geom_cloud {ggallin} | R Documentation |
geom_cloud
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).
Geom Proto
Arguments
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. |
max_alpha |
The maximum alpha at the maximum density. The cloud will have alpha no greater than this value. |
se_mult |
The ‘multiplier’ of standard errors of the given
|
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 shabbychef@gmail.com
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')