V0.3.1

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mlr3pipelines
 Title: Preprocessing Operators and Pipelines for 'mlr3'
-Version: 0.3.0-9000
+Version: 0.3.1
 Authors@R:
     c(person(given = "Martin",
              family = "Binder",
@@ -82,10 +82,11 @@ Suggests:
     methods,
     vtreat
 Remotes:
-    mlr-org/mlr3,
     Bioconductor/Biobase
 ByteCompile: true
 Encoding: UTF-8
+Config/testthat/edition: 3
+Config/testthat/parallel: true
 LazyData: true
 NeedsCompilation: no
 Roxygen: list(markdown = TRUE, r6 = FALSE)

NEWS.md

@@ -1,4 +1,4 @@
-# mlr3pipelines 0.3.0-9000
+# mlr3pipelines 0.3.1
 
 * Changed PipeOps:
   - PipeOpMissInd now also allows for setting type = integer
@@ -8,6 +8,12 @@
   - fix how pipeline_robustify determines the type of newly created columns when using PipeOpMissInd
   - PipeOpFeatureUnion: Fixed a minor bug when checking for duplicates
 * added an autotest for ParamSets of PipeOps: expect_valid_pipeop_param_set
+* More informative error message when PipeOp input value has wrong type
+* Fix automatic detection of R6 type hierarchy
+* Performance improvements for GraphLearner
+* GraphLearner allows custom id
+* Use parallel tests
+* Removed bibtex dependency
 
 # mlr3pipelines 0.3.0
 

tests/testthat/helper_compat.R

@@ -0,0 +1,12 @@
+
+# compatibility to with broken testthat v3 behaviour
+expect_equal = function(object, expected, ..., info = NULL, label = NULL) {
+  expect_true(all.equal(object, expected, ...), info = info, label = label)
+}
+
+# suppress warnings as long as half the world still uses v2
+context = function(...) suppressWarnings(testthat::context(...))
+expect_is = function(...) suppressWarnings(testthat::expect_is(...))
+expect_equivalent = function(...) suppressWarnings(testthat::expect_equivalent(...))
+
+library("checkmate")

tests/testthat/test_pipeop_encodeimpact.R

@@ -61,11 +61,11 @@ test_that("PipeOpImpactEncode on Classification", {
 
   op$param_set$values$smoothing = 1e-4
   op$train(list(testtask))
-  expect_equal(mean(abs(op$state$impact$a - expm), na.rm = TRUE), 0.5e-4)
+  expect_equal(mean(abs(op$state$impact$a - expm), na.rm = TRUE), 1e-4 / 2 - 1e-4^2 * 3 / 8)
 
   op$param_set$values$smoothing = 1e-8
   op$train(list(testtask))
-  expect_equal(mean(abs(op$state$impact$a - expm), na.rm = TRUE) * 1e4, 0.5e-4)
+  expect_equal(mean(abs(op$state$impact$a - expm), na.rm = TRUE), 0)  # equal to 0 within tolerance
 
   op$param_set$values$smoothing = 6.362e-9  # similar to what glm uses
   encoded = op$train(list(testtask))[[1]]$data()

tests/testthat/test_pipeop_textvectorizer.R

@@ -269,6 +269,6 @@ test_that("PipeOpTextVectorizer - factor sequence", {
   op = PipeOpTextVectorizer$new(param_vals = list(stopwords_language = "none", return_type = "factor_sequence", sequence_length = 4L))
   result = op$train(list(task$clone()$filter(2:3)))[[1]]
   prd = op$predict(list(task$clone()$filter(rows = 1L)))[[1]]
-  expect_true(all(is.na(prd$data()[, paste0("txt.V", 1:4)])))
+  expect_true(all(is.na(prd$data()[, paste0("txt.V", 1:4)])), info = paste(capture.output(print(prd$data())), collapse = "\n"))
   expect_true(prd$nrow == 1L)
 })