Tests cleanup (#596)

* start silencing messages * start using `skip_if_not_or_load_if_installed` * finish `skip_if_not_or_load_if_installed` * fix failures * hide more messages [skip ci] * remove remaining `requiet()` and style * back to skipping some tests for check_prior --------- Co-authored-by: Indrajeet Patil <[email protected]>
easystats · Mar 27, 2023 · db2548d · db2548d
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commit db2548d
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diff --git a/tests/testthat/helper.R b/tests/testthat/helper.R
@@ -1,10 +1,6 @@
-requiet <- function(package) {
-  testthat::skip_if_not_installed(package)
-  suppressPackageStartupMessages(
-    require(package, warn.conflicts = FALSE, character.only = TRUE)
-  )
+skip_if_not_or_load_if_installed <- function(package, minimum_version = NULL) {
+  testthat::skip_if_not_installed(package, minimum_version = minimum_version)
+  suppressMessages(suppressWarnings(suppressPackageStartupMessages(
+    require(package, warn.conflicts = FALSE, character.only = TRUE, quietly = TRUE)
+  )))
 }
-
-# load hard dependencies
-library(insight)
-library(datawizard)
diff --git a/tests/testthat/test-BFBayesFactor.R b/tests/testthat/test-BFBayesFactor.R
@@ -1,86 +1,85 @@
-if (requiet("BayesFactor")) {
+test_that("p_direction", {
+  skip_if_not_or_load_if_installed("BayesFactor")
   set.seed(333)
-  x <- BayesFactor::correlationBF(y = iris$Sepal.Length, x = iris$Sepal.Width)
-  test_that("p_direction", {
-    expect_equal(as.numeric(p_direction(x)), 0.9225, tolerance = 1)
-  })
+  x <- correlationBF(y = iris$Sepal.Length, x = iris$Sepal.Width)
+  expect_equal(as.numeric(p_direction(x)), 0.9225, tolerance = 1)
+})
 
-
-  # BF t.test one sample ---------------------------
+test_that("p_direction: BF t.test one sample", {
+  skip_if_not_or_load_if_installed("BayesFactor")
   data(sleep)
   diffScores <- sleep$extra[1:10] - sleep$extra[11:20]
-  x <- BayesFactor::ttestBF(x = diffScores)
-  test_that("p_direction", {
-    expect_equal(as.numeric(p_direction(x)), 0.99675, tolerance = 1)
-  })
+  x <- ttestBF(x = diffScores)
+  expect_equal(as.numeric(p_direction(x)), 0.99675, tolerance = 1)
+})
 
 
-  # BF t.test two samples ---------------------------
+test_that("p_direction: BF t.test two samples", {
+  skip_if_not_or_load_if_installed("BayesFactor")
   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", {
-    expect_equal(as.numeric(p_direction(x)), 1, tolerance = 1)
-  })
+  x <- ttestBF(formula = weight ~ feed, data = chickwts)
+  expect_equal(as.numeric(p_direction(x)), 1, tolerance = 1)
+})
 
-  # BF t.test meta-analytic ---------------------------
+test_that("p_direction: BF t.test meta-analytic", {
+  skip_if_not_or_load_if_installed("BayesFactor")
   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", {
-    expect_equal(as.numeric(p_direction(x)), 0.99975, tolerance = 1)
-  })
+  x <- meta.ttestBF(t = t, n1 = N, rscale = 1)
+  expect_equal(as.numeric(p_direction(x)), 0.99975, tolerance = 1)
+})
 
-  # # ---------------------------
-  # # "BF ANOVA"
-  # data(ToothGrowth)
-  # ToothGrowth$dose <- factor(ToothGrowth$dose)
-  # levels(ToothGrowth$dose) <- c("Low", "Medium", "High")
-  # x <- BayesFactor::anovaBF(len ~ supp*dose, data=ToothGrowth)
-  # test_that("p_direction", {
-  #   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
-  # })
-  #
-  # # ---------------------------
-  # # "BF ANOVA Random"
-  # data(puzzles)
-  # x <- BayesFactor::anovaBF(RT ~ shape*color + ID, data = puzzles, whichRandom="ID")
-  # test_that("p_direction", {
-  #   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
-  # })
-  #
-  #
-  # # ---------------------------
-  # # "BF lm"
-  # x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth)
-  # test_that("p_direction", {
-  #   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
-  # })
-  #
-  #
-  # x2 <- BayesFactor::lmBF(len ~ supp + dose + supp:dose, data = ToothGrowth)
-  # x <- x / x2
-  # test_that("p_direction", {
-  #   expect_equal(as.numeric(p_direction(x)), 91.9, tol=0.1)
-  # })
+# # ---------------------------
+# # "BF ANOVA"
+# data(ToothGrowth)
+# ToothGrowth$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)
+# })
+#
+# # ---------------------------
+# # "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)
+# })
+#
+#
+# # ---------------------------
+# # "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)
+# })
 
 
-  test_that("rope_range", {
-    x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth)
-    expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10)
+test_that("rope_range", {
+  skip_if_not_or_load_if_installed("BayesFactor")
+  x <- lmBF(len ~ supp + dose, data = ToothGrowth)
+  expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10)
 
-    x <- BayesFactor::ttestBF(
-      ToothGrowth$len[ToothGrowth$supp == "OJ"],
-      ToothGrowth$len[ToothGrowth$supp == "VC"]
-    )
-    expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10)
+  x <- ttestBF(
+    ToothGrowth$len[ToothGrowth$supp == "OJ"],
+    ToothGrowth$len[ToothGrowth$supp == "VC"]
+  )
+  expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10)
 
-    x <- BayesFactor::ttestBF(formula = len ~ supp, data = ToothGrowth)
-    expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10)
+  x <- ttestBF(formula = len ~ supp, data = ToothGrowth)
+  expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10)
 
-    # else
-    x <- BayesFactor::correlationBF(ToothGrowth$len, ToothGrowth$dose)
-    expect_equal(rope_range(x, verbose = FALSE), c(-0.05, 0.05))
-  })
-}
+  # else
+  x <- correlationBF(ToothGrowth$len, ToothGrowth$dose)
+  expect_equal(rope_range(x, verbose = FALSE), c(-0.05, 0.05))
+})