[R-package] Improvements, readability, and bug fixes (#378)

* Define environment in examples (xgboost clash)

* Large R code changes

R-package/man/lgb.unloader.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/lgb.unloader.R
+\name{lgb.unloader}
+\alias{lgb.unloader}
+\title{LightGBM unloading error fix}
+\usage{
+lgb.unloader(restore = TRUE, wipe = FALSE, envir = .GlobalEnv)
+}
+\arguments{
+\item{wipe}{Whether to wipe all \code{lgb.Dataset} and \code{lgb.Booster} from the global environment. Defaults to \code{FALSE} which means to not remove them.}
+
+\item{envir}{The environment to perform wiping on if \code{wipe == TRUE}. Defaults to \code{.GlobalEnv} which is the global environment.}
+
+\item{restart}{Whether to reload \code{LightGBM} immediately after detaching from R. Defaults to \code{TRUE} which means automatically reload \code{LightGBM} once unloading is performed.}
+}
+\value{
+NULL invisibly.
+}
+\description{
+Attempts to unload LightGBM packages so you can remove objects cleanly without having to restart R. This is useful for instance if an object becomes stuck for no apparent reason and you do not want to restart R to fix the lost object.
+}
+\examples{
+\dontrun{
+library(lightgbm)
+data(agaricus.train, package = "lightgbm")
+train <- agaricus.train
+dtrain <- lgb.Dataset(train$data, label = train$label)
+data(agaricus.test, package = "lightgbm")
+test <- agaricus.test
+dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
+params <- list(objective = "regression", metric = "l2")
+valids <- list(test = dtest)
+model <- lgb.train(params,
+                   dtrain,
+                   100,
+                   valids,
+                   min_data = 1,
+                   learning_rate = 1,
+                   early_stopping_rounds = 10)
+lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv)
+rm(model, dtrain, dtest) # Not needed if wipe = TRUE
+gc() # Not needed if wipe = TRUE
+
+library(lightgbm)
+# Do whatever you want again with LightGBM without object clashing
+}
+
+}
+

R-package/man/predict.lgb.Booster.Rd

@@ -39,17 +39,24 @@ Predicted values based on class \code{lgb.Booster}
 }
 \examples{
 \dontrun{
-  library(lightgbm)
-  data(agaricus.train, package='lightgbm')
-  train <- agaricus.train
-  dtrain <- lgb.Dataset(train$data, label=train$label)
-  data(agaricus.test, package='lightgbm')
-  test <- agaricus.test
-  dtest <- lgb.Dataset.create.valid(dtrain, test$data, label=test$label)
-  params <- list(objective="regression", metric="l2")
-  valids <- list(test=dtest)
-  model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
-  preds <- predict(model, test$data)
+library(lightgbm)
+data(agaricus.train, package = "lightgbm")
+train <- agaricus.train
+dtrain <- lgb.Dataset(train$data, label = train$label)
+data(agaricus.test, package = "lightgbm")
+test <- agaricus.test
+dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
+params <- list(objective = "regression", metric = "l2")
+valids <- list(test = dtest)
+model <- lgb.train(params,
+                   dtrain,
+                   100,
+                   valids,
+                   min_data = 1,
+                   learning_rate = 1,
+                   early_stopping_rounds = 10)
+preds <- predict(model, test$data)
 }
+
 }
 

R-package/man/readRDS.lgb.Booster.Rd

@@ -20,17 +20,24 @@ Attemps to load a model using RDS.
 \examples{
 \dontrun{
   library(lightgbm)
-  data(agaricus.train, package='lightgbm')
+  data(agaricus.train, package = "lightgbm")
   train <- agaricus.train
-  dtrain <- lgb.Dataset(train$data, label=train$label)
-  data(agaricus.test, package='lightgbm')
+  dtrain <- lgb.Dataset(train$data, label = train$label)
+  data(agaricus.test, package = "lightgbm")
   test <- agaricus.test
-  dtest <- lgb.Dataset.create.valid(dtrain, test$data, label=test$label)
-  params <- list(objective="regression", metric="l2")
-  valids <- list(test=dtest)
-  model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
+  dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
+  params <- list(objective = "regression", metric = "l2")
+  valids <- list(test = dtest)
+  model <- lgb.train(params,
+                     dtrain,
+                     100,
+                     valids,
+                     min_data = 1,
+                     learning_rate = 1,
+                     early_stopping_rounds = 10)
   saveRDS.lgb.Booster(model, "model.rds")
   new_model <- readRDS.lgb.Booster("model.rds")
 }
+
 }
 

R-package/man/saveRDS.lgb.Booster.Rd

@@ -31,16 +31,23 @@ Attemps to save a model using RDS. Has an additional parameter (\code{raw}) whic
 \examples{
 \dontrun{
   library(lightgbm)
-  data(agaricus.train, package='lightgbm')
+  data(agaricus.train, package = "lightgbm")
   train <- agaricus.train
-  dtrain <- lgb.Dataset(train$data, label=train$label)
-  data(agaricus.test, package='lightgbm')
+  dtrain <- lgb.Dataset(train$data, label = train$label)
+  data(agaricus.test, package = "lightgbm")
   test <- agaricus.test
-  dtest <- lgb.Dataset.create.valid(dtrain, test$data, label=test$label)
-  params <- list(objective="regression", metric="l2")
-  valids <- list(test=dtest)
-  model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
+  dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
+  params <- list(objective = "regression", metric = "l2")
+  valids <- list(test = dtest)
+  model <- lgb.train(params,
+                     dtrain,
+                     100,
+                     valids,
+                     min_data = 1,
+                     learning_rate = 1,
+                     early_stopping_rounds = 10)
   saveRDS.lgb.Booster(model, "model.rds")
 }
+
 }
 

R-package/man/setinfo.Rd

@@ -36,14 +36,18 @@ The \code{name} field can be one of the following:
 }
 \examples{
 \dontrun{
-  data(agaricus.train, package='lightgbm')
-  train <- agaricus.train
-  dtrain <- lgb.Dataset(train$data, label=train$label)
-  lgb.Dataset.construct(dtrain)
-  labels <- getinfo(dtrain, 'label')
-  setinfo(dtrain, 'label', 1-labels)
-  labels2 <- getinfo(dtrain, 'label')
-  stopifnot(all.equal(labels2, 1-labels))
+library(lightgbm)
+data(agaricus.train, package = "lightgbm")
+train <- agaricus.train
+dtrain <- lgb.Dataset(train$data, label = train$label)
+lgb.Dataset.construct(dtrain)
+
+labels <- lightgbm::getinfo(dtrain, "label")
+lightgbm::setinfo(dtrain, "label", 1 - labels)
+
+labels2 <- lightgbm::getinfo(dtrain, "label")
+stopifnot(all.equal(labels2, 1 - labels))
 }
+
 }
 

R-package/man/slice.Rd

@@ -25,12 +25,14 @@ orginal lgb.Dataset object
 }
 \examples{
 \dontrun{
-  data(agaricus.train, package='lightgbm')
-  train <- agaricus.train
-  dtrain <- lgb.Dataset(train$data, label=train$label)
+library(lightgbm)
+data(agaricus.train, package = "lightgbm")
+train <- agaricus.train
+dtrain <- lgb.Dataset(train$data, label = train$label)
 
-  dsub <- slice(dtrain, 1:42)
-  labels1 <- getinfo(dsub, 'label')
+dsub <- lightgbm::slice(dtrain, 1:42)
+labels <- lightgbm::getinfo(dsub, "label")
 }
+
 }