diff --git a/R/map_estimate.R b/R/map_estimate.R
index c0ee9345c..9731e7023 100644
--- a/R/map_estimate.R
+++ b/R/map_estimate.R
@@ -50,7 +50,9 @@ map_estimate <- function(x, precision = 2^10, method = "kernel", ...) {
 #' @export
 map_estimate.numeric <- function(x, precision = 2^10, method = "kernel", ...) {
   out <- map_estimate(data.frame(x = x),
-                      precision, method = method, ...)
+    precision,
+    method = method, ...
+  )
   out[[1]] <- NULL
   attr(out, "data") <- x
   out
diff --git a/tests/testthat/test-blavaan.R b/tests/testthat/test-blavaan.R
index cf30057c1..da0125acd 100644
--- a/tests/testthat/test-blavaan.R
+++ b/tests/testthat/test-blavaan.R
@@ -82,19 +82,19 @@ test_that("blavaan, all", {
   x <- suppressWarnings(weighted_posteriors(bfit, bfit2))
   expect_identical(ncol(x), 14L)
 
-  # bfit_prior <- unupdate(bfit)
-  # capture.output(x <- expect_warning(bayesfactor_parameters(bfit, prior = bfit_prior)))
-  # expect_identical(nrow(x), 14L)
-  #
-  # x <- expect_warning(si(bfit, prior = bfit_prior))
-  # expect_identical(nrow(x), 14L)
-  #
-  # ## Prior/posterior checks ----
-  # suppressWarnings(x <- check_prior(bfit))
-  # expect_equal(nrow(x), 13)
-  #
-  # x <- check_prior(bfit, simulate_priors = FALSE)
-  # expect_identical(nrow(x), 14L)
+  bfit_prior <- unupdate(bfit)
+  capture.output(x <- expect_warning(bayesfactor_parameters(bfit, prior = bfit_prior)))
+  expect_identical(nrow(x), 14L)
+
+  x <- expect_warning(si(bfit, prior = bfit_prior))
+  expect_identical(nrow(x), 14L)
+
+  ## Prior/posterior checks ----
+  suppressWarnings(x <- check_prior(bfit))
+  expect_equal(nrow(x), 13)
+
+  x <- check_prior(bfit, simulate_priors = FALSE)
+  expect_identical(nrow(x), 14L)
 
   x <- diagnostic_posterior(bfit)
   expect_identical(nrow(x), 14L)
@@ -107,6 +107,6 @@ test_that("blavaan, all", {
   expect_identical(nrow(x), 13L)
   # YES this is 13! We have two parameters with the same prior.
 
-  # x <- describe_posterior(bfit, test = "all", rope_range = c(-0.1, 0.1))
-  # expect_identical(nrow(x), 14L)
+  x <- describe_posterior(bfit, test = "all", rope_range = c(-0.1, 0.1))
+  expect_identical(nrow(x), 14L)
 })
diff --git a/tests/testthat/test-different_models.R b/tests/testthat/test-different_models.R
index fdc4e5116..feec60e4d 100644
--- a/tests/testthat/test-different_models.R
+++ b/tests/testthat/test-different_models.R
@@ -26,14 +26,14 @@ test_that("insight::get_predicted", {
   rez <- p_direction(x)
   expect_equal(c(nrow(rez), ncol(rez)), c(32, 2))
 
-  # rez <- p_map(x)
-  # expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))
-  #
-  # rez <- p_significance(x)
-  # expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))
-  #
-  # rez <- rope(x)
-  # expect_equal(c(nrow(rez), ncol(rez)), c(2, 5))
+  rez <- p_map(x)
+  expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))
+
+  rez <- p_significance(x)
+  expect_equal(c(nrow(rez), ncol(rez)), c(2, 2))
+
+  rez <- rope(x)
+  expect_equal(c(nrow(rez), ncol(rez)), c(2, 5))
 
   rez <- describe_posterior(x)
   expect_equal(c(nrow(rez), ncol(rez)), c(32, 5))
diff --git a/tests/testthat/test-rope.R b/tests/testthat/test-rope.R
index 740172614..fa837eb2b 100644
--- a/tests/testthat/test-rope.R
+++ b/tests/testthat/test-rope.R
@@ -18,7 +18,6 @@ test_that("rope", {
 
   expect_equal(equivalence_test(distribution_normal(1000, 0, 0.001), ci = 1)$ROPE_Equivalence, "Accepted")
 
-  # print(rope(rnorm(1000, mean = 0, sd = 3), ci = .5))
   expect_equal(rope(rnorm(1000, mean = 0, sd = 3), ci = c(.1, .5, .9), verbose = FALSE)$CI, c(.1, .5, .9))
 
   x <- equivalence_test(distribution_normal(1000, 1, 1), ci = c(.50, .99))
@@ -71,31 +70,31 @@ test_that("rope", {
 })
 
 
-# if ( skip_if_not_or_load_if_installed("brms")) {
-#   set.seed(123)
-#   model <- brm(mpg ~ wt + gear, data = mtcars, iter = 500)
-#   rope <- rope(model, verbose = FALSE)
-#
-#   test_that("rope (brms)", {
-#     expect_equal(rope$ROPE_high, -rope$ROPE_low, tolerance = 0.01)
-#     expect_equal(rope$ROPE_high[1], 0.6026948)
-#     expect_equal(rope$ROPE_Percentage, c(0.00, 0.00, 0.50), tolerance = 0.1)
-#   })
-#
-#   model <- brm(mvbind(mpg, disp) ~ wt + gear, data = mtcars, iter = 500)
-#   rope <- rope(model, verbose = FALSE)
-#
-#   test_that("rope (brms, multivariate)", {
-#     expect_equal(rope$ROPE_high, -rope$ROPE_low, tolerance = 0.01)
-#     expect_equal(rope$ROPE_high[1], 0.6026948, tolerance = 0.01)
-#     expect_equal(rope$ROPE_high[4], 12.3938694, tolerance = 0.01)
-#     expect_equal(
-#       rope$ROPE_Percentage,
-#       c(0, 0, 0.493457, 0.072897, 0, 0.508411),
-#       tolerance = 0.1
-#     )
-#   })
-# }
+skip_if_not_or_load_if_installed("brms")
+set.seed(123)
+model <- brm(mpg ~ wt + gear, data = mtcars, iter = 500)
+rope <- rope(model, verbose = FALSE)
+
+test_that("rope (brms)", {
+  expect_equal(rope$ROPE_high, -rope$ROPE_low, tolerance = 0.01)
+  expect_equal(rope$ROPE_high[1], 0.6026948)
+  expect_equal(rope$ROPE_Percentage, c(0.00, 0.00, 0.50), tolerance = 0.1)
+})
+
+model <- brm(mvbind(mpg, disp) ~ wt + gear, data = mtcars, iter = 500)
+rope <- rope(model, verbose = FALSE)
+
+test_that("rope (brms, multivariate)", {
+  expect_equal(rope$ROPE_high, -rope$ROPE_low, tolerance = 0.01)
+  expect_equal(rope$ROPE_high[1], 0.6026948, tolerance = 0.01)
+  expect_equal(rope$ROPE_high[4], 12.3938694, tolerance = 0.01)
+  expect_equal(
+    rope$ROPE_Percentage,
+    c(0, 0, 0.493457, 0.072897, 0, 0.508411),
+    tolerance = 0.1
+  )
+})
+
 
 test_that("BayesFactor", {
   skip_if_not_or_load_if_installed("BayesFactor")