refactor: use more set_values() (#1239)

* refactor: use more set_values() * docs: adjust text to reference set_values for changing param set
mlr-org · Jan 6, 2025 · 9c95317 · 9c95317
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commit 9c95317
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Showing 19 changed files with 21 additions and 21 deletions.
diff --git a/R/Learner.R b/R/Learner.R
@@ -72,10 +72,10 @@
 #' All information about hyperparameters is stored in the slot `param_set` which is a [paradox::ParamSet].
 #' The printer gives an overview about the ids of available hyperparameters, their storage type, lower and upper bounds,
 #' possible levels (for factors), default values and assigned values.
-#' To set hyperparameters, assign a named list to the subslot `values`:
+#' To set hyperparameters, call the `set_values()` method on the `param_set`:
 #' ```
 #' lrn = lrn("classif.rpart")
-#' lrn$param_set$values = list(minsplit = 3, cp = 0.01)
+#' lrn$param_set$set_values(minsplit = 3, cp = 0.01)
 #' ```
 #' Note that this operation replaces all previously set hyperparameter values.
 #' If you only intend to change one specific hyperparameter value and leave the others as-is, you can use the helper function [mlr3misc::insert_named()]:

diff --git a/R/LearnerClassifDebug.R b/R/LearnerClassifDebug.R
@@ -37,7 +37,7 @@
 #' @export
 #' @examples
 #' learner = lrn("classif.debug")
-#' learner$param_set$values = list(message_train = 1, save_tasks = TRUE)
+#' learner$param_set$set_values(message_train = 1, save_tasks = TRUE)
 #'
 #' # this should signal a message
 #' task = tsk("penguins")

diff --git a/R/LearnerClassifFeatureless.R b/R/LearnerClassifFeatureless.R
@@ -34,7 +34,7 @@ LearnerClassifFeatureless = R6Class("LearnerClassifFeatureless", inherit = Learn
       ps = ps(
         method = p_fct(c("mode", "sample", "weighted.sample"), default = "mode", tags = "predict")
       )
-      ps$values = list(method = "mode")
+      ps$set_values(method = "mode")
       super$initialize(
         id = "classif.featureless",
         feature_types = mlr_reflections$task_feature_types,

diff --git a/R/LearnerClassifRpart.R b/R/LearnerClassifRpart.R
@@ -37,7 +37,7 @@ LearnerClassifRpart = R6Class("LearnerClassifRpart", inherit = LearnerClassif,
         usesurrogate   = p_int(0L, 2L, default = 2L, tags = "train"),
         xval           = p_int(0L, default = 10L, tags = "train")
       )
-      ps$values = list(xval = 0L)
+      ps$set_values(xval = 0L)
 
       super$initialize(
         id = "classif.rpart",

diff --git a/R/LearnerRegrFeatureless.R b/R/LearnerRegrFeatureless.R
@@ -23,7 +23,7 @@ LearnerRegrFeatureless = R6Class("LearnerRegrFeatureless", inherit = LearnerRegr
       ps = ps(
         robust = p_lgl(default = TRUE, tags = "train")
       )
-      ps$values = list(robust = FALSE)
+      ps$set_values(robust = FALSE)
 
       super$initialize(
         id = "regr.featureless",

diff --git a/R/LearnerRegrRpart.R b/R/LearnerRegrRpart.R
@@ -37,7 +37,7 @@ LearnerRegrRpart = R6Class("LearnerRegrRpart", inherit = LearnerRegr,
         usesurrogate   = p_int(0L, 2L, default = 2L, tags = "train"),
         xval           = p_int(0L, default = 10L, tags = "train")
       )
-      ps$values = list(xval = 0L)
+      ps$set_values(xval = 0L)
 
       super$initialize(
         id = "regr.rpart",

diff --git a/R/MeasureClassifCosts.R b/R/MeasureClassifCosts.R
@@ -45,7 +45,7 @@ MeasureClassifCosts = R6Class("MeasureClassifCosts",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       param_set = ps(normalize = p_lgl(tags = "required"))
-      param_set$values = list(normalize = TRUE)
+      param_set$set_values(normalize = TRUE)
 
       super$initialize(
         id = "classif.costs",

diff --git a/R/MeasureDebug.R b/R/MeasureDebug.R
@@ -27,7 +27,7 @@ MeasureDebugClassif = R6Class("MeasureDebugClassif",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       param_set = ps(na_ratio = p_dbl(0, 1, tags = "required"))
-      param_set$values = list(na_ratio = 0)
+      param_set$set_values(na_ratio = 0)
       super$initialize(
         id = "debug_classif",
         param_set = param_set,

