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[R] simplified the code; parameter style consistency

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This commit is contained in:
Vadim Khotilovich 2016-06-27 01:57:57 -05:00
parent 8473b18c3d
commit 56bd442b31
4 changed files with 51 additions and 75 deletions
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23
R-package/R/xgb.DMatrix.save.R
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@ -2,8 +2,8 @@
#' #'
#' Save xgb.DMatrix object to binary file #' Save xgb.DMatrix object to binary file
#' #'
#' @param DMatrix the DMatrix object #' @param dmatrix the \code{xgb.DMatrix} object
#' @param fname the name of the binary file. #' @param fname the name of the file to write.
#' #'
#' @examples #' @examples
#' data(agaricus.train, package='xgboost') #' data(agaricus.train, package='xgboost')
@ -12,15 +12,12 @@
#' xgb.DMatrix.save(dtrain, 'xgb.DMatrix.data') #' xgb.DMatrix.save(dtrain, 'xgb.DMatrix.data')
#' dtrain <- xgb.DMatrix('xgb.DMatrix.data') #' dtrain <- xgb.DMatrix('xgb.DMatrix.data')
#' @export #' @export
xgb.DMatrix.save <- function(DMatrix, fname) { xgb.DMatrix.save <- function(dmatrix, fname) {
if (typeof(fname) != "character") { if (typeof(fname) != "character")
stop("xgb.save: fname must be character") stop("fname must be character")
} if (class(dmatrix) != "xgb.DMatrix")
if (class(DMatrix) == "xgb.DMatrix") { stop("the input data must be xgb.DMatrix")
.Call("XGDMatrixSaveBinary_R", DMatrix, fname, as.integer(FALSE),
PACKAGE = "xgboost") .Call("XGDMatrixSaveBinary_R", dmatrix, fname, 0L, PACKAGE = "xgboost")
return(TRUE) return(TRUE)
}
stop("xgb.DMatrix.save: the input must be xgb.DMatrix")
return(FALSE)
} }

63
R-package/R/xgb.dump.R
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@ -2,11 +2,6 @@
#' #'
#' Save a xgboost model to text file. Could be parsed later. #' Save a xgboost model to text file. Could be parsed later.
#' #'
#' @importFrom magrittr %>%
#' @importFrom stringr str_replace
#' @importFrom data.table fread
#' @importFrom data.table :=
#' @importFrom data.table setnames
#' @param model the model object. #' @param model the model object.
#' @param fname the name of the text file where to save the model text dump. If not provided or set to \code{NULL} the function will return the model as a \code{character} vector. #' @param fname the name of the text file where to save the model text dump. If not provided or set to \code{NULL} the function will return the model as a \code{character} vector.
#' @param fmap feature map file representing the type of feature. #' @param fmap feature map file representing the type of feature.
@ -15,10 +10,11 @@
#' See demo/ for walkthrough example in R, and #' See demo/ for walkthrough example in R, and
#' \url{https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt} #' \url{https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt}
#' for example Format. #' for example Format.
#' @param with.stats whether dump statistics of splits #' @param with_stats whether dump statistics of splits
#' When this option is on, the model dump comes with two additional statistics: #' When this option is on, the model dump comes with two additional statistics:
#' gain is the approximate loss function gain we get in each split; #' gain is the approximate loss function gain we get in each split;
#' cover is the sum of second order gradient in each node. #' cover is the sum of second order gradient in each node.
#' @param ... currently not used
#' #'
#' @return #' @return
#' if fname is not provided or set to \code{NULL} the function will return the model as a \code{character} vector. Otherwise it will return \code{TRUE}. #' if fname is not provided or set to \code{NULL} the function will return the model as a \code{character} vector. Otherwise it will return \code{TRUE}.
@ -28,43 +24,36 @@
#' data(agaricus.test, package='xgboost') #' data(agaricus.test, package='xgboost')
#' train <- agaricus.train #' train <- agaricus.train
#' test <- agaricus.test #' test <- agaricus.test
#' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, #' bst <- xgboost(data = train$data, label = train$label, max_depth = 2,
#' eta = 1, nthread = 2, nround = 2,objective = "binary:logistic") #' eta = 1, nthread = 2, nrounds = 2, objective = "binary:logistic")
#' # save the model in file 'xgb.model.dump' #' # save the model in file 'xgb.model.dump'
#' xgb.dump(bst, 'xgb.model.dump', with.stats = TRUE) #' xgb.dump(bst, 'xgb.model.dump', with_stats = TRUE)
#' #'
#' # print the model without saving it to a file #' # print the model without saving it to a file
#' print(xgb.dump(bst)) #' print(xgb.dump(bst))
#' @export #' @export
xgb.dump <- function(model = NULL, fname = NULL, fmap = "", with.stats=FALSE) { xgb.dump <- function(model = NULL, fname = NULL, fmap = "", with_stats=FALSE, ...) {
if (class(model) != "xgb.Booster") { check.deprecation(...)
stop("model: argument must be type xgb.Booster") if (class(model) != "xgb.Booster")
stop("model: argument must be of type xgb.Booster")
if (!(class(fname) %in% c("character", "NULL") && length(fname) <= 1))
stop("fname: argument must be of type character (when provided)")
if (!(class(fmap) %in% c("character", "NULL") && length(fmap) <= 1))
stop("fmap: argument must be of type character (when provided)")
model <- xgb.Booster.check(model)
model_dump <- .Call("XGBoosterDumpModel_R", model$handle, fmap, as.integer(with_stats), PACKAGE = "xgboost")
if (is.null(fname))
model_dump <- str_replace_all(model_dump, '\t', '')
model_dump <- unlist(str_split(model_dump, '\n'))
model_dump <- grep('(^$|^0$)', model_dump, invert = TRUE, value = TRUE)
if (is.null(fname)) {
return(model_dump)
} else { } else {
model <- xgb.Booster.check(model) writeLines(model_dump, fname)
}
if (!(class(fname) %in% c("character", "NULL") && length(fname) <= 1)) {
stop("fname: argument must be type character (when provided)")
}
if (!(class(fmap) %in% c("character", "NULL") && length(fname) <= 1)) {
stop("fmap: argument must be type character (when provided)")
}
longString <- .Call("XGBoosterDumpModel_R", model$handle, fmap, as.integer(with.stats), PACKAGE = "xgboost")
dt <- fread(paste(longString, collapse = ""), sep = "\n", header = F)
setnames(dt, "Lines")
if(is.null(fname)) {
result <- dt[Lines != "0"][, Lines := str_replace(Lines, "^\t+", "")][Lines != ""][, paste(Lines)]
return(result)
} else {
result <- dt[Lines != "0"][Lines != ""][, paste(Lines)] %>% writeLines(fname)
return(TRUE) return(TRUE)
} }
} }
# Avoid error messages during CRAN check.
# The reason is that these variables are never declared
# They are mainly column names inferred by Data.table...
globalVariables(c("Lines", "."))

