Areas, Densities, and Frequency Polygons with Fading Gradient

geom_area_fade() behaves like ggplot2::geom_area() but uses grid::linearGradient() to create area plots. The gradient is always anchored at y = 0: maximum transparency there, fading to opaque at the data values. Opacity scales with the absolute distance from zero, so equal |y| values always receive the same alpha – full opacity is reached only at the extreme with the largest absolute value. This works for positive values, negative values, and groups that cross zero (where a three-stop gradient is used).

When fill is mapped to a variable (e.g. aes(fill = z)), the geom combines the horizontal colour gradient produced by ggplot2 with the vertical alpha fade, creating a two-dimensional gradient effect. This requires a device that supports Porter-Duff compositing (e.g. ragg::agg_png(), grDevices::svg()). On unsupported devices the geom falls back to a single-colour vertical fade and emits an informational message.

geom_density_fade() computes and draws a kernel density estimate – a smoothed version of the histogram – with the same vertical alpha gradient as geom_area_fade(). Under the hood this is GeomAreaFade paired with ggplot2::stat_density(), so all smoothing parameters (bw, adjust, kernel, bounds, ...) are forwarded to the stat.

geom_freqpoly_fade() draws a frequency polygon (like ggplot2::geom_freqpoly()) filled with the same linear gradient as geom_area_fade().

Usage

geom_area_fade(
  mapping = NULL,
  data = NULL,
  stat = "align",
  position = "stack",
  ...,
  alpha_fade_to = 0,
  alpha_scope = "global",
  orientation = NA,
  outline.type = "upper",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_density_fade(
  mapping = NULL,
  data = NULL,
  stat = "density",
  position = "identity",
  ...,
  bw = "nrd0",
  adjust = 1,
  kernel = "gaussian",
  bounds = c(-Inf, Inf),
  alpha_fade_to = 0,
  alpha_scope = "global",
  orientation = NA,
  outline.type = "upper",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_freqpoly_fade(
  mapping = NULL,
  data = NULL,
  stat = "bin",
  position = "identity",
  ...,
  binwidth = NULL,
  bins = NULL,
  alpha_fade_to = 0,
  alpha_scope = "global",
  orientation = NA,
  pad = TRUE,
  outline.type = "upper",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

Use to override the default connection between geom_freqpoly_fade() and stat_bin().

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Other arguments passed on to layer()'s params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a stat_*() function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a geom_*() function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

alpha_fade_to

A single finite number between 0 and 1. The alpha value at y = 0 (the baseline). Defaults to 0 (fully transparent).

alpha_scope

How to scale alpha across groups. "global" (default) computes the maximum absolute y value across all groups in the panel so that equal |y| always maps to equal alpha. "group" computes the maximum per group, giving each group the full alpha range independently – useful with position = "identity" when groups have very different amplitudes.

orientation

The orientation of the layer. The default (NA) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting orientation to either "x" or "y". See the Orientation section for more detail.

outline.type

Which edges of the area to draw an outline on. One of "upper" (default), "lower", "both" ("upper" and "lower"), "full" (closed polygon outline), or "none". When no colour is specified explicitly the outline inherits the fill colour.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().

bw

The smoothing bandwidth to be used. If numeric, the standard deviation of the smoothing kernel. If character, a rule to choose the bandwidth, as listed in stats::bw.nrd().

adjust

A multiplicate bandwidth adjustment. This makes it focused on giving the kernel bandwidth more or less smoothing.

kernel

Kernel. See stats::density() for more details.

bounds

Known lower and upper bounds for the variable. Default is c(-Inf, Inf).

binwidth

Width of each bin in data units. When supplied, takes precedence over bins. Forwarded to ggplot2::stat_bin().

bins

Number of bins. Overridden by binwidth. Defaults to 30. Forwarded to ggplot2::stat_bin().

pad

If TRUE, adds empty bins at either end of x. This ensures frequency polygons touch 0. Defaults to FALSE.

