Removed limit for future.globals.maxSize

vignettes/ale-small-datasets.Rmd

@@ -1,7 +1,7 @@
 ---
 title: "Analyzing small datasets (fewer than 2000 rows) with ALE"
 author: "Chitu Okoli"
-date: "January 9, 2024"
+date: "November 14, 2024"
 output: rmarkdown::html_vignette
 vignette: >
   %\VignetteIndexEntry{Analyzing small datasets (fewer than 2000 rows) with ALE}
@@ -29,6 +29,14 @@ We begin by loading the necessary libraries.
 library(ale)
 ```
 
+```{r allow max future size, include=FALSE}
+# Resolution to https://forum.posit.co/t/the-total-size-of-the-x-globals-exported-for-future-expression-in-r-cmd-check-only-on-ubuntu-latest-devel/194864
+# Remove limit for future sizes to stop complaints by ubuntu-latest (devel) https://future.futureverse.org/reference/future.options.html#options-for-controlling-futures-1
+options(future.globals.maxSize = +Inf)
+```
+
+
+
 ## attitude dataset
 
 Most analyses use the `attitude` dataset, built-in with R: "From a survey of the clerical employees of a large financial organization, the data are aggregated from the questionnaires of the approximately 35 employees for each of 30 (randomly selected) departments." Since we're talking about "small" datasets, we figure that we might as well demonstrate principles with extremely small examples.

vignettes/ale-x-datatypes.Rmd

@@ -1,7 +1,7 @@
 ---
 title: "ale function handling of various datatypes for x"
 author: "Chitu Okoli"
-date: "January 9, 2024"
+date: "November 14, 2024"
 output: rmarkdown::html_vignette
 vignette: >
   %\VignetteIndexEntry{ale function handling of various datatypes for x}
@@ -25,6 +25,14 @@ library(ale)
 library(dplyr)
 ```
 
+```{r allow max future size, include=FALSE}
+# Resolution to https://forum.posit.co/t/the-total-size-of-the-x-globals-exported-for-future-expression-in-r-cmd-check-only-on-ubuntu-latest-devel/194864
+# Remove limit for future sizes to stop complaints by ubuntu-latest (devel) https://future.futureverse.org/reference/future.options.html#options-for-controlling-futures-1
+options(future.globals.maxSize = +Inf)
+```
+
+
+
 ## `var_cars`: modified `mtcars` dataset (Motor Trend Car Road Tests)
 
 For this demonstration, we use a modified version of the built-in `mtcars` dataset so that it has binary (logical), categorical (factor, that is, non-ordered categories), ordinal (ordered factor), discrete interval (integer), and continuous interval (numeric or double) values. This modified version, called `var_cars`, will let us test all the different basic variations of x variables. For the factor, it adds the country of the car manufacturer.