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Convert a tna object to cograph parameters

Source: R/from-qgraph.R
from_tna.Rd

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 = 2,
  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 2. Edges that round to zero are removed unless show_zero_edges = TRUE.

show_zero_edges

Logical. If TRUE, keep edges even if their weight rounds to zero. Default: FALSE.

...

Additional parameters passed to the plotting engine (e.g., layout, node_fill, donut_color).

Value

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

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.

TNA networks are always treated as directed because transition matrices represent directional state changes.

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

  • edge_color = "#003355": Dark blue edges

  • edge_labels = TRUE: Show transition weights on edges

  • edge_label_size = 0.6: Readable edge labels

  • edge_label_position = 0.7: Labels positioned toward target

  • edge_start_style = "dotted": Dotted line at edge source

  • edge_start_length = 0.2: 20% of edge is dotted

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
if (requireNamespace("tna", quietly = TRUE)) {
  library(tna)
  trans <- tna(group_regulation)
  from_tna(trans)  # Plots with donut rings showing initial probabilities

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

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

  # Extract parameters without plotting
  params <- from_tna(trans, plot = FALSE)
  # Modify and plot manually
  params$node_fill <- "coral"
  do.call(splot, params)
}
#> 'tna' package version 1.2.0
#> ------------------------------------------------------
#>   Tikka, S., López-Pernas, S., and Saqr, M. (2025). 
#>   tna: An R Package for Transition Network Analysis.
#>   Applied Psychological Measurement.
#>   https://doi.org/10.1177/01466216251348840
#> ------------------------------------------------------
#> Please type 'citation("tna")' for more citation information.
#> See the package website at https://sonsoles.me/tna/
#> 
#> Attaching package: ‘tna’
#> The following objects are masked from ‘package:igraph’:
#> 
#>     cliques, communities, compare