feat: cache results

R/EnsembleFSResult.R

@@ -28,14 +28,14 @@
 EnsembleFSResult = R6Class("EnsembleFSResult",
   public = list(
 
-    #' @field benchmark_result (`BenchmarkResult`)\cr
+    #' @field benchmark_result ([mlr3::BenchmarkResult])\cr
     #' The benchmark result.
     benchmark_result = NULL,
 
     #' @description
     #' Creates a new instance of this [R6][R6::R6Class] class.
     #'
-    #' @param benchmark_result (`BenchmarkResult`)\cr
+    #' @param benchmark_result ([mlr3::BenchmarkResult])\cr
     #'  The benchmark result object.
     #' @param result ([data.table::data.table])\cr
     #'  The result of the ensemble feature selection results.
@@ -53,6 +53,11 @@ EnsembleFSResult = R6Class("EnsembleFSResult",
     feature_ranking = function(method = "inclusion_probability") {
       assert_choice(method, choices = "inclusion_probability")
 
+      # cached results
+      if (!is.null(private$.feature_ranking[[method]])) {
+        return(private$.feature_ranking[[method]])
+      }
+
       features = self$benchmark_result$tasks$task[[1]]$feature_names
 
       count = map_int(features, function(feature) {
@@ -64,25 +69,36 @@ EnsembleFSResult = R6Class("EnsembleFSResult",
       res = data.table(feature = features, inclusion_probability = count / nrow(self$result))
       setorderv(res, "inclusion_probability", order = -1L)
 
-      res
+      private$.feature_ranking[[method]] = res
+      private$.feature_ranking[[method]]
     },
 
     #' @description
     #' Calculates the stability of the selected features with the `stabm` package.
+    #' The results are cached.
+    #' When the same stability measure is requested again with different arguments, the cache must be reset.
     #'
     #' @param stability_measure (`character(1)`)\cr
     #'  The stability measure to be used.
     #'  One of the measures returned by [stabm::listStabilityMeasures()] in lower case.
     #'  Default is `"jaccard"`.
     #' @param ... (`any`)\cr
     #'  Additional arguments passed to the stability measure function.
-    stability = function(stability_measure = "jaccard", ...) {
+    #' @param reset_cache (`logical(1)`)\cr
+    #'  If `TRUE`, the cached results are ignored.
+    stability = function(stability_measure = "jaccard", ..., reset_cache = FALSE) {
       funs = stabm::listStabilityMeasures()$Name
       keys =  tolower(gsub("stability", "", funs))
       assert_choice(stability_measure, choices = keys)
 
+      # cached results
+      if (!is.null(private$.stability[[stability_measure]]) && !reset_cache) {
+        return(private$.stability[[stability_measure]])
+      }
+
       fun = get(funs[which(stability_measure == keys)], envir = asNamespace("stabm"))
-      fun(self$result$features, ...)
+      private$.stability[[stability_measure]] = fun(self$result$features, ...)
+      private$.stability[[stability_measure]]
     }
   ),
 
@@ -98,7 +114,9 @@ EnsembleFSResult = R6Class("EnsembleFSResult",
   ),
 
   private = list(
-    .result = NULL
+    .result = NULL,
+    .stability = NULL,
+    .feature_ranking = NULL
   )
 )