In richelbilderbeek/tracerer: Tracer from R

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

tracerer: 'Tracer for R' is an R package that does the same as Tracer does, from within R.

To use tracerer, it needs to be loaded:

library(tracerer)

When loading beast2_example_output.log in Tracer, the following is displayed:

Most prominently, at the left, the effective sample sizes (ESSes) are shown.

The show the ESSes using tracerer:

estimates <- parse_beast_tracelog_file(
  get_tracerer_path("beast2_example_output.log")
)
estimates <- remove_burn_ins(estimates, burn_in_fraction = 0.1)
esses <- calc_esses(estimates, sample_interval = 1000)
table <- t(esses)
colnames(table) <- c("ESS")
knitr::kable(table)

At the top-right, some measures of the variable posterior is shown. To reproduce these measures in tracerer:

sum_stats <- calc_summary_stats(
  estimates$posterior,
  sample_interval = 1000
)
table <- t(sum_stats)
colnames(table) <- c("sum_stat")
knitr::kable(table)

Unlike Tracer, in tracerer all summary statistics can be obtained at once:

sum_stats <- calc_summary_stats(
  estimates,
  sample_interval = 1000
)
knitr::kable(sum_stats)

At the bottom-right, a histogram of the posterior estimates is shown. To reproduce these measures in tracerer:

ggplot2::ggplot(
  data = remove_burn_ins(estimates, burn_in_fraction = 0.1),
  ggplot2::aes(posterior)
) + ggplot2::geom_histogram(binwidth = 0.21) +
  ggplot2::scale_x_continuous(breaks = seq(-75, -68))

Tracer can also show the trace of each estimated variable:

Same can be done with tracerer:

ggplot2::ggplot(
  data = remove_burn_ins(estimates, burn_in_fraction = 0.1),
  ggplot2::aes(x = Sample)
) + ggplot2::geom_line(ggplot2::aes(y = posterior))

tracerer can also use part of DensiTree's functionality. Here is beast2_example_output.trees displayed by DensiTree:

The same is achieved in tracerer with:

trees <- parse_beast_trees(
  get_tracerer_path("beast2_example_output.trees")
)
phangorn::densiTree(trees, width = 2)

richelbilderbeek/tracerer documentation built on Oct. 2, 2023, 7:32 a.m.