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# r - How can a data ellipse be superimposed on a ggplot2 scatterplot?

Keywords：r

Question:

I have an R function which produces 95% confidence ellipses for scatterplots. The output looks like this, having a default of 50 points for each ellipse (50 rows):

``````           [,1]         [,2]
[1,]  0.097733810  0.044957994
[2,]  0.084433494  0.050337990
[3,]  0.069746783  0.054891438
``````

I would like to superimpose a number of such ellipses for each level of a factor called 'site' on a `ggplot2` scatterplot, produced from this command:

``````> plat1 <- ggplot(mapping=aes(shape=site, size=geom), shape=factor(site)); plat1 + geom_point(aes(x=PC1.1,y=PC2.1))
``````

This is run on a dataset, called `dflat` which looks like this:

``````site      geom         PC1.1        PC2.1       PC3.1        PC1.2       PC2.2
1 Buhlen 1259.5649 -0.0387975838 -0.022889782  0.01355317  0.008705276  0.02441577
2 Buhlen  653.6607 -0.0009398704 -0.013076251  0.02898955 -0.001345149  0.03133990
``````

The result is fine, but when I try to add the ellipse (let's say for this one site, called "Buhlen"):

``````> plat1 + geom_point(aes(x=PC1.1,y=PC2.1)) + geom_path(data=subset(dflat, site="Buhlen"),mapping=aes(x=ELLI(PC1.1,PC2.1)[,1],y=ELLI(PC1.1,PC2.1)[,2]))
``````

I get an error message: ```"Error in data.frame(x = c(0.0977338099339815, 0.0844334944904515, 0.0697467834016782, : arguments imply differing number of rows: 50, 211```

I've managed to fix this in the past, but I cannot remember how. It seems that geom_path is relying on the same points rather than plotting new ones. Any help would be appreciated.

``````#bootstrap
set.seed(101)
n <- 1000
x <- rnorm(n, mean=2)
y <- 1.5 + 0.4*x + rnorm(n)
df <- data.frame(x=x, y=y, group="A")
x <- rnorm(n, mean=2)
y <- 1.5*x + 0.4 + rnorm(n)
df <- rbind(df, data.frame(x=x, y=y, group="B"))

#calculating ellipses
library(ellipse)
df_ell <- data.frame()
for(g in levels(df\$group)){
df_ell <- rbind(df_ell, cbind(as.data.frame(with(df[df\$group==g,], ellipse(cor(x, y),
scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g))
}
#drawing
library(ggplot2)
p <- ggplot(data=df, aes(x=x, y=y,colour=group)) + geom_point(size=1.5, alpha=.6) +
geom_path(data=df_ell, aes(x=x, y=y,colour=group), size=1, linetype=2)
``````

Output looks like this:

Here is more complex example.

Keelan Evanini, Ingrid Rosenfelder and Josef Fruehwald (JoFrhwld@gmail.com) have created a ggplot2 stat implementation of a 95% confidence interval ellipses (and an easier way to plot ellipses in ggplot2):

GitHub stat-ellipse.R

their site

You can use it as:

``````library(ggplot2)
library(devtools)
library(digest)
source_url("https://raw.github.com/low-decarie/FAAV/master/r/stat-ellipse.R")
qplot(data=df, x=x, y=y, colour=colour)+stat_ellipse()
``````

To create the data

``````set.seed(101)
n <- 1000
x <- rnorm(n, mean=2)
y <- 1.5 + 0.4*x + rnorm(n)
colour <- sample(c("first", "second"), size=n, replace=T)
df <- data.frame(x=x, y=y, colour=colour)
``````