ANTsR (version 1.0)

joinEigenanatomy: Simple joinEigenanatomy function.

Description

joinEigenanatomy joins the input matrix using a community membership approach.

Usage

joinEigenanatomy(datamatrix, mask = NA, listEanatImages,
  graphdensity = 0.65, joinMethod = NA, 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

# NOT RUN {
# if you dont have images
mat<-replicate(100, rnorm(20))
mydecom<-sparseDecom( mat )
kk<-joinEigenanatomy( mat, mask=NA, mydecom$eigenanatomyimages , 0.1 )
# or select optimal parameter from a list
kk<-joinEigenanatomy( mat, mask=NA, mydecom$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 )
kki<-joinEigenanatomy( mat, mask=mask, mydecom$eigenanatomyimages , 0.1 )
if ( usePkg("igraph") ) {
  mydecomf<-sparseDecom( mat, inmask=mask, initializationList=kki$fusedlist ,
    sparseness=0, nvecs=length(kki$fusedlist) )
 }
# }