Plot Pathways as a Probability Heatmap — plot

Heatmap visualisation of the pathway table: rows are pathways (sorted), columns are next-state probabilities under the fitted tree. The modal next state of each row is annotated in bold; rows whose modal next state flips relative to their parent pathway are flagged in the row labels (with a leading caret >). A side strip on the left encodes the pathway count on a log scale.

This is the natural pathway-focused visualisation: one glance shows which pathways are common, which are sharp (high mass on a single next state), which are diffuse (mass spread evenly), and which carry trajectory-specific structure that order-1 misses.

Usage

plot_pathways(
  tree,
  top = 20L,
  sort_by = c("count", "divergence", "depth"),
  min_count = 5L,
  show_flips = TRUE,
  title = NULL,
  ...
)

Arguments

tree: A transitiontrees.
top: Integer. Maximum number of pathways to show. Default 20.
sort_by: Character. One of "count" (default), "divergence", or "depth".
min_count: Integer. Drop pathways with fewer than this many occurrences. Default 5.
show_flips: Logical. Mark modal-flip pathways with a leading caret in the label. Default TRUE.
title: Character. Plot title; if NULL (default) a title is derived from sort_by.
...: Ignored.

Value

A ggplot object.

Examples

# \donttest{
seqs <- replicate(50, sample(c("A","B","C"), 12, replace = TRUE),
                  simplify = FALSE)
tree <- context_tree(seqs, max_depth = 3)
plot_pathways(tree)

plot_pathways(tree, sort_by = "divergence", top = 12)

# }