fix: parameters

DESCRIPTION

@@ -65,7 +65,7 @@ Remotes:
     mlr-org/mlr3,
     mlr-org/bbotk,
     mlr-org/mlr3tuning,
-    mlr-org/mlr3fselect
+    mlr-org/mlr3fselect@efs_updates
 Config/testthat/edition: 3
 Config/testthat/parallel: true
 Encoding: UTF-8

R/EnsembleFSResult.R

@@ -31,6 +31,7 @@
 #' @template param_theme
 #' @param stability_args (`list`)\cr
 #'  Additional arguments passed to the stability measure function.
+#' @param ... (ignored).
 #'
 #' @return [ggplot2::ggplot()].
 #' @examples
@@ -67,93 +68,97 @@
 #' }
 #' }
 #' @export
-autoplot.EnsembleFSResult = function(object, type = "pareto",
-                                     pareto_front = "stepwise",
-                                     stability_measure = "jaccard",
-                                     stability_args = NULL,
-                                     theme = theme_minimal()) {
+autoplot.EnsembleFSResult = function(
+  object,
+  type = "pareto",
+  pareto_front = "stepwise",
+  stability_measure = "jaccard",
+  stability_args = NULL,
+  theme = theme_minimal(),
+  ...
+  ) {
   assert_string(type)
   assert_choice(pareto_front, choices = c("stepwise", "estimated", "none"))
   result = object$result
   measure_id = object$measure
 
   switch(type,
-         "pareto" = {
-           p = ggplot(result, mapping = aes(
-             x = .data[["n_features"]],
-             y = .data[[measure_id]],
-             color = learner_id)) +
-             geom_point() +
-             scale_color_viridis_d("Learner ID", end = 0.8, alpha = 0.8) +
-             xlab("Number of Features") +
-             ylab(measure_id) +
-             theme
+    "pareto" = {
+      p = ggplot(result, mapping = aes(
+        x = .data[["n_features"]],
+        y = .data[[measure_id]],
+        color = .data[["learner_id"]])) +
+        geom_point() +
+        scale_color_viridis_d("Learner ID", end = 0.8, alpha = 0.8) +
+        xlab("Number of Features") +
+        ylab(measure_id) +
+        theme
 
-           if (pareto_front == "stepwise") {
-             pf = object$pareto_front(type = "empirical")
-             pf_step = stepwise_pf(pf)
-             p = p +
-               geom_line(data = pf_step, mapping = aes(
-                 x = .data[["n_features"]],
-                 y = .data[[measure_id]]),
-                 color = "black", linewidth = 0.7)
-           } else if (pareto_front == "estimated") {
-             pfe = object$pareto_front(type = "estimated")
-             p = p +
-               geom_line(data = pfe, mapping = aes(
-                 x = .data[["n_features"]],
-                 y = .data[[measure_id]]),
-                 color = "black", linetype = "dashed", linewidth = 0.7)
-           }
+      if (pareto_front == "stepwise") {
+        pf = object$pareto_front(type = "empirical")
+        pf_step = stepwise_pf(pf)
+        p = p +
+          geom_line(data = pf_step, mapping = aes(
+            x = .data[["n_features"]],
+            y = .data[[measure_id]]),
+            color = "black", linewidth = 0.7)
+      } else if (pareto_front == "estimated") {
+        pfe = object$pareto_front(type = "estimated")
+        p = p +
+          geom_line(data = pfe, mapping = aes(
+            x = .data[["n_features"]],
+            y = .data[[measure_id]]),
+            color = "black", linetype = "dashed", linewidth = 0.7)
+      }
 
-           p
-         },
+      p
+    },
 
-         "performance" = {
-           ggplot(result, aes(
-             x = .data[["learner_id"]],
-             y = .data[[measure_id]],
-             fill = learner_id)) +
-             geom_boxplot(show.legend = FALSE) +
-             scale_fill_viridis_d(end = 0.8, alpha = 0.8) +
-             ylab(measure_id) +
-             theme +
-             theme(axis.title.x = element_blank())
-         },
+    "performance" = {
+      ggplot(result, aes(
+        x = .data[["learner_id"]],
+        y = .data[[measure_id]],
+        fill = .data[["learner_id"]])) +
+        geom_boxplot(show.legend = FALSE) +
+        scale_fill_viridis_d(end = 0.8, alpha = 0.8) +
+        ylab(measure_id) +
+        theme +
+        theme(axis.title.x = element_blank())
+    },
 
-         "n_features" = {
-           ggplot(result, aes(
-             x = .data[["learner_id"]],
-             y = .data[["n_features"]],
-             fill = learner_id)) +
-             geom_boxplot(show.legend = FALSE) +
-             scale_fill_viridis_d(end = 0.8, alpha = 0.8) +
-             ylab("Number of Features") +
-             theme +
-             theme(axis.title.x = element_blank())
-         },
+    "n_features" = {
+      ggplot(result, aes(
+        x = .data[["learner_id"]],
+        y = .data[["n_features"]],
+        fill = .data[["learner_id"]]))+
+        geom_boxplot(show.legend = FALSE) +
+        scale_fill_viridis_d(end = 0.8, alpha = 0.8) +
+        ylab("Number of Features") +
+        theme +
+        theme(axis.title.x = element_blank())
+    },
 
-         "stability" = {
-           # get stability per learner
-           stab_res = object$stability(
-             stability_measure = stability_measure,
-             stability_args = stability_args,
-             global = FALSE,
-             reset_cache = FALSE)
-           data = data.table(learner_id = names(stab_res), value = stab_res)
+    "stability" = {
+      # get stability per learner
+      stab_res = object$stability(
+        stability_measure = stability_measure,
+        stability_args = stability_args,
+        global = FALSE,
+        reset_cache = FALSE)
+      data = data.table(learner_id = names(stab_res), value = stab_res)
 
-           ggplot(data, mapping = aes(
-             x = .data[["learner_id"]],
-             y = .data[["value"]],
-             fill = .data[["learner_id"]])) +
-             geom_bar(stat = "identity", alpha = 0.8, show.legend = FALSE) +
-             scale_fill_viridis_d(end = 0.8, alpha = 0.8) +
-             ylab(stability_measure) +
-             theme +
-             theme(axis.title.x = element_blank())
-         },
+      ggplot(data, mapping = aes(
+        x = .data[["learner_id"]],
+        y = .data[["value"]],
+        fill = .data[["learner_id"]])) +
+        geom_bar(stat = "identity", alpha = 0.8, show.legend = FALSE) +
+        scale_fill_viridis_d(end = 0.8, alpha = 0.8) +
+        ylab(stability_measure) +
+        theme +
+        theme(axis.title.x = element_blank())
+    },
 
-         stopf("Unknown plot type '%s'", type)
+    stopf("Unknown plot type '%s'", type)
   )
 }