[R] Add missing DMatrix functions (#9929)
* `XGDMatrixGetQuantileCut` * `XGDMatrixNumNonMissing` * `XGDMatrixGetDataAsCSR` --------- Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
This commit is contained in:
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@ -37,6 +37,9 @@ export(xgb.create.features)
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export(xgb.cv)
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export(xgb.dump)
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export(xgb.gblinear.history)
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export(xgb.get.DMatrix.data)
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export(xgb.get.DMatrix.num.non.missing)
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export(xgb.get.DMatrix.qcut)
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export(xgb.get.config)
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export(xgb.ggplot.deepness)
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export(xgb.ggplot.importance)
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@ -60,6 +63,7 @@ export(xgb.unserialize)
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export(xgboost)
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import(methods)
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importClassesFrom(Matrix,dgCMatrix)
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importClassesFrom(Matrix,dgRMatrix)
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importClassesFrom(Matrix,dgeMatrix)
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importFrom(Matrix,colSums)
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importFrom(Matrix,sparse.model.matrix)
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@ -83,6 +87,7 @@ importFrom(graphics,points)
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importFrom(graphics,title)
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importFrom(jsonlite,fromJSON)
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importFrom(jsonlite,toJSON)
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importFrom(methods,new)
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importFrom(stats,median)
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importFrom(stats,predict)
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importFrom(utils,head)
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@ -526,6 +526,111 @@ setinfo.xgb.DMatrix <- function(object, name, info) {
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stop("setinfo: unknown info name ", name)
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}
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#' @title Get Quantile Cuts from DMatrix
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#' @description Get the quantile cuts (a.k.a. borders) from an `xgb.DMatrix`
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#' that has been quantized for the histogram method (`tree_method="hist"`).
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#'
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#' These cuts are used in order to assign observations to bins - i.e. these are ordered
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#' boundaries which are used to determine assignment condition `border_low < x < border_high`.
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#' As such, the first and last bin will be outside of the range of the data, so as to include
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#' all of the observations there.
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#'
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#' If a given column has 'n' bins, then there will be 'n+1' cuts / borders for that column,
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#' which will be output in sorted order from lowest to highest.
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#'
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#' Different columns can have different numbers of bins according to their range.
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#' @param dmat An `xgb.DMatrix` object, as returned by \link{xgb.DMatrix}.
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#' @param output Output format for the quantile cuts. Possible options are:\itemize{
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#' \item `"list"` will return the output as a list with one entry per column, where
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#' each column will have a numeric vector with the cuts. The list will be named if
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#' `dmat` has column names assigned to it.
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#' \item `"arrays"` will return a list with entries `indptr` (base-0 indexing) and
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#' `data`. Here, the cuts for column 'i' are obtained by slicing 'data' from entries
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#' `indptr[i]+1` to `indptr[i+1]`.
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#' }
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#' @return The quantile cuts, in the format specified by parameter `output`.
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#' @examples
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#' library(xgboost)
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#' data(mtcars)
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#' y <- mtcars$mpg
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#' x <- as.matrix(mtcars[, -1])
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#' dm <- xgb.DMatrix(x, label = y, nthread = 1)
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#'
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#' # DMatrix is not quantized right away, but will be once a hist model is generated
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#' model <- xgb.train(
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#' data = dm,
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#' params = list(
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#' tree_method = "hist",
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#' max_bin = 8,
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#' nthread = 1
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#' ),
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#' nrounds = 3
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#' )
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#'
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#' # Now can get the quantile cuts
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#' xgb.get.DMatrix.qcut(dm)
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#' @export
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xgb.get.DMatrix.qcut <- function(dmat, output = c("list", "arrays")) { # nolint
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stopifnot(inherits(dmat, "xgb.DMatrix"))
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output <- head(output, 1L)
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stopifnot(output %in% c("list", "arrays"))
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res <- .Call(XGDMatrixGetQuantileCut_R, dmat)
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if (output == "arrays") {
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return(res)
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} else {
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feature_names <- getinfo(dmat, "feature_name")
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ncols <- length(res$indptr) - 1
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out <- lapply(
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seq(1, ncols),
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function(col) {
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st <- res$indptr[col]
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end <- res$indptr[col + 1]
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if (end <= st) {
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return(numeric())
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}
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return(res$data[seq(1 + st, end)])
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}
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)
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if (NROW(feature_names)) {
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names(out) <- feature_names
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}
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return(out)
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}
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}
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#' @title Get Number of Non-Missing Entries in DMatrix
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#' @param dmat An `xgb.DMatrix` object, as returned by \link{xgb.DMatrix}.
