use insight helpers (#402)

easystats/easystats#220

R/check_normality.R

@@ -61,7 +61,7 @@ check_normality.default <- function(x, ...) {
   p.val <- .check_normality(stats::rstandard(x), x)
 
   attr(p.val, "data") <- x
-  attr(p.val, "object_name") <- .safe_deparse(substitute(x))
+  attr(p.val, "object_name") <- insight::safe_deparse(substitute(x))
   attr(p.val, "effects") <- "fixed"
   class(p.val) <- unique(c("check_normality", "see_check_normality", class(p.val)))
 
@@ -149,7 +149,7 @@ check_normality.merMod <- function(x, effects = c("fixed", "random"), ...) {
   }
 
   attr(p.val, "data") <- x
-  attr(p.val, "object_name") <- .safe_deparse(substitute(x))
+  attr(p.val, "object_name") <- insight::safe_deparse(substitute(x))
   attr(p.val, "effects") <- effects
   class(p.val) <- unique(c("check_normality", "see_check_normality", class(p.val)))
 
@@ -171,7 +171,7 @@ check_normality.afex_aov <- function(x, ...) {
   p.val <- .check_normality(r, x)
 
   attr(p.val, "data") <- x
-  attr(p.val, "object_name") <- .safe_deparse(substitute(x))
+  attr(p.val, "object_name") <- insight::safe_deparse(substitute(x))
   class(p.val) <- unique(c("check_normality", "see_check_normality", class(p.val)))
 
   invisible(p.val)

R/compare_performance.R

@@ -106,7 +106,7 @@ compare_performance <- function(..., metrics = "all", rank = FALSE, estimator =
   # iterate over all models, i.e. model-performance for each model
   m <- mapply(function(.x, .y) {
     dat <- model_performance(.x, metrics = metrics, estimator = estimator, verbose = FALSE)
-    model_name <- gsub("\"", "", .safe_deparse(.y), fixed = TRUE)
+    model_name <- gsub("\"", "", insight::safe_deparse(.y), fixed = TRUE)
     perf_df <- data.frame(Name = model_name, Model = class(.x)[1], dat, stringsAsFactors = FALSE)
     attributes(perf_df) <- c(attributes(perf_df), attributes(dat)[!names(attributes(dat)) %in% c("names", "row.names", "class")])
     return(perf_df)

R/helpers.R

@@ -1,7 +1,3 @@
-# trim leading / trailing whitespaces
-.trim <- function(x) gsub("^\\s+|\\s+$", "", x)
-
-
 .get_BIC <- function(x, estimator = "ML") {
   # check ML estimator
   if (missing(estimator) && inherits(x, "lmerMod")) {
@@ -25,14 +21,6 @@
 }
 
 
-
-
-# safe deparse, works for very long strings
-.safe_deparse <- function(string) {
-  paste0(sapply(deparse(string, width.cutoff = 500), .trim, simplify = TRUE), collapse = "")
-}
-
-
 .std <- function(x) {
   if (!is.numeric(x)) {
     return(x)

R/icc.R

@@ -360,7 +360,7 @@ print.icc_decomposed <- function(x, digits = 2, ...) {
   if (is.null(reform)) {
     reform <- "all random effects"
   } else {
-    reform <- .safe_deparse(reform)
+    reform <- insight::safe_deparse(reform)
   }
 
   cat(sprintf("Conditioned on: %s\n\n", reform))

R/performance_roc.R

@@ -49,8 +49,8 @@ performance_roc <- function(x, ..., predictions, new_data) {
   dots <- list(...)
 
   object_names <- c(
-    .safe_deparse(substitute(x)),
-    sapply(match.call(expand.dots = FALSE)$`...`, .safe_deparse)
+    insight::safe_deparse(substitute(x)),
+    sapply(match.call(expand.dots = FALSE)$`...`, insight::safe_deparse)
   )
 
   if (insight::is_model(x)) {