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library(testthat)
library(caret)
library(recipes)
context('selection with recipes')
# ------------------------------------------------------------------------------
data(BloodBrain)
x_dat <- bbbDescr[, c("tpsa", "clogp", "mw")]
x_dat$mw <- log(x_dat$mw)
# ------------------------------------------------------------------------------
test_that("sbf with recipes", {
ctrl <- sbfControl(functions = lmSBF, method = "cv")
set.seed(3997)
sbf_xy <-
sbf(x = x_dat[-(1:100),],
y = logBBB[-(1:100)],
sbfControl = ctrl)
pred_xy <- predict(sbf_xy, x_dat[1:100,])
dat <- bbbDescr[, c("tpsa", "clogp", "mw")]
dat$y <- logBBB
rec <- recipe(y ~ ., data = dat) %>% step_log(mw)
set.seed(3997)
sbf_rec <- sbf(rec, data = dat[-(1:100), ], sbfControl = ctrl)
pred_rec <- predict(sbf_rec, dat[1:100,-4])
expect_equal(coef(sbf_xy$fit), coef(sbf_rec$fit))
expect_equal(pred_xy, pred_rec)
})
# ------------------------------------------------------------------------------
test_that("safs with recipes", {
ctrl <- safsControl(functions = caretSA, method = "cv", number = 3)
set.seed(3997)
sa_xy <-
safs(x = x_dat[-(1:100),],
y = logBBB[-(1:100)],
safsControl = ctrl,
iters = 2,
differences = FALSE,
method = "lm",
trControl = trainControl(method = "cv")
)
pred_xy <- predict(sa_xy, x_dat[1:100,])
dat <- bbbDescr[, c("tpsa", "clogp", "mw")]
dat$y <- logBBB
rec <- recipe(y ~ ., data = dat) %>% step_log(mw)
set.seed(3997)
sa_rec <-
safs(rec,
data = dat[-(1:100),],
safsControl = ctrl,
iters = 2,
differences = FALSE,
method = "lm",
trControl = trainControl(method = "cv")
)
pred_rec <- predict(sa_rec, dat[1:100,-4])
expect_equal(coef(sa_xy$fit$finalModel), coef(sa_rec$fit$finalModel))
expect_equal(pred_xy, pred_rec)
})
# ------------------------------------------------------------------------------
test_that("gafs with recipes", {
ctrl <- gafsControl(functions = caretGA, method = "cv", number = 3)
set.seed(3997)
ga_xy <-
gafs(x = x_dat[-(1:100),],
y = logBBB[-(1:100)],
gafsControl = ctrl,
popSize = 4,
iters = 2,
differences = FALSE,
method = "lm",
trControl = trainControl(method = "cv")
)
pred_xy <- predict(ga_xy, x_dat[1:100,])
dat <- bbbDescr[, c("tpsa", "clogp", "mw")]
dat$y <- logBBB
rec <- recipe(y ~ ., data = dat) %>% step_log(mw)
set.seed(3997)
ga_rec <-
gafs(rec,
data = dat[-(1:100),],
gafsControl = ctrl,
popSize = 4,
iters = 2,
differences = FALSE,
method = "lm",
trControl = trainControl(method = "cv")
)
pred_rec <- predict(ga_rec, dat[1:100,-4])
expect_equal(coef(ga_xy$fit$finalModel), coef(ga_rec$fit$finalModel))
expect_equal(pred_xy, pred_rec)
})
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