Value

A ggplot2::layer() object that can be added to a ggplot2::ggplot().

Coordinate systems

geom_area_fade(), geom_density_fade(), and geom_freqpoly_fade() only support linear gradients. When used with ggplot2::coord_polar() or ggplot2::coord_radial(), they fall back to standard area rendering (equivalent to ggplot2::geom_area()), which means no gradient fill is added. A warning is emitted in this case.

alpha_scope = "global" under faceting

alpha_scope = "global" ties opacity to absolute height across the whole layer, so two ridges / areas / bars of equal height render at equal alpha regardless of which panel they're in. This is meaningful only when panels share a common y scale. Under facet_wrap(scales = "free_y") (or facet_grid(rows = ..., scales = "free")) each panel rescales y independently, so the visual height of a shape no longer reflects its data height; the alpha encoding then conflicts with what the eye reads from the panel size. For comparable alpha across free-y panels you have two options: stick to the default scales = "fixed", or accept that under free scales alpha_scope = "group" is the more honest choice (each shape independently uses its own alpha range).

Legend key under coord_flip

The legend key glyph always shows the canonical (data-axis) fade direction – vertical for the default orientation, horizontal under orientation = "y". Under ggplot2::coord_flip() the rendered geom rotates correctly but the legend key does not: ggplot2's legend builder is coord-independent by design (draw_key has no access to the coord). For a legend key that matches a horizontal layout, prefer aes(y = ...) with auto-detected orientation = "y" over aes(x = ...) + coord_flip().

Orientation

This geom treats each axis differently and, thus, can thus have two orientations. Often the orientation is easy to deduce from a combination of the given mappings and the types of positional scales in use. Thus, ggplot2 will by default try to guess which orientation the layer should have. Under rare circumstances, the orientation is ambiguous and guessing may fail. In that case the orientation can be specified directly using the orientation parameter, which can be either "x" or "y". The value gives the axis that the geom should run along, "x" being the default orientation you would expect for the geom.

References

Murrell, P. (2021). "Luminance Masks in R Graphics." Technical Report 2021-04, Department of Statistics, The University of Auckland. Version 1. https://www.stat.auckland.ac.nz/~paul/Reports/GraphicsEngine/masks/masks.html

Murrell, P. (2022). "Vectorised Pattern Fills in R Graphics." Technical Report 2022-01, Department of Statistics, The University of Auckland. Version 1. https://www.stat.auckland.ac.nz/~paul/Reports/GraphicsEngine/vecpat/vecpat.html

Murrell, P., Pedersen, T. L., and Skintzos, P. (2023). "Porter-Duff Compositing Operators in R Graphics." Department of Statistics, The University of Auckland. Version 1. https://www.stat.auckland.ac.nz/~paul/Reports/GraphicsEngine/compositing/compositing.html

Murrell, P. (2023). "Groups, Compositing Operators, and Affine Transformations in R Graphics." Technical Report 2021-02, Department of Statistics, The University of Auckland. Version 3. https://www.stat.auckland.ac.nz/~paul/Reports/GraphicsEngine/groups/groups.html

Aesthetics

geom_area_fade() understands the following aesthetics. Required aesthetics are displayed in bold and defaults are displayed for optional aesthetics:

•	`x`
•	`y`
•	`alpha`	→ `NA`
•	`colour`	→ via `theme()`
•	`fill`	→ via `theme()`
•	`group`	→ inferred
•	`linetype`	→ via `theme()`
•	`linewidth`	→ via `theme()`

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Examples

library(ggplot2)
df1 <- data.frame(
  g = c("a", "a", "a", "b", "b", "b"),
  x = c(1, 3, 5, 2, 4, 6),
  y = c(2, 5, 1, 3, 6, 7)
)

a <- ggplot(df1, aes(x, y, fill = g)) +
  theme_minimal()

# Default behaviour: opaque at data line, transparent at y = 0
# the outline colour remains unaffected
a + geom_area_fade()