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#' @return The number of non-missing entries in the DMatrix
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#' @export
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xgb.get.DMatrix.num.non.missing <- function(dmat) { # nolint
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stopifnot(inherits(dmat, "xgb.DMatrix"))
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return(.Call(XGDMatrixNumNonMissing_R, dmat))
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}
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#' @title Get DMatrix Data
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#' @param dmat An `xgb.DMatrix` object, as returned by \link{xgb.DMatrix}.
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#' @return The data held in the DMatrix, as a sparse CSR matrix (class `dgRMatrix`
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#' from package `Matrix`). If it had feature names, these will be added as column names
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#' in the output.
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#' @export
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xgb.get.DMatrix.data <- function(dmat) {
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stopifnot(inherits(dmat, "xgb.DMatrix"))
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res <- .Call(XGDMatrixGetDataAsCSR_R, dmat)
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out <- methods::new("dgRMatrix")
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nrows <- as.integer(length(res$indptr) - 1)
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out@p <- res$indptr
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out@j <- res$indices
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out@x <- res$data
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out@Dim <- as.integer(c(nrows, res$ncols))
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feature_names <- getinfo(dmat, "feature_name")
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dim_names <- list(NULL, NULL)
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if (NROW(feature_names)) {
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dim_names[[2L]] <- feature_names
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}
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out@Dimnames <- dim_names
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return(out)
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}
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#' Get a new DMatrix containing the specified rows of
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#' original xgb.DMatrix object
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@ -82,7 +82,7 @@ NULL
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NULL
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# Various imports
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#' @importClassesFrom Matrix dgCMatrix dgeMatrix
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#' @importClassesFrom Matrix dgCMatrix dgeMatrix dgRMatrix
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#' @importFrom Matrix colSums
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#' @importFrom Matrix sparse.model.matrix
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#' @importFrom Matrix sparseVector
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@ -98,6 +98,7 @@ NULL
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#' @importFrom data.table setnames
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#' @importFrom jsonlite fromJSON
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#' @importFrom jsonlite toJSON
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#' @importFrom methods new
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#' @importFrom utils object.size str tail
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#' @importFrom stats predict
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#' @importFrom stats median
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19
R-package/man/xgb.get.DMatrix.data.Rd
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19
R-package/man/xgb.get.DMatrix.data.Rd
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@ -0,0 +1,19 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.DMatrix.R
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\name{xgb.get.DMatrix.data}
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\alias{xgb.get.DMatrix.data}
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\title{Get DMatrix Data}
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\usage{
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xgb.get.DMatrix.data(dmat)
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}
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\arguments{
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\item{dmat}{An \code{xgb.DMatrix} object, as returned by \link{xgb.DMatrix}.}
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}
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\value{
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The data held in the DMatrix, as a sparse CSR matrix (class \code{dgRMatrix}
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from package \code{Matrix}). If it had feature names, these will be added as column names
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in the output.
