tests: use more specialised testthat functions

tests/testthat/test_GraphLearner.R

@@ -932,7 +932,7 @@ test_that("validation, internal_valid_scores", {
   # None of the Learners can do validation -> NULL
   glrn1 = as_learner(as_graph(lrn("classif.rpart")))$train(tsk("iris"))
   expect_false("validation" %in% glrn1$properties)
-  expect_equal(glrn1$internal_valid_scores, NULL)
+  expect_null(glrn1$internal_valid_scores)
 
   glrn2 = as_learner(as_graph(lrn("classif.debug")))
   expect_true("validation" %in% glrn2$properties)
@@ -945,7 +945,7 @@ test_that("validation, internal_valid_scores", {
 
   set_validate(glrn2, NULL)
   glrn2$train(tsk("iris"))
-  expect_true(is.null(glrn2$internal_valid_scores))
+  expect_null(glrn2$internal_valid_scores)
 
   # No validation set specified --> No internal_valid_scores
   expect_equal(
@@ -960,13 +960,13 @@ test_that("internal_tuned_values", {
   task = tsk("iris")
   glrn1 = as_learner(as_graph(lrn("classif.rpart")))$train(task)
   expect_false("internal_tuning" %in% glrn1$properties)
-  expect_equal(glrn1$internal_tuned_values, NULL)
+  expect_null(glrn1$internal_tuned_values)
 
   # learner wQ
   # ith internal tuning
   glrn2 = as_learner(as_graph(lrn("classif.debug")))
   expect_true("internal_tuning" %in% glrn2$properties)
-  expect_equal(glrn2$internal_tuned_values, NULL)
+  expect_null(glrn2$internal_tuned_values)
   glrn2$train(task)
   expect_equal(glrn2$internal_tuned_values, named_list())
   glrn2$param_set$set_values(classif.debug.early_stopping = TRUE, classif.debug.iter = 1000)
@@ -981,8 +981,8 @@ test_that("set_validate", {
   expect_equal(glrn$validate, "test")
   expect_equal(glrn$graph$pipeops$classif.debug$learner$validate, "predefined")
   set_validate(glrn, NULL)
-  expect_equal(glrn$validate, NULL)
-  expect_equal(glrn$graph$pipeops$classif.debug$learner$validate, NULL)
+  expect_null(glrn$validate)
+  expect_null(glrn$graph$pipeops$classif.debug$learner$validate)
   set_validate(glrn, 0.2, ids = "classif.debug")
   expect_equal(glrn$validate, 0.2)
   expect_equal(glrn$graph$pipeops$classif.debug$learner$validate, "predefined")
@@ -1002,7 +1002,7 @@ test_that("set_validate", {
   expect_equal(glrn2$validate, 0.25)
   expect_equal(glrn2$graph$pipeops$polearner$learner$validate, "predefined")
   expect_equal(glrn2$graph$pipeops$polearner$learner$graph$pipeops$final$learner$validate, "predefined")
-  expect_equal(glrn2$graph$pipeops$polearner$learner$graph$pipeops$classif.debug$learner$validate, NULL)
+  expect_null(glrn2$graph$pipeops$polearner$learner$graph$pipeops$classif.debug$learner$validate)
 
   # graphlearner in graphlearner: failure handling
   glrn = as_learner(po("pca") %>>% lrn("classif.debug"))
@@ -1013,15 +1013,15 @@ test_that("set_validate", {
     set_validate(gglrn, validate = "test", args = list(po_glrn = list(ids = "pca"))),
     "Trying to heuristically reset"
   )
-  expect_equal(gglrn$validate, NULL)
+  expect_null(gglrn$validate)
 
   # base_learner is not final learner
   glrn = as_learner(lrn("classif.debug") %>>% po("nop"))
   set_validate(glrn, 0.3)
   expect_equal(glrn$graph$pipeops$classif.debug$validate, "predefined")
   set_validate(glrn, NULL)
-  expect_equal(glrn$graph$pipeops$classif.debug$validate, NULL)
-  expect_equal(glrn$validate, NULL)
+  expect_null(glrn$graph$pipeops$classif.debug$validate)
+  expect_null(glrn$validate)
 
   # args and args_all
   bglrn = as_learner(ppl("branch", list(lrn("classif.debug", id = "d1"), lrn("classif.debug", id = "d2"))))
@@ -1033,13 +1033,13 @@ test_that("set_validate", {
   # args
   set_validate(gglrn, validate = 0.2, args = list(po_glrn = list(ids = "d1")))
   expect_equal(gglrn$graph$pipeops[[1L]]$learner$graph$pipeops$d1$validate, "predefined")
-  expect_equal(gglrn$graph$pipeops[[1L]]$learner$graph$pipeops$d2$validate, NULL)
+  expect_null(gglrn$graph$pipeops[[1L]]$learner$graph$pipeops$d2$validate)
 
   # args all
   gglrn = as_learner(obj)
   set_validate(gglrn, validate = 0.2, args_all = list(ids = "d1"))
   expect_equal(gglrn$graph$pipeops[[1L]]$learner$graph$pipeops$d1$validate, "predefined")
-  expect_equal(gglrn$graph$pipeops[[1L]]$learner$graph$pipeops$d2$validate, NULL)
+  expect_null(gglrn$graph$pipeops[[1L]]$learner$graph$pipeops$d2$validate)
 })
 
 test_that("marshal", {

tests/testthat/test_PipeOp.R

@@ -87,13 +87,13 @@ test_that("Informative error and warning messages", {
 
   # two 'expect_warning', because we want to 'expect' that there is exactly one warning.
   # a function argument for expect_warning that tests exactly this would be a good idea, and has therefore been removed -.-
-  expect_warning(expect_warning(gr$train(tsk("iris")), "This happened PipeOp classif.debug's \\$train\\(\\)$"), NA)
+  expect_no_warning(expect_warning(gr$train(tsk("iris")), "This happened PipeOp classif.debug's \\$train\\(\\)$"))
 
