[R] [CI] use lintr 3.1.0 (#9456)

R-package/R/xgb.model.dt.tree.R

@@ -86,8 +86,7 @@ xgb.model.dt.tree <- function(feature_names = NULL, model = NULL, text = NULL,
     text <- xgb.dump(model = model, with_stats = TRUE)
   }
 
-  if (length(text) < 2 ||
-      sum(grepl('leaf=(\\d+)', text)) < 1) {
+  if (length(text) < 2 || !any(grepl('leaf=(\\d+)', text))) {
     stop("Non-tree model detected! This function can only be used with tree models.")
   }
 

R-package/R/xgb.plot.deepness.R

@@ -136,7 +136,7 @@ get.leaf.depth <- function(dt_tree) {
     # list of paths to each leaf in a tree
     paths <- lapply(paths_tmp$vpath, names)
     # combine into a resulting path lengths table for a tree
-    data.table(Depth = sapply(paths, length), ID = To[Leaf == TRUE])
+    data.table(Depth = lengths(paths), ID = To[Leaf == TRUE])
   }, by = Tree]
 }
 

R-package/demo/interaction_constraints.R

@@ -44,7 +44,7 @@ treeInteractions <- function(input_tree, input_max_depth) {
 
   # Remove non-interactions (same variable)
   interaction_list <- lapply(interaction_list, unique)  # remove same variables
-  interaction_length <- sapply(interaction_list, length)
+  interaction_length <- lengths(interaction_list)
   interaction_list <- interaction_list[interaction_length > 1]
   interaction_list <- unique(lapply(interaction_list, sort))
   return(interaction_list)

R-package/tests/testthat/test_helpers.R

@@ -189,7 +189,7 @@ test_that("SHAPs sum to predictions, with or without DART", {
     tol <- 1e-5
 
     expect_equal(rowSums(shap), pred, tol = tol)
-    expect_equal(apply(shapi, 1, sum), pred, tol = tol)
+    expect_equal(rowSums(shapi), pred, tol = tol)
     for (i in seq_len(nrow(d)))
       for (f in list(rowSums, colSums))
         expect_equal(f(shapi[i, , ]), shap[i, ], tol = tol)