Documentation improvements

R/helper-splat.r

@@ -6,6 +6,7 @@
 # 
 # @arguments function to splat
 # @value a function
+# 
 #X hp_per_cyl <- function(hp, cyl, ...) hp / cyl
 #X splat(hp_per_cyl)(mtcars[1,])
 #X splat(hp_per_cyl)(mtcars)

R/helper-try.r

@@ -6,6 +6,7 @@
 # @argument should all error messages be suppressed?
 # @value a function
 # @seealso \code{\link{try_default}}
+# @keyword debugging
 #X f <- function(x) if (x == 1) stop("Error!") else 1
 #X \dontrun{
 #X f(1)

R/indexed-array.r

@@ -3,7 +3,7 @@
 # 
 # @arguments environment containing data frame
 # @argument list of indices
-# @keywords internal
+# @keyword internal
 # @alias [[.indexed_array
 # @alias names.indexed_array
 # @alias length.indexed_array

R/indexed-data-frame.r

@@ -3,7 +3,7 @@
 # 
 # @arguments environment containing data frame
 # @argument list of indices
-# @keywords internal
+# @keyword internal
 # @alias length.indexed
 # @alias names.indexed
 # @alias as.list.indexed

R/ninteraction.r

@@ -1,7 +1,7 @@
 # Numerical interaction
 # A purely numerical interaction function that powers \code{aaply}.
 # 
-# @keywords internal
+# @keyword internal
 ninteraction <- function(.variables, drop = FALSE) {  
   if (length(.variables) == 0) {
     res <- structure(rep.int(1L, nrow(.variables)), n = 1L)

R/ply-array.r

@@ -10,7 +10,7 @@
 # \code{laply} is very similar in spirit to \code{\link{sapply}} except that
 # it will always return an array, and the output is transposed with respect
 # \code{sapply} - each element of the list corresponds to a column, not a 
-# row.  
+# row.
 # 
 # 
 # @keyword manip
@@ -20,7 +20,6 @@
 # @arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
 # @arguments should extra dimensions of length 1 be dropped, simplifying the output.  Defaults to \code{TRUE}
 # @value if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)
-# 
 #X laply(baseball, is.factor)
 #X # cf
 #X ldply(baseball, is.factor)
@@ -52,7 +51,6 @@ laply <-  function(.data, .fun = NULL, ..., .progress = "none", .drop = TRUE) {
 # \code{daply} with a function that operates column-wise is similar to
 # \code{\link{aggregate}}. 
 # 
-# 
 # @keyword manip
 # @arguments data frame to be processed
 # @arguments variables to split data frame by, as quoted variables, a formula or character vector
@@ -61,7 +59,6 @@ laply <-  function(.data, .fun = NULL, ..., .progress = "none", .drop = TRUE) {
 # @arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
 # @arguments should extra dimensions of length 1 be dropped, simplifying the output.  Defaults to \code{TRUE}
 # @value if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)
-# 
 #X daply(baseball, .(year), nrow)
 #X
 #X # Several different ways of summarising by variables that should not be 
@@ -102,7 +99,6 @@ daply <- function(.data, .variables, .fun = NULL, ..., .progress = "none", .drop
 # @arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
 # @arguments should extra dimensions of length 1 be dropped, simplifying the output.  Defaults to \code{TRUE}
 # @value if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)
-#
 #X dim(ozone)
 #X aaply(ozone, 1, mean)
 #X aaply(ozone, 1, mean, .drop = FALSE)

