Fix_gamlss (#828)

* fix issue with find_formula.gamlss with namespace

* news, version

* lintr

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: insight
 Title: Easy Access to Model Information for Various Model Objects
-Version: 0.19.6.4
+Version: 0.19.6.5
 Authors@R: 
     c(person(given = "Daniel",
              family = "Lüdecke",

NEWS.md

@@ -17,6 +17,9 @@
 * Fixed issue in `model_info()`, where in some cases logistic regression models
   were erroneously considered as `"bernoulli"` models.
 
+* Fixed issue in `find_formula()` for models of class `gamlss` when the `random()`
+  function was used with namespace in the formula (i.e. `... + gamlss::random()`).
+
 # insight 0.19.6
 
 ## General

R/find_formula.R

@@ -192,9 +192,21 @@ find_formula.gamlss <- function(x, verbose = TRUE, ...) {
       if (length(f.random) == 1L) {
         f.random <- f.random[[1]]
       } else if (grepl("random\\((.*)\\)", safe_deparse(f.cond))) {
-        re <- gsub("(.*)random\\((.*)\\)", "\\2", safe_deparse(f.cond))
+        f.cond <- safe_deparse(f.cond)
+        # remove namespace prefixes
+        if (grepl("::", f.cond, fixed = TRUE)) {
+          # Here's a regular expression pattern in R that removes any word
+          # followed by two colons from a string: This pattern matches a word
+          # boundary (\\b), followed by one or more word characters (\\w+),
+          # followed by two colons (::)
+          f.cond <- gsub("\\b\\w+::", "\\2", f.cond)
+        }
+        re <- gsub("(.*)random\\((.*)\\)", "\\2", f.cond)
         f.random <- stats::as.formula(paste0("~1|", re))
-        f.cond <- stats::update.formula(f.cond, stats::as.formula(paste0(". ~ . - random(", re, ")")))
+        f.cond <- stats::update.formula(
+          stats::as.formula(f.cond),
+          stats::as.formula(paste0(". ~ . - random(", re, ")"))
+        )
       }
 
       compact_list(list(
@@ -1787,7 +1799,7 @@ find_formula.model_fit <- function(x, verbose = TRUE, ...) {
   if (grepl("(.*)poly\\((.*),\\s*raw\\s*=\\s*T\\)", f)) {
     if (verbose) {
       format_warning(
-        "Looks like you are using `poly()` with \"raw = T\". This results in unexpected behaviour, because `all.vars()` considers `T` as variable.",
+        "Looks like you are using `poly()` with \"raw = T\". This results in unexpected behaviour, because `all.vars()` considers `T` as variable.", # nolint
         "Please use \"raw = TRUE\"."
       )
     }
@@ -1813,7 +1825,7 @@ find_formula.model_fit <- function(x, verbose = TRUE, ...) {
     } else {
       if (verbose) {
         format_warning(paste0(
-          "Using `$` in model formulas can produce unexpected results. Specify your model using the `data` argument instead.",
+          "Using `$` in model formulas can produce unexpected results. Specify your model using the `data` argument instead.", # nolint
           "\n  Try: ", fc$formula, ", data = ", fc$data
         ))
       }

tests/testthat/test-gamlss.R

@@ -49,15 +49,15 @@ test_that("find_response", {
 })
 
 test_that("get_response", {
-  expect_equal(get_response(m_gamlss1), abdom$y)
+  expect_identical(get_response(m_gamlss1), abdom$y)
 })
 
 test_that("get_predictors", {
   expect_identical(colnames(get_predictors(m_gamlss1)), "x")
 })
 
 test_that("get_data", {
-  expect_equal(nrow(get_data(m_gamlss1)), 610)
+  expect_identical(nrow(get_data(m_gamlss1)), 610L)
   expect_identical(colnames(get_data(m_gamlss1)), c("y", "x"))
 })
 
@@ -101,7 +101,7 @@ test_that("find_terms", {
 })
 
 test_that("n_obs", {
-  expect_equal(n_obs(m_gamlss1), 610)
+  expect_identical(n_obs(m_gamlss1), 610L)
 })
 
 test_that("link_function", {
@@ -122,7 +122,7 @@ test_that("find_parameters", {
       tau = "(Intercept)"
     )
   )
-  expect_equal(nrow(get_parameters(m_gamlss1)), 6)
+  expect_identical(nrow(get_parameters(m_gamlss1)), 6L)
 })
 
 test_that("is_multivariate", {
@@ -136,3 +136,21 @@ test_that("find_algorithm", {
 test_that("find_statistic", {
   expect_identical(find_statistic(m_gamlss1), "t-statistic")
 })
+
+test_that("find_formula works with namespace colons", {
+  data(iris)
+  m <- gamlss::gamlss(
+    Sepal.Length ~ Sepal.Width + gamlss::random(Species),
+    sigma.formula = ~Sepal.Width,
+    data = iris
+  )
+  expect_equal(
+    find_formula(m),
+    list(
+      conditional = Sepal.Length ~ Sepal.Width,
+      random = ~ 1 | Species,
+      sigma = ~Sepal.Width
+    ),
+    ignore_attr = TRUE
+  )
+})