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}
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\description{
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Get DMatrix Data
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}
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17
R-package/man/xgb.get.DMatrix.num.non.missing.Rd
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17
R-package/man/xgb.get.DMatrix.num.non.missing.Rd
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@ -0,0 +1,17 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.DMatrix.R
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\name{xgb.get.DMatrix.num.non.missing}
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\alias{xgb.get.DMatrix.num.non.missing}
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\title{Get Number of Non-Missing Entries in DMatrix}
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\usage{
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xgb.get.DMatrix.num.non.missing(dmat)
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}
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\arguments{
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\item{dmat}{An \code{xgb.DMatrix} object, as returned by \link{xgb.DMatrix}.}
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}
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\value{
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The number of non-missing entries in the DMatrix
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}
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\description{
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Get Number of Non-Missing Entries in DMatrix
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}
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58
R-package/man/xgb.get.DMatrix.qcut.Rd
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58
R-package/man/xgb.get.DMatrix.qcut.Rd
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@ -0,0 +1,58 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.DMatrix.R
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\name{xgb.get.DMatrix.qcut}
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\alias{xgb.get.DMatrix.qcut}
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\title{Get Quantile Cuts from DMatrix}
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\usage{
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xgb.get.DMatrix.qcut(dmat, output = c("list", "arrays"))
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}
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\arguments{
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\item{dmat}{An \code{xgb.DMatrix} object, as returned by \link{xgb.DMatrix}.}
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\item{output}{Output format for the quantile cuts. Possible options are:\itemize{
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\item \code{"list"} will return the output as a list with one entry per column, where
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each column will have a numeric vector with the cuts. The list will be named if
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\code{dmat} has column names assigned to it.
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\item \code{"arrays"} will return a list with entries \code{indptr} (base-0 indexing) and
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\code{data}. Here, the cuts for column 'i' are obtained by slicing 'data' from entries
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\code{indptr[i]+1} to \code{indptr[i+1]}.
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}}
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}
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\value{
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The quantile cuts, in the format specified by parameter \code{output}.
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}
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\description{
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Get the quantile cuts (a.k.a. borders) from an \code{xgb.DMatrix}
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that has been quantized for the histogram method (\code{tree_method="hist"}).
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These cuts are used in order to assign observations to bins - i.e. these are ordered
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boundaries which are used to determine assignment condition \verb{border_low < x < border_high}.
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As such, the first and last bin will be outside of the range of the data, so as to include
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all of the observations there.
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If a given column has 'n' bins, then there will be 'n+1' cuts / borders for that column,
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which will be output in sorted order from lowest to highest.
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Different columns can have different numbers of bins according to their range.
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}
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\examples{
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library(xgboost)
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data(mtcars)
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y <- mtcars$mpg
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x <- as.matrix(mtcars[, -1])
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dm <- xgb.DMatrix(x, label = y, nthread = 1)
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# DMatrix is not quantized right away, but will be once a hist model is generated
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model <- xgb.train(
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data = dm,
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params = list(
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tree_method = "hist",
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max_bin = 8,
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nthread = 1
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),
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nrounds = 3
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)
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# Now can get the quantile cuts
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xgb.get.DMatrix.qcut(dm)
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}
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@ -63,6 +63,7 @@ OBJECTS= \
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$(PKGROOT)/src/gbm/gblinear.o \
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$(PKGROOT)/src/gbm/gblinear_model.o \
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$(PKGROOT)/src/data/adapter.o \
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$(PKGROOT)/src/data/array_interface.o \
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$(PKGROOT)/src/data/simple_dmatrix.o \
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$(PKGROOT)/src/data/data.o \
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$(PKGROOT)/src/data/sparse_page_raw_format.o \
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@ -63,6 +63,7 @@ OBJECTS= \
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$(PKGROOT)/src/gbm/gblinear.o \
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$(PKGROOT)/src/gbm/gblinear_model.o \
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$(PKGROOT)/src/data/adapter.o \
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$(PKGROOT)/src/data/array_interface.o \
