rotates, translates and scales one matrix onto an other using Procrustes fitting
rotates, translates and scales one matrix onto an other using Procrustes fitting
rotonto(x, y, scale = FALSE, signref = TRUE, reflection = TRUE, weights = NULL, centerweight = FALSE) rotreverse(mat, rot) ## S3 method for class 'matrix' rotreverse(mat, rot) ## S3 method for class 'mesh3d' rotreverse(mat, rot)
x |
k x m matrix to be rotated onto (targetmatrix) |
y |
k x m matrix which will be rotated (reference matrix) |
scale |
logical: scale matrix to minimize sums of squares |
signref |
logical: report if reflections were involved in the rotation |
reflection |
allow reflections. |
weights |
vector of length k, containing weights for each landmark. |
centerweight |
logical or vector of weights: if weights are defined and centerweigths=TRUE,
the matrix will be centered according to these weights instead of the
barycenter. If centerweight is a vector of length |
mat |
matrix on which the reverse transformations have to be applied |
rot |
an object resulting from the former application of rotonto |
rotate a matrix onto an other without loosing information about the location of the targetmatrix and reverse this transformations using rotreverse
yrot |
rotated and translated matrix |
Y |
centred and rotated reference matrix |
X |
centred target matrix |
trans |
vector between original position of target and centered reference (during rotation process) |
transy |
vector between original position of reference and centered reference (during rotation process) |
gamm |
rotation matrix |
bet |
scaling factor applied |
reflect |
if |
all lines containing NA, or NaN are ignored in computing the transformation.
Stefan Schlager
Lissitz, R. W., Schoenemann, P. H., & Lingoes, J. C. (1976). A solution to the weighted Procrustes problem in which the transformation is in agreement with the loss function. Psychometrika, 41,547-550.
if (require(shapes)) {
lims <- c(min(gorf.dat[,,1:2]),max(gorf.dat[,,1:2]))
rot <- rotonto(gorf.dat[,,1],gorf.dat[,,2]) ### rotate the second onto the first config
plot(rot$yrot,pch=19,xlim=lims,ylim=lims) ## view result
points(gorf.dat [,,2],pch=19,col=2) ## view original config
rev1 <- rotreverse(rot$yrot,rot)
points(rev1,cex=2) ### show inversion by larger circles around original configuration
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