diff --git a/dev/articles/profiling.html b/dev/articles/profiling.html index e4bc64ad6a..787c8e20e7 100644 --- a/dev/articles/profiling.html +++ b/dev/articles/profiling.html @@ -145,7 +145,7 @@
In general, a minimal plot is used so that profiles are focused on +
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/news/index.html b/dev/news/index.html index 338a309782..36d8aeb658 100644 --- a/dev/news/index.html +++ b/dev/news/index.html @@ -86,7 +86,8 @@
geom_rug()
prints a warning when na.rm = FALSE
, as per documentation (@pn317, #5905)
(internal) rearranged the code of Facet$draw_paensl()
method (@teunbrand).
geom_rug()
prints a warning when na.rm = FALSE
, as per documentation (@pn317, #5905)
position_dodge(preserve = "single")
now handles multi-row geoms better, such as geom_violin()
(@teunbrand based on @clauswilke’s work, #2801).
position_jitterdodge()
now dodges by group
(@teunbrand, #3656)
The arrow.fill
parameter is now applied to more line-based functions: geom_path()
, geom_line()
, geom_step()
geom_function()
, line geometries in geom_sf()
and element_line()
.
benchplot(ggplot(mtcars, aes(mpg, wt)) + geom_point())
#> step user.self sys.self elapsed
-#> 1 construct 0.003 0 0.004
-#> 2 build 0.019 0 0.019
-#> 3 render 0.020 0 0.020
-#> 4 draw 0.021 0 0.021
-#> 5 TOTAL 0.063 0 0.064
+#> 1 construct 0.003 0 0.003
+#> 2 build 0.018 0 0.018
+#> 3 render 0.019 0 0.019
+#> 4 draw 0.020 0 0.020
+#> 5 TOTAL 0.060 0 0.060
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 0.040 0 0.039
-#> 3 render 0.047 0 0.046
-#> 4 draw 0.037 0 0.037
-#> 5 TOTAL 0.127 0 0.125
+#> 1 construct 0.002 0 0.002
+#> 2 build 0.036 0 0.037
+#> 3 render 0.044 0 0.044
+#> 4 draw 0.035 0 0.035
+#> 5 TOTAL 0.117 0 0.118
# With tidy eval:
p <- expr(ggplot(mtcars, aes(mpg, wt)) + geom_point())
benchplot(!!p)
#> step user.self sys.self elapsed
-#> 1 construct 0.003 0 0.002
-#> 2 build 0.019 0 0.019
-#> 3 render 0.021 0 0.020
-#> 4 draw 0.021 0 0.021
-#> 5 TOTAL 0.064 0 0.062
+#> 1 construct 0.003 0 0.003
+#> 2 build 0.018 0 0.018
+#> 3 render 0.019 0 0.019
+#> 4 draw 0.020 0 0.020
+#> 5 TOTAL 0.060 0 0.060