24
R-package/R/xgb.save.R
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@ -3,29 +3,25 @@
#' Save xgboost model from xgboost or xgb.train #' Save xgboost model from xgboost or xgb.train
#' #'
#' @param model the model object. #' @param model the model object.
#' @param fname the name of the binary file. #' @param fname the name of the file to write.
#' #'
#' @examples #' @examples
#' data(agaricus.train, package='xgboost') #' data(agaricus.train, package='xgboost')
#' data(agaricus.test, package='xgboost') #' data(agaricus.test, package='xgboost')
#' train <- agaricus.train #' train <- agaricus.train
#' test <- agaricus.test #' test <- agaricus.test
#' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, #' bst <- xgboost(data = train$data, label = train$label, max_depth = 2,
#' eta = 1, nthread = 2, nround = 2,objective = "binary:logistic") #' eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic")
#' xgb.save(bst, 'xgb.model') #' xgb.save(bst, 'xgb.model')
#' bst <- xgb.load('xgb.model') #' bst <- xgb.load('xgb.model')
#' pred <- predict(bst, test$data) #' pred <- predict(bst, test$data)
#' @export #' @export
xgb.save <- function(model, fname) { xgb.save <- function(model, fname) {
if (typeof(fname) != "character") { if (typeof(fname) != "character")
stop("xgb.save: fname must be character") stop("fname must be character")
} if (class(model) != "xgb.Booster")
if (class(model) == "xgb.Booster") { stop("the input must be xgb.Booster. Use xgb.DMatrix.save to save xgb.DMatrix object.")
model <- xgb.Booster.check(model)
.Call("XGBoosterSaveModel_R", model$handle, fname, PACKAGE = "xgboost") .Call("XGBoosterSaveModel_R", model$handle, fname, PACKAGE = "xgboost")
return(TRUE) return(TRUE)
}
stop("xgb.save: the input must be xgb.Booster. Use xgb.DMatrix.save to save
xgb.DMatrix object.")
return(FALSE)
} }

16
R-package/R/xgb.save.raw.R
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@ -10,20 +10,14 @@
#' data(agaricus.test, package='xgboost') #' data(agaricus.test, package='xgboost')
#' train <- agaricus.train #' train <- agaricus.train
#' test <- agaricus.test #' test <- agaricus.test
#' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, #' bst <- xgboost(data = train$data, label = train$label, max_depth = 2,
#' eta = 1, nthread = 2, nround = 2,objective = "binary:logistic") #' eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic")
#' raw <- xgb.save.raw(bst) #' raw <- xgb.save.raw(bst)
#' bst <- xgb.load(raw) #' bst <- xgb.load(raw)
#' pred <- predict(bst, test$data) #' pred <- predict(bst, test$data)
#'
#' @export #' @export
xgb.save.raw <- function(model) { xgb.save.raw <- function(model) {
if (class(model) == "xgb.Booster"){ model <- xgb.get.handle(model)
model <- model$handle .Call("XGBoosterModelToRaw_R", model, PACKAGE = "xgboost")
}
if (class(model) == "xgb.Booster.handle") {
raw <- .Call("XGBoosterModelToRaw_R", model, PACKAGE = "xgboost")
return(raw)
}
stop("xgb.raw: the input must be xgb.Booster.handle. Use xgb.DMatrix.save to save
xgb.DMatrix object.")
} }