[R] remove default values in internal utility functions (#9457)

Author: jameslamb

R-package/R/utils.R

@@ -140,7 +140,7 @@ check.custom.eval <- function(env = parent.frame()) {
 
 
 # Update a booster handle for an iteration with dtrain data
-xgb.iter.update <- function(booster_handle, dtrain, iter, obj = NULL) {
+xgb.iter.update <- function(booster_handle, dtrain, iter, obj) {
   if (!identical(class(booster_handle), "xgb.Booster.handle")) {
     stop("booster_handle must be of xgb.Booster.handle class")
   }
@@ -163,7 +163,7 @@ xgb.iter.update <- function(booster_handle, dtrain, iter, obj = NULL) {
 # Evaluate one iteration.
 # Returns a named vector of evaluation metrics
 # with the names in a 'datasetname-metricname' format.
-xgb.iter.eval <- function(booster_handle, watchlist, iter, feval = NULL) {
+xgb.iter.eval <- function(booster_handle, watchlist, iter, feval) {
   if (!identical(class(booster_handle), "xgb.Booster.handle"))
     stop("class of booster_handle must be xgb.Booster.handle")
 
@@ -234,7 +234,7 @@ generate.cv.folds <- function(nfold, nrows, stratified, label, params) {
         y <- factor(y)
       }
     }
-    folds <- xgb.createFolds(y, nfold)
+    folds <- xgb.createFolds(y = y, k = nfold)
   } else {
     # make simple non-stratified folds
     kstep <- length(rnd_idx) %/% nfold
@@ -251,7 +251,7 @@ generate.cv.folds <- function(nfold, nrows, stratified, label, params) {
 # Creates CV folds stratified by the values of y.
 # It was borrowed from caret::createFolds and simplified
 # by always returning an unnamed list of fold indices.
-xgb.createFolds <- function(y, k = 10) {
+xgb.createFolds <- function(y, k) {
   if (is.numeric(y)) {
     ## Group the numeric data based on their magnitudes
     ## and sample within those groups.

R-package/R/xgb.cv.R

@@ -223,8 +223,18 @@ xgb.cv <- function(params = list(), data, nrounds, nfold, label = NULL, missing
     for (f in cb$pre_iter) f()
 
     msg <- lapply(bst_folds, function(fd) {
-      xgb.iter.update(fd$bst, fd$dtrain, iteration - 1, obj)
-      xgb.iter.eval(fd$bst, fd$watchlist, iteration - 1, feval)
+      xgb.iter.update(
+        booster_handle = fd$bst,
+        dtrain = fd$dtrain,
+        iter = iteration - 1,
+        obj = obj
+      )
+      xgb.iter.eval(
+        booster_handle = fd$bst,
+        watchlist = fd$watchlist,
+        iter = iteration - 1,
+        feval = feval
+      )
     })
     msg <- simplify2array(msg)
     bst_evaluation <- rowMeans(msg)

R-package/R/xgb.train.R

@@ -390,10 +390,21 @@ xgb.train <- function(params = list(), data, nrounds, watchlist = list(),
 
     for (f in cb$pre_iter) f()
 
-    xgb.iter.update(bst$handle, dtrain, iteration - 1, obj)
+    xgb.iter.update(
+        booster_handle = bst$handle,
+        dtrain = dtrain,
+        iter = iteration - 1,
+        obj = obj
+    )
 
-    if (length(watchlist) > 0)
-      bst_evaluation <- xgb.iter.eval(bst$handle, watchlist, iteration - 1, feval)  # nolint: object_usage_linter
+    if (length(watchlist) > 0) {
+      bst_evaluation <- xgb.iter.eval(  # nolint: object_usage_linter
+        booster_handle = bst$handle,
+        watchlist = watchlist,
+        iter = iteration - 1,
+        feval = feval
+      )
+    }
 
     xgb.attr(bst$handle, 'niter') <- iteration - 1