Improve error message if any data is NULL

R/data.R

@@ -77,6 +77,9 @@ write_stan_json <- function(data, file, always_decimal = FALSE) {
 
   for (var_name in data_names) {
     var <- data[[var_name]]
+    if (is.null(var)) {
+      stop("Variable '", var_name, "' is NULL.", call. = FALSE)
+    }
     if (!(is.numeric(var) || is.factor(var) || is.logical(var) ||
           is.data.frame(var) || is.list(var))) {
       stop("Variable '", var_name, "' is of invalid type.", call. = FALSE)
@@ -176,7 +179,10 @@ process_data <- function(data, model_variables = NULL) {
           call. = FALSE
         )
       }
-      for(var_name in names(data_variables)) {
+      for (var_name in names(data_variables)) {
+        if (is.null(data[[var_name]])) {
+          stop("Variable '", var_name, "' is NULL.", call. = FALSE)
+        }
         # distinguish between scalars and arrays/vectors of length 1
         if (length(data[[var_name]]) == 1
             && data_variables[[var_name]]$dimensions == 1) {

tests/testthat/test-data.R

@@ -44,6 +44,19 @@ test_that("process_data works for inputs of length one", {
   expect_equal(jsonlite::read_json(process_data(data, model_variables = mod$variables())), list(val = list(5)))
 })
 
+test_that("process_data errors on NULL data variables", {
+  stan_file <- write_stan_file("
+  data {
+    int N;
+  }
+  ")
+  mod <- cmdstan_model(stan_file, compile = FALSE)
+  expect_error(
+    process_data(list(N = NULL), model_variables = mod$variables()),
+    "Variable 'N' is NULL"
+  )
+})
+
 test_that("process_fitted_params() works with basic input types", {
   temp_file <- tempfile()
   temp_files <- c(tempfile(),

tests/testthat/test-json.R

@@ -116,6 +116,13 @@ test_that("write_stan_json errors if NAs", {
   )
 })
 
+test_that("write_stan_json errors if NULL variables", {
+  expect_error(
+    write_stan_json(list(N = NULL), tempfile()),
+    "Variable 'N' is NULL"
+  )
+})
+
 test_that("write_stan_json() errors if data is not a list", {
   expect_error(
     write_stan_json(1:10),