In general, a minimal plot is used so that profiles are focused on
low-level, general code, rather than implementations of specific geoms.
This might be expanded at the point where improving performance of
specific geoms becomes a focus. Further, the profile focuses on the
diff --git a/dev/pkgdown.yml b/dev/pkgdown.yml
index a06b342bd7..cd37d32fac 100644
--- a/dev/pkgdown.yml
+++ b/dev/pkgdown.yml
@@ -13,7 +13,7 @@ articles:
ggplot2-specs: ggplot2-specs.html
ggplot2: ggplot2.html
profiling: profiling.html
-last_built: 2025-02-27T09:22Z
+last_built: 2025-03-07T17:56Z
urls:
reference: https://ggplot2.tidyverse.org/reference
article: https://ggplot2.tidyverse.org/articles
diff --git a/dev/reference/benchplot.html b/dev/reference/benchplot.html
index a1303584fe..f8c895d9ef 100644
--- a/dev/reference/benchplot.html
+++ b/dev/reference/benchplot.html
@@ -91,29 +91,29 @@
benchplot(ggplot(mtcars, aes(mpg, wt)) + geom_point())
#> step user.self sys.self elapsed
-#> 1 construct 0.004 0 0.003
-#> 2 build 0.019 0 0.019
-#> 3 render 0.020 0 0.020
-#> 4 draw 0.018 0 0.019
-#> 5 TOTAL 0.061 0 0.061
+#> 1 construct 0.003 0 0.002
+#> 2 build 0.020 0 0.020
+#> 3 render 0.021 0 0.020
+#> 4 draw 0.019 0 0.019
+#> 5 TOTAL 0.063 0 0.061
benchplot(ggplot(mtcars, aes(mpg, wt)) + geom_point() + facet_grid(. ~ cyl))
#> step user.self sys.self elapsed
#> 1 construct 0.003 0 0.003
-#> 2 build 0.020 0 0.021
-#> 3 render 0.052 0 0.052
-#> 4 draw 0.033 0 0.033
-#> 5 TOTAL 0.108 0 0.109
+#> 2 build 0.021 0 0.021
+#> 3 render 0.049 0 0.048
+#> 4 draw 0.033 0 0.034
+#> 5 TOTAL 0.106 0 0.106
# With tidy eval:
p <- expr(ggplot(mtcars, aes(mpg, wt)) + geom_point())
benchplot(!!p)
#> step user.self sys.self elapsed
-#> 1 construct 0.002 0 0.003
-#> 2 build 0.020 0 0.019
-#> 3 render 0.020 0 0.020
-#> 4 draw 0.019 0 0.018
-#> 5 TOTAL 0.061 0 0.060
+#> 1 construct 0.002 0 0.002
+#> 2 build 0.019 0 0.019
+#> 3 render 0.020 0 0.021
+#> 4 draw 0.018 0 0.019
+#> 5 TOTAL 0.059 0 0.061