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$(PKGROOT)/src/data/simple_dmatrix.o \
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$(PKGROOT)/src/data/data.o \
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$(PKGROOT)/src/data/sparse_page_raw_format.o \
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@ -45,6 +45,9 @@ extern SEXP XGDMatrixCreateFromDF_R(SEXP, SEXP, SEXP);
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extern SEXP XGDMatrixGetStrFeatureInfo_R(SEXP, SEXP);
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extern SEXP XGDMatrixNumCol_R(SEXP);
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extern SEXP XGDMatrixNumRow_R(SEXP);
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extern SEXP XGDMatrixGetQuantileCut_R(SEXP);
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extern SEXP XGDMatrixNumNonMissing_R(SEXP);
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extern SEXP XGDMatrixGetDataAsCSR_R(SEXP);
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extern SEXP XGDMatrixSaveBinary_R(SEXP, SEXP, SEXP);
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extern SEXP XGDMatrixSetInfo_R(SEXP, SEXP, SEXP);
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extern SEXP XGDMatrixSetStrFeatureInfo_R(SEXP, SEXP, SEXP);
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@ -84,6 +87,9 @@ static const R_CallMethodDef CallEntries[] = {
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{"XGDMatrixGetStrFeatureInfo_R", (DL_FUNC) &XGDMatrixGetStrFeatureInfo_R, 2},
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{"XGDMatrixNumCol_R", (DL_FUNC) &XGDMatrixNumCol_R, 1},
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{"XGDMatrixNumRow_R", (DL_FUNC) &XGDMatrixNumRow_R, 1},
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{"XGDMatrixGetQuantileCut_R", (DL_FUNC) &XGDMatrixGetQuantileCut_R, 1},
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{"XGDMatrixNumNonMissing_R", (DL_FUNC) &XGDMatrixNumNonMissing_R, 1},
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{"XGDMatrixGetDataAsCSR_R", (DL_FUNC) &XGDMatrixGetDataAsCSR_R, 1},
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{"XGDMatrixSaveBinary_R", (DL_FUNC) &XGDMatrixSaveBinary_R, 3},
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{"XGDMatrixSetInfo_R", (DL_FUNC) &XGDMatrixSetInfo_R, 3},
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{"XGDMatrixSetStrFeatureInfo_R", (DL_FUNC) &XGDMatrixSetStrFeatureInfo_R, 3},
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@ -1,5 +1,5 @@
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/**
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* Copyright 2014-2023 by XGBoost Contributors
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* Copyright 2014-2024, XGBoost Contributors
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*/
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#include <dmlc/common.h>
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#include <dmlc/omp.h>
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@ -9,9 +9,11 @@
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#include <xgboost/logging.h>
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#include <algorithm>
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#include <cmath>
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#include <cstdint>
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#include <cstdio>
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#include <cstring>
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#include <limits>
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#include <sstream>
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#include <string>
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#include <utility>
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@ -20,14 +22,14 @@
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#include "../../src/c_api/c_api_error.h"
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#include "../../src/c_api/c_api_utils.h" // MakeSparseFromPtr
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#include "../../src/common/threading_utils.h"
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#include "../../src/data/array_interface.h" // for ArrayInterface
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#include "./xgboost_R.h" // Must follow other includes.
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namespace {
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struct ErrorWithUnwind : public std::exception {};
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void ThrowExceptionFromRError(void *unused, Rboolean jump) {
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void ThrowExceptionFromRError(void *, Rboolean jump) {
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if (jump) {
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throw ErrorWithUnwind();
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}
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@ -49,6 +51,30 @@ SEXP SafeMkChar(const char *c_str, SEXP continuation_token) {
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continuation_token);
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}
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SEXP WrappedAllocReal(void *void_ptr) {
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size_t *size = static_cast<size_t*>(void_ptr);
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return Rf_allocVector(REALSXP, *size);
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}
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SEXP SafeAllocReal(size_t size, SEXP continuation_token) {
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return R_UnwindProtect(
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WrappedAllocReal, static_cast<void*>(&size),
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ThrowExceptionFromRError, nullptr,
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continuation_token);
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}
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SEXP WrappedAllocInteger(void *void_ptr) {
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size_t *size = static_cast<size_t*>(void_ptr);
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return Rf_allocVector(INTSXP, *size);
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}
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SEXP SafeAllocInteger(size_t size, SEXP continuation_token) {
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return R_UnwindProtect(
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WrappedAllocInteger, static_cast<void*>(&size),
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ThrowExceptionFromRError, nullptr,
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continuation_token);
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}
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[[nodiscard]] std::string MakeArrayInterfaceFromRMat(SEXP R_mat) {
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SEXP mat_dims = Rf_getAttrib(R_mat, R_DimSymbol);
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if (Rf_xlength(mat_dims) > 2) {
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@ -136,6 +162,37 @@ SEXP SafeMkChar(const char *c_str, SEXP continuation_token) {
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jconfig["nthread"] = Rf_asInteger(n_threads);
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return Json::Dump(jconfig);
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}
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// Allocate a R vector and copy an array interface encoded object to it.
