Coerce to data frame class

DESCRIPTION

@@ -21,6 +21,7 @@ Suggests:
     knitr,
     rmarkdown,
     testthat (>= 3.0.0),
+    tibble,
     withr
 Config/testthat/edition: 3
 Imports: 

R/coev_make_stancode.R

@@ -81,6 +81,8 @@ coev_make_stancode <- function(data, variables, id, tree,
   # check arguments
   run_checks(data, variables, id, tree, effects_mat,
              dist_mat, prior, scale, prior_only)
+  # coerce data argument to data frame
+  data <- as.data.frame(data)
   # extract distributions and variable names from named list
   distributions <- as.character(variables)
   variables <- names(variables)

R/coev_make_standata.R

@@ -76,6 +76,8 @@ coev_make_standata <- function(data, variables, id, tree,
   # check arguments
   run_checks(data, variables, id, tree, effects_mat,
              dist_mat, prior, scale, prior_only)
+  # coerce data argument to data frame
+  data <- as.data.frame(data)
   # warning if scale = FALSE
   if (!scale) {
     warning2(

tests/testthat/test-coev_make_stancode.R

@@ -757,3 +757,31 @@ test_that("coev_make_stancode() works with repeated observations", {
     )$check_syntax(quiet = TRUE)
   )
 })
+
+test_that("coev_make_stancode() works with tibbles", {
+  # simulate data
+  withr::with_seed(1, {
+    n <- 20
+    tree <- ape::rcoal(n)
+    d <- tibble::tibble(
+      id = tree$tip.label,
+      x = rbinom(n, size = 1, prob = 0.5),
+      y = ordered(sample(1:4, size = n, replace = TRUE))
+    )
+  })
+  # make stan code
+  sc <-
+    coev_make_stancode(
+      data = d,
+      variables = list(
+        x = "bernoulli_logit",
+        y = "ordered_logistic"
+      ),
+      id = "id",
+      tree = tree
+    )
+  # expect string of length one
+  expect_no_error(sc)
+  expect_type(sc, "character")
+  expect_length(sc, 1)
+})

tests/testthat/test-coev_make_standata.R

@@ -741,3 +741,36 @@ test_that("coev_make_stancode() scales data correctly", {
   expect_identical(sd2$y[,"y"], as.numeric(scale(d$y)))
   expect_identical(sd2$y[,"z"], as.numeric(exp(scale(log(d$z)))))
 })
+
+test_that("coev_make_standata() works with tibbles", {
+  # simulate data
+  withr::with_seed(1, {
+    n <- 20
+    tree <- ape::rcoal(n)
+    d <- tibble::tibble(
+      id = tree$tip.label,
+      x = rbinom(n, size = 1, prob = 0.5),
+      y = ordered(sample(1:4, size = n, replace = TRUE))
+    )
+  })
+  # make stan data
+  sd <-
+    coev_make_standata(
+      data = d,
+      variables = list(
+        x = "bernoulli_logit",
+        y = "ordered_logistic"
+      ),
+      id = "id",
+      tree = tree
+    )
+  # expect list with correct names and prior_only = 0
+  expect_no_error(sd)
+  expect_type(sd, "list")
+  expect_equal(
+    names(sd),
+    c("N_tips", "N_obs", "J", "N_seg", "node_seq", "parent", "ts", "tip",
+      "effects_mat", "num_effects", "y", "miss", "tip_id", "prior_only")
+  )
+  expect_equal(sd$prior_only, 0)
+})