Merge pull request #331 from m-muecke/set-values

refactor: use more `set_values()`
mlr-org · Jan 2, 2025 · 4f8d0d1 · 4f8d0d1
2 parents de0032f + fe2baf9
commit 4f8d0d1
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Showing 13 changed files with 13 additions and 13 deletions.
diff --git a/R/LearnerClassifKKNN.R b/R/LearnerClassifKKNN.R
@@ -36,7 +36,7 @@ LearnerClassifKKNN = R6Class("LearnerClassifKKNN",
         ykernel     = p_uty(default = NULL, tags = "train"),
         store_model = p_lgl(default = FALSE, tags = "train")
       )
-      ps$values = list(k = 7L)
+      ps$set_values(k = 7L)
 
       super$initialize(
         id = "classif.kknn",

diff --git a/R/LearnerClassifNnet.R b/R/LearnerClassifNnet.R
@@ -52,7 +52,7 @@ LearnerClassifNnet = R6Class("LearnerClassifNnet",
         trace     = p_lgl(default = TRUE, tags = "train"),
         formula   = p_uty(tags = "train")
       )
-      ps$values = list(size = 3L)
+      ps$set_values(size = 3L)
 
       super$initialize(
         id = "classif.nnet",

diff --git a/R/LearnerClassifRanger.R b/R/LearnerClassifRanger.R
@@ -76,7 +76,7 @@ LearnerClassifRanger = R6Class("LearnerClassifRanger",
         write.forest                 = p_lgl(default = TRUE, tags = "train")
       )
 
-      ps$values = list(num.threads = 1L)
+      ps$set_values(num.threads = 1L)
 
       super$initialize(
         id = "classif.ranger",

diff --git a/R/LearnerClassifXgboost.R b/R/LearnerClassifXgboost.R
@@ -157,7 +157,7 @@ LearnerClassifXgboost = R6Class("LearnerClassifXgboost",
       )
 
       # custom defaults
-      ps$values = list(nrounds = 1000L, nthread = 1L, verbose = 0L)
+      ps$set_values(nrounds = 1000L, nthread = 1L, verbose = 0L)
 
       super$initialize(
         id = "classif.xgboost",

diff --git a/R/LearnerRegrCVGlmnet.R b/R/LearnerRegrCVGlmnet.R
@@ -71,7 +71,7 @@ LearnerRegrCVGlmnet = R6Class("LearnerRegrCVGlmnet",
         upper.limits         = p_uty(tags = "train")
       )
 
-      ps$values = list(family = "gaussian")
+      ps$set_values(family = "gaussian")
 
       super$initialize(
         id = "regr.cv_glmnet",

diff --git a/R/LearnerRegrGlmnet.R b/R/LearnerRegrGlmnet.R
@@ -71,7 +71,7 @@ LearnerRegrGlmnet = R6Class("LearnerRegrGlmnet",
         upper.limits          = p_uty(tags = "train")
       )
 
-      ps$values = list(family = "gaussian")
+      ps$set_values(family = "gaussian")
 
       super$initialize(
         id = "regr.glmnet",

diff --git a/R/LearnerRegrKKNN.R b/R/LearnerRegrKKNN.R
@@ -37,7 +37,7 @@ LearnerRegrKKNN = R6Class("LearnerRegrKKNN",
         store_model = p_lgl(default = FALSE, tags = "train")
       )
 
-      ps$values = list(k = 7L)
+      ps$set_values(k = 7L)
 
       super$initialize(
         id = "regr.kknn",

diff --git a/R/LearnerRegrNnet.R b/R/LearnerRegrNnet.R
@@ -52,7 +52,7 @@ LearnerRegrNnet = R6Class("LearnerRegrNnet",
         trace     = p_lgl(default = TRUE, tags = "train"),
         formula   = p_uty(tags = "train")
       )
-      ps$values = list(size = 3L)
+      ps$set_values(size = 3L)
 
       super$initialize(
         id = "regr.nnet",

diff --git a/R/LearnerRegrRanger.R b/R/LearnerRegrRanger.R
@@ -58,7 +58,7 @@ LearnerRegrRanger = R6Class("LearnerRegrRanger",
         write.forest                 = p_lgl(default = TRUE, tags = "train")
       )
 
-      ps$values = list(num.threads = 1L)
+      ps$set_values(num.threads = 1L)
 
       super$initialize(
         id = "regr.ranger",

diff --git a/R/LearnerRegrXgboost.R b/R/LearnerRegrXgboost.R
@@ -135,7 +135,7 @@ LearnerRegrXgboost = R6Class("LearnerRegrXgboost",
       # param deps
 
       # custom defaults
-      ps$values = list(nrounds = 1000L, nthread = 1L, verbose = 0L)
+      ps$set_values(nrounds = 1000L, nthread = 1L, verbose = 0L)
 
       super$initialize(
         id = "regr.xgboost",

diff --git a/tests/testthat/test_classif_kknn.R b/tests/testthat/test_classif_kknn.R
@@ -28,7 +28,7 @@ test_that("custom model", {
   expect_data_table(mod$data)
   expect_list(mod$pv, names = "unique")
 
-  learner$param_set$values = list(k = 3, store_model = FALSE)
+  learner$param_set$set_values(k = 3, store_model = FALSE)
   learner$train(task)$predict(task)
   expect_null(learner$model$kknn)
 })

diff --git a/tests/testthat/test_classif_ranger.R b/tests/testthat/test_classif_ranger.R
@@ -3,7 +3,7 @@ skip_if_not_installed("ranger")
 test_that("autotest", {
   learner = mlr3::lrn("classif.ranger")
   expect_learner(learner)
-  learner$param_set$values = list(num.trees = 30L, importance = "impurity")
+  learner$param_set$set_values(num.trees = 30L, importance = "impurity")
   result = run_autotest(learner)
   expect_true(result, info = result$error)
 })

diff --git a/tests/testthat/test_regr_kknn.R b/tests/testthat/test_regr_kknn.R
@@ -28,7 +28,7 @@ test_that("custom model", {
   expect_data_table(mod$data)
   expect_list(mod$pv, names = "unique")
 
-  learner$param_set$values = list(k = 3, store_model = FALSE)
+  learner$param_set$set_values(k = 3, store_model = FALSE)
   learner$train(task)$predict(task)
   expect_null(learner$model$kknn)
 })