prepare CRAN release (#902)

* prepare CRAN release

* add dep

* Update DESCRIPTION

* Update test-brms_gr_random_effects.R

* minior

* lintr

* style

* submitted

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 0.20.1
-Date: 2024-06-11 14:53:20 UTC
-SHA: 622b973d4f2c62cb42d6fc4b4c04907533096fcb
+Version: 0.20.2
+Date: 2024-07-13 14:49:57 UTC
+SHA: 37daa8e0de05efc3991dee23a895598725cbff3e

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: insight
 Title: Easy Access to Model Information for Various Model Objects
-Version: 0.20.1.14
+Version: 0.20.2
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -93,6 +93,7 @@ Suggests:
     betareg,
     bife,
     biglm,
+    BH,
     blavaan (>= 0.5-5),
     blme,
     boot,
@@ -180,6 +181,7 @@ Suggests:
     psych,
     quantreg,
     Rcpp,
+    RcppEigen,
     rmarkdown,
     rms,
     robustbase,
@@ -212,4 +214,3 @@ Roxygen: list(markdown = TRUE)
 Config/testthat/edition: 3
 Config/testthat/parallel: true
 Config/Needs/website: easystats/easystatstemplate
-Remotes: easystats/performance

R/find_random.R

@@ -54,7 +54,6 @@ find_random.default <- function(x, split_nested = FALSE, flatten = FALSE) {
     l <- .find_random_effects(x, f, split_nested)
   }
 
-
   if (is_empty_object(l)) {
     return(NULL)
   }
@@ -76,7 +75,6 @@ find_random.afex_aov <- function(x, split_nested = FALSE, flatten = FALSE) {
 }
 
 
-
 .find_random_effects <- function(x, f, split_nested) {
   if (!object_has_names(f, "random") && !object_has_names(f, "zero_inflated_random")) {
     return(NULL)
@@ -100,7 +98,6 @@ find_random.afex_aov <- function(x, split_nested = FALSE, flatten = FALSE) {
     r1 <- NULL
   }
 
-
   if (object_has_names(f, "zero_inflated_random")) {
     if (is.list(f$zero_inflated_random)) {
       r2 <- unique(unlist(
@@ -114,6 +111,5 @@ find_random.afex_aov <- function(x, split_nested = FALSE, flatten = FALSE) {
     r2 <- NULL
   }
 
-
   compact_list(list(random = r1, zero_inflated_random = r2))
 }

R/helper_functions.R

@@ -1,6 +1,6 @@
 # small wrapper around this commonly used try-catch
 .safe <- function(code, on_error = NULL) {
-  if (isTRUE(getOption("easystats_erros", FALSE)) && is.null(on_error)) {
+  if (isTRUE(getOption("easystats_errors", FALSE)) && is.null(on_error)) {
     code
   } else {
     tryCatch(code, error = function(e) on_error)
@@ -122,7 +122,6 @@
 }
 
 
-
 # extract random effects from formula
 .get_model_random <- function(f, model, split_nested = FALSE) {
   is_special <- inherits(
@@ -195,7 +194,6 @@
 }
 
 
-
 # in case we need the random effects terms as formula (symbol),
 # not as character string, then call this functions instead of
 # .get_model_random()
@@ -220,10 +218,8 @@
 }
 
 
-
 # helper to access model components ----------------
 
-
 .all_elements <- function() {
   c(
     "conditional", "conditional1", "conditional2", "conditional3", "precision",
@@ -284,7 +280,6 @@
     return(auxiliary_parameters)
   }
 
-
   elements <- switch(effects,
     all = elements,
     fixed = elements[!elements %in% random_parameters],
@@ -304,7 +299,6 @@
 }
 
 
-
 # Filter parameters from Stan-model fits
 .filter_pars <- function(l, parameters = NULL, is_mv = NULL) {
   if (!is.null(parameters)) {
@@ -325,7 +319,6 @@
 }
 
