[R-package] remove unnecessary comments (#3356)

* [R-package] remove unused code and comments * put check back * other typos
microsoft · Sep 11, 2020 · 788f3a1 · 788f3a1
1 parent fee6f4a
commit 788f3a1
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Showing 24 changed files with 24 additions and 92 deletions.
diff --git a/R-package/R/callback.R b/R-package/R/callback.R
@@ -25,7 +25,6 @@ CB_ENV <- R6::R6Class(
 
 cb.reset.parameters <- function(new_params) {
 
-  # Check for parameter list
   if (!identical(class(new_params), "list")) {
     stop(sQuote("new_params"), " must be a list")
   }
@@ -151,7 +150,6 @@ merge.eval.string <- function(env) {
 
   }
 
-  # Return tabulated separated message
   paste0(msg, collapse = "\t")
 
 }
@@ -188,7 +186,6 @@ cb.print.evaluation <- function(period = 1L) {
   attr(callback, "call") <- match.call()
   attr(callback, "name") <- "cb.print.evaluation"
 
-  # Return callback
   callback
 
 }
@@ -198,7 +195,6 @@ cb.record.evaluation <- function() {
   # Create callback
   callback <- function(env) {
 
-    # Return empty if empty evaluation list
     if (length(env$eval_list) <= 0L) {
       return()
     }
@@ -263,14 +259,12 @@ cb.record.evaluation <- function() {
   attr(callback, "call") <- match.call()
   attr(callback, "name") <- "cb.record.evaluation"
 
-  # Return callback
   callback
 
 }
 
 cb.early.stop <- function(stopping_rounds, first_metric_only = FALSE, verbose = TRUE) {
 
-  # Initialize variables
   factor_to_bigger_better <- NULL
   best_iter <- NULL
   best_score <- NULL
@@ -397,11 +391,9 @@ cb.early.stop <- function(stopping_rounds, first_metric_only = FALSE, verbose =
     }
   }
 
-  # Set attributes
   attr(callback, "call") <- match.call()
   attr(callback, "name") <- "cb.early.stop"
 
-  # Return callback
   callback
 
 }

diff --git a/R-package/R/lgb.Booster.R b/R-package/R/lgb.Booster.R
@@ -180,7 +180,6 @@ Booster <- R6::R6Class(
       private$num_dataset <- private$num_dataset + 1L
       private$is_predicted_cur_iter <- c(private$is_predicted_cur_iter, FALSE)
 
-      # Return self
       return(invisible(self))
 
     },
@@ -200,7 +199,6 @@ Booster <- R6::R6Class(
         , params_str
       )
 
-      # Return self
       return(invisible(self))
 
     },
@@ -304,7 +302,6 @@ Booster <- R6::R6Class(
         private$is_predicted_cur_iter[[i]] <- FALSE
       }
 
-      # Return self
       return(invisible(self))
 
     },
@@ -418,7 +415,6 @@ Booster <- R6::R6Class(
         )
       }
 
-      # Return ret
       return(ret)
 
     },
@@ -441,7 +437,6 @@ Booster <- R6::R6Class(
         , lgb.c_str(filename)
       )
 
-      # Return self
       return(invisible(self))
     },
 
@@ -471,7 +466,6 @@ Booster <- R6::R6Class(
         num_iteration <- self$best_iter
       }
 
-      # Return dumped model
       lgb.call.return.str(
         "LGBM_BoosterDumpModel_R"
         , private$handle
@@ -582,7 +576,6 @@ Booster <- R6::R6Class(
         private$is_predicted_cur_iter[[idx]] <- TRUE
       }
 
-      # Return prediction buffer
       return(private$predict_buffer[[data_name]])
     },
 
@@ -614,7 +607,6 @@ Booster <- R6::R6Class(
 
       }
 
-      # Return evaluation names
       return(private$eval_names)
 
     },
@@ -690,7 +682,6 @@ Booster <- R6::R6Class(
         ret <- append(ret, list(res))
       }
 
-      # Return ret
       return(ret)
 
