geom_cloud: geom_cloud

In shabbychef/ggallin: Grab Bag of 'ggplot2' Functions

Description

Draw a normal uncertainty cloud as a ribbon

Draws overlapping ribbons of the same identity to create a cloud of (Gaussian) uncertainty. Similar to an errorbar geom in use, but visually less distracting (sometimes).

Usage

geom_cloud(mapping = NULL, data = NULL, ..., na.rm = TRUE, steps = 7,
  se_mult = 1, max_alpha = 1, inherit.aes = TRUE)

Arguments

mapping	Set of aesthetic mappings created by aes() or 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.
...	Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.
na.rm	If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
steps	The integer number of steps, or equivalently, the number of overlapping ribbons. A larger number makes a smoother cloud at the possible expense of rendering time. Values larger than around 20 are typically not necessary.
se_mult	The ‘multiplier’ of standard errors of the given ymin and ymax. If these are at one standard error, then let se_mult take the default value of 1.
max_alpha	The maximum alpha at the maximum density. The cloud will have alpha no greater than this value.
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().

Details

Assumes that ymin and ymax are plotted at a fixed number of standard errors away from y, then computes a Gaussian density with that standard deviation, plotting a cloud (based on geom_ribbon) with alpha proportional to the density. This appears as a vertical ‘cloud’ of uncertainty. In use, this geom should be comparable to geom_errorbar.

A sample output from geom_cloud:

Aesthetics

geom_cloud understands the following aesthetics (required aesthetics are in bold):

• x

• y

• ymin

• ymax

• fill

Only one of ymin and ymax is strictly required.

Note

This is a thin wrapper on the geom_ribbon geom.

Author(s)

Steven E. Pav [e-mail]

See Also

geom_ribbon: The underlying geom

Examples

set.seed(2134)
nobs <- 200
mydat <- data.frame(grp=sample(c(0,1),nobs,replace=TRUE),
  colfac=sample(letters[1:2],nobs,replace=TRUE),
  rowfac=sample(letters[10 + (1:3)],nobs,replace=TRUE)) 
mydat$x <- seq(0,1,length.out=nobs) + 0.33 * mydat$grp
mydat$y <- 0.25 * rnorm(nobs) + 2 * mydat$grp
mydat$grp <- factor(mydat$grp)
mydat$se  <- sqrt(mydat$x)

ggplot(mydat,aes(x=x,y=y,ymin=y-se,ymax=y+se,color=grp)) +
facet_grid(rowfac ~ colfac) + 
geom_line() + 
geom_errorbar() + 
labs(title='uncertainty by errorbar')

ggplot(mydat,aes(x=x,y=y,ymin=y-se,ymax=y+se,fill=grp)) +
facet_grid(rowfac ~ colfac) + 
geom_line() + 
geom_cloud(steps=15,max_alpha=0.85) +
labs(title='uncertainty by cloudr')

shabbychef/ggallin documentation built on April 4, 2021, 12:39 p.m.