clumpiness metric from fragstats

clumpy

landscape_padded <- pad_raster(landscape)
# landscape_padded <- landscape

adjacent_cells <- raster::adjacent(
    landscape_padded,
    cells =  seq_len(raster::ncell(landscape_padded)),
    directions = 4,
    pairs = TRUE
)

tb <- table(landscape_padded[adjacent_cells[, 1]],
            landscape_padded[adjacent_cells[, 2]])


like_adjacencies <- diag(tb)
like_adjacencies <- like_adjacencies[2:length(like_adjacencies)]
other_adjacencies <- tb[lower.tri(tb, diag = TRUE)]


area_class <- tibble::as.tibble(raster::freq(landscape))

min_e <- dplyr::mutate(
    area_class,
    value = count * 10000,
    n = trunc(sqrt(count)),
    m = count - n ^ 2,
    min_e = dplyr::case_when(
        m == 0 ~ n * 4,
        n ^ 2 < count &
            count <= n * (1 + n) ~ 4 * n + 2,
        count > n * (1 + n) ~ 4 * n + 4
    )
) %>%
    dplyr::pull(min_e)

g <- like_adjacencies / (colSums(other_adjacencies) - min_e)

prop_class <-
    (lsm_c_pland(landscape) %>% dplyr::pull(value)) / 100

clumpy <- purrr::map_dbl(seq_along(g), function(row_ind) {
    if (g[row_ind] < (prop_class[row_ind]) & prop_class[row_ind] < .5) {
        clumpy <-
            (g[row_ind] - prop_class[row_ind]) / prop_class[row_ind]
    } else{
        clumpy <-
            (g[row_ind] - prop_class[row_ind]) / (1 - prop_class[row_ind])
    }
    
})