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[[nodiscard]] SEXP CopyArrayToR(const char *array_str, SEXP ctoken) {
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xgboost::ArrayInterface<1> array{xgboost::StringView{array_str}};
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// R supports only int and double.
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bool is_int =
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xgboost::DispatchDType(array.type, [](auto t) { return std::is_integral_v<decltype(t)>; });
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bool is_float = xgboost::DispatchDType(
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array.type, [](auto v) { return std::is_floating_point_v<decltype(v)>; });
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CHECK(is_int || is_float) << "Internal error: Invalid DType.";
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CHECK(array.is_contiguous) << "Internal error: Return by XGBoost should be contiguous";
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// Allocate memory in R
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SEXP out =
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Rf_protect(is_int ? SafeAllocInteger(array.n, ctoken) : SafeAllocReal(array.n, ctoken));
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xgboost::DispatchDType(array.type, [&](auto t) {
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using T = decltype(t);
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auto in_ptr = static_cast<T const *>(array.data);
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if (is_int) {
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auto out_ptr = INTEGER(out);
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std::copy_n(in_ptr, array.n, out_ptr);
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} else {
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auto out_ptr = REAL(out);
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std::copy_n(in_ptr, array.n, out_ptr);
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}
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});
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Rf_unprotect(1);
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return out;
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}
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} // namespace
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struct RRNGStateController {
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@ -540,6 +597,73 @@ XGB_DLL SEXP XGDMatrixNumCol_R(SEXP handle) {
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return ScalarInteger(static_cast<int>(ncol));
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}
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XGB_DLL SEXP XGDMatrixGetQuantileCut_R(SEXP handle) {
|
||||
const char *out_names[] = {"indptr", "data", ""};
|
||||
SEXP continuation_token = Rf_protect(R_MakeUnwindCont());
|
||||
SEXP out = Rf_protect(Rf_mkNamed(VECSXP, out_names));
|
||||
R_API_BEGIN();
|
||||
const char *out_indptr;
|
||||
const char *out_data;
|
||||
CHECK_CALL(XGDMatrixGetQuantileCut(R_ExternalPtrAddr(handle), "{}", &out_indptr, &out_data));
|
||||
try {
|
||||
SET_VECTOR_ELT(out, 0, CopyArrayToR(out_indptr, continuation_token));
