changed argument names

3 files changed, 23 insertions, 23 deletions

diff --git a/R/partition.R b/R/partition.R
index e64e1fb..7c0af2b 100644
--- a/R/partition.R
+++ b/R/partition.R
@@ -1,19 +1,19 @@
-#' Subset an idframe object
+#' Subset an idframe data
 #' 
-#' Subsetting method for objects of class \code{idframe}
+#' Subsetting method for datas of class \code{idframe}
 #' 
-#' @param object an object of class \code{idframe}
+#' @param data an object of class \code{idframe}
 #' @param indices the indices that need to be subsetted
 #' @export
-dataSlice <- function(object,indices){
+dataSlice <- function(data,indices){
   # check if the class is correct
-  if(class(object)!='idframe')
-    stop("Not an idframe object")
+  if(class(data)!='idframe')
+    stop("Not an idframe data")
   
-  if(!all(indices %in% seq(to=dim(object$output)[1],by=1)))
+  if(!all(indices %in% seq(to=dim(data$output)[1],by=1)))
     stop("Invalid indices")
   
-  trim <- object
+  trim <- data
   trim$output <- trim$output[indices,,drop=F]
   trim$input <- trim$input[indices,,drop=F]
   
@@ -32,9 +32,9 @@ dataSlice <- function(object,indices){
 #' The function splits the data into training and validation sets and returns them bundled
 #' as a list. The size of the sets are determined by the parameter \code{p}.
 #' 
-#' @param object an object of class \code{idframe}
+#' @param data an object of class \code{idframe}
 #' @param p the percentage of the data that goes to training (Default : \code{0.6})
-#' @return list containing estimation and validation idframe objects
+#' @return list containing estimation and validation idframe datas
 #' 
 #' @examples
 #' data(cstr)
@@ -43,18 +43,18 @@ dataSlice <- function(object,indices){
 #' test <- splitList$validation # testing set
 #' 
 #' @export
-dataPartition <- function(object,p=0.6){
+dataPartition <- function(data,p=0.6){
   # check if the class is correct
-  if(class(object)!='idframe')
-    stop("Not an idframe object")
+  if(class(data)!='idframe')
+    stop("Not an idframe data")
   
-  index <- seq_along(object$output[,1])
+  index <- seq_along(data$output[,1])
   
   trainIndex <- index[1:round(p*length(index))]
   testIndex <- index[!(index %in% trainIndex)]
   
-  train <- dataSlice(object,trainIndex)
-  test <- dataSlice(object,testIndex)
+  train <- dataSlice(data,trainIndex)
+  test <- dataSlice(data,testIndex)
   
   return(list(estimation=train,validation=test))
 }
\ No newline at end of file
diff --git a/man/dataPartition.Rd b/man/dataPartition.Rd
index afcc473..2ac7ef5 100644
--- a/man/dataPartition.Rd
+++ b/man/dataPartition.Rd
@@ -4,15 +4,15 @@
 \alias{dataPartition}
 \title{Split data into training and validation sets}
 \usage{
-dataPartition(object, p = 0.6)
+dataPartition(data, p = 0.6)
 }
 \arguments{
-\item{object}{an object of class \code{idframe}}
+\item{data}{an object of class \code{idframe}}
 
 \item{p}{the percentage of the data that goes to training (Default : \code{0.6})}
 }
 \value{
-list containing estimation and validation idframe objects
+list containing estimation and validation idframe datas
 }
 \description{
 The function splits the data into training and validation sets and returns them bundled
diff --git a/man/dataSlice.Rd b/man/dataSlice.Rd
index 2489cc3..52eb438 100644
--- a/man/dataSlice.Rd
+++ b/man/dataSlice.Rd
@@ -2,16 +2,16 @@
 % Please edit documentation in R/partition.R
 \name{dataSlice}
 \alias{dataSlice}
-\title{Subset an idframe object}
+\title{Subset an idframe data}
 \usage{
-dataSlice(object, indices)
+dataSlice(data, indices)
 }
 \arguments{
-\item{object}{an object of class \code{idframe}}
+\item{data}{an object of class \code{idframe}}
 
 \item{indices}{the indices that need to be subsetted}
 }
 \description{
-Subsetting method for objects of class \code{idframe}
+Subsetting method for datas of class \code{idframe}
 }