fix PMCMRplus

.Rbuildignore

@@ -14,3 +14,4 @@ man-roxygen
 ^\.lintr
 ^.editorconfig$
 ^.ignore$
+^.vscode

.gitignore

@@ -102,3 +102,5 @@ $RECYCLE.BIN/
 !.vscode/extensions.json
 *.code-workspace
 .vscode
+check/*
+CRAN-RELEASE

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mlr3benchmark
 Title: Analysis and Visualisation of Benchmark Experiments
-Version: 0.1.2.9000
+Version: 0.1.3
 Authors@R:
     c(person(given = "Sonabend",
            family = "Raphael",
@@ -36,10 +36,10 @@ Imports:
     ggplot2,
     mlr3misc,
     R6
-Suggests: 
+Suggests:
     mlr3,
     mlr3learners,
-    PMCMR,
+    PMCMRplus,
     rpart,
     testthat,
     xgboost

NEWS.md

@@ -1,6 +1,7 @@
-# mlr3benchmark 0.1.2.9000
+# mlr3benchmark 0.1.3
 
 * Fix README
+* Fix for PMCMRplus
 
 # mlr3benchmark 0.1.2
 

R/BenchmarkAggr.R

@@ -207,7 +207,7 @@ BenchmarkAggr = R6Class("BenchmarkAggr",
     },
 
     #' @description Posthoc Friedman Nemenyi tests. Computed with
-    #' [PMCMR::posthoc.friedman.nemenyi.test]. If global `$friedman_test` is non-significant then
+    #' [PMCMRplus::frdAllPairsNemenyiTest]. If global `$friedman_test` is non-significant then
     #' this is returned and no post-hocs computed. Also returns critical difference
     #' @param meas `(character(1))` \cr
     #' Measure to rank the data against, should be in `$measures`. Can be `NULL` if only one measure
@@ -216,8 +216,8 @@ BenchmarkAggr = R6Class("BenchmarkAggr",
     #' p.value for which the global test will be considered significant.
     friedman_posthoc = function(meas = NULL, p.value = 0.05) { # nolint
 
-      if (!requireNamespace("PMCMR", quietly = TRUE)) {
-        stop("Package PMCMR required for post-hoc Friedman tests.")
+      if (!requireNamespace("PMCMRplus", quietly = TRUE)) {
+        stop("Package PMCMRplus required for post-hoc Friedman tests.")
       }
 
       if (self$nlrns == 2) {
@@ -242,7 +242,7 @@ BenchmarkAggr = R6Class("BenchmarkAggr",
       if (f.rejnull) {
         form = as.formula(paste0(meas, " ~ ", self$col_roles$learner_id, " | ",
                                  self$col_roles$task_id))
-        nem_test = PMCMR::posthoc.friedman.nemenyi.test(form, data = private$.dt) # nolint
+        nem_test = PMCMRplus::frdAllPairsNemenyiTest(form, data = private$.dt) # nolint
         nem_test$f.rejnull = f.rejnull # nolint
         return(nem_test)
       } else {

R/autoplot.BenchmarkAggr.R

@@ -64,7 +64,7 @@
 #' # mean and error bars
 #' autoplot(obj, type = "mean", level = 0.95)
 #'
-#' if (requireNamespace("PMCMR", quietly = TRUE)) {
+#' if (requireNamespace("PMCMRplus", quietly = TRUE)) {
 #'   # critical differences
 #'   autoplot(obj, type = "cd",style = 1)
 #'   autoplot(obj, type = "cd",style = 2)

tests/testthat/test_BenchmarkAggr.R

@@ -63,7 +63,7 @@ test_that("public methods", {
                data.table(tasks = factor(c("A", "B")), learners = factor(c("L3", "L3")),
                           RMSE = c(3, 4), MSE = c(9, 16)))
 
-  skip_if_not_installed("PMCMR")
+  skip_if_not_installed("PMCMRplus")
   expect_error(ba$friedman_posthoc(), "measures")
   expect_warning(ba$friedman_posthoc(meas = "RMSE"), "Cannot reject")
   expect_silent(ba$friedman_posthoc(p.value = 0.9, meas = "RMSE"))

tests/testthat/test_autoplot_BenchmarkAggr.R

@@ -8,13 +8,13 @@ test_that("autoplot.BenchmarkAggr", {
   expect_true(is.ggplot(autoplot(ba, type = "mean")))
   expect_true(is.ggplot(autoplot(ba, type = "box")))
 
-  skip_if_not_installed("PMCMR")
+  skip_if_not_installed("PMCMRplus")
   expect_true(is.ggplot(autoplot(ba, type = "fn")))
   expect_true(is.ggplot(autoplot(ba, type = "cd")))
 })
 
 test_that("autoplot.BenchmarkAggr cd", {
-  skip_if_not_installed("PMCMR")
+  skip_if_not_installed("PMCMRplus")
 
   set.seed(1)
   df = data.frame(task_id = factor(rep(c("A", "B"), each = 5)),
@@ -30,19 +30,21 @@ test_that("autoplot.BenchmarkAggr cd", {
 })
 
 test_that("autoplot with BenchmarkAggr from mlr3::benchmark()", {
-  skip_if_not_installed("PMCMR")
+  skip_if_not_installed("PMCMRplus")
   skip_if_not_installed("mlr3")
   skip_if_not_installed("ggplot2")
   skip_if_not_installed("mlr3learners")
   skip_if_not_installed("rpart")
-  skip_if_not_installed("ranger")
   set.seed(1)
 
   library("mlr3")
-  task = tsks(c("iris", "sonar", "wine", "zoo"))
-  learns = lrns(c("classif.featureless", "classif.rpart", "classif.ranger"))
+
+  task = tsks(c("iris", "sonar"))
+  learns = c(lrns(c("classif.featureless", "classif.rpart")),
+    lrn("classif.rpart", id = "rpart2")
+  )
   bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
-  ba = BenchmarkAggr$new(bm$aggregate())
+  ba = as.BenchmarkAggr(bm)
 
-  expect_true(ggplot2::is.ggplot(autoplot(ba, type = "cd")))
+  expect_true(ggplot2::is.ggplot(autoplot(ba, type = "cd", p.value = 0.2)))
 })