Simple joinEigenanatomy function. — joinEigenanatomy • ANTsR

joinEigenanatomy joins the input matrix using a community membership approach.

joinEigenanatomy(
  datamatrix,
  mask = NULL,
  listEanatImages,
  graphdensity = 0.65,
  joinMethod = "walktrap",
  verbose = F
)

Arguments

datamatrix	input matrix before decomposition
mask	mask used to create datamatrix
listEanatImages	list containing pointers to eanat images
graphdensity	target graph density or densities to search over
joinMethod	see igraph's community detection
verbose	bool

Value

return(list(fusedlist = newelist, fusedproj = myproj, memberships = communitymembership , graph=gg, bestdensity=graphdensity ))

Examples

if (FALSE) {
# if you dont have images
mat<-replicate(100, rnorm(20))
mydecom<-sparseDecom( mat )
kk<-joinEigenanatomy( mat, mask=NULL, mydecom$eigenanatomyimages , 0.1 )
# or select optimal parameter from a list
kk<-joinEigenanatomy( mat, mask=NULL, mydecom$eigenanatomyimages , c(1:10)/50 )
# something similar may be done with images
mask<-as.antsImage( t(as.matrix(array(rep(1,ncol(mat)),ncol(mat)))) )
mydecom<-sparseDecom( mat, inmask=mask )
eanatimages = matrixToImages( mydecom$eigenanatomyimages, mask )
kki<-joinEigenanatomy( mat, mask=mask, eanatimages , 0.1 )
if ( usePkg("igraph") ) {
  mydecomf<-sparseDecom( mat, inmask=mask, initializationList=kki$fusedlist ,
    sparseness=0, nvecs=length(kki$fusedlist) )
 }
}