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# uses
# component.dist
# reachability
# geodist
# symmetrize
# components.c
# geodist.c
#
# from R package sna
# function to check for ill-conditioned data in the RM
# requires package sna
##checkdata<-function(x)
##{
## k<-ncol(x)
## adj<-matrix(0,nc=k,nr=k)
## for (i in 1:k) for(j in 1:k) {
## adj[i,j]<- 1*any(x[,i]>x[,j],na.rm=TRUE)
## }
##
## #library(sna)
## #adj <- diag.remove(adj)
## # %print(adj) # adjacency marix
## cd <- component.dist(adj, connected = "strong")
## cm <- cd$membership
## cmp <- max(cm)
##
##
## if(cmp>1) {
## cat("Data:",deparse(substitute(x)),"are ill-conditioned\n")
## cat("Number of strong components",cmp,"\n")
## cat("Component membership of items: ",cm,"\n")
## } else
## cat("Data:",deparse(substitute(x)),"are well-conditioned\n")
##}
##
######################################################
component.dist<-
function (dat, connected = c("strong", "weak", "unilateral",
"recursive"))
{
# dat <- as.sociomatrix.sna(dat)
# if (is.list(dat))
# return(lapply(dat, component.dist, connected = connected))
# else if (length(dim(dat)) > 2)
# return(apply(dat, 1, component.dist, connected = connected))
n <- dim(dat)[2]
if (any(dat != t(dat)))
dat <- switch(match.arg(connected), weak = symmetrize(dat,
rule = "weak"), unilateral = reachability(dat), strong = symmetrize(reachability(dat),
rule = "strong"), recursive = symmetrize(dat, rule = "strong"))
# if (match.arg(connected) == "unilateral")
# if (any(dat != t(dat)))
# warning("Nonunique unilateral component partition detected in component.dist. Problem vertices will be arbitrarily assigned to one of their components.\n")
membership <- rep(0, n)
membership <- .C("component_dist_R", as.double(dat), as.double(n),
membership = as.double(membership), PACKAGE="eRm")$membership
o <- list()
o$membership <- membership
o$csize <- vector()
for (i in 1:max(membership)) o$csize[i] <- length(membership[membership ==
i])
o$cdist <- vector()
for (i in 1:n) o$cdist[i] <- length(o$csize[o$csize == i])
o
}
#reachability - Find the reachability matrix of a graph.
reachability<-function(dat,geodist.precomp=NULL){
#Pre-process the raw input
# dat<-as.sociomatrix.sna(dat)
# if(is.list(dat))
# return(lapply(dat,reachability,geodist.precomp=geodist.precomp))
# else if(length(dim(dat))>2)
# return(apply(dat,1,reachability,geodist.precomp=geodist.precomp))
# return(unlist(apply(dat,1,function(x,geodist.precomp){list(reachability(x, geodist.precomp=geodist.precomp))},geodist.precomp=geodist.precomp),recursive=FALSE))
#End pre-processing
#Get the counts matrix
if(is.null(geodist.precomp))
cnt<-geodist(dat)$counts
else
cnt<-geodist.precomp$counts
#Dichotomize and return
apply(cnt>0,c(1,2),as.numeric)
}
#geodist - Find the numbers and lengths of geodesics among nodes in a graph
#using a BFS, a la Brandes (2000). (Thanks, Ulrik!)
geodist<-function(dat,inf.replace=Inf){
#Pre-process the raw input
# dat<-as.sociomatrix.sna(dat)
# if(is.list(dat))
# return(lapply(dat,geodist,inf.replace=inf.replace))
# else if(length(dim(dat))>2)
# return(apply(dat,1,geodist,inf.replace=inf.replace))
#End pre-processing
n<-dim(dat)[2]
#Initialize the matrices
sigma<-matrix(0,nrow=n,ncol=n)
gd<-matrix(Inf,nrow=n,ncol=n)
#Perform the calculation
geo<-.C("geodist_R",as.double(dat),as.double(n),gd=as.double(gd), sigma=as.double(sigma),NAOK=TRUE,PACKAGE="eRm")
#Return the results
o<-list()
o$counts<-matrix(geo$sigma,n,n)
o$gdist<-matrix(geo$gd,n,n)
o$gdist[o$gdist==Inf]<-inf.replace #Patch Infs, if desired
o
}
#symmetrize - Convert a graph or graph stack to a symmetric form. Current rules
#for symmetrizing include "upper" and "lower" diagonals, "weak" connectedness
#rule, and a "strong" connectedness rule.
symmetrize<-function(mats,rule="weak"){
#Pre-process the raw input
# mats<-as.sociomatrix.sna(mats)
# if(is.list(mats))
# return(lapply(mats,symmetrize,rule=rule))
#End pre-processing
#Build the input data structures
# if(length(dim(mats))>2){
# m<-dim(mats)[1]
# n<-dim(mats)[2]
# o<-dim(mats)[3]
# d<-mats
# }else{
m<-1
n<-dim(mats)[1]
o<-dim(mats)[2]
d<-array(dim=c(1,n,o))
d[1,,]<-mats
# }
#Apply the symmetry rule
for(i in 1:m){
if(rule=="upper"){
# temp<-d[i,,]
# for(j in 1:n)
# temp[j:n,j]<-temp[j,j:n]
# d[i,,]<-temp
# }else if(rule=="lower"){
# temp<-d[i,,]
# for(j in 1:n)
# temp[j,j:n]<-temp[j:n,j]
# d[i,,]<-temp
# }else if(rule=="weak"){
# d[i,,]<-matrix(as.numeric(d[i,,]|t(d[i,,])),nrow=n,ncol=o)
}else if(rule=="strong"){
d[i,,]<-matrix(as.numeric(d[i,,]&t(d[i,,])),nrow=n,ncol=o)
}
}
#Return the symmetrized matrix
if(m==1)
out<-d[1,,]
else
out<-d
out
}
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