library(poppr)
data(Pinf)
diversity_ci(Pinf, n = 100L)
## Not run:
# # With pretty results
# diversity_ci(Pinf, n = 100L, raw = FALSE)
#
# # This can be done in a parallel fasion (OSX uses "multicore", Windows uses "snow")
# system.time(diversity_ci(Pinf, 10000L, parallel = "multicore", ncpus = 4L))
# system.time(diversity_ci(Pinf, 10000L))
#
# # We often get many requests for a clonal fraction statistic. As this is
# # simply the number of observed MLGs over the number of samples, we
# # recommended that people calculate it themselves. With this function, you
# # can add it in:
#
# CF <- function(x){
# x <- drop(as.matrix(x))
# if (length(dim(x)) > 1){
# res <- rowSums(x > 0)/rowSums(x)
# } else {
# res <- sum(x > 0)/sum(x)
# }
# return(res)
# }
# # Show pretty results
#
# diversity_ci(Pinf, 1000L, CF = CF, center = TRUE, raw = FALSE)
# diversity_ci(Pinf, 1000L, CF = CF, rarefy = TRUE, raw = FALSE)
# ## End(Not run)
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