Formula interface to ggridges plots
gf_ridgeline(
object = NULL,
gformula = NULL,
data = NULL,
...,
height,
scale = 1,
min_height = 0,
color,
fill,
alpha,
group,
linetype,
linewidth,
point_size,
point_shape,
point_colour,
point_fill,
point_alpha,
point_stroke,
xlab,
ylab,
title,
subtitle,
caption,
geom = "ridgeline",
stat = "identity",
position = "identity",
show.legend = NA,
show.help = NULL,
inherit = TRUE,
environment = parent.frame()
)
gf_density_ridges(
object = NULL,
gformula = NULL,
data = NULL,
...,
height,
scale = 1,
rel_min_height = 0,
color,
fill,
alpha,
group,
linetype,
linewidth,
point_size,
point_shape,
point_colour,
point_fill,
point_alpha,
point_stroke,
panel_scaling = TRUE,
xlab,
ylab,
title,
subtitle,
caption,
geom = "density_ridges",
stat = "density_ridges",
position = "points_sina",
show.legend = NA,
show.help = NULL,
inherit = TRUE,
environment = parent.frame()
)
gf_density_ridges2(
object = NULL,
gformula = NULL,
data = NULL,
...,
height,
scale = 1,
rel_min_height = 0,
color,
fill,
alpha,
group,
linetype,
linewidth,
point_size,
point_shape,
point_colour,
point_fill,
point_alpha,
point_stroke,
panel_scaling = TRUE,
xlab,
ylab,
title,
subtitle,
caption,
geom = "density_ridges2",
stat = "density_ridges",
position = "points_sina",
show.legend = NA,
show.help = NULL,
inherit = TRUE,
environment = parent.frame()
)
gf_density_ridgeline_gradient(
object = NULL,
gformula = NULL,
data = NULL,
...,
height,
color,
fill,
alpha,
group,
linetype,
linewidth,
gradient_lwd = 0.5,
xlab,
ylab,
title,
subtitle,
caption,
geom = "ridgeline_gradient",
stat = "identity",
position = "identity",
show.legend = NA,
show.help = NULL,
inherit = TRUE,
environment = parent.frame()
)
gf_density_ridges_gradient(
object = NULL,
gformula = NULL,
data = NULL,
...,
height,
panel_scaling = TRUE,
color,
fill = ~stat(x),
alpha,
group,
linetype,
linewidth,
gradient_lwd = 0.5,
xlab,
ylab,
title,
subtitle,
caption,
geom = "density_ridges_gradient",
stat = "density_ridges",
position = "points_sina",
show.legend = NA,
show.help = NULL,
inherit = TRUE,
environment = parent.frame()
)
When chaining, this holds an object produced in the earlier portions of the chain. Most users can safely ignore this argument. See details and examples.
A formula with shape ~ x
.
Faceting can be achieved by including |
in the formula.
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)
).
Additional arguments. Typically these are
(a) ggplot2 aesthetics to be set with attribute = value
,
(b) ggplot2 aesthetics to be mapped with attribute = ~ expression
, or
(c) attributes of the layer as a whole, which are set with attribute = value
.
The height of each ridgeline at the respective x value.
Automatically calculated and provided by ggridges::stat_density_ridges()
if the default stat is not changed.
A scaling factor to scale the height of the ridgelines relative to the spacing between them. A value of 1 indicates that the maximum point of any ridgeline touches the baseline right above, assuming even spacing between baselines.
A height cutoff on the drawn ridgelines. All values that fall below this cutoff will be removed. The main purpose of this cutoff is to remove long tails right at the baseline level, but other uses are possible. The cutoff is applied before any height scaling is applied via the scale aesthetic. Default is 0, so negative values are removed.
A color or a formula used for mapping color.
A color for filling, or a formula used for mapping fill.
Opacity (0 = invisible, 1 = opaque).
Used for grouping.
A linetype (numeric or "dashed", "dotted", etc.) or a formula used for mapping linetype.
A numerical line width or a formula used for mapping linewidth.
As in ggridges::geom_ridgeline()
.
Label for x-axis. See also gf_labs()
.
Label for y-axis. See also gf_labs()
.
Title, sub-title, and caption for the plot.
See also gf_labs()
.
Use to override the default connection between
geom_density()
and stat_density()
.
Position adjustment, either as a string naming the adjustment
(e.g. "jitter"
to use position_jitter
), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
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.
If TRUE
, display some minimal help.
A logical indicating whether default attributes are inherited.
An environment in which to look for variables not found in data
.
Lines with heights below this cutoff will be removed. The cutoff is
measured relative to the overall maximum, so rel_min_height = 0.01
would
remove everything. Default is 0, so nothing is removed.
If TRUE
, the default, relative scaling is calculated separately
for each panel. If FALSE
, relative scaling is calculated globally.
A parameter to needed to remove rendering artifacts inside the rendered gradients. Should ideally be 0, but often needs to be around 0.5 or higher.
Note that the ggridges::stat_density_ridges()
makes joint density estimation
across all datasets. This may not generate the desired result when using
faceted plots. As an alternative, you can set stat = "density"
to use
ggplot2::stat_density()
. In this case, it is required to add the aesthetic mapping
height = after_stat(density)
(see examples).
data.frame(
x = rep(1:5, 3), y = c(rep(0, 5), rep(1, 5), rep(3, 5)),
height = c(0, 1, 3, 4, 0, 1, 2, 3, 5, 4, 0, 5, 4, 4, 1)
) |>
gf_ridgeline(y ~ x, height = ~ height, group = ~y, fill = "lightblue", alpha = 0.7)
diamonds |>
gf_density_ridges(cut ~ price,
scale = 2, fill = ~ cut, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
#> Picking joint bandwidth of 458
diamonds |>
gf_density_ridges(clarity ~ price | cut,
scale = 2, fill = ~ clarity, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
#> Picking joint bandwidth of 796
#> Picking joint bandwidth of 751
#> Picking joint bandwidth of 677
#> Picking joint bandwidth of 718
#> Picking joint bandwidth of 400
if (FALSE) {
diamonds |>
gf_density_ridges(clarity ~ price | cut, height = ~after_stat(density), stat = "density",
scale = 2, fill = ~ clarity, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
}
if (FALSE) {
diamonds |>
gf_density_ridges2(cut ~ price, scale = 2, fill = ~ cut, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
}
diamonds |>
gf_density_ridges(cut ~ price,
scale = 2, fill = ~ cut, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
#> Picking joint bandwidth of 458
diamonds |>
gf_density_ridges(clarity ~ price | cut,
scale = 2, fill = ~ clarity, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
#> Picking joint bandwidth of 796
#> Picking joint bandwidth of 751
#> Picking joint bandwidth of 677
#> Picking joint bandwidth of 718
#> Picking joint bandwidth of 400
if (FALSE) {
diamonds |>
gf_density_ridges(clarity ~ price | cut, height = ~ after_stat(density), stat = "density",
scale = 2, fill = ~ clarity, alpha = 0.6, show.legend = FALSE) |>
gf_theme(theme_ridges()) |>
gf_refine(
scale_y_discrete(expand = c(0.01, 0)),
scale_x_continuous(expand = c(0.01, 0))
)
}
if (FALSE) {
mosaicData::Weather |>
gf_density_ridges_gradient(month ~ high_temp | city ~ ., fill = ~stat(x),
group = ~ month, show.legend = FALSE, rel_min_height = 0.02) |>
gf_refine(scale_fill_viridis_c(option = "B"), theme_bw())
}