diff --git a/R/MeasureSelectedFeatures.R b/R/MeasureSelectedFeatures.R
@@ -31,7 +31,7 @@ MeasureSelectedFeatures = R6Class("MeasureSelectedFeatures",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       param_set = ps(normalize = p_lgl(tags = "required"))
-      param_set$values = list(normalize = FALSE)
+      param_set$set_values(normalize = FALSE)
 
       super$initialize(
         id = "selected_features",

diff --git a/R/Resampling.R b/R/Resampling.R
@@ -56,7 +56,7 @@
 #' r$param_set$values
 #'
 #' # Do only 3 repeats on 10% of the data
-#' r$param_set$values = list(ratio = 0.1, repeats = 3)
+#' r$param_set$set_values(ratio = 0.1, repeats = 3)
 #' r$param_set$values
 #'
 #' # Instantiate on penguins task

diff --git a/R/ResamplingBootstrap.R b/R/ResamplingBootstrap.R
@@ -49,7 +49,7 @@ ResamplingBootstrap = R6Class("ResamplingBootstrap", inherit = Resampling,
         ratio   = p_dbl(0, upper = 1, tags = "required"),
         repeats = p_int(1L, tags = "required")
       )
-      ps$values = list(ratio = 1, repeats = 30L)
+      ps$set_values(ratio = 1, repeats = 30L)
 
       super$initialize(id = "bootstrap", param_set = ps, duplicated_ids = TRUE,
         label = "Bootstrap", man = "mlr3::mlr_resamplings_bootstrap")

diff --git a/R/ResamplingCV.R b/R/ResamplingCV.R
@@ -44,7 +44,7 @@ ResamplingCV = R6Class("ResamplingCV", inherit = Resampling,
       ps = ps(
         folds = p_int(2L, tags = "required")
       )
-      ps$values = list(folds = 10L)
+      ps$set_values(folds = 10L)
 
       super$initialize(id = "cv", param_set = ps,
         label = "Cross-Validation", man = "mlr3::mlr_resamplings_cv")

diff --git a/R/ResamplingHoldout.R b/R/ResamplingHoldout.R
@@ -45,7 +45,7 @@ ResamplingHoldout = R6Class("ResamplingHoldout", inherit = Resampling,
       ps = ps(
         ratio = p_dbl(0, 1, tags = "required")
       )
-      ps$values = list(ratio = 2 / 3)
+      ps$set_values(ratio = 2 / 3)
 
       super$initialize(id = "holdout", param_set = ps,
         label = "Holdout", man = "mlr3::mlr_resamplings_holdout")

diff --git a/R/ResamplingRepeatedCV.R b/R/ResamplingRepeatedCV.R
@@ -56,7 +56,7 @@ ResamplingRepeatedCV = R6Class("ResamplingRepeatedCV", inherit = Resampling,
         folds   = p_int(2L, tags = "required"),
         repeats = p_int(1L)
       )
-      ps$values = list(repeats = 10L, folds = 10L)
+      ps$set_values(repeats = 10L, folds = 10L)
       super$initialize(id = "repeated_cv", param_set = ps,
         label = "Repeated Cross-Validation", man = "mlr3::mlr_resamplings_repeated_cv")
     },

diff --git a/R/ResamplingSubsampling.R b/R/ResamplingSubsampling.R
@@ -48,7 +48,7 @@ ResamplingSubsampling = R6Class("ResamplingSubsampling", inherit = Resampling,
         ratio   = p_dbl(0, 1, tags = "required"),
         repeats = p_int(1, tags = "required")
       )
-      ps$values = list(repeats = 30L, ratio = 2 / 3)
+      ps$set_values(repeats = 30L, ratio = 2 / 3)
 
       super$initialize(id = "subsampling", param_set = ps,
         label = "Subsampling", man = "mlr3::mlr_resamplings_subsampling")

diff --git a/R/TaskGeneratorMoons.R b/R/TaskGeneratorMoons.R
@@ -27,7 +27,7 @@ TaskGeneratorMoons = R6Class("TaskGeneratorMoons",
       ps = ps(
         sigma = p_dbl(0, tags = "required")
       )
-      ps$values = list(sigma = 1)
+      ps$set_values(sigma = 1)
 
       super$initialize(id = "moons", task_type = "classif", param_set = ps,
         label = "Moons Classification", man = "mlr3::mlr_task_generators_moons")

diff --git a/man/Learner.Rd b/man/Learner.Rd
diff --git a/man/Resampling.Rd b/man/Resampling.Rd
diff --git a/man/mlr_learners_classif.debug.Rd b/man/mlr_learners_classif.debug.Rd