#' Structure Analyses of Ecological Network
#'
#' Analysis of the structure of an ecological flow network.
#'
#' @param x A network object.
#' @return \item{A}{
#'
#' } \item{ns}{A vector of structure based network statistics. These include n
#' = number of nodes, L = number of edges, C = connectivity, LD = link density,
#' ppr = pathway proliferation rate, lam1A = dominant eigenvalue, mlam1A =
#' multiplicity of dominant eigenvalue, rho = damping ratio, R = distance of
#' the dominant eigen value from the eigen spectra, d = difference between
#' dominant eigen value and link density, no.scc = number of strongly connected
#' components, no.scc.big = number of strongly connected components with more
#' than one node, pscc = percent of nodes in strongly connected components. }
#' @author Matthew K. Lau Stuart R. Borrett
#' @seealso \code{\link{structure.statistics}}
#' @references Fath, B. D., Borrett, S. R. 2006. A Matlab function for Network
#' Environ Analysis. Environ. Model. Softw. 21, 375-405.
#' @examples
#'
#'
#'
#' data(troModels)
#' enaStructure(troModels[[6]])
#'
#'
#'
#' @export enaStructure
enaStructure <- function(x = 'network object'){
#Check for network class
if (class(x) != 'network'){warning('x is not a network class object')}
Flow <- t(as.matrix(x,attrname = 'flow')) #get flows
A <- sign(Flow) # get adjacency matrix
sp <- structure.statistics(A) # calls structure.statistics helper function
#Output orientation
orient <- get.orient()
if (orient=='rc'){A <- t(A)}else{}
return(list('A'=A,'ns'=sp)) # "A" is the adjacency matrix oriented
# column to row and "sp" is a list of
# structural network staistics
}
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