# Change overall opacity
a + geom_area_fade(alpha = .25)


# Keep some opacity at the baseline
a + geom_area_fade(alpha_fade_to = .25)


# Suppress the default upper outline
a + geom_area_fade(outline.type = "none")


# Closed outline (all four edges)
a + geom_area_fade(outline.type = "full")


# Horizontal orientation
a + geom_area_fade(aes(y, x), orientation = "y")


# Disable stat alignment (useful when x values are already aligned)
a + geom_area_fade(stat = "identity")


# Draw upper and lower outlines (no left/right edges)
a + geom_area_fade(outline.type = "both", stat = "identity")


# Use the "alpha_scope" argument to scale the alpha
# value of the gradients separately for each group
df2 <- data.frame(
  g = c("a", "a", "a", "b", "b", "b"),
  x = c(1, 3, 5, 2, 4, 6),
  y = c(1, 2, 1, 9, 10, 8)
)
b <- ggplot(df2, aes(x, y, fill = g)) +
  theme_minimal()

# With alpha_scope = "group", each group uses the alpha range independently
b + geom_area_fade(
  alpha_scope = "group",
  position = "identity"
  )


# Compare with the default where small groups appear washed out
# next to dominant groups, especially when position = "identity"
b + geom_area_fade(
  alpha_scope = "global", # default
  position = "identity"
  )


# Negative values are supported too:
# the gradient fades towards y = 0 from both sides
d <- ggplot(df2, aes(x, y - mean(y))) +
  theme_minimal()
d + geom_area_fade()


# Overwrite both fill and colour
d + geom_area_fade(
  fill = "#0833F5",
  colour = "#d77e7b",
  outline.type = "lower"
  )


# A 2D-gradient is produced when fill is mapped to a variable
# this may not work on all graphic devices, see vignette for details
d + geom_area_fade(
  aes(fill = y),
  colour = "#333333",
  outline.type = "both"
  )


# Basic density curve: opaque at the peak, fully transparent at the baseline.
ggplot(diamonds, aes(carat)) +
  geom_density_fade()


# Map the values to y to flip the orientation
ggplot(diamonds, aes(y = carat)) +
  geom_density_fade()


# `alpha_fade_to` controls the alpha at the baseline.
# The default `0` is fully transparent; raise it to keep some
# opacity at the floor.
ggplot(diamonds, aes(carat)) +
  geom_density_fade(alpha_fade_to = 0.2)


# Multiple groups via `fill`. With the default `alpha_scope = "global"`
# the tallest peak in the layer reaches full opacity; shorter peaks fade
# in proportion. `xlim()` trims the long tails for clarity.
ggplot(diamonds, aes(depth, fill = cut)) +
  geom_density_fade() +
  xlim(55, 70)
#> Warning: Removed 45 rows containing non-finite outside the scale range
#> (`stat_density()`).


# Switch to `alpha_scope = "group"` so every
# area hits full opacity independently
ggplot(diamonds, aes(depth, fill = cut)) +
  geom_density_fade(alpha_scope = "group") +
  xlim(55, 70)
#> Warning: Removed 45 rows containing non-finite outside the scale range
#> (`stat_density()`).


# You can use position = "fill" to produce a conditional density estimate
ggplot(diamonds, aes(carat, after_stat(count), fill = cut)) +
  geom_density_fade(position = "fill")


# Basic frequency polygon with fading gradient
ggplot(faithful, aes(waiting)) +
  geom_freqpoly_fade(
    colour = "#3b528b",
    bins = 20
  ) +
  theme_minimal()


# Rather than stacking histograms, compare frequency polygons
ggplot(iris, aes(Sepal.Length, fill = Species, colour = Species)) +
  geom_freqpoly_fade(
    alpha = 0.8,
    position = "identity",
    bins = 20
  ) +
  scale_fill_viridis_d() +
  scale_colour_viridis_d() +
  theme_minimal()