geom_serialaxes_density: Smoothed density estimates for "widens" data under serial...

In ggmulti: High Dimensional Data Visualization

Smoothed density estimates for "widens" data under serial axes coordinate

Description

Computes and draws kernel density estimates on serial axes coordinate for each non-aesthetics component defined in the mapping aes().

Usage

geom_serialaxes_density(
  mapping = NULL,
  data = NULL,
  stat = "serialaxes_density",
  position = "identity_",
  ...,
  axes.sequence = character(0L),
  merge = TRUE,
  scale.y = c("data", "group"),
  as.mix = TRUE,
  positive = TRUE,
  prop = 0.9,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_serialaxes_density(
  mapping = NULL,
  data = NULL,
  geom = "serialaxes_density",
  position = "stack_",
  ...,
  axes.sequence = character(0L),
  merge = TRUE,
  axes.position = NULL,
  scaling = c("data", "variable", "observation", "none"),
  bw = "nrd0",
  adjust = 1,
  kernel = "gaussian",
  n = 512,
  trim = FALSE,
  na.rm = FALSE,
  orientation = NA,
  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	The statistical transformation to use on the data for this layer, either as a ggproto Geom subclass or as a string naming the stat stripped of the stat_ prefix (e.g. "count" rather than "stat_count")
position	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.
...	Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.
axes.sequence	A vector to define the axes sequence. In serial axes coordinate, the sequence can be either determined in mapping (function aes()) or by axes.sequence. The only difference is that the mapping aesthetics will omit the duplicated axes (check examples in geom_serialaxes).
merge	Should axes.sequence be merged with mapping aesthetics as a single mapping uneval object?
scale.y	one of data and group to specify. Type Description data (default) The density estimates are scaled by the whole data set group The density estimates are scaled by each group If the scale.y is data, it is meaningful to compare the density (shape and area) across all groups; else it is only meaningful to compare the density within each group. See details.
as.mix	Logical. Within each group, if TRUE, the sum of the density estimate area is mixed and scaled to maximum 1. The area of each subgroup (in general, within each group one color represents one subgroup) is proportional to the count; if FALSE the area of each subgroup is the same, with maximum 1. See details.
positive	If y is set as the density estimate, where the smoothed curved is faced to, right ('positive') or left ('negative') as vertical layout; up ('positive') or down ('negative') as horizontal layout?
prop	adjust the proportional maximum height of the estimate (density, histogram, ...).
na.rm	If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
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.
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.
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. borders().
geom	The geometric object to use to display the data, either as a ggproto Geom subclass or as a string naming the geom stripped of the geom_ prefix (e.g. "point" rather than "geom_point")
axes.position	A numerical vector to determine the axes sequence position; the length should be the same with the length of axes.sequence (or mapping aesthetics, see examples).
scaling	one of data, variable, observation or none (not suggested the layout is the same with data) to specify how the data is scaled.
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 possible to adjust the bandwidth while still using the a bandwidth estimator. For example, adjust = 1/2 means use half of the default bandwidth.
kernel	Kernel. See list of available kernels in density().
n	number of equally spaced points at which the density is to be estimated, should be a power of two, see density() for details
trim	If FALSE, the default, each density is computed on the full range of the data. If TRUE, each density is computed over the range of that group: this typically means the estimated x values will not line-up, and hence you won't be able to stack density values. This parameter only matters if you are displaying multiple densities in one plot or if you are manually adjusting the scale limits.

See Also

geom_density_, geom_serialaxes, geom_serialaxes_quantile, geom_serialaxes_hist

Examples

p <- ggplot(iris, mapping = aes(Sepal.Length = Sepal.Length,
                                Sepal.Width = Sepal.Width,
                                Petal.Length = Petal.Length,
                                Petal.Width = Petal.Width,
                                colour = Species,
                                fill = Species)) +
       geom_serialaxes(alpha = 0.2) +
       geom_serialaxes_density(alpha = 0.5) +
       scale_x_continuous(breaks = 1:4,
                          labels = colnames(iris)[-5]) +
       scale_y_continuous(labels = NULL) +
       xlab("variable") +
       ylab("") +
       theme(axis.text.x = element_text(angle = 45, vjust = 0.5))
p

ggmulti documentation built on Nov. 10, 2022, 5:12 p.m.