|
||||
SET_VECTOR_ELT(out, 1, CopyArrayToR(out_data, continuation_token));
|
||||
} catch (ErrorWithUnwind &e) {
|
||||
R_ContinueUnwind(continuation_token);
|
||||
}
|
||||
R_API_END();
|
||||
Rf_unprotect(2);
|
||||
return out;
|
||||
}
|
||||
|
||||
XGB_DLL SEXP XGDMatrixNumNonMissing_R(SEXP handle) {
|
||||
SEXP out = Rf_protect(Rf_allocVector(REALSXP, 1));
|
||||
R_API_BEGIN();
|
||||
bst_ulong out_;
|
||||
CHECK_CALL(XGDMatrixNumNonMissing(R_ExternalPtrAddr(handle), &out_));
|
||||
REAL(out)[0] = static_cast<double>(out_);
|
||||
R_API_END();
|
||||
Rf_unprotect(1);
|
||||
return out;
|
||||
}
|
||||
|
||||
XGB_DLL SEXP XGDMatrixGetDataAsCSR_R(SEXP handle) {
|
||||
const char *out_names[] = {"indptr", "indices", "data", "ncols", ""};
|
||||
SEXP out = Rf_protect(Rf_mkNamed(VECSXP, out_names));
|
||||
R_API_BEGIN();
|
||||
|
||||
bst_ulong nrows, ncols, nnz;
|
||||
CHECK_CALL(XGDMatrixNumRow(R_ExternalPtrAddr(handle), &nrows));
|
||||
CHECK_CALL(XGDMatrixNumCol(R_ExternalPtrAddr(handle), &ncols));
|
||||
CHECK_CALL(XGDMatrixNumNonMissing(R_ExternalPtrAddr(handle), &nnz));
|
||||
if (std::max(nrows, ncols) > std::numeric_limits<int>::max()) {
|
||||
Rf_error("%s", "Error: resulting DMatrix data does not fit into R 'dgRMatrix'.");
|
||||
}
|
||||
|
||||
SET_VECTOR_ELT(out, 0, Rf_allocVector(INTSXP, nrows + 1));
|
||||
SET_VECTOR_ELT(out, 1, Rf_allocVector(INTSXP, nnz));
|
||||
SET_VECTOR_ELT(out, 2, Rf_allocVector(REALSXP, nnz));
|
||||
SET_VECTOR_ELT(out, 3, Rf_ScalarInteger(ncols));
|
||||
|
||||
std::unique_ptr<bst_ulong[]> indptr(new bst_ulong[nrows + 1]);
|
||||
std::unique_ptr<unsigned[]> indices(new unsigned[nnz]);
|
||||
std::unique_ptr<float[]> data(new float[nnz]);
|
||||
|
||||
CHECK_CALL(XGDMatrixGetDataAsCSR(R_ExternalPtrAddr(handle),
|
||||
"{}",
|
||||
indptr.get(),
|
||||
indices.get(),
|
||||
data.get()));
|
||||
|
||||
std::copy(indptr.get(), indptr.get() + nrows + 1, INTEGER(VECTOR_ELT(out, 0)));
|
||||
std::copy(indices.get(), indices.get() + nnz, INTEGER(VECTOR_ELT(out, 1)));
|
||||
std::copy(data.get(), data.get() + nnz, REAL(VECTOR_ELT(out, 2)));
|
||||
|
||||
R_API_END();
|
||||
Rf_unprotect(1);
|
||||
return out;
|
||||
}
|
||||
|
||||
// functions related to booster
|
||||
void _BoosterFinalizer(SEXP ext) {
|
||||
if (R_ExternalPtrAddr(ext) == NULL) return;
|
||||
|
||||
@ -143,6 +143,31 @@ XGB_DLL SEXP XGDMatrixNumRow_R(SEXP handle);
|
||||
*/
|
||||
XGB_DLL SEXP XGDMatrixNumCol_R(SEXP handle);
|
||||
|
||||
/*!
|
||||
* \brief return the quantile cuts used for the histogram method
|
||||
* \param handle an instance of data matrix
|
||||
* \return A list with entries 'indptr' and 'data'
|
||||
*/
|
||||
XGB_DLL SEXP XGDMatrixGetQuantileCut_R(SEXP handle);
|
||||
|
||||
/*!
|
||||
* \brief get the number of non-missing entries in a dmatrix
|
||||
* \param handle an instance of data matrix
|
||||
* \return the number of non-missing entries
|
||||
*/
|
||||
XGB_DLL SEXP XGDMatrixNumNonMissing_R(SEXP handle);
|
||||
|
||||
/*!
|
||||
* \brief get the data in a dmatrix in CSR format
|
||||
* \param handle an instance of data matrix
|
||||
* \return R list with the following entries in this order:
|
||||
* - 'indptr
|
||||
* - 'indices
|
||||
* - 'data'
|
||||
* - 'ncol'
|
||||
*/
|
||||
XGB_DLL SEXP XGDMatrixGetDataAsCSR_R(SEXP handle);
|
||||
|
||||
/*!
