clean few line length lints

easystats/easystats#334

R/binned_residuals.R

@@ -123,11 +123,29 @@ print.binned_residuals <- function(x, ...) {
 
   if (!is.null(resid_ok)) {
     if (resid_ok < 0.8) {
-      insight::print_color(sprintf("Warning: Probably bad model fit. Only about %g%% of the residuals are inside the error bounds.\n", round(100 * resid_ok)), "red")
+      insight::print_color(
+        sprintf(
+          "Warning: Probably bad model fit. Only about %g%% of the residuals are inside the error bounds.\n",
+          round(100 * resid_ok)
+        ),
+        "red"
+      )
     } else if (resid_ok < 0.95) {
-      insight::print_color(sprintf("Warning: About %g%% of the residuals are inside the error bounds (~95%% or higher would be good).\n", round(100 * resid_ok)), "yellow")
+      insight::print_color(
+        sprintf(
+          "Warning: About %g%% of the residuals are inside the error bounds (~95%% or higher would be good).\n",
+          round(100 * resid_ok)
+        ),
+        "yellow"
+      )
     } else {
-      insight::print_color(sprintf("Ok: About %g%% of the residuals are inside the error bounds.\n", round(100 * resid_ok)), "green")
+      insight::print_color(
+        sprintf(
+          "Ok: About %g%% of the residuals are inside the error bounds.\n",
+          round(100 * resid_ok)
+        ),
+        "green"
+      )
     }
   }
 }

R/check_autocorrelation.R

@@ -60,9 +60,21 @@ plot.check_autocorrelation <- function(x, ...) {
 #' @export
 print.check_autocorrelation <- function(x, ...) {
   if (x < 0.05) {
-    insight::print_color(sprintf("Warning: Autocorrelated residuals detected (%s).", insight::format_p(x)), "red")
+    insight::print_color(
+      sprintf(
+        "Warning: Autocorrelated residuals detected (%s).",
+        insight::format_p(x)
+      ),
+      "red"
+    )
   } else {
-    insight::print_color(sprintf("OK: Residuals appear to be independent and not autocorrelated (%s).", insight::format_p(x)), "green")
+    insight::print_color(
+      sprintf(
+        "OK: Residuals appear to be independent and not autocorrelated (%s).",
+        insight::format_p(x)
+      ),
+      "green"
+    )
   }
   invisible(x)
 }

R/check_factorstructure.R

@@ -136,10 +136,18 @@ check_kmo <- function(x, n = NULL, ...) {
 
   # TODO: add interpret_kmo in effectsize and use that here for more fine-grained interpretation
   if (MSA < 0.5) {
-    text <- sprintf("The Kaiser, Meyer, Olkin (KMO) overall measure of sampling adequacy suggests that factor analysis is likely to be inappropriate (KMO = %.2f).", MSA)
+    text <-
+      sprintf(
+        "The Kaiser, Meyer, Olkin (KMO) overall measure of sampling adequacy suggests that factor analysis is likely to be inappropriate (KMO = %.2f).",
+        MSA
+      )
     color <- "red"
   } else {
-    text <- sprintf("The Kaiser, Meyer, Olkin (KMO) overall measure of sampling adequacy suggests that data seems appropriate for factor analysis (KMO = %.2f).", MSA)
+    text <-
+      sprintf(
+        "The Kaiser, Meyer, Olkin (KMO) overall measure of sampling adequacy suggests that data seems appropriate for factor analysis (KMO = %.2f).",
+        MSA
+      )
     color <- "green"
   }
 

R/check_model_diagnostics.R

@@ -51,7 +51,12 @@
 
   if (is.null(res_)) {
     if (verbose) {
-      insight::format_alert(sprintf("QQ plot could not be created. Cannot extract residuals from objects of class `%s`.", class(model)[1]))
+      insight::format_alert(
+        sprintf(
+          "QQ plot could not be created. Cannot extract residuals from objects of class `%s`.",
+          class(model)[1]
+        )
+      )
     }
     return(NULL)
   }

R/performance_roc.R

@@ -14,7 +14,8 @@
 #' @param ... One or more models with binomial outcome. In this case,
 #'   `new_data` is ignored.
 #'
-#' @note There is also a [`plot()`-method](https://easystats.github.io/see/articles/performance.html) implemented in the \href{https://easystats.github.io/see/}{\pkg{see}-package}.
+#' @note There is also a [`plot()`-method](https://easystats.github.io/see/articles/performance.html)
+#' implemented in the \href{https://easystats.github.io/see/}{\pkg{see}-package}.
 #'
 #' @return A data frame with three columns, the x/y-coordinate pairs for the ROC
 #'   curve (`Sensitivity` and `Specificity`), and a column with the

R/performance_score.R

@@ -66,14 +66,21 @@ performance_score <- function(model, verbose = TRUE, ...) {
   }
 
   if (minfo$is_ordinal || minfo$is_multinomial) {
-    if (verbose) insight::print_color("Can't calculate proper scoring rules for ordinal, multinomial or cumulative link models.\n", "red")
+    if (verbose) {
+      insight::print_color("Can't calculate proper scoring rules for ordinal, multinomial or cumulative link models.\n", "red")
+    }
     return(list(logarithmic = NA, quadratic = NA, spherical = NA))
   }
 
   resp <- insight::get_response(model, verbose = verbose)
 
   if (!is.null(ncol(resp)) && ncol(resp) > 1) {
-    if (verbose) insight::print_color("Can't calculate proper scoring rules for models without integer response values.\n", "red")
+    if (verbose) {
+      insight::print_color(
+        "Can't calculate proper scoring rules for models without integer response values.\n",
+        "red"
+      )
+    }
     return(list(logarithmic = NA, quadratic = NA, spherical = NA))
   }