from_tna: Convert a tna object to cograph parameters

In cograph: Analysis and Visualization of Complex Networks

Convert a tna object to cograph parameters

Description

Extracts the transition matrix, labels, and initial state probabilities from a tna object and plots with cograph. Initial probabilities are mapped to donut fills.

Usage

from_tna(
  tna_object,
  engine = c("splot", "soplot"),
  plot = TRUE,
  weight_digits = NULL,
  show_zero_edges = FALSE,
  ...
)

Arguments

tna_object	A tna object from tna::tna()
engine	Which cograph renderer to use: "splot" or "soplot". Default: "splot".
plot	Logical. If TRUE (default), immediately plot using the chosen engine.
weight_digits	Number of decimal places to round edge weights to. Default NULL, which picks the number of digits from the matrix: 0 when every non-zero weight is a whole number (counts, as in ftna/ctna models) and 2 otherwise (probabilities). Edges whose weight rounds to zero at this precision are dropped unless show_zero_edges = TRUE.
show_zero_edges	Logical. Zero is how this representation stores "no edge", so an edge whose weight rounds to zero at weight_digits is dropped. With TRUE such an edge is instead drawn at the smallest magnitude weight_digits can express, carrying its sign; every other weight is unchanged. Default: FALSE.
...	Additional parameters passed to the plotting engine (e.g., layout, node_fill, donut_color).

Details

Conversion Process

The tna object's transition matrix becomes edge weights, labels become node labels, and initial state probabilities (inits) are mapped to donut_fill values to visualize starting state distributions.

Directedness is read from the tna object when available; otherwise it is inferred from matrix symmetry. Transition matrices are usually directed, while symmetric co-occurrence matrices are treated as undirected.

The default donut_inner_ratio of 0.8 creates thin rings that effectively visualize probability values without obscuring node labels.

Parameter Mapping

The following tna properties are automatically extracted:

• weights: Transition matrix -> edge weights

• labels: State labels -> node labels

• inits: Initial probabilities -> donut_fill (0-1 scale)

TNA Visual Defaults

The following visual defaults are applied for TNA plots (all can be overridden via ...):

• layout = "oval": Oval/elliptical node arrangement

• node_fill: Colors from TNA palette (Accent/Set3 based on state count)

• node_size = 7: Larger nodes for readability

• arrow_size = 0.61: Prominent directional arrows for directed networks

• edge_color = "#003355": Dark blue edges

• edge_labels = TRUE: Show transition weights on edges

• edge_label_size = 0.4: Readable edge labels

• edge_label_position = 0.7: Labels positioned toward target

• edge_start_style = "dotted": Dotted line at edge source for directed networks

• edge_start_length = 0.2: 20% of directed edges are dotted

• edge_label_style = "estimate" and edge_label_leading_zero = FALSE: labels show the weight alone, written without a leading zero (.42, not 0.42)

• minimum = 0.01: transitions weaker than 0.01 are not drawn

Value

Invisibly, a named list of cograph parameters that can be passed to splot() or soplot().

See Also

cograph for creating networks from scratch, splot and soplot for plotting engines, from_qgraph for qgraph object conversion

Examples

# Convert and plot a tna object
model <- tna::tna(regulation_net)
from_tna(model)  # Plots with donut rings showing initial probabilities

# Use soplot engine instead
from_tna(model, engine = "soplot")

# Customize the visualization
from_tna(model, layout = "circle", donut_color = c("steelblue", "gray90"))

# Extract parameters without plotting
params <- from_tna(model, plot = FALSE)
# Modify and plot manually
params$node_fill <- "coral"
do.call(splot, params)

cograph documentation built on Sept. 30, 2026, 5:08 p.m.