@@ -507,14 +507,27 @@ setMethod("colCollapse", signature(x = "xgCMatrix"),

 #' @inherit MatrixGenerics::colQuantiles

 #' @export

 setMethod("colQuantiles", signature(x = "xgCMatrix"),

-          function(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm=FALSE, drop = TRUE){

+          function(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm=FALSE, type = 7L, drop = TRUE){

   if(! is.null(rows)){

     x <- x[rows, , drop = FALSE]

   }

   if(! is.null(cols)){

     x <- x[, cols, drop = FALSE]

   }

-  mat <- dgCMatrix_colQuantiles(x, probs, na_rm = na.rm)

+  if(type == 7L){

+    mat <- dgCMatrix_colQuantiles(x, probs, na_rm = na.rm)

+  }else{

+    mat <- t(expand_and_reduce_sparse_matrix_to_matrix(x, n_result_rows = length(probs), function(values){

+      if(na.rm){

+        values <- values[!is.na(values)]

+        stats::quantile(values, probs = probs, na.rm = na.rm, names = FALSE, type = type)

+      }else if(any(is.na(values))){

+        rep(NA_real_, length(probs))

+      }else{

+        stats::quantile(values, probs = probs, na.rm = na.rm, names = FALSE, type = type)

+      }

+    }))

+  }

   # Add dim names

   digits <- max(2L, getOption("digits"))

   colnames(mat) <- sprintf("%.*g%%", digits, 100 * probs)

@@ -34,3 +34,26 @@ reduce_sparse_matrix_to_matrix <- function(sp_mat, n_result_rows, reduce_functio

     }

   }

 }

+

+

+expand_and_reduce_sparse_matrix_to_matrix <- function(sp_mat, n_result_rows, reduce_function = function(dense_values){ NA_real_}){

+  if(length(sp_mat@p) == 0){

+    numeric(0)

+  }else{

+    res <- vapply(seq_len(length(sp_mat@p)-1), function(index){

+      start_pos <- sp_mat@p[index]

+      end_pos <- sp_mat@p[index + 1]

+      number_of_zeros <- nrow(sp_mat) - (end_pos - start_pos)

+      values <- sp_mat@x[start_pos + seq_len(end_pos - start_pos)]

+      row_indices <- sp_mat@i[start_pos + seq_len(end_pos - start_pos)]

+      dense_values <- rep(0, nrow(sp_mat))

+      dense_values[row_indices + 1] <- values

+      reduce_function(dense_values)

+    }, FUN.VALUE = rep(0.0, n_result_rows))

+    if(n_result_rows == 1){

+      matrix(res, nrow=1, ncol=length(res))

+    }else{

+      res

+    }

+  }

+}

@@ -11,6 +11,7 @@

   cols = NULL,

   probs = seq(from = 0, to = 1, by = 0.25),

   na.rm = FALSE,

+  type = 7L,

   drop = TRUE

 )

@@ -39,6 +40,11 @@ done.}

 \item{na.rm}{If \code{\link[base:logical]{TRUE}}, \code{\link{NA}}s

 are excluded first, otherwise not.}

+\item{type}{An integer specifying the type of estimator. See

+\code{stats::\link[stats]{quantile}()}. for more details. Note, that this

+is not a generic argument and not all implementation of this function have

+to provide it.}

+

 \item{drop}{If \code{TRUE} a vector is returned if \code{J == 1}.

 Note, that this is not a generic argument and not all implementation of

 this function have to provide it.}

@@ -199,6 +199,17 @@ for(idx in seq_along(matrix_list)){

     expect_equal(colQuantiles(sp_mat), matrixStats::colQuantiles(mat))

     expect_equal(colQuantiles(sp_mat, na.rm=TRUE), matrixStats::colQuantiles(mat, na.rm=TRUE))

     expect_equal(colQuantiles(sp_mat, rows = row_subset, cols = col_subset), matrixStats::colQuantiles(mat, rows = row_subset, cols = col_subset))

+

+    expect_equal(colQuantiles(sp_mat, type = 1L), matrixStats::colQuantiles(mat, type = 1L))

+    expect_equal(colQuantiles(sp_mat, type = 2L), matrixStats::colQuantiles(mat, type = 2L))

+    expect_equal(colQuantiles(sp_mat, type = 3L), matrixStats::colQuantiles(mat, type = 3L))

+

+    expect_equal(colQuantiles(sp_mat, type = 4L), matrixStats::colQuantiles(mat, type = 4L))

+    expect_equal(colQuantiles(sp_mat, type = 5L), matrixStats::colQuantiles(mat, type = 5L))

+    expect_equal(colQuantiles(sp_mat, type = 6L), matrixStats::colQuantiles(mat, type = 6L))

+    expect_equal(colQuantiles(sp_mat, type = 7L), matrixStats::colQuantiles(mat, type = 7L))

+    expect_equal(colQuantiles(sp_mat, type = 8L), matrixStats::colQuantiles(mat, type = 8L))

+    expect_equal(colQuantiles(sp_mat, type = 9L), matrixStats::colQuantiles(mat, type = 9L))

   })