ahn_gen function

Generate networks characterising habitat physical configurations

Generate undirected networks (weighted or unweighted, connected or disconnected) characterising the physical attributes and spatial organizations (or distributions) of habitat components (i.e. habitat configurations).

ahn_gen(N, L, mu, lamda, Connected = TRUE, Weighted = TRUE, eta = 1,
  A = 25, X = NULL, Y = NULL, U = NULL, V = NULL)

Arguments

• N: The number of nodes
• L: A side length of the rectangle landscape within which nodes are anchored
• mu: the critical Dij (i.e. Euclidean distance between node i and j) at which the link removing probability curve P(Dij, mu, lamda) transits from concave to convex (see ahn_prob)
• lamda: the steepness of the link removing probability curve P(Dij, mu, lamda), see ahn_prob
• Connected: TRUE for connected while FALSE ignores whether the networks are connected or not
• Weighted: TRUE for weighted while FALSE for unweighted networks
• eta: mediates the weight, i.e. (Dij)^-eta, of the link rewiring node i from one network component and node j from another network component (i and j are with an Euclidean distance of Dij) when the network becomes disconnected after removing links from the initial complete network with the probability P(Dij, mu, lamda) = [1 + exp(-lamda(Dij - mu))]^-1 when both Connected = TRUE and Weighted = TRUE
• A: The area of the rectangle landscape within which the network is defined
• X: A vector of X coordinates for the N nodes (sampled from [0, L] uniformly at random if NULL)
• Y: A vector of Y coordinates for the N nodes (sampled from [0, A/L] uniformly at random if NULL)
• U: A vector with N elements specifying node attributes (qualitative or quantitive), by default NULL
• V: A vector with N elements specifying node attributes (qualitative or quantitive), by default NULL

Returns

Return an animal habitat network (an igraph object)

Examples

# generate a connected and weighted network
ahn_gen(N = 10, L = 5, mu = 1, lamda = 5)


N <- 10
x <- runif(N, 0, 5)
ql <- sample(LETTERS, N, replace = TRUE)
qn <- sample(1:20, N, replace = TRUE)

# specify the X coordinates, node attributes U and V for a connected and unweighted network
ahn_gen(N, L = 5, mu = 1, lamda = 5, Weighted = FALSE, X = x, U = ql, V = qn)

# specify the Y coordinates, node attributes U and V for a weighted network, no matter if the
# network will be connected or not
ahn_gen(N, L = 5, mu = 1, lamda = 5, Weighted = TRUE, Connected = FALSE, Y = x, U = ql, V = qn)