     }
@@ -761,7 +752,6 @@ predict.lgb.Booster <- function(object,
                                 reshape = FALSE,
                                 ...) {
 
-  # Check booster existence
   if (!lgb.is.Booster(object)) {
     stop("predict.lgb.Booster: object should be an ", sQuote("lgb.Booster"))
   }
@@ -874,12 +864,10 @@ lgb.load <- function(filename = NULL, model_str = NULL) {
 #' @export
 lgb.save <- function(booster, filename, num_iteration = NULL) {
 
-  # Check if booster is booster
   if (!lgb.is.Booster(booster)) {
     stop("lgb.save: booster should be an ", sQuote("lgb.Booster"))
   }
 
-  # Check if file name is character
   if (!(is.character(filename) && length(filename) == 1L)) {
     stop("lgb.save: filename should be a string")
   }
@@ -922,7 +910,6 @@ lgb.save <- function(booster, filename, num_iteration = NULL) {
 #' @export
 lgb.dump <- function(booster, num_iteration = NULL) {
 
-  # Check if booster is booster
   if (!lgb.is.Booster(booster)) {
     stop("lgb.save: booster should be an ", sQuote("lgb.Booster"))
   }
@@ -1014,7 +1001,6 @@ lgb.get.eval.result <- function(booster, data_name, eval_name, iters = NULL, is_
     stop("lgb.get.eval.result: wrong eval name")
   }
 
-  # Create result
   result <- booster$record_evals[[data_name]][[eval_name]][[.EVAL_KEY()]]
 
   # Check if error is requested

diff --git a/R-package/R/lgb.Dataset.R b/R-package/R/lgb.Dataset.R
@@ -105,7 +105,6 @@ Dataset <- R6::R6Class(
         , ...
       )
 
-      # Return ret
       return(invisible(ret))
 
     },
@@ -312,7 +311,6 @@ Dataset <- R6::R6Class(
         stop("lgb.Dataset.construct: label should be set")
       }
 
-      # Return self
       return(invisible(self))
 
     },
@@ -405,7 +403,6 @@ Dataset <- R6::R6Class(
 
       }
 
-      # Return self
       return(invisible(self))
 
     },
@@ -504,7 +501,6 @@ Dataset <- R6::R6Class(
 
       }
 
-      # Return self
       return(invisible(self))
 
     },
@@ -677,7 +673,6 @@ Dataset <- R6::R6Class(
     # Set predictor
     set_predictor = function(predictor) {
 
-      # Return self is identical predictor
       if (identical(private$predictor, predictor)) {
         return(invisible(self))
       }
@@ -847,7 +842,6 @@ dim.lgb.Dataset <- function(x, ...) {
     stop("dim.lgb.Dataset: input data should be an lgb.Dataset object")
   }
 
-  # Return dimensions
   x$dim()
 
 }
@@ -902,10 +896,8 @@ dimnames.lgb.Dataset <- function(x) {
     stop("lgb.Dataset does not have rownames")
   }
 
-  # Check for second value missing
   if (is.null(value[[2L]])) {
 
-    # No column names
     x$set_colnames(NULL)
     return(x)
 
@@ -1010,7 +1002,6 @@ getinfo.lgb.Dataset <- function(dataset, name, ...) {
     stop("getinfo.lgb.Dataset: input dataset should be an lgb.Dataset object")
   }
 
-  # Return information
   dataset$getinfo(name)
 
 }
@@ -1059,7 +1050,6 @@ setinfo <- function(dataset, ...) {
 #' @export
 setinfo.lgb.Dataset <- function(dataset, name, info, ...) {
 
-  # Check if dataset is not a dataset
   if (!lgb.is.Dataset(dataset)) {
     stop("setinfo.lgb.Dataset: input dataset should be an lgb.Dataset object")
   }
@@ -1092,7 +1082,6 @@ setinfo.lgb.Dataset <- function(dataset, name, info, ...) {
 #' @export
 lgb.Dataset.set.categorical <- function(dataset, categorical_feature) {
 