R/ply-data-frame.r

@@ -52,7 +52,6 @@ ldply <- function(.data, .fun = NULL, ..., .progress = "none") {
 # @arguments other arguments passed on to \code{.fun}
 # @arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
 # @value a data frame
-#X 
 #X ddply(baseball, .(year), "nrow") 
 #X ddply(baseball, .(lg), c("nrow", "ncol")) 
 #X 
@@ -86,7 +85,6 @@ ddply <- function(.data, .variables, .fun = NULL, ..., .progress = "none", .drop
 # frame. If there are no results, then this function will return a data frame
 # with zero rows and columns (\code{data.frame()}).
 # 
-# 
 # @keyword manip
 # @arguments matrix, array or data frame to be processed
 # @arguments a vector giving the subscripts to split up \code{data} by.  1 splits up by rows, 2 by columns and c(1,2) by rows and columns, and so on for higher dimensions

R/ply-list.r

@@ -17,7 +17,6 @@
 # @arguments other arguments passed on to \code{.fun}
 # @arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
 # @value list of results
-# 
 #X llply(llply(mtcars, round), table)
 #X llply(baseball, summary)
 #X # Examples from ?lapply
@@ -129,7 +128,6 @@ dlply <- function(.data, .variables, .fun = NULL, ..., .progress = "none", .drop
 # @arguments other arguments passed on to \code{.fun}
 # @arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
 # @value list of results
-# 
 #X alply(ozone, 3, quantile)
 #X alply(ozone, 3, function(x) table(round(x)))
 alply <- function(.data, .margins, .fun = NULL, ..., .progress = "none") {

R/ply-mapply.r

@@ -97,7 +97,6 @@ mlply <- function(.data, .fun = NULL, ..., .progress = "none") {
 # This function combines the result into a list.  If there are no results,
 # then this function will return a list of length 0  (\code{list()}).
 # 
-# 
 # @keyword manip
 # @arguments matrix or data frame to use as source of arguments
 # @arguments function to be called with varying arguments

R/progress.r

@@ -21,8 +21,7 @@
 # 
 # @arguments type of progress bar to create
 # @seealso \code{\link{progress_none}}, \code{\link{progress_text}}, \code{\link{progress_tk}}, \code{\link{progress_win}}
-# @keywords asdf
-# @keywords
+# @keyword utilities
 #X l_ply(1:1000, identity, .progress = "none")
 #X l_ply(1:1000, identity, .progress = "tk")
 #X l_ply(1:1000, identity, .progress = "text")
@@ -38,7 +37,7 @@ create_progress_bar <- function(name = "none") {
 # This the default progress bar used by plyr functions.  It's very simple to
 # understand - it does nothing!
 # 
-# @keywords internal
+# @keyword internal
 #X l_ply(1:100, identity, .progress = "none")
 progress_none <- function() {
   list(

R/rbind.r

@@ -54,6 +54,10 @@ rbind.fill <- function(...) {
 # @keyword manip 
 compact <- function(l) Filter(Negate(is.null), l)
 
+# Convert list to data frame
+# Works like cbind, but crams everything into a column
+# 
+# @keyword internal
 as_df <- function(output) {
   if (length(output) == 0) return(data.frame())
   # Convert list to data.frame

R/simplify-array.r

@@ -5,7 +5,7 @@
 # @arguments list of input data
 # @arguments a data frame of labels, one row for each element of res
 # @arguments should extra dimensions be dropped (TRUE) or preserved (FALSE)
-# @keywords internal
+# @keyword internal
 list_to_array <- function(res, labels = NULL, .drop = FALSE) {
   if (length(res) == 0) return(vector())
   n <- length(res)

R/simplify-data-frame.r

@@ -3,7 +3,7 @@
 # 
 # @arguments list of input data
 # @arguments a data frame of labels, one row for each element of res
-# @keywords internal
+# @keyword internal
 list_to_dataframe <- function(res, labels = NULL) { 
   if (length(res) == 0) return(data.frame())
 

R/simplify-vector.r

@@ -2,7 +2,7 @@
 # Reduce/simplify a list of homogenous objects to a vector
 # 
 # @arguments list of input data
-# @keywords internal
+# @keyword internal
 list_to_vector <- function(res) {
   if (length(res) == 0) return(vector())
   n <- length(res)

