library("devtools")
install_github("dipetkov/reemsplots2")Now, with the function make_eems_plots, we can produce a set of several figures to visualize the results of analyzing geo-referenced genetic data with EEMS as well as to evaluate the EEMS model fit.
library("reemsplots2")
mcmcpath <- system.file("extdata", "EEMS-example", package = "reemsplots2")
plots <- make_eems_plots(mcmcpath, longlat = TRUE)
#> Joining, by = "id"
#> Generate effective migration surface (posterior mean of m rates). See plots$mrates01 and plots$mrates02.
#> Generate effective diversity surface (posterior mean of q rates). See plots$qrates01 and plots$qrates02.
#> Generate average dissimilarities within and between demes. See plots$rdist01, plots$rdist02 and plots$rdist03.
#> Generate posterior probability trace. See plots$pilog01.
names(plots)
#> [1] "mrates01" "mrates02" "qrates01" "qrates02" "rdist01" "rdist02"
#> [7] "rdist03" "pilogl01"plots$mrates01
plots$mrates02
plots$qrates01
plots$qrates02
plots$rdist01
plots$rdist02
plots$rdist03
plots$pilogl01