library(BayesFactor)

set.seed(333)

context("BF correlation")
x <- BayesFactor::correlationBF(y = iris$Sepal.Length, x = iris$Sepal.Width)
test_that("p_direction", {
  testthat::skip_on_travis() # Until insight v3 is released
  expect_equal(as.numeric(p_direction(x)), 0.9225, tol = 1)
})


# ---------------------------
context("BF t.test one sample")
data(sleep)
diffScores <- sleep$extra[1:10] - sleep$extra[11:20]
x <- BayesFactor::ttestBF(x = diffScores)
test_that("p_direction", {
  testthat::skip_on_travis() # Until insight v3 is released
  expect_equal(as.numeric(p_direction(x)), 0.99675, tol = 1)
})


# ---------------------------
context("BF t.test two samples")
data(chickwts)
chickwts <- chickwts[chickwts$feed %in% c("horsebean", "linseed"), ]
chickwts$feed <- factor(chickwts$feed)
x <- BayesFactor::ttestBF(formula = weight ~ feed, data = chickwts)
test_that("p_direction", {
  testthat::skip_on_travis() # Until insight v3 is released
  expect_equal(as.numeric(p_direction(x)), 1, tol = 1)
})

# ---------------------------
context("BF t.test meta-analytic")
t <- c(-.15, 2.39, 2.42, 2.43)
N <- c(100, 150, 97, 99)
x <- BayesFactor::meta.ttestBF(t = t, n1 = N, rscale = 1)
test_that("p_direction", {
  testthat::skip_on_travis() # Until insight v3 is released
  expect_equal(as.numeric(p_direction(x)), 0.99975, tol = 1)
})

# # ---------------------------
# context("BF ANOVA")
# data(ToothGrowth)
# ToothGrowth$dose <- factor(ToothGrowth$dose)
# levels(ToothGrowth$dose) <- c("Low", "Medium", "High")
# x <- BayesFactor::anovaBF(len ~ supp*dose, data=ToothGrowth)
# test_that("p_direction", {
#   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
# })
#
# # ---------------------------
# context("BF ANOVA Random")
# data(puzzles)
# x <- BayesFactor::anovaBF(RT ~ shape*color + ID, data = puzzles, whichRandom="ID")
# test_that("p_direction", {
#   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
# })
#
#
# # ---------------------------
# context("BF lm")
# x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth)
# test_that("p_direction", {
#   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
# })
#
#
# x2 <- BayesFactor::lmBF(len ~ supp + dose + supp:dose, data = ToothGrowth)
# x <- x / x2
# test_that("p_direction", {
#   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
# })