Nothing
dataPrep <- function(img, nb, vars = NULL, subsample = 1) {
if (!is.matrix(img)) stop("img must be a matrix!")
if (missing(nb))
stop("Missing nb!")
else {
if (!(length(nb) %in% c(1,3) && is.vector(nb)))
stop("nb must be either a scalar or a vector of length 3!")
if (any(nb < 1)) stop("nb must be positive!")
}
if (length(nb)==1) nb <- rep(nb,3)
h <- nb[1]; w1 <- nb[2]; w2 <- nb[3];
if (subsample <= 0 || subsample > 1)
stop("subsample must be in (0,1]!")
n2 <- nrow(img) - h # images row to be considered
m2 <- ncol(img) - w1 - w2 # images column to be considered
I <- as.integer(seq.int(1, n2, length.out=ceiling(subsample*n2)))
J <- as.integer(seq.int(1, m2, length.out=ceiling(subsample*m2)))
M <- length(I)*length(J)
if (is.null(vars)) {
n <- (w1+w2+1)*h + w1 + 1 # find number of neighbors
data <- matrix(0, M, n); # stack rows in window of each pixel
k <- 1
for (i in I) {
for (j in J) {
data[k,] <- c(img[i+h,j+w1],
img[i:(i+h),j:(j+w1-1)],
img[i:(i+h-1),(j+w1):(j+w1+w2)])
k <- k + 1
}
}
data <- as.data.frame(data)
} else {
vars <- c("V1",vars);
vars.id<-unique(na.omit(as.numeric(unlist(strsplit(unlist(vars), "[^0-9]+")))))
n <- length(vars.id);
data <- matrix(0,M,n);
k <- 1
for (i in I) {
for (j in J ) {
data[k,] <- matrix(c(img[i+h,j+w1],
img[i:(i+h),j:(j+w1-1)],
img[i:(i+h-1),(j+w1):(j+w1+w2)])[vars.id],1,n)
k <- k + 1
}
}
data <- as.data.frame(data)
colnames(data) <- vars
}
data
}
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