-  expect_warning(suppressWarnings(gr$train(tsk("iris"))), NA)
+  expect_no_warning(suppressWarnings(gr$train(tsk("iris"))))
 
-  expect_warning(expect_warning(gr$predict(tsk("iris")), "This happened PipeOp classif.debug's \\$predict\\(\\)$"), NA)
+  expect_no_warning(expect_warning(gr$predict(tsk("iris")), "This happened PipeOp classif.debug's \\$predict\\(\\)$"))
 
-  expect_warning(suppressWarnings(gr$predict(tsk("iris"))), NA)
+  expect_no_warning(suppressWarnings(gr$predict(tsk("iris"))))
 
 
   gr$param_set$values$classif.debug.warning_train = 0
@@ -119,8 +119,8 @@ test_that("Informative error and warning messages", {
     )
   )$new(id = "potest", input = data.table(name = "input", train = "*", predict = "*"), output = data.table(name = "input", train = "*", predict = "*"))
 
-  expect_warning(potest$train(list(1)), NA)
-  expect_warning(potest$predict(list(1)), NA)
+  expect_no_warning(potest$train(list(1)))
+  expect_no_warning(potest$predict(list(1)))
 
 })
 

tests/testthat/test_multiplicities.R

@@ -55,7 +55,7 @@ test_that("PipeOp - unpack_multiplicities", {
   expect_error(unpack_multiplicities(list(a = Multiplicity(x = 1, z = 2), b = Multiplicity(x = 10, y = 20)), c(0, 0), c("a", "b"), "test"), regexp = "bad multiplicities")
   expect_equal(unpack_multiplicities(list(a = Multiplicity(x = 1, z = 2), b = Multiplicity(x = 10, y = 20)), c(0, 1), c("a", "b"), "test"),
     list(x = list(a = 1, b = Multiplicity(x = 10, y = 20)), z = list(a = 2, b = Multiplicity(x = 10, y = 20))))
-  expect_equal(unpack_multiplicities(list(0), 0, "a", "test"), NULL)
+  expect_null(unpack_multiplicities(list(0), 0, "a", "test"))
 })
 
 test_that("PipeOp - evaluate_multiplicities", {
@@ -112,7 +112,7 @@ test_that("PipeOp - evaluate_multiplicities", {
   old_state = po$state
   po$param_set$values$state = "error"
   expect_error(po$train(as.Multiplicity(list(0, as.Multiplicity(0)))), regexp = "Error")
-  expect_equal(po$state, NULL)  # state is completely reset to NULL
+  expect_null(po$state)  # state is completely reset to NULL
 })
 
 test_that("Graph - add_edge", {

tests/testthat/test_parvals.R

@@ -6,8 +6,8 @@ test_that("graph param vals", {
   gr$add_pipeop(PipeOpPCA$new())
   expect_equal(gr$ids(TRUE), c("scale", "pca"))
 
-  expect_equal(gr$pipeops$scale$param_set$values$center, NULL)
-  expect_equal(gr$param_set$values$scale.center, NULL)
+  expect_null(gr$pipeops$scale$param_set$values$center)
+  expect_null(gr$param_set$values$scale.center)
   gr$param_set$values$scale.center = FALSE
   expect_equal(gr$pipeops$scale$param_set$values$center, FALSE)
   expect_equal(gr$param_set$values$scale.center, FALSE)
@@ -16,8 +16,8 @@ test_that("graph param vals", {
   expect_equal(gr$param_set$values$scale.center, TRUE)
 
 
-  expect_equal(gr$pipeops$pca$param_set$values$center, NULL)
-  expect_equal(gr$param_set$values$pca.center, NULL)
+  expect_nulll(gr$pipeops$pca$param_set$values$center)
+  expect_null(gr$param_set$values$pca.center)
   gr$param_set$values$pca.center = FALSE
   expect_equal(gr$pipeops$pca$param_set$values$center, FALSE)
   expect_equal(gr$param_set$values$pca.center, FALSE)

tests/testthat/test_pipeop_learner.R

@@ -191,13 +191,13 @@ test_that("validation", {
   expect_equal(obj$validate, "predefined")
   expect_equal(obj$learner$validate, "predefined")
   set_validate(obj, NULL)
-  expect_equal(obj$validate, NULL)
-  expect_equal(obj$learner$validate, NULL)
+  expect_null(obj$validate)
+  expect_null(obj$learner$validate)
   expect_warning({obj$learner$validate = 0.3}, "unexpected behaviour") # nolint
 
   obj = as_pipeop(as_learner(as_graph(lrn("classif.debug"))))
   expect_error(set_validate(obj, "predefined", ids = "none_existing"), "Trying to heuristically")
-  expect_equal(obj$validate, NULL)
+  expect_null(obj$validate)
 })
 
 test_that("internal_tuned_values, internal_valid_scores", {

tests/testthat/test_typecheck.R

@@ -3,7 +3,7 @@ context("Typecheck")
 
 test_that("utility function works", {
   skip_if_not_installed("rpart")
-  expect_equal(get_r6_inheritance("data.table"), NULL)
+  expect_null(get_r6_inheritance("data.table"))
 
   expect_equal(get_r6_inheritance("PipeOp"), "PipeOp")