# library(gpuRcuda)
# context("cudaMatrix Row and Column Methods")
#
# # set seed
# set.seed(123)
#
# ORDER_X <- 4
# ORDER_Y <- 5
#
# # Base R objects
# A <- matrix(rnorm(ORDER_X*ORDER_Y), nrow=ORDER_X, ncol=ORDER_Y)
#
# R <- rowSums(A)
# C <- colSums(A)
# RM <- rowMeans(A)
# CM <- colMeans(A)
#
#
# test_that("cudaMatrix Single Precision Column Sums",
# {
#
# has_gpu_skip()
#
# fgpuX <- cudaMatrix(A, type="float")
#
# gpuC <- colSums(fgpuX)
#
# expect_is(gpuC, "fcudaVector")
# expect_equal(gpuC[], C, tolerance=1e-06,
# info="float colSums not equivalent")
# })
#
# test_that("cudaMatrix Double Precision Column Sums",
# {
#
# has_gpu_skip()
# has_double_skip()
#
# dgpuX <- cudaMatrix(A, type="double")
#
# gpuC <- colSums(dgpuX)
#
# expect_is(gpuC, "dcudaVector")
# expect_equal(gpuC[], C, tolerance=.Machine$double.eps ^ 0.5,
# info="double colSums not equivalent")
# })
#
#
# test_that("cudaMatrix Single Precision Row Sums",
# {
#
# has_gpu_skip()
#
# fgpuX <- cudaMatrix(A, type="float")
#
# gpuC <- rowSums(fgpuX)
#
# expect_is(gpuC, "fcudaVector")
# expect_equal(gpuC[], R, tolerance=1e-06,
# info="float rowSums values not equivalent")
# })
#
# test_that("cudaMatrix Double Precision Row Sums",
# {
#
# has_gpu_skip()
# has_double_skip()
#
# dgpuX <- cudaMatrix(A, type="double")
#
# gpuC <- rowSums(dgpuX)
#
# expect_is(gpuC, "dcudaVector")
# expect_equal(gpuC[], R, tolerance=.Machine$double.eps ^ 0.5,
# info="double rowSums not equivalent")
# })
#
# test_that("cudaMatrix Single Precision Column Means",
# {
#
# has_gpu_skip()
#
# fgpuX <- cudaMatrix(A, type="float")
#
# gpuC <- colMeans(fgpuX)
#
# expect_is(gpuC, "fcudaVector")
# expect_equal(gpuC[], CM, tolerance=1e-06,
# info="float colMeans values not equivalent")
# })
#
# test_that("cudaMatrix Double Precision Column Means",
# {
#
# has_gpu_skip()
# has_double_skip()
#
# dgpuX <- cudaMatrix(A, type="double")
#
# gpuC <- colMeans(dgpuX)
#
# expect_is(gpuC, "dcudaVector")
# expect_equal(gpuC[], CM, tolerance=.Machine$double.eps ^ 0.5,
# info="double colMeans not equivalent")
# })
#
#
# test_that("cudaMatrix Single Precision Row Means",
# {
#
# has_gpu_skip()
#
# fgpuX <- cudaMatrix(A, type="float")
#
# gpuC <- rowMeans(fgpuX)
#
# expect_is(gpuC, "fcudaVector")
# expect_equal(gpuC[], RM, tolerance=1e-06,
# info="float rowMeans not equivalent")
# })
#
# test_that("cudaMatrix Double Precision Row Means",
# {
#
# has_gpu_skip()
# has_double_skip()
#
# dgpuX <- cudaMatrix(A, type="double")
#
# gpuC <- rowMeans(dgpuX)
#
# expect_is(gpuC, "dcudaVector")
# expect_equal(gpuC[], RM, tolerance=.Machine$double.eps ^ 0.5,
# info="double rowMeans not equivalent")
# })
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