-  # Check if dataset is not a dataset
   if (!lgb.is.Dataset(dataset)) {
     stop("lgb.Dataset.set.categorical: input dataset should be an lgb.Dataset object")
   }

diff --git a/R-package/R/lgb.Predictor.R b/R-package/R/lgb.Predictor.R
@@ -51,7 +51,6 @@ Predictor <- R6::R6Class(
 
       } else {
 
-        # Model file is unknown
         stop("lgb.Predictor: modelfile must be either a character filename or an lgb.Booster.handle")
 
       }
@@ -93,7 +92,6 @@ Predictor <- R6::R6Class(
         start_iteration <- 0L
       }
 
-      # Set temporary variable
       num_row <- 0L
 
       # Check if data is a file name and not a matrix
@@ -149,7 +147,8 @@ Predictor <- R6::R6Class(
 
         # Check if data is a matrix
         if (is.matrix(data)) {
-          # Check whether matrix is the correct type first ("double")
+          # this if() prevents the memory and computational costs
+          # of converting something that is already "double" to "double"
           if (storage.mode(data) != "double") {
             storage.mode(data) <- "double"
           }
@@ -193,7 +192,6 @@ Predictor <- R6::R6Class(
 
         } else {
 
-          # Cannot predict on unknown class
           stop("predict: cannot predict on data of class ", sQuote(class(data)))
 
         }
@@ -227,7 +225,6 @@ Predictor <- R6::R6Class(
 
       }
 
-      # Return predictions
       return(preds)
 
     }

diff --git a/R-package/R/lgb.cv.R b/R-package/R/lgb.cv.R
@@ -91,7 +91,6 @@ lgb.cv <- function(params = list()
                    , ...
                    ) {
 
-  # validate parameters
   if (nrounds <= 0L) {
     stop("nrounds should be greater than zero")
   }
@@ -118,9 +117,10 @@ lgb.cv <- function(params = list()
     params$objective <- "NONE"
   }
 
-  # If loss is a single function, store it as a 1-element list
+  # If eval is a single function, store it as a 1-element list
   # (for backwards compatibility). If it is a list of functions, store
-  # all of them
+  # all of them. This makes it possible to pass any mix of strings like "auc"
+  # and custom functions to eval
   if (is.function(eval)) {
     eval_functions <- list(eval)
   }
@@ -276,7 +276,6 @@ lgb.cv <- function(params = list()
     )
   }
 
-  # Categorize callbacks
   cb <- categorize.callbacks(callbacks)
 
   # Construct booster for each fold. The data.table() code below is used to
@@ -354,7 +353,6 @@ lgb.cv <- function(params = list()
     env$iteration <- i
     env$eval_list <- list()
 
-    # Loop through "pre_iter" element
     for (f in cb$pre_iter) {
       f(env)
     }
@@ -430,7 +428,6 @@ lgb.cv <- function(params = list()
     })
   }
 
-  # Return booster
   return(cv_booster)
 
 }
@@ -493,7 +490,6 @@ generate.cv.folds <- function(nfold, nrows, stratified, label, group, params) {
 
   }
 
-  # Return folds
   return(folds)
 
 }
@@ -564,7 +560,6 @@ lgb.stratified.folds <- function(y, k = 10L) {
 
   }
 
-  # Return data
   out <- split(seq(along = y), foldVector)
   names(out) <- NULL
   out
@@ -592,15 +587,14 @@ lgb.merge.cv.result <- function(msg, showsd = TRUE) {
   })
 
   # Get evaluation. Just taking the first element here to
-  # get structture (name, higher_bettter, data_name)
+  # get structure (name, higher_better, data_name)
   ret_eval <- msg[[1L]]
 
   # Go through evaluation length items
   for (j in seq_len(eval_len)) {
     ret_eval[[j]]$value <- mean(eval_result[[j]])
   }
 
-  # Preinit evaluation error
   ret_eval_err <- NULL
 
   # Check for standard deviation

diff --git a/R-package/R/lgb.importance.R b/R-package/R/lgb.importance.R
@@ -75,7 +75,6 @@ lgb.importance <- function(model, percentage = TRUE) {
     )]
   }
 
-  # Return importance table
   return(tree_imp_dt)
 
 }