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R/aes-evaluation.R

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#' Below follows an overview of the three stages of evaluation and how aesthetic
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#' evaluation can be controlled.
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#'
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#' ## Stage 1: direct input
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#' ## Stage 1: direct input at the start
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#' The default is to map at the beginning, using the layer data provided by
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#' the user. If you want to map directly from the layer data you should not do
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#' anything special. This is the only stage where the original layer data can
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#' ```
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#'
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#' ## Complex staging
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#' If you want to map the same aesthetic multiple times, e.g. map `x` to a
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#' data column for the stat, but remap it for the geom, you can use the
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#' `stage()` function to collect multiple mappings.
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#' Sometimes, you may want to map the same aesthetic multiple times, e.g. map
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#' `x` to a data column at the start for the layer stat, but remap it later to
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#' a variable from the stat transformation for the layer geom. The `stage()`
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#' function allows you to control multiple mappings for the same aesthetic
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#' across all three stages of evaluation.
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#'
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#' ```r
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#' # Use stage to modify the scaled fill
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#' ggplot(mpg, aes(class, hwy)) +
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#' geom_boxplot(aes(fill = stage(class, after_scale = alpha(fill, 0.4))))
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#'
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#' # Using data for computing summary, but placing label elsewhere.
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#' # Also, we're making our own computed variable to use for the label.
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#' # Also, we're making our own computed variables to use for the label.
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#' ggplot(mpg, aes(class, displ)) +
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#' geom_violin() +
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#' stat_summary(
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#' )
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#' ```
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#'
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#' Conceptually, `aes(x)` is equivalent to `aes(stage(start = x))`, and
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#' `aes(after_stat(count))` is equivalent to `aes(stage(after_stat = count))`,
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#' and so on. `stage()` is most useful when at least two of its arguments are
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#' specified.
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#'
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#' ## Theme access
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#' The `from_theme()` function can be used to acces the [`element_geom()`]
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#' fields of the `theme(geom)` argument. Using `aes(colour = from_theme(ink))`

man/aes_eval.Rd

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