R/nbAndGraConversion.R

In BayesX: R Utilities Accompanying the Software Package BayesX

## Author: Daniel Sabanes Bove [daniel *.* sabanesbove *a*t* campus *.* lmu *.*
## de] Project: BayesX Time-stamp: <[nbAndGraConversion.R] by DSB Son 22/02/2009
## 19:10 (CET) on daniel@puc-home> Description: Convert an nb object (neighborhood
## structure) from package spdep to the graph format required by BayesX, and vice
## versa.  History: 19/02/2009 file creation: first version (without optional
## weights, as weights are not considered in read/write.gra) 22/02/2009 remove
## spdep dependence
nb2gra <- function(nbObject) {
  ## check if S3 class of nbObject is 'nb'
  stopifnot(inherits(x = nbObject, what = "nb"))
  
  ## convert to (negative) binary neighbors matrix
  regionIds <- attr(nbObject, "region.id")
  ret <- matrix(data = 0, nrow = length(regionIds), ncol = length(regionIds), dimnames = list(regionIds, 
    regionIds))
  
  for (i in seq_along(nbObject)) {
    ret[i, nbObject[[i]]] <- -1
  }
  
  
  ## and to gra format
  diag(ret) <- -rowSums(ret)
  class(ret) <- "gra"
  
  return(ret)
}


gra2nb <- function(graObject) {
  ## check if S3 class of nbObject is 'gra'
  stopifnot(inherits(x = graObject, what = "gra"))
  
  ## save region names and delete them (so that the list below will not have names
  ## attached)
  regionNames <- rownames(graObject)
  dimnames(graObject) <- NULL
  
  ## make list of neighbors
  ret <- apply(graObject, MARGIN = 1, FUN = function(row) which(row == -1))
  
  ## attach necessary attributes
  ret <- structure(ret, class = "nb", region.id = regionNames, call = match.call(), 
    type = "queen", sym = TRUE)
  
  ## and return the nb object
  return(ret)
}