Base R Graphics Network Plotting

Plots a network with base R graphics (polygon(), lines(), xspline()). splot() uses the same snake_case argument names as the grid-based soplot(). Result objects of tna, Nestimate and cograph analyses are plotted by the methods described in Details.

Usage

splot.net_bootstrap(
  x,
  display = c("styled", "significant", "full"),
  show_ci = FALSE,
  show_stars = TRUE,
  inherit_style = TRUE,
  ...
)

splot.tna_communities(x, ...)

splot.cograph_communities(x, ...)

splot.net_mlvar(x, type = "temporal", combined = TRUE, ...)

splot.netobject(x, ...)

splot.boot_glasso(
  x,
  use_thresholded = TRUE,
  show_inclusion = TRUE,
  inclusion_threshold = NULL,
  edge_positive_color = "#2E7D32",
  edge_negative_color = "#C62828",
  ...
)

splot.wtna_mixed(x, type = c("overlay", "group"), ...)

splot.net_permutation(
  x,
  show_nonsig = FALSE,
  show_effect = FALSE,
  edge_positive_color = "#009900",
  edge_negative_color = "#C62828",
  edge_nonsig_color = "#888888",
  edge_nonsig_style = 2L,
  show_stars = TRUE,
  ...
)

splot(
  x,
  layout = "oval",
  directed = NULL,
  seed = 42,
  theme = NULL,
  node_size = NULL,
  node_size2 = NULL,
  scale_nodes_by = NULL,
  node_size_range = c(2, 8),
  scale_nodes_scale = 1,
  node_shape = "circle",
  node_svg = NULL,
  svg_preserve_aspect = TRUE,
  node_fill = NULL,
  node_border_color = NULL,
  node_border_width = 1,
  node_alpha = 1,
  labels = TRUE,
  label_abbrev = NULL,
  label_size = NULL,
  label_color = "black",
  label_position = "center",
  label_fontface = "plain",
  label_fontfamily = "sans",
  label_hjust = 0.5,
  label_vjust = 0.5,
  label_angle = 0,
  pie_values = NULL,
  pie_colors = NULL,
  pie_border_width = NULL,
  donut_fill = NULL,
  donut_values = NULL,
  donut_color = NULL,
  donut_colors = NULL,
  donut_border_color = NULL,
  donut_border_width = NULL,
  donut_inner_border_color = NULL,
  donut_inner_border_width = NULL,
  donut_outer_border_color = NULL,
  donut_line_type = "solid",
  donut_border_lty = NULL,
  donut_inner_ratio = 0.8,
  donut_bg_color = "gray90",
  donut_shape = "circle",
  donut_show_value = FALSE,
  donut_value_size = 0.8,
  donut_value_color = "black",
  donut_value_fontface = "bold",
  donut_value_fontfamily = "sans",
  donut_value_digits = 2,
  donut_value_prefix = "",
  donut_value_suffix = "",
  donut_empty = TRUE,
  donut2_values = NULL,
  donut2_colors = NULL,
  donut2_inner_ratio = 0.4,
  edge_color = NULL,
  edge_width = NULL,
  edge_size = NULL,
  esize = NULL,
  edge_width_range = c(0.1, 4),
  edge_scale_mode = "linear",
  edge_cutoff = NULL,
  cut = NULL,
  edge_alpha = 0.8,
  edge_labels = FALSE,
  edge_label_size = 0.8,
  edge_label_color = "gray30",
  edge_label_bg = NA,
  edge_label_position = 0.5,
  edge_label_offset = 0,
  edge_label_fontface = "plain",
  edge_label_shadow = FALSE,
  edge_label_shadow_color = "gray40",
  edge_label_shadow_offset = 0.5,
  edge_label_shadow_alpha = 0.5,
  edge_label_halo = TRUE,
  edge_style = 1,
  curvature = 0,
  curve_scale = TRUE,
  curve_shape = 0,
  curve_pivot = 0.5,
  curves = TRUE,
  arrow_size = 1,
  arrow_angle = pi/6,
  show_arrows = TRUE,
  bidirectional = FALSE,
  loop_rotation = NULL,
  show = NULL,
  edge_start_style = "solid",
  edge_start_length = 0.15,
  edge_start_dot_density = "12",
  edge_ci = NULL,
  edge_ci_scale = 2,
  edge_ci_alpha = 0.15,
  edge_ci_color = NA,
  edge_ci_style = 2,
  edge_ci_arrows = FALSE,
  edge_priority = NULL,
  edge_label_style = "none",
  edge_label_template = NULL,
  edge_label_digits = 2,
  edge_label_oneline = TRUE,
  edge_label_ci_format = "bracket",
  edge_label_leading_zero = TRUE,
  edge_ci_lower = NULL,
  edge_ci_upper = NULL,
  edge_label_p = NULL,
  edge_label_p_diff = NULL,
  edge_label_p_digits = 3,
  edge_label_p_prefix = "p=",
  edge_label_stars = NULL,
  weight_digits = 2,
  threshold = 0,
  minimum = 0,
  maximum = NULL,
  edge_positive_color = "#2E7D32",
  positive_color = NULL,
  edge_negative_color = "#C62828",
  negative_color = NULL,
  edge_duplicates = NULL,
  title = NULL,
  title_size = 1.2,
  margins = c(0.1, 0.1, 0.1, 0.1),
  background = "white",
  rescale = TRUE,
  layout_scale = 1,
  layout_margin = 0.15,
  aspect = TRUE,
  use_pch = FALSE,
  usePCH = NULL,
  scaling = "default",
  align_panels = FALSE,
  legend = FALSE,
  legend_position = "topright",
  legend_size = 0.8,
  legend_edge_colors = TRUE,
  legend_node_sizes = FALSE,
  groups = NULL,
  node_names = NULL,
  tna_styling = NULL,
  psych_styling = NULL,
  predictability = NULL,
  i = NULL,
  filetype = "default",
  filename = file.path(tempdir(), "splot"),
  width = 7,
  height = 7,
  res = 600,
  ...
)

