Made vignette build time quicker

graemeleehickey · Jan 12, 2025 · 1f3caf2 · 1f3caf2
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diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION
diff --git a/NEWS.md b/NEWS.md
@@ -20,6 +20,8 @@
 
 -   Wrapped a bunch of examples from being run on CRAN submission to avoid Debian system NOTE.
 
+-   Reduced computational time for vignettes to to avoid Debian system NOTE on CRAN submission.
+
 # joineRML 0.4.6
 
 ## Housekeeping

diff --git a/cran-comments.md b/cran-comments.md
@@ -1,7 +1,6 @@
 ## Other notes
 
 * Addresses all NOTES from CRAN Package Check Results.
-* I have stopped several examples from running in order to avoid the NOTE on the Debian system. I cannot reproduce these, but am happy to wrap in `\dontrun{}` blocks.
 
 ## Test environments
 
@@ -18,8 +17,6 @@
 
 Win-Builder NOTE: "checking CRAN incoming feasibility ... NOTE"
 
-Debian NOTE: "Re-building vignettes had CPU time 5.5 times elapsed time" -- I cannot reproduce this. It passes every other platform. I suspect the qpdf compression tool is the cause, but that was requested by CMD tests.
-
 ## Reverse dependencies
 
 We checked 3 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.

diff --git a/vignettes/joineRML-tidy.Rmd b/vignettes/joineRML-tidy.Rmd
@@ -55,7 +55,7 @@ Further to that, we only select the first 50 individuals to speed up these examp
 hvd <- hvd[hvd$num <= 50, ]
 ```
 
-```{r hvd_model_fit}
+```{r hvd_model_fit, cache = TRUE}
 set.seed(12345)
 fit <- mjoint(
   formLongFixed = list(

diff --git a/vignettes/joineRML.Rmd b/vignettes/joineRML.Rmd
@@ -64,6 +64,12 @@ hvd <- heart.valve[!is.na(heart.valve$grad) & !is.na(heart.valve$lvmi), ]
 
 Strictly speaking, this is not necessary because `joineRML` can handle the situation of different measurement schedules *within* subjects That is, a subject does not need to have all multiple longitudinal outcomes recorded at each visit. It is conceivable that some biomarkers will be measured more or less frequently than others. For example, invasive measurements may only be recorded annually, whereas a simple biomarker measurement might be recorded more frequently. `joineRML` can handle this situation by specifying each longitudinal outcome its own data frame.
 
+Further to that, we only select the first 50 individuals to speed up these examples:
+
+```{r hvd_data_small}
+hvd <- hvd[hvd$num <= 50, ]
+```
+
 ## Model fitting
 
 The main function in the `joineRML` package is the `mjoint()` function. Its main (required) arguments are: