context("Compare to ri")


# test_that("Compare to ri", {
#
#   # setup -------------------------------------------------------------------
#
#   y <- c(8, 6, 2, 0, 3, 1, 1, 1, 2, 2, 0, 1, 0, 2, 2, 4, 1, 1)
#   Z <- c(1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0)
#   cluster <- c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9)
#   block <- c(rep(1, 4), rep(2, 6), rep(3, 8))
#
#   # in ri -------------------------------------------------------------------
#   library(ri)
#
#   perms <-
#     genperms(Z, blockvar = block, clustvar = cluster)
#
#   probs <-
#     genprobexact(Z, blockvar = block, clustvar = cluster)
#
#   ate <- estate(y, Z, prob = probs)
#
#   Ys <-
#     genouts(y, Z, ate = 0)
#
#   distout <-
#     gendist(Ys, perms, prob = probs)
#
#   ri1_out <- dispdist(distout, ate, display.plot = FALSE)
#
#   # in ri2 ------------------------------------------------------------------
#
#   library(ri2)
#
#   declaration <- declare_ra(
#     blocks = block,
#     clusters = cluster,
#     block_m = tapply(Z, block, sum) / 2
#   )
#
#   ri2_out <- conduct_ri(
#     y ~ Z,
#     sharp_hypothesis = 0,
#     declaration = declaration,
#     data = data.frame(y, Z)
#   )
#
#   # checks
#   expect_equal(probs, declaration$probabilities_matrix[, 2])
#
#   expect_equal(sort(distout), sort(ri2_out$sims_df$est_sim))
#
#   expect_equal(
#     summary(ri2_out, p = "two-tailed")$two_tailed_p_value,
#     ri1_out$two.tailed.p.value.abs
#   )
#
#   expect_equal(
#     summary(ri2_out, p = "lower")$lower_p_value,
#     ri1_out$lesser.p.value
#   )
#
#   expect_equal(
#     summary(ri2_out, p = "upper")$upper_p_value,
#     ri1_out$greater.p.value
#   )
#
#   expect_equivalent(
#     quantile(ri2_out$sims_df$est_sim, probs = 0.025),
#     ri1_out$quantile[1]
#   )
#   expect_equivalent(
#     quantile(ri2_out$sims_df$est_sim, probs = 0.975),
#     ri1_out$quantile[2]
#   )
# })