RRPP (version 2.0.3)

convert2ggplot: Convert RRPP plots to ggplot objects

Description

Function attempts to coerce plot information from an RRPP plot object to an amenable ggplot object.

Usage

convert2ggplot(object)

Arguments

object

A plot object produced from plot.lm.rrpp and type equals either "PC" or "regression, plot.predict.lm.rrpp, or plot.ordinate. Essentially, any RRPP plot except a series of diagnostic plots should work.

Author

Michael Collyer

Details

This function will attempt to use the plot arguments from an RRPP plot object to make a ggplot that can be additionally updated, as desired. Not all plot characteristics can be converted. For example, text arguments are not currently passed to ggplot, as the text function and geom_text arguments do not easily align. However, one can use text arguments produced by a RRPP plot object and geom_text to augment a ggplot object the way they like.

This function assumes no responsibility for arguments made by ggplot. It merely produces a ggplot object that should resemble an RRPP plot default. Any augmentation of ggplot objects can be done either by direct intervention of the ggplot produced or reformatting the initial RRPP plot produced. One should not expect direct correspondence between R base plot parameters and ggplot parameters. For example, error bars will generally appear as different widths, without an easy way to control them, changing from one format to the other.

Examples

if (FALSE) {
### Linear Model Example

data(Pupfish)
fit <- lm.rrpp(coords ~ log(CS) + Sex*Pop, SS.type = "I", 
data = Pupfish, print.progress = FALSE) 

# Predictions (holding alternative effects constant)

shapeDF <- expand.grid(Sex = levels(Pupfish$Sex), 
Pop = levels(Pupfish$Pop))
rownames(shapeDF) <- paste(shapeDF$Sex, shapeDF$Pop, sep = ".")

shapePreds <- predict(fit, shapeDF)
summary(shapePreds, PC = TRUE)

# Plot prediction

P <- plot(shapePreds, PC = TRUE, ellipse = TRUE)
convert2ggplot(P)

### Ordination Example

data("PlethMorph")

Y <- as.data.frame(PlethMorph[c("TailLength", "HeadLength", 
                               "Snout.eye", "BodyWidth", 
                               "Forelimb", "Hindlimb")])
Y <- as.matrix(Y)
R <- lm.rrpp(Y ~ SVL, data = PlethMorph, 
             print.progress = FALSE)$LM$residuals

# PCA (on correlation matrix)


PCA.ols <- ordinate(R, scale. = TRUE)
PCA.ols$rot
prcomp(R, scale. = TRUE)$rotation # should be the same


PCA.gls <- ordinate(R, scale. = TRUE, 
                   transform. = FALSE, 
                   Cov = PlethMorph$PhyCov)
               
P <- plot(PCA.gls)
convert2ggplot(P)                   
}