Nothing
test_that("WPL0 with exact transport", {
set.seed(84370158)
n <- 32
p <- 5
s <- 21
x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
x_ <- t(x)
beta <- (1:p)/p
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
post_mu <- x %*% post_beta
transp <- "exact"
l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
testthat::skip_on_cran()
l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
nc <- parallel::detectCores()-1
if (nc > 2) nc <- 2
cl <- parallel::makeCluster(nc)
doParallel::registerDoParallel(cl)
l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
parallel::stopCluster(cl)
testthat::expect_equal(l0$min_combination, l0.2$min_combination)
testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
})
testthat::test_that("WPL0 with sinkhorn transport", {
set.seed(84370158)
n <- 32
p <- 5
s <- 21
x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
x_ <- t(x)
beta <- (1:p)/p
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
post_mu <- x %*% post_beta
transp <- "sinkhorn"
l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
testthat::skip_on_cran()
l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
nc <- parallel::detectCores()-1
if (nc > 2) nc <- 2
cl <- parallel::makeCluster(nc)
doParallel::registerDoParallel(cl)
l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
parallel::stopCluster(cl)
testthat::expect_equal(l0$min_combination, l0.2$min_combination)
testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
})
testthat::test_that("WPL0 with greenkhorn transport", {
set.seed(84370158)
n <- 32
p <- 5
s <- 21
x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
x_ <- t(x)
beta <- (1:p)/p
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
post_mu <- x %*% post_beta
transp <- "greenkhorn"
l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
testthat::skip_on_cran()
l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
nc <- parallel::detectCores()-1
if (nc > 2) nc <- 2
cl <- parallel::makeCluster(nc)
doParallel::registerDoParallel(cl)
l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
parallel::stopCluster(cl)
testthat::expect_equal(l0$min_combination, l0.2$min_combination)
testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
})
# testthat::test_that("WPL0 with randkhorn transport", {
# set.seed(84370158)
#
# n <- 128
# p <- 5
# s <- 99
#
# x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
# x_ <- t(x)
# beta <- (1:p)/p
# y <- x %*% beta + stats::rnorm(n)
# post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
# post_mu <- x %*% post_beta
# transp <- "randkhorn"
#
#
# l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("selection.variable"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = NULL)
#
# l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("projection"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = NULL)
#
# cl <- parallel::makeCluster(parallel::detectCores()-1)
# doParallel::registerDoParallel(cl)
# l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("selection.variable"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = cl)
# doParallel::registerDoParallel(cl)
# l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("projection"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = cl)
# parallel::stopCluster(cl)
#
# testthat::expect_equal(l0$min_combination, l0.2$min_combination)
# testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
#
# })
#
# testthat::test_that("WPL0 with gandkhorn transport", {
# set.seed(84370158)
#
# n <- 128
# p <- 5
# s <- 99
#
# x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
# x_ <- t(x)
# beta <- (1:p)/p
# y <- x %*% beta + stats::rnorm(n)
# post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
# post_mu <- x %*% post_beta
# transp <- "gandkhorn"
#
#
# l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("selection.variable"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = NULL)
#
# l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("projection"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = NULL)
#
# cl <- parallel::makeCluster(parallel::detectCores()-1)
# doParallel::registerDoParallel(cl)
# l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("selection.variable"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = cl)
# doParallel::registerDoParallel(cl)
# l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
# method = c("projection"),
# transport.method = transp,
# epsilon = 0.05, OTmaxit = 100,
# parallel = cl)
# parallel::stopCluster(cl)
#
# testthat::expect_equal(l0$min_combination, l0.2$min_combination)
# testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
#
# })
testthat::test_that("WPL0 with hilbert transport", {
set.seed(84370158)
n <- 32
p <- 5
s <- 21
x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
x_ <- t(x)
beta <- (1:p)/p
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
post_mu <- x %*% post_beta
transp <- "hilbert"
l0 <- WpProj:::WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
l0.1 <- WpProj:::WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
nc <- parallel::detectCores()-1
if (nc > 2) nc <- 2
cl <- parallel::makeCluster(nc)
doParallel::registerDoParallel(cl)
l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
parallel::stopCluster(cl)
testthat::expect_equal(l0$min_combination, l0.2$min_combination)
testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
})
testthat::test_that("WPL0 with rank transport", {
set.seed(84370158)
n <- 128
p <- 5
s <- 99
x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
x_ <- t(x)
beta <- (1:p)/p
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
post_mu <- x %*% post_beta
transp <- "rank"
l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
nc <- parallel::detectCores()-1
if (nc > 2) nc <- 2
cl <- parallel::makeCluster(nc)
doParallel::registerDoParallel(cl)
l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
parallel::stopCluster(cl)
testthat::expect_equal(l0$min_combination, l0.2$min_combination)
testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
})
testthat::test_that("WPL0 with univariate.approximation.pwr transport", {
set.seed(84370158)
n <- 32
p <- 5
s <- 21
x <- matrix( stats::rnorm( p * n ), nrow = n, ncol = p )
x_ <- t(x)
beta <- (1:p)/p
y <- x %*% beta + stats::rnorm(n)
post_beta <- matrix(beta, nrow=p, ncol=s) + stats::rnorm(p*s, 0, 0.1)
post_mu <- x %*% post_beta
transp <- "univariate.approximation.pwr"
l0 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
l0.1 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = NULL)
nc <- parallel::detectCores()-1
if (nc > 2) nc <- 2
cl <- parallel::makeCluster(nc)
doParallel::registerDoParallel(cl)
l0.2 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("selection.variable"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
l0.3 <- WPL0(X = x, Y = NULL, theta = post_beta, power = 2,
method = c("projection"),
transport.method = transp,
epsilon = 0.05, OTmaxit = 100,
parallel = cl)
parallel::stopCluster(cl)
testthat::expect_equal(l0$min_combination, l0.2$min_combination)
testthat::expect_equal(l0.1$min_combination, l0.3$min_combination)
})
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