Simple Principal Component Analysis

my.pca  <- function(dat.feature)
{ 
    ## Purpose: Principal Component Analysis
    ## Arguments:
    ##   dat.feature: a data feature matrix, where each column is a feature vector. 
    ## Return: PCA plots and result. 
    ## Author: Feiming Chen, Date: 15 Feb 2017, 09:59
    ## ________________________________________________
    p <- prcomp(dat.feature)
    plot(p, main = "Scree Plot", xlab = "Principal Components")
    dev.new()
    biplot(p)
    print(summary(p))
    invisible(p)
}
if (F) {                                # Unit Test
    d <- matrix(rnorm(1000), 20)
    my.pca(d)
}