#' A function to compute moments with a linear transect
#' @param ab matrix of abundances
#' @param clust matrix of hierarchical clustering
#' @param area vector of areas for clustering levels
#' @param q vector of orders
compute.moments.tri <- function(ab, clust, area, q)
{
# todo: check clust validity
ab <- as.matrix(ab)
n <- dim(ab)[1] # nr of samples
nlev <- dim(clust)[2] # nr of hierarchy levels
nn <- sum(apply(clust, 2, max)) # nr of cells
m <- qD <- matrix(0, nrow = nn, ncol = length(q))
a <- rep(0, nn)
H <- rep(0, nn)
pmin <- nmin <- rep(0, nn)
counter <- 1 # current cell
for (lev in 1:nlev)
{
for (ii in 1:max(clust[, lev], na.rm = T))
{
p <- ab[clust[, lev] == ii, ]
if (is.matrix(p)) p <- colSums(p)
if (sum(p) > 0)
{
m[counter, ] <- mom(p, q)
a[counter] <- area[lev]
H[counter] <- shannon(p)
nmin[counter] <- min(p[p > 0])
pmin[counter] <- nmin[counter]/sum(p)
counter <- counter + 1
}
}
}
qD <- m ^ (1/(1-matrix(q, nrow = dim(m)[1], ncol = dim(m)[2], byrow = T)))
qD[, q == 1] <- exp(H)
counter <- counter - 1
return(list(mom = m[1:counter,], H = H[1:counter], qD = qD[1:counter,],
a = a[1:counter], q = q, pmin = pmin[1:counter], nmin = nmin[1:counter]))
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.