Hello Warrenkevin,
To visualize changes in shape I use the geomorph package. Below is the
script I use to run my own analysis. I think it can help you to adapt to
your data. Any doubt you can ask me again or you can also check the google
group geomorph-r-package.
Best regards
Julio
library (geomorph)
# import
data <- readland.tps("raw_data.tps", specID = "imageID")
classifier <- read.csv(file ="./classifier.csv",
header = TRUE, na.strings = c("NA",""))
## GPA
gpa_data <- gpagen(data, curves= NULL)
## geomorph data.frame
gdf_data <- geomorph.data.frame(gpa_data,
group = classifier$group,
sex = classifier$sex)
# mean shape
ref_data <- mshape(gpa_data$coords)
# wireframe
links_data <- define.links(ref_data, ptsize = 2, links = NULL)
# to customize the wireframe
GP <- gridPar(pt.bg = "grey", # reference
pt.size = 1,
link.col="darkgrey",
link.lwd= 3,
link.lty = 2,
tar.pt.bg = "black", #target
tar.pt.size = 1.5,
tar.link.col = "black",
tar.link.lwd = 3,
tar.link.lty = 1,
txt.cex = 1, # adjust number of landmark
txt.adj = c(0.5, NA),
txt.pos = 3, # pos 1(below), 2 (left), 3(top), 4(right)
txt.col = "black")
# Plot the changes on PCA
using the function plotRefToTarget(). # Read the documentantion of this
function. It is very flexible to visualize PCA, Regression etc.
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