rotations (version 0.1)

plot.SO3: Visualizing random rotations.

Description

This function produces a three-dimensional globe onto which one of the columns of the provided sample of rotations is drawn. The data are centered around a provided matrix and the user can choose to display this center or not. Based on ggplot2 package by Wickham (2009).

Usage

## S3 method for class 'SO3':
plot(x, center = mean(x), col = 1,
    to_range = FALSE, show_estimates = NULL,
    label_points = NULL, mean_regions = NULL,
    median_regions = NULL, alp = NULL, m = 300, ...)

Arguments

x

n rotations in SO3 format.

center

rotation about which to center the observations.

col

integer 1 to 3 indicating which column to display.

to_range

show only part of the globe that is in range of the data?

show_estimates

character vector to specify which of the four estimates of the principal direction to show. Possibilities are "all", "proj.mean", "proj.median", "geom.mean", "geom.median."

label_points

vector of labels.

mean_regions

character vector to specify which of the three confidence regions to show for the projected mean. Possibilities are "all", "eigen theory","eigen bootstrap, "moment theory", "moment bootstrap."

median_regions

character vector to specify which of the three confidence regions to show for the projected median. Possibilities are "all", "theory", "bootstrap."

alp

alpha level to be used for confidence regions.

m

number of bootstrap replicates to use in Zhang confidence region.

...

parameters passed onto the points layer.

Value

• A ggplot2 object with the data displayed on spherical grid.

References

Wickham H (2009). ggplot2: elegant graphics for data analysis. Springer New York. ISBN 978-0-387-98140-6, .

Examples

r<-rvmises(200,1.0)
Rs<-genR(r)
plot(Rs,center=mean(Rs),show_estimates=NULL,shape=4)
# Z is computed internally and contains information on depth
plot(Rs,center=mean(Rs),show_estimates=c("proj.mean", "geom.mean"),
 label_points=sample(LETTERS, 200, replace=TRUE)) + aes(size=Z, alpha=Z) +
 scale_size(limits=c(-1,1), range=c(0.5,2.5))