 
-
 .filter_pars_univariate <- function(l, parameters) {
   lapply(l, function(component) {
     unlist(sapply(
@@ -339,14 +332,12 @@
 }
 
 
-
 # remove column
 .remove_column <- function(data, variables) {
   data[, -which(colnames(data) %in% variables), drop = FALSE]
 }
 
 
-
 .grep_smoothers <- function(x) {
   startsWith(x, "s(") |
     startsWith(x, "ti(") |
@@ -364,15 +355,13 @@
 }
 
 
-
 .grep_zi_smoothers <- function(x) {
   grepl("^(s\\.\\d\\()", x, perl = TRUE) |
     grepl("^(gam::s\\.\\d\\()", x, perl = TRUE) |
     grepl("^(mgcv::s\\.\\d\\()", x, perl = TRUE)
 }
 
 
-
 .grep_non_smoothers <- function(x) {
   grepl("^(?!(s\\())", x, perl = TRUE) &
     # this one captures smoothers in zi- or mv-models from gam
@@ -393,7 +382,6 @@
 }
 
 
-
 # .split_formula <- function(f) {
 #   rhs <- if (length(f) > 2L)
 #     f[[3L]]
@@ -418,7 +406,6 @@
 # }
 
 
-
 .gam_family <- function(x) {
   faminfo <- .safe(stats::family(x))
 
@@ -431,7 +418,6 @@
 }
 
 
-
 # for models with zero-inflation component, return
 # required component of model-summary
 .filter_component <- function(dat, component) {
@@ -452,8 +438,6 @@
 }
 
 
-
-
 #' @keywords internal
 .gather <- function(x,
                     names_to = "key",
@@ -480,7 +464,6 @@
 }
 
 
-
 .is_baysian_emmeans <- function(x) {
   if (inherits(x, "emm_list")) {
     x <- x[[1]]
@@ -490,7 +473,6 @@
 }
 
 
-
 .is_bayesian_model <- function(x) {
   inherits(x, c(
     "brmsfit", "stanfit", "MCMCglmm", "stanreg",
@@ -502,7 +484,6 @@
 }
 
 
-
 # safe conversion from factor to numeric
 .factor_to_numeric <- function(x, lowest = NULL) {
   if (is.data.frame(x)) {
@@ -549,9 +530,6 @@
 }
 
 
-
-
-
 ## copied from lme4::findbars() -----------------------
 
 
@@ -567,7 +545,6 @@
 }
 
 
-
 .expandDoubleVerts <- function(term) {
   if (!is.name(term) && is.language(term)) {
     if (term[[1]] == as.name("(")) {
@@ -586,7 +563,6 @@
 }
 
 
-
 .findbars <- function(term) {
   fb <- function(term) {
     if (is.name(term) || !is.language(term)) {
@@ -651,8 +627,6 @@
 }
 
 
-
-
 ## copied from lme4::nobars() -----------------------
 
 
@@ -672,7 +646,6 @@
 }
 
 
-
 .nobars_ <- function(term) {
   if (!(any(c("|", "||") %in% all.names(term)))) {
     return(term)
@@ -712,7 +685,6 @@
 }
 
 
-
 .isBar <- function(term) {
   if (is.call(term) && ((term[[1]] == as.name("|") || term[[1]] == as.name("||")))) {
     return(TRUE)
@@ -733,7 +705,6 @@
 }
 
 
-
 # classify emmeans objects -------------
 
 

R/print.easystats_check.R

@@ -1,21 +1,21 @@
 #' @export
 print.easystats_check <- function(x, ...) {
   # check attributes
-  title <- attr(x, "title")
-  text <- attr(x, "text")
+  my_title <- attr(x, "title")
+  my_text <- attr(x, "text")
   color <- attr(x, "color")
 