R/split-data-frame.r

@@ -53,7 +53,7 @@ splitter_d <- function(data, .variables = NULL, drop = TRUE) {
 # 
 # @arguments list of variables to split up by
 # @argument whether all possible combinations should be considered, or only those present in the data
-# @keywords internal
+# @keyword internal
 split_labels <- function(splits, drop) {
   factors <- llply(splits, addNA, ifany = TRUE)
   splitv <- addNA(interaction(factors, drop = drop, lex.order = TRUE), 

R/split.r

@@ -2,7 +2,7 @@
 # Subset splits
 # Subset splits, ensuring that labels keep matching
 # 
-# @keywords internal
+# @keyword internal
 "[.split" <- function(x, i, ...) {
   structure(
     NextMethod(),
@@ -26,7 +26,7 @@ as.list.split <- function(x, ...) {
 # Print split
 # Don't print labels, so it appears like a regular list
 # 
-# @keywords internal
+# @keyword internal
 print.split <- function(x, ...) {
   print(as.list(x))
 }

R/utils.r

@@ -11,7 +11,7 @@ is.discrete <- function(x) is.factor(x) || is.character(x) || is.logical(x)
 # Un-rowname
 # Strip rownames from an object
 # 
-# @keywords internal
+# @keyword internal
 unrowname <- function(x) {
   rownames(x) <- NULL
   x

man/aaply-ym.rd

@@ -27,16 +27,7 @@ always return an array, and when the function returns >1 d data structures,
 those dimensions are added on to the highest dimensions, rather than the
 lowest dimensions.  This makes \code{aaply} idempotent, so that
 \code{apply(input, X, identity)} is equivalent to \code{aperm(input, X)}.
-
-
-@keyword manip
-@arguments matrix, array or data frame to be processed
-@arguments a vector giving the subscripts to split up \code{data} by.  1 splits up by rows, 2 by columns and c(1,2) by rows and columns, and so on for higher dimensions
-@arguments function to apply to each piece
-@arguments other arguments passed on to \code{.fun}
-@arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
-@arguments should extra dimensions of length 1 be dropped, simplifying the output.  Defaults to \code{TRUE}
-@value if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)}
+}
 
 \examples{dim(ozone)
 aaply(ozone, 1, mean)

man/adply-du.rd

@@ -20,8 +20,7 @@ input into simpler pieces, apply \code{.fun} to each piece, and then combine
 the pieces into a single data structure. This function splits matrices,
 arrays and data frames by dimensions and combines the result into a data
 frame. If there are no results, then this function will return a data frame
-with zero rows and columns (\code{data.frame()}).
-}
+with zero rows and columns (\code{data.frame()}).}
 
 \examples{}
 \keyword{manip}

man/alply-wh.rd

@@ -24,15 +24,7 @@ If there are no results, then this function will return a list of length 0
 
 \code{alply} is somewhat similar to \code{\link{apply}} for cases where the
 results are not atomic.
-
-
-@keyword manip
-@arguments matrix, array or data frame to be processed
-@arguments a vector giving the subscripts to split up \code{data} by.  1 splits up by rows, 2 by columns and c(1,2) by rows and columns, and so on for higher dimensions
-@arguments function to apply to each piece
-@arguments other arguments passed on to \code{.fun}
-@arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
-@value list of results}
+}
 
 \examples{alply(ozone, 3, quantile)
 alply(ozone, 3, function(x) table(round(x)))}

man/as-df-d2.rd

@@ -0,0 +1,17 @@
+\name{as_df}
+\alias{as_df}
+\title{Convert list to data frame}
+\author{Hadley Wickham <h.wickham@gmail.com>}
+
+\description{
+Works like cbind, but crams everything into a column
+}
+\usage{as_df(output)}
+\arguments{
+\item{output}{}
+}
+
+\details{}
+
+\examples{}
+\keyword{internal}

man/create-progress-bar-4d.rd

@@ -33,4 +33,4 @@ See the examples.}
 l_ply(1:1000, identity, .progress = "tk")
 l_ply(1:1000, identity, .progress = "text")
 l_ply(1:1000, identity, .progress = progress_text(char = "-"))}
-
+\keyword{utilities}

man/daply-7r.rd

@@ -23,17 +23,7 @@ by variable and combines the result into an array.  If there are no results,
 then this function will return a vector of length 0 (\code{vector()}).
 
