renaming

R/GraphLearner.R

@@ -173,7 +173,7 @@ GraphLearner = R6Class("GraphLearner", inherit = Learner,
     }
   ),
   private = list(
-    .contingent_properties = function() {
+    .dependent_properties = function() {
       if (some(self$graph$pipeops, function(p) "uses_test_task" %in% p$properties)) {
         "uses_test_task"
       } else {

R/PipeOp.R

@@ -340,11 +340,11 @@ PipeOp = R6Class("PipeOp",
       if (!missing(rhs)) {
         private$.properties = sort(assert_subset(rhs, mlr_reflections$pipeops$properties))
       }
-      contingent_properties = private$.contingent_properties()
-      if (!length(contingent_properties)) {
+      dependent_properties = private$.dependent_properties()
+      if (!length(dependent_properties)) {
         return(private$.properties)
       }
-      sort(c(private$.properties, contingent_properties))
+      sort(c(private$.properties, dependent_properties))
     },
     id = function(val) {
       if (!missing(val)) {
@@ -426,7 +426,7 @@ PipeOp = R6Class("PipeOp",
   ),
 
   private = list(
-    .contingent_properties = function(rhs) {
+    .dependent_properties = function(rhs) {
       character(0)
     },
     .properties = NULL,

R/PipeOpLearner.R

@@ -134,7 +134,7 @@ PipeOpLearner = R6Class("PipeOpLearner", inherit = PipeOp,
   ),
   private = list(
     .learner = NULL,
-    .contingent_properties = function() {
+    .dependent_properties = function() {
       if ("uses_test_task" %in% private$.learner$properties) {
         "uses_test_task"
       } else {

R/PipeOpLearnerCV.R

@@ -171,7 +171,7 @@ PipeOpLearnerCV = R6Class("PipeOpLearnerCV",
     }
   ),
   private = list(
-    .contingent_properties = function() {
+    .dependent_properties = function() {
       if ("uses_test_task" %in% private$.learner$properties) {
         "uses_test_task"
       } else {

tests/testthat/helper_functions.R

@@ -422,7 +422,7 @@ expect_datapreproc_pipeop_class = function(poclass, constargs = list(), task,
   expect_true(n_use >= 4)
   expect_true(task$nrow >= 5)
   # overlay between use and test rows
-  tasktrain$partition(tasktrain$row_roles$use[seq(n_use - 2, n_use)], "test", remove = FALSE)
+  tasktrain$divide(tasktrain$row_roles$use[seq(n_use - 2, n_use)], "test", remove = FALSE)
   tasktrain$row_roles$use = tasktrain$row_roles$use[seq(1, n_use - 2)]
 
   taskpredict = tasktrain$clone(deep = TRUE)

tests/testthat/test_GraphLearner.R

@@ -571,7 +571,7 @@ test_that("GraphLearner hashes", {
 test_that("early stopped xgboost learner works in graph", {
   graph = po("pca") %>>% po("select", selector = selector_name("PC1")) %>>% lrn("classif.debug", uses_test_task = TRUE)
   glrn = as_learner(graph)
-  task = tsk("iris")$partition(1:10, "test")
+  task = tsk("iris")$divide(1:10, "test")
   glrn$train(task)
   expect_true("PC1" %in% glrn$model$classif.debug$train_task$test_task$feature_names)
 })

tests/testthat/test_pipeop_impute.R

@@ -408,7 +408,7 @@ test_that("More tests for Integers", {
 test_that("impute, test rows and affect_columns", {
   po_impute = po("imputeconstant", affect_columns = selector_name("insulin"), constant = 2)
   task = tsk("pima")
-  task$partition(1:30, "test")
+  task$divide(1:30, "test")
   outtrain = po_impute$train(list(task))[[1L]]
   outpredict = po_impute$predict(list(task$test_task))[[1L]]
   expect_true(isTRUE(all.equal(outtrain$test_task$data(), outpredict$data())))