|
||||
* \brief create xgboost learner
|
||||
* \param dmats a list of dmatrix handles that will be cached
|
||||
|
||||
@ -375,3 +375,62 @@ test_that("xgb.DMatrix: can take multi-dimensional 'base_margin'", {
|
||||
)
|
||||
expect_equal(pred_only_x, pred_w_base - b, tolerance = 1e-5)
|
||||
})
|
||||
|
||||
test_that("xgb.DMatrix: number of non-missing matches data", {
|
||||
x <- matrix(1:10, nrow = 5)
|
||||
dm1 <- xgb.DMatrix(x)
|
||||
expect_equal(xgb.get.DMatrix.num.non.missing(dm1), 10)
|
||||
|
||||
x[2, 2] <- NA
|
||||
x[4, 1] <- NA
|
||||
dm2 <- xgb.DMatrix(x)
|
||||
expect_equal(xgb.get.DMatrix.num.non.missing(dm2), 8)
|
||||
})
|
||||
|
||||
test_that("xgb.DMatrix: retrieving data as CSR", {
|
||||
data(mtcars)
|
||||
dm <- xgb.DMatrix(as.matrix(mtcars))
|
||||
csr <- xgb.get.DMatrix.data(dm)
|
||||
expect_equal(dim(csr), dim(mtcars))
|
||||
expect_equal(colnames(csr), colnames(mtcars))
|
||||
expect_equal(unname(as.matrix(csr)), unname(as.matrix(mtcars)), tolerance = 1e-6)
|
||||
})
|
||||
|
||||
test_that("xgb.DMatrix: quantile cuts look correct", {
|
||||
data(mtcars)
|
||||
y <- mtcars$mpg
|
||||
x <- as.matrix(mtcars[, -1])
|
||||
dm <- xgb.DMatrix(x, label = y)
|
||||
model <- xgb.train(
|
||||
data = dm,
|
||||
params = list(
|
||||
tree_method = "hist",
|
||||
max_bin = 8,
|
||||
nthread = 1
|
||||
),
|
||||
nrounds = 3
|
||||
)
|
||||
qcut_list <- xgb.get.DMatrix.qcut(dm, "list")
|
||||
qcut_arrays <- xgb.get.DMatrix.qcut(dm, "arrays")
|
||||
|
||||
expect_equal(length(qcut_arrays), 2)
|
||||
expect_equal(names(qcut_arrays), c("indptr", "data"))
|
||||
expect_equal(length(qcut_arrays$indptr), ncol(x) + 1)
|
||||
expect_true(min(diff(qcut_arrays$indptr)) > 0)
|
||||
|
||||
col_min <- apply(x, 2, min)
|
||||
col_max <- apply(x, 2, max)
|
||||
|
||||
expect_equal(length(qcut_list), ncol(x))
|
||||
expect_equal(names(qcut_list), colnames(x))
|
||||
lapply(
|
||||
seq(1, ncol(x)),
|
||||
function(col) {
|
||||
cuts <- qcut_list[[col]]
|
||||
expect_true(min(diff(cuts)) > 0)
|
||||
expect_true(col_min[col] > cuts[1])
|
||||
expect_true(col_max[col] < cuts[length(cuts)])
|
||||
expect_true(length(cuts) <= 9)
|
||||
}
|
||||
)
|
||||
})
|
||||
|
||||
13
src/data/array_interface.cc
Normal file
13
src/data/array_interface.cc
Normal file
@ -0,0 +1,13 @@
|
||||
/**
|
||||
* Copyright 2019-2024, XGBoost Contributors
|
||||
*/
|
||||
#include "array_interface.h"
|
||||
|
||||
#include "../common/common.h" // for AssertGPUSupport
|
||||
|
||||
namespace xgboost {
|
||||
#if !defined(XGBOOST_USE_CUDA)
|
||||
void ArrayInterfaceHandler::SyncCudaStream(int64_t) { common::AssertGPUSupport(); }
|
||||
bool ArrayInterfaceHandler::IsCudaPtr(void const *) { return false; }
|
||||
#endif // !defined(XGBOOST_USE_CUDA)
|
||||
} // namespace xgboost
|
||||
@ -375,11 +375,6 @@ struct ToDType<int64_t> {
|
||||
static constexpr ArrayInterfaceHandler::Type kType = ArrayInterfaceHandler::kI8;
|
||||
};
|
||||
|
||||
#if !defined(XGBOOST_USE_CUDA)
|
||||
inline void ArrayInterfaceHandler::SyncCudaStream(int64_t) { common::AssertGPUSupport(); }
|
||||
inline bool ArrayInterfaceHandler::IsCudaPtr(void const *) { return false; }
|
||||
#endif // !defined(XGBOOST_USE_CUDA)
|
||||
|
||||
/**
|
||||
* \brief A type erased view over __array_interface__ protocol defined by numpy
|
||||
*
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user