Arguments

x

Network input. Can be:

A square numeric matrix (adjacency/weight matrix)
A data frame with edge list (from, to, optional weight columns)
An igraph object
A CographNetwork or cograph_network object
A tna object (from tna package)
A group_tna object (list of tna objects from tna package). Use parameter i to select a specific group, or omit to plot all groups.
A result object handled by one of the methods: net_bootstrap, net_permutation, boot_glasso, netobject, net_mlvar and wtna_mixed from Nestimate, tna_communities from tna, and cograph_communities.

display

Display mode of splot.net_bootstrap(): "styled" (default), "significant" or "full".

show_ci

Logical. Add the confidence bounds to the edge labels of a net_bootstrap plot. Default FALSE.

show_stars

Logical. Show significance stars in the edge labels of a net_bootstrap or net_permutation plot. Default TRUE.

inherit_style

Logical. Take labels, layout and colors from the original network of a net_bootstrap object. Default TRUE.

...

For splot(), additional arguments passed to the layout function. For the methods, additional arguments passed to splot(), or to plot_mixed_network() for splot.wtna_mixed() with type = "overlay". Arguments supplied here override the styling defaults of a method. For a multi-panel input, such as a group_tna, group_tna_bootstrap, group_tna_permutation or net_permutation_group object, combined = TRUE (default) arranges the panels with graphics::par(mfrow = ...), and combined = FALSE plots them into a layout set up beforehand, for example with panel_layout(). It has no effect for a single network.

type

For a net_mlvar object, the network to plot: "temporal" or "t" (default), "contemporaneous" or "c", "between" or "b", or "all" or "a" for a 1 x 3 panel, matched without regard to case. For a wtna_mixed object, "overlay" (default) plots both networks on one canvas with plot_mixed_network, the co-occurrences as straight undirected edges and the transitions as curved directed edges, and "group" plots each network in its own panel.

combined

Logical. With type = "all" for a net_mlvar object, TRUE (default) arranges the three panels in a 1 x 3 grid, and FALSE plots them into a layout set up beforehand, for example with panel_layout(). Ignored for a single network.

use_thresholded

Logical. Plot $thresholded_pcor of a boot_glasso object, or $original_pcor when FALSE. Default TRUE.

show_inclusion

Logical. Map the inclusion probability of each edge of a boot_glasso object to its opacity, from 0.2 to 1. Default TRUE.

inclusion_threshold

Numeric. Minimum inclusion probability of a plotted boot_glasso edge. NULL (default) uses 1 - x$alpha, or 0.95 when x$alpha is absent.

edge_positive_color

Color for positive weights. The default is "#2E7D32", and "#009900" for splot.net_permutation().

edge_negative_color

Color for negative weights. Default "#C62828".

show_nonsig

Logical. Show non-significant edges of a net_permutation plot. Default FALSE.

show_effect

Logical. Show the effect size in parentheses in the edge labels of a net_permutation plot. Default FALSE.

edge_nonsig_color

Color of non-significant edges. Default "#888888".

edge_nonsig_style

Line type of non-significant edges. Default 2.

layout

Layout algorithm: "oval" (default), "circle", "spring", "groups", "target" (qgraph-style focal-node BFS levels; node of interest via target), "saqr" (Start/End transition flow; start/ end/jitter), or a matrix of x,y coordinates, or an igraph layout function. Also supports igraph two-letter codes: "kk", "fr", "drl", "mds", "ni", etc.

directed

Logical. Force directed interpretation. NULL for auto-detect.

seed

Random seed for deterministic layouts. Default 42.

theme

Theme name: "classic", "dark", "minimal", "colorblind", etc.

node_size

Node size(s). Single value or vector. Default NULL, which resolves to 7 with default scaling.

node_size2

Secondary node size for ellipse/rectangle height.

scale_nodes_by

Scale node sizes by a centrality measure. Can be:

