test prediction summarization with funs when type = 'mean'

tests/testthat/test-predict.R

@@ -370,6 +370,7 @@ test_that("global_fixed options produce equal results with balanced data", {
 })
 
 test_that("summarising via funs is equivalent to manual summary", {
+  # type = "response"
   set.seed(1)
   pred1 <- predict(
     gaussian_example_fit,
@@ -378,14 +379,36 @@ test_that("summarising via funs is equivalent to manual summary", {
   )
   pred1 <- pred1$simulated |> dplyr::filter(time > 1)
   set.seed(1)
-  pred2 <- predict(gaussian_example_fit, n_draws = 2L, expand = FALSE)
+  pred2 <- predict(
+    gaussian_example_fit, n_draws = 2L, expand = FALSE
+  )
   pred2 <- pred2$simulated |>
     dplyr::group_by(time, .draw) |>
-    dplyr::summarise(y_mean = mean(y_new), y_sd = sd(y_new)) |>
     dplyr::filter(time > 1) |>
+    dplyr::summarise(mean_y = mean(y_new), sd_y = sd(y_new)) |>
+    dplyr::arrange(.draw)
+  expect_equal(pred1$mean_y, pred2$mean_y)
+  expect_equal(pred1$sd_y, pred2$sd_y)
+  # type = "mean"
+  set.seed(1)
+  pred3 <- predict(
+    gaussian_example_fit,
+    type = "mean",
+    funs = list(y = list(mean = mean, sd = sd)),
+    n_draws = 2L
+  )
+  pred3 <- pred3$simulated |> dplyr::filter(time > 1)
+  set.seed(1)
+  pred4 <- predict(
+    gaussian_example_fit, type = "mean", n_draws = 2L, expand = FALSE
+  )
+  pred4 <- pred4$simulated |>
+    dplyr::group_by(time, .draw) |>
+    dplyr::filter(time > 1) |>
+    dplyr::summarise(mean_y = mean(y_mean), sd_y = sd(y_mean)) |>
     dplyr::arrange(.draw)
-  expect_equal(pred1$mean_y, pred2$y_mean)
-  expect_equal(pred1$sd_y, pred2$y_sd)
+  expect_equal(pred3$mean_y, pred4$mean_y)
+  expect_equal(pred3$sd_y, pred4$sd_y)
 })
 
 test_that("predict with loglik works", {