 \code{daply} with a function that operates column-wise is similar to
-\code{\link{aggregate}}.
-
-
-@keyword manip
-@arguments data frame to be processed
-@arguments variables to split data frame by, as quoted variables, a formula or character vector
-@arguments function to apply to each piece
-@arguments other arguments passed on to \code{.fun}
-@arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
-@arguments should extra dimensions of length 1 be dropped, simplifying the output.  Defaults to \code{TRUE}
-@value if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)}
+\code{\link{aggregate}}.}
 
 \examples{daply(baseball, .(year), nrow)
 

man/ddply-5k.rd

@@ -30,8 +30,7 @@ length, it will be \code{rbind}ed together and converted to a data frame.
 Any other values will result in an error.
 }
 
-\examples{
-ddply(baseball, .(year), "nrow") 
+\examples{ddply(baseball, .(year), "nrow") 
 ddply(baseball, .(lg), c("nrow", "ncol")) 
 
 mean_rbi <- function(df) mean(df$rbi, na.rm=TRUE)

man/failwith-sc.rd

@@ -24,4 +24,4 @@ f(2)
 safef <- failwith(NULL, f)
 safef(1)
 safef(2) }
-
+\keyword{debugging}

man/get--split-0n.rd

@@ -16,4 +16,4 @@ Subset splits, ensuring that labels keep matching
 \details{}
 
 \examples{}
-
+\keyword{internal}

man/indexed-array-4w.rd

@@ -18,4 +18,4 @@ Create a indexed array, a space efficient way of indexing into a large array
 \details{}
 
 \examples{}
-
+\keyword{internal}

man/indexed-df-uf.rd

@@ -21,4 +21,4 @@ Create a indexed list, a space efficient way of indexing into a large data frame
 \details{}
 
 \examples{}
-
+\keyword{internal}

man/laply-10.rd

@@ -25,15 +25,7 @@ then this function will return a vector of length 0 (\code{vector()}).
 it will always return an array, and the output is transposed with respect
 \code{sapply} - each element of the list corresponds to a column, not a
 row.
-
-
-@keyword manip
-@arguments input list
-@arguments function to apply to each piece
-@arguments other arguments passed on to \code{.fun}
-@arguments name of the progress bar to use, see \code{\link{create_progress_bar}}
-@arguments should extra dimensions of length 1 be dropped, simplifying the output.  Defaults to \code{TRUE}
-@value if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)}
+}
 
 \examples{laply(baseball, is.factor)
 # cf

man/list-to-array-ki.rd

@@ -16,4 +16,4 @@ Reduce/simplify a list of homogenous objects to an array
 \details{}
 
 \examples{}
-
+\keyword{internal}

man/list-to-dataframe-zb.rd

@@ -15,4 +15,4 @@ Reduce/simplify a list of homogenous objects to a data frame
 \details{}
 
 \examples{}
-
+\keyword{internal}

man/list-to-vector-27.rd

@@ -0,0 +1,17 @@
+\name{list_to_vector}
+\alias{list_to_vector}
+\title{List to vector}
+\author{Hadley Wickham <h.wickham@gmail.com>}
+
+\description{
+Reduce/simplify a list of homogenous objects to a vector
+}
+\usage{list_to_vector(res)}
+\arguments{
+\item{res}{list of input data}
+}
+
+\details{}
+
+\examples{}
+\keyword{internal}