Anthropometry (version 1.2)

projShapes: Helper function for plotting the shapes

Description

Helper function for plotting the projections of the shapes. It displays the projection on the xy plane of the recorded points and mean shape for a given cluster. To that end, first it is needed to carry out a generalized Procrustes analysis in the cluster to obtain the full Procrustes rotated data.

Usage

projShapes(clust,array3D,asig,prototypes)

Arguments

clust

Cluster for which represent its mean shape together with the recorded points.

array3D

Array with the 3D landmarks of the sample points. Each row corresponds to an observation, and each column corresponds to a dimension (x,y,z).

asig

Clustering optimal results.

prototypes

Vector of optimal prototypes.

Value

• Numerical vector with the percentile values of an archetypoid.

References

Vinue, G., Simo, A., and Alemany, S., (2014). The k-means algorithm for 3D shapes with an application to apparel design, Advances in Data Analysis and Classification, 1--30.

See Also

LloydShapes, HartiganShapes, trimmedLloydShapes

Examples

landmarksNoNa <- na.exclude(landmarksSampleSpaSurv)
dim(landmarksNoNa) 
#[1] 574 198 
numLandmarks <- (dim(landmarksNoNa)[2]) / 3
#[1] 66
#In the interests of simplicity of the computation involved:
landmarksNoNa_First50 <- landmarksNoNa[1 : 50, ] 
(numIndiv <- dim(landmarksNoNa_First50)[1])
#[1] 50         
    
array3D <- array3Dlandm(numLandmarks, numIndiv, landmarksNoNa_First50)
 
numClust <- 3 ; alpha <- 0.01 ; algSteps <- 5 ; niter <- 5 ; stopCr <- 0.0001
set.seed(2013)
res <- trimmedLloydShapes(array3D,numIndiv,alpha,numClust,algSteps,niter,stopCr,TRUE) 
clust_kmeansProc <- res$asig

prototypes <- anthrCases("anthropometry", "kmeansProcrustes", res)

projShapes(1, array3D, clust_kmeansProc, prototypes)
legend("topleft", c("Registrated data", "Mean shape"), pch = 1, col = 1:2, text.col = 1:2)
title("Procrustes registrated data for cluster 1 \n with its mean shape superimposed", 
      sub = "Plane xy")