Simplicial Complex Visualization — plot

Visualize higher-order pathways as smooth blobs overlaid on a network layout. Source nodes are blue, target nodes are red.

Usage

plot_simplicial(
  x = NULL,
  pathways = NULL,
  method = "hon",
  max_pathways = 10L,
  layout = "circle",
  labels = NULL,
  node_color = "#4A7FB5",
  target_color = "#E8734A",
  ring_color = "#F5A623",
  node_size = 22,
  label_size = 5,
  blob_alpha = 0.25,
  blob_colors = NULL,
  blob_linetype = NULL,
  blob_linewidth = 0.7,
  blob_line_alpha = 0.8,
  shadow = TRUE,
  title = NULL,
  dismantled = FALSE,
  ncol = NULL,
  ...
)

Arguments

x: A network object: tna, netobject, matrix, igraph, cograph_network, net_hon, or net_hypa. When x is a tna or netobject with sequence data and pathways is NULL, higher-order pathways are built automatically using the method parameter.
pathways: Character vector of pathway strings, a list of character vectors, or a net_hon / net_hypa object. String separators: "A B -> C", "A, B, C", "A - B - C", "A B C". Last state is the target. When NULL and x is a model with sequence data, pathways are built automatically.
method: Higher-order method when auto-building from a tna/netobject: "hon" (default) or "hypa".
max_pathways: Maximum number of pathways to display. HON pathways are ranked by count, HYPA by anomaly ratio. NULL shows all. Default 10.
layout: "circle" (default) or a coordinate matrix.
labels: Display labels. NULL uses state names.
node_color: Source node fill color.
target_color: Target node fill color.
ring_color: Donut ring color.
node_size: Node point size.
label_size: Label text size.
blob_alpha: Blob fill transparency.
blob_colors: Blob fill colors (recycled).
blob_linetype: Blob border line styles (recycled).
blob_linewidth: Blob border line width.
blob_line_alpha: Blob border line transparency.
shadow: Draw soft drop shadows?
title: Plot title.
dismantled: If TRUE, one panel per pathway arranged in a grid layout.
ncol: Number of columns in the grid when dismantled = TRUE. Default NULL auto-selects based on the number of pathways.
...: Additional arguments passed to Nestimate::build_hon() or Nestimate::build_hypa() when auto-building.

Value

A ggplot object (or combined grid if dismantled), invisibly.

Details

Supports direct use with tna and netobject models: when x has sequence data, HON or HYPA pathways are built automatically (requires the Nestimate package). Pathways can also be passed as net_hon or net_hypa objects, with labels auto-translated when x is a tna/netobject.

Examples

if (FALSE) { # \dontrun{
mat <- matrix(runif(16), 4, 4,
              dimnames = list(LETTERS[1:4], LETTERS[1:4]))
diag(mat) <- 0
plot_simplicial(mat, c("A B -> C", "B C -> D"))

# Direct from tna model (requires Nestimate):
# model <- tna::tna(tna::group_regulation)
# plot_simplicial(model, dismantled = TRUE)
# plot_simplicial(model, method = "hypa")

# With pre-built HON + tna for label translation:
# hon <- Nestimate::build_hon(as.data.frame(model$data))
# plot_simplicial(model, hon, dismantled = TRUE)
} # }