Description Usage Arguments Value Author(s) Examples
Decomposes two matrices into paired sparse eigenevectors to maximize canonical correlation.
1 |
inmatrix |
input as inmatrix=list(mat1,mat2). n by p input matrix and n by q input matrix , spatial variable lies along columns. |
inmask |
optional pair of antsImage masks |
other params |
see sccan for other parameters |
outputs a decomposition of a pair of matrices
Avants BB
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ## Not run:
mat<-replicate(100, rnorm(20))
mat2<-replicate(100, rnorm(20))
mydecom<-sparseDecom2( inmatrix=list(mat,mat2), sparseness=c(0.1,0.3) , nvecs=3, its=3, perms=0)
wt<-0.666
mat3<-mat*wt+mat2*(1-wt)
mydecom<-sparseDecom2( inmatrix=list(mat,mat3), sparseness=c(0.2,0.2), nvecs=5, its=10, perms=200 )
# a masked example
im<-antsImageRead( getANTsRData('r64') ,2)
dd<- im > 250
mask<-antsImageClone( im )
mask[ !dd ]<-0
mask[ dd ]<-1
mat1<-matrix( rnorm(sum(dd)*10) , nrow=10 )
mat2<-matrix( rnorm(sum(dd)*10) , nrow=10 )
initlist<-list()
for ( nvecs in 1:2 ) {
init1<-antsImageClone( mask )
init1[dd]<-rnorm(sum(dd))
initlist<-lappend( initlist, init1 )
}
ff<-sparseDecom2( inmatrix=list(mat1,mat2), inmask=list(mask,mask),
sparseness=c(0.1,0.1) ,nvecs=length(initlist) , smooth=1, cthresh=c(0,0), initializationList = initlist ,ell1 = 11 )
## End(Not run)
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