\name{iProcrustes} \alias{iProcrustes} \title{Procrustes analysis. Using singular value decomposition (SVD) to determine a linear transformation to align the points in X to the points in a reference matrix Y. } \description{ Based on generalized Procrustes analysis, this function determines a linear transformation (rotation/reflection and scalling) of the points in matrix \code{x} to align them to their reference points in matrix \code{xbar}. The alignemnt is carried out by minimizing the distance between the points in \code{x} and \code{xbar}. } \usage{ iProcrustes(x, xbar, rotation.only=TRUE, scalling=TRUE, translate=FALSE) } \arguments{ \item{x}{A numerical matrix to be align to points in \code{xbar}, the second arguement. The columns represents the coordinates of the points. The matrices \code{x} and \code{xbar} must have the same dimensions.} \item{xbar}{A numerical, reference matrix to which points in matrix \code{x} are to be aligned.} \item{rotation.only}{Logical. When \code{rotaion.only} is TRUE, it allows the function to lose reflection component of the linear transformation. Although it might not give the best-fitting aligenment, when dealing with flow cytometry data alignment, a non-reflection transformation is prefered. When \code{rotaion.only} is FALSE, it allows the function to retain the reflection component.} \item{scalling}{Logical. When \code{scalling} is FALSE, it allows the function to calculate the linear transformation without a scalling factor. That is, the returning scalling factor is set to \eqn{1}.} \item{translate}{Logical. Set \code{translate} to FALSE when the points in matrices x and xbar are already centralized prior to applying this function. When \code{translate} is TRUE, it allows the function to translate the centroid the points in matrix \code{x} to that of points in \code{xbar}.} } \details{ Suppose the points in matrix \eqn{X} and \eqn{\bar{X}} are centralized (meaning their centroids are at the origin). The linear transformation of \eqn{X} for aligning \eqn{X} to its reference matrix \eqn{\bar{X}}., i.e., min \eqn{||sXQ - \bar{X}||_F}, is given by: \deqn{Q = VU^T,} and \deqn{s = trace(\bar{X}^TXQ) / trace(X^T X),} where V and U are the sigular value vectors of \eqn{\bar{X}^T X} (that is, \eqn{\bar{X}^T X = U \Sigma V^T}), and \eqn{s} is the scalling factor. } \value{ A list of the linear tranformation with items \item{Q}{An orthogonal, rotation/reflection matrix.} \item{scal}{A scalling factor}. \item{T}{(optional) A translation vector used to shift the centroid of the points in matrix \code{x} to the origin. Returned when \code{translate} is TRUE.} \item{T.xbar}{(optional) Centered \code{xbar} (that is, the centroid of the points in \code{xbar} is translated to the origin). Returned when \code{translate} is TRUE.} Note that the return values of this function do not include the transformed matrix \eqn{scal* x* Q} or \eqn{scal*(x-IT)*Q}, where \eqn{T} is the translation vector and \eqn{I} is an \eqn{n-by-1} vector with elements \eqn{1}. } \author{C. J. Wong \email{cwon2@fhcrc.org}} \seealso{\code{\link{gpaSet}}} \examples{ ## Example 1 x <- matrix(runif(20), nrow=10, ncol=2)+ 1.4 s <- matrix(c(cos(60), -sin(60), sin(60), cos(60)), nrow=2, ncol=2, byrow=TRUE) xbar <- 2.2 *(x \%*\% s) - 0.1 lt <- iProcrustes(x, xbar, translate=TRUE) ## return linear transformation lt ## showing result I <- matrix(1, nrow=nrow(x), ncol=1) tx <- x - I \%*\% lt$T ## get the transformed matrix xnew xnew <- lt$scal * (tx \%*\% lt$Q) if (require(lattice)) { xyplot(V1 ~ V2, do.call(make.groups, lapply(list(x=x, xbar=xbar, T.xbar=lt$T.xbar, xnew=xnew),as.data.frame)), group=which, aspect=c(0.7), pch=c(1,3,2,4), col.symbol="black", main=("Align the points in x to xbar"), key=list(points=list(pch=c(1,3,2,4), col="black"), space="right", text=list(c("x", "xbar", "T.xbar", "xnew")))) } ## Example 2. centralized x and xbar prior to using iProcrustes x <- matrix(runif(10), nrow=5, ncol=2) s <- matrix(c(cos(60), -sin(60), sin(60), cos(60)), nrow=2, ncol=2, byrow=TRUE) xbar <- 1.2 *(x \%*\% s) - 2 I <- matrix(1, nrow=nrow(x), ncol=1) x <- x-(I \%*\% colMeans(x)) ## shift the centroid of points in x to the origin xbar <- xbar - (I \%*\% colMeans(xbar)) ## shift centroid to the origin lt <- iProcrustes(x, xbar, translate=FALSE) ## return linear transformation ## only return the rotation/reflection matrix and scalling factor lt xnew=lt$scal *(x \%*\% lt$Q) ## transformed matrix aligned to centralized xbar if (require(lattice)) { xyplot(V1 ~ V2, do.call(make.groups, lapply(list(x=x,xbar=xbar, xnew=xnew), as.data.frame)), group=which, auto.key=list(space="right")) } }