Nothing
rescale.tucker <-
function(x, mode="A", newscale=1, ...){
# Rescales Weights of fit Tucker model
# Nathaniel E. Helwig (helwig@umn.edu)
# last updated: May 25, 2018
# check mode and dimensions
mode <- mode[1]
mydim <- c(ncol(x$A),ncol(x$B),ncol(x$C))
apdim <- 1:3
if(is.null(x$D)){
if(!any(mode==c("A","B","C"))) stop("Incorrect input for 'mode'. Must set to 'A', 'B', or 'C' for 3-way Tucker")
} else {
mydim <- c(mydim,ncol(x$D))
apdim <- c(apdim,4)
if(!any(mode==c("A","B","C","D"))) stop("Incorrect input for 'mode'. Must set to 'A', 'B', 'C', or 'D' for 4-way Parafac.")
}
# rescale factors
if(mode=="A"){
if(length(newscale)!=mydim[1]) newscale <- rep(newscale[1],mydim[1])
if(any(newscale <= 0)) stop("Input 'newscale' must contain positive values.")
Ascale <- sqrt(colMeans(x$A^2))
if(any(Ascale == 0)) Ascale[Ascale == 0] <- 1
svec <- newscale/Ascale
if(mydim[1]==1L) { Smat <- matrix(svec) } else { Smat <- diag(svec) }
x$A <- x$A %*% Smat
if(mydim[1]==1L) { Smat <- matrix(1/svec) } else { Smat <- diag(1/svec) }
Gmat <- matrix(x$G, mydim[1], prod(mydim[-1]))
x$G <- array(Smat %*% Gmat, dim=mydim)
return(x)
} else if(mode=="B"){
if(length(newscale)!=mydim[2]) newscale <- rep(newscale[1],mydim[2])
if(any(newscale <= 0)) stop("Input 'newscale' must contain positive values.")
permvec <- c(apdim[2],apdim[-2])
Bscale <- sqrt(colMeans(x$B^2))
if(any(Bscale == 0)) Bscale[Bscale == 0] <- 1
svec <- newscale/Bscale
if(mydim[2]==1L) { Smat <- matrix(svec) } else { Smat <- diag(svec) }
x$B <- x$B %*% Smat
if(mydim[2]==1L) { Smat <- matrix(1/svec) } else { Smat <- diag(1/svec) }
Gmat <- matrix(aperm(x$G, permvec), mydim[2], prod(mydim[-2]))
x$G <- aperm(array(Smat %*% Gmat, dim=c(mydim[2],mydim[-2])), sort(permvec,index=T)$ix)
return(x)
} else if(mode=="C"){
if(length(newscale)!=mydim[3]) newscale <- rep(newscale[1],mydim[3])
if(any(newscale <= 0)) stop("Input 'newscale' must contain positive values.")
permvec <- c(apdim[3],apdim[-3])
Cscale <- sqrt(colMeans(x$C^2))
if(any(Cscale == 0)) Cscale[Cscale == 0] <- 1
svec <- newscale/Cscale
if(mydim[3]==1L) { Smat <- matrix(svec) } else { Smat <- diag(svec) }
x$C <- x$C %*% Smat
if(mydim[3]==1L) { Smat <- matrix(1/svec) } else { Smat <- diag(1/svec) }
Gmat <- matrix(aperm(x$G, permvec), mydim[3], prod(mydim[-3]))
x$G <- aperm(array(Smat %*% Gmat, dim=c(mydim[3],mydim[-3])), sort(permvec,index=T)$ix)
return(x)
} else if(mode=="D"){
if(length(newscale)!=mydim[4]) newscale <- rep(newscale[1],mydim[4])
if(any(newscale <= 0)) stop("Input 'newscale' must contain positive values.")
permvec <- c(apdim[4],apdim[-4])
Dscale <- sqrt(colMeans(x$D^2))
if(any(Dscale == 0)) Dscale[Dscale == 0] <- 1
svec <- newscale/Dscale
if(mydim[4]==1L) { Smat <- matrix(svec) } else { Smat <- diag(svec) }
x$D <- x$D %*% Smat
if(mydim[4]==1L) { Smat <- matrix(1/svec) } else { Smat <- diag(1/svec) }
Gmat <- matrix(aperm(x$G, permvec), mydim[4], prod(mydim[-4]))
x$G <- aperm(array(Smat %*% Gmat, dim=c(mydim[4],mydim[-4])), sort(permvec,index=T)$ix)
return(x)
}
}
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