library(testthat)
test_that("unscale correctly", {
n <- 300
d = 4
X <- as.data.frame(matrix(runif(n = n*d, min = -2, max = 2), nrow = n, ncol = d))
X_sc = scale(X)
X_sc_param = list(mu = attr(X_sc, "scaled:center"),
sd = attr(X_sc, "scaled:scale"))
expect_true(all(scale_x(X_sc, mu = X_sc_param$mu, s = X_sc_param$sd,
reverse = TRUE) - X < 10^(-15)))
})
test_that("scale correctly with parameter estimated on train data", {
n <- 1000
d = 4
X <- as.data.frame(matrix(runif(n = n*d, min = -2, max = 2), nrow = n, ncol = d))
train = sample(seq_len(n), 0.8*n)
X_train = X[train, ]
X_test = X[-train, ]
X_train_sc = scale(X_train)
X_test_sc = scale(X_test)
X_test_sc_param = list(mu = attr(X_test_sc, "scaled:center"),
sd = attr(X_test_sc, "scaled:scale"))
scale_x(X_test, mu = X_test_sc_param$mu, s = X_test_sc_param$sd,
reverse = FALSE) - X_test_sc
X_train_sc_param = list(mu = attr(X_train_sc, "scaled:center"),
sd = attr(X_train_sc, "scaled:scale"))
scale_x(X_test, mu = X_train_sc_param$mu, s = X_train_sc_param$sd,
reverse = FALSE) - X_test_sc
})
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