Plot demographic history encoded in a slendr model

Usage

plot_model(
  model,
  sizes = TRUE,
  proportions = FALSE,
  gene_flow = TRUE,
  log = FALSE,
  order = NULL,
  file = NULL,
  samples = NULL,
  ...
)

Arguments

model: Compiled slendr_model model object
sizes: Should population size changes be visualized?
proportions: Should gene flow proportions be visualized (FALSE by default to prevent cluttering and overplotting)
gene_flow: Should gene-flow arrows be visualized (default TRUE).
log: Should the y-axis be plotted on a log scale? Useful for models over very long time-scales.
order: Order of the populations along the x-axis, given as a character vector of population names. If NULL (the default), the default plotting algorithm will be used, ordering populations from the most ancestral to the most recent using an in-order tree traversal.
file: Output file for a figure saved via ggsave
samples: Sampling schedule to be visualized over the model
...: Optional argument which will be passed to ggsave

Value

A ggplot2 object with the visualized slendr model

Examples

check_dependencies(python = TRUE, quit = TRUE) # dependencies must be present

init_env()
#> The interface to all required Python modules has been activated.

# load an example model with an already simulated tree sequence
path <- system.file("extdata/models/introgression", package = "slendr")
model <- read_model(path)

plot_model(model, sizes = FALSE, log = TRUE)