data(nancycats)
poppr(nancycats)
## Not run:
# # Sampling
# poppr(nancycats, sample = 999, total = FALSE, plot = TRUE)
#
# # Customizing the plot
# library("ggplot2")
# p <- last_plot()
# p + facet_wrap(~population, scales = "free_y", ncol = 1)
#
# # Turning off diversity statistics (see get_stats)
# poppr(nancycats, total=FALSE, H = FALSE, G = FALSE, lambda = FALSE, E5 = FALSE)
#
# # The previous version of poppr contained a definition of Hexp, which
# # was calculated as (N/(N - 1))*lambda. It basically looks like an unbiased
# # Simpson's index. This statistic was originally included in poppr because it
# # was originally included in the program multilocus. It was finally figured
# # to be an unbiased Simpson's diversity metric (Lande, 1996; Good, 1953).
#
# data(Aeut)
#
# uSimp <- function(x){
# lambda <- vegan::diversity(x, "simpson")
# x <- drop(as.matrix(x))
# if (length(dim(x)) > 1){
# N <- rowSums(x)
# } else {
# N <- sum(x)
# }
# return((N/(N-1))*lambda)
# }
# poppr(Aeut, uSimp = uSimp)
#
#
# # Demonstration with viral data
# # Note: this is a larger data set that could take a couple of minutes to run
# # on slower computers.
# data(H3N2)
# strata(H3N2) <- data.frame(other(H3N2)$x)
# setPop(H3N2) <- ~country
# poppr(H3N2, total = FALSE, sublist=c("Austria", "China", "USA"),
# clonecorrect = TRUE, strata = ~country/year)
# ## End(Not run)
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