   # no attributes found? check list elements then...
-  if (is.null(title) && is.null(text) && is.null(color)) {
-    if ("title" %in% names(x)) title <- x$title
-    if ("text" %in% names(x)) text <- x$text
+  if (is.null(my_title) && is.null(my_text) && is.null(color)) {
+    if ("title" %in% names(x)) my_title <- x$title
+    if ("text" %in% names(x)) my_text <- x$text
     if ("color" %in% names(x)) color <- x$color
   }
 
-  if (!is.null(title)) {
-    print_color(paste0("# ", title, "\n\n"), "blue")
+  if (!is.null(my_title)) {
+    print_color(paste0("# ", my_title, "\n\n"), "blue")
   }
 
-  print_color(text, color)
+  print_color(my_text, color)
   invisible(x)
 }

R/utilities.R

@@ -131,7 +131,7 @@ safe_deparse_symbol <- function(x) {
   } else {
     out <- NULL
   }
-  return(out)
+  out
 }
 
 

cran-comments.md

@@ -1 +1 @@
-This is a hotfix release that fixes memory allocation issues when `insight::get_datagrid()` was called with the deprecated argument `at = NULL`.
+Maintainance release.

tests/testthat/test-GLMMadaptive.R

@@ -384,7 +384,7 @@ test_that("detect custom families", {
   # we set the zeros from the logistic regression
   DF$y[as.logical(rbinom(n * K, size = 1, prob = plogis(eta_zi)))] <- 0
 
-    hurdle.lognormal <- function() {
+  hurdle.lognormal <- function() {
     stats <- make.link("identity")
     log_dens <- function(y, eta, mu_fun, phis, eta_zi) {
       sigma <- exp(phis)

tests/testthat/test-brms_gr_random_effects.R

@@ -1,6 +1,8 @@
 skip_on_cran()
 skip_on_os("mac")
 skip_if_not_installed("brms")
+skip_if_not_installed("BH")
+skip_if_not_installed("RcppEigen")
 skip_if_not_installed("withr")
 
 withr::with_environment(

tests/testthat/test-r2_nakagawa_bernoulli.R

@@ -3,7 +3,7 @@ skip_on_cran()
 skip_if_not_installed("glmmTMB")
 skip_if_not_installed("MuMIn")
 skip_if_not_installed("lme4")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 skip_if_not_installed("datawizard")
 
 

tests/testthat/test-r2_nakagawa_beta.R

@@ -2,7 +2,7 @@ skip_on_cran()
 
 skip_if_not_installed("glmmTMB")
 skip_if_not_installed("MuMIn")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 
 
 # ==============================================================================

tests/testthat/test-r2_nakagawa_binomial.R

@@ -3,7 +3,7 @@ skip_on_cran()
 skip_if_not_installed("glmmTMB")
 skip_if_not_installed("MuMIn")
 skip_if_not_installed("lme4")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 
 
 # ==============================================================================

tests/testthat/test-r2_nakagawa_gamma.R

@@ -1,7 +1,7 @@
 skip_on_cran()
 
 skip_if_not_installed("MuMIn")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 
 # ==============================================================================
 # Gamma mixed models, glmmTMB ----

tests/testthat/test-r2_nakagawa_linear.R

@@ -3,7 +3,7 @@ skip_on_cran()
 skip_if_not_installed("glmmTMB")
 skip_if_not_installed("MuMIn")
 skip_if_not_installed("lme4")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 
 
 # ==============================================================================

tests/testthat/test-r2_nakagawa_negbin.R

@@ -3,7 +3,7 @@ skip_on_cran()
 skip_if_not_installed("glmmTMB")
 skip_if_not_installed("MuMIn")
 skip_if_not_installed("lme4")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 
 
 # ==============================================================================

tests/testthat/test-r2_nakagawa_negbin_zi.R

@@ -2,7 +2,7 @@ skip_on_cran()
 
 skip_if_not_installed("glmmTMB")
 skip_if_not_installed("MuMIn")
-skip_if_not_installed("performance")
+skip_if_not_installed("performance", minimum_version = "0.12.1")
 
 
 # ==============================================================================