x2 = rep(LETTERS[1:4], n %/% 4),
+ x3 = factor(rep(LETTERS[1:2], n %/% 2)),
+ x4 = seq_len(n) > n %/% 3,
+ x5 = seq(as.Date("2008-11-01"), as.Date("2008-11-21"), length.out = n)
+ )
+ X <- generateNA(X, seed = 1L)
+ conv <- convert(X)
+ reve <- revert(conv)
+
+ expect_equal(X, reve)
+ expect_equal(
+ unname(sapply(conv$X, class)), 
+ c("integer", "factor", "factor", "factor", "numeric")
+ )
+
+ Ximp <- missRanger(X, seed = 1L, verbose = FALSE, pmm.k = 3L)
+ expect_equal(sapply(Ximp, class), sapply(X, class))
+})