A measure name: "degree", "strength", "betweenness", "closeness", "eigenvector", "pagerank", "authority", "hub", "harmonic", etc.
A directional shorthand: "indegree", "outdegree", "instrength", "outstrength", "incloseness", "outcloseness", "inharmonic", "outharmonic", "ineccentricity", "outeccentricity".
A list with measure and parameters: list("pagerank", damping = 0.9)

When used, node_size is ignored. Use node_size_range to control the min/max size. Default NULL (no centrality scaling).

node_size_range

Size range for centrality-based scaling. Numeric vector c(min_size, max_size). Default c(2, 8).

scale_nodes_scale

Dampening exponent for centrality-based sizing. Values < 1 compress differences (e.g., 0.5 applies square root), values > 1 exaggerate differences. Default 1 (linear).

node_shape

Node shape(s): "circle", "square", "triangle", "diamond", "pentagon", "hexagon", "star", "heart", "ellipse", "cross", or any custom SVG shape registered with register_svg_shape().

node_svg

Custom SVG for nodes: path to SVG file OR inline SVG string.

svg_preserve_aspect

Logical: maintain SVG aspect ratio? Default TRUE.

node_fill

Node fill color(s).

node_border_color

Node border color(s).

node_border_width

Node border width(s).

node_alpha

Node transparency (0-1). Default 1.

labels

Node labels: TRUE (use node names/indices), FALSE (none), or character vector.

label_abbrev

Controls label abbreviation in the same way as plot_mcml(): NULL keeps full labels, an integer truncates labels to that maximum number of characters, and "auto" adapts the maximum length to the number of nodes.

label_size

Label character expansion factor.

label_color

Label text color.

label_position

Label position: "center", "above", "below", "left", "right".

label_fontface

Font face for labels: "plain", "bold", "italic", "bold.italic". Default "plain".

label_fontfamily

Font family for labels: "sans", "serif", "mono". Default "sans".

label_hjust

Horizontal justification (0=left, 0.5=center, 1=right). Default 0.5.

label_vjust

Vertical justification (0=bottom, 0.5=center, 1=top). Default 0.5.

label_angle

Text rotation angle in degrees. Default 0.

pie_values

List of numeric vectors for pie chart nodes. Each element corresponds to a node and contains values for pie segments. If a simple numeric vector with values between 0 and 1 is provided (e.g., centrality scores), it is automatically converted to donut_fill for convenience.

pie_colors

List of color vectors for pie segments.

pie_border_width

Border width for pie slice dividers. NULL uses node_border_width.

donut_fill

Numeric value (0-1) for donut fill proportion. This is the qgraph-style API: 0.1 = 10% filled, 0.5 = 50% filled, 1.0 = fully filled. Can be a single value (all nodes) or vector (per-node values).

donut_values

Deprecated. Use donut_fill for simple fill proportion.

donut_color

Fill color(s) for the donut ring. Single color sets fill for all nodes. Two colors set fill and background for all nodes. More than 2 colors set per-node fill colors (recycled to n_nodes). Default: "maroon" fill, "gray90" background when node_shape="donut".

donut_colors

Deprecated. Use donut_color instead.

donut_border_color

Border color for donut rings. NULL uses node_border_color.

donut_border_width

Border width for donut rings. NULL uses node_border_width.

donut_inner_border_color

Color for the inner boundary (where the donut meets its hole). NULL (default) uses donut_border_color. Can be scalar or per-node vector.

donut_inner_border_width

Width for the inner boundary border. NULL (default) uses donut_border_width. Can be scalar or per-node vector.

donut_outer_border_color

Color for outer boundary border (enables double border). NULL (default) shows single border. Set to a color for double border effect. Can be scalar or per-node vector.

donut_line_type

Line type for donut borders: "solid", "dashed", "dotted", or numeric (1=solid, 2=dashed, 3=dotted). Can be scalar or per-node vector.

donut_border_lty

Deprecated. Use donut_line_type instead.

donut_inner_ratio

Inner radius ratio for donut (0-1). Default 0.8.

donut_bg_color

Background color for unfilled donut portion.

donut_shape

Base shape for donut: "circle", "square", "hexagon", "triangle", "diamond", "pentagon". Can be a single value or per-node vector. Default inherits from node_shape (e.g., hexagon nodes get hexagon donuts). Set explicitly to override (e.g., donut_shape = "hexagon" for hexagon donuts on all nodes regardless of node_shape).

donut_show_value

Logical: show value in donut center? Default FALSE.

donut_value_size

Font size for donut center value.

donut_value_color

Color for donut center value.

donut_value_fontface

Font face for donut center value: "plain", "bold", "italic", "bold.italic". Default "bold".

donut_value_fontfamily

Font family for donut center value: "sans", "serif", "mono". Default "sans".

donut_value_digits

Decimal places for donut center value. Default 2.

donut_value_prefix

Text before donut center value (e.g., "$"). Default "".

donut_value_suffix

Text after donut center value (e.g., "%"). Default "".

donut_empty

Logical: render empty donut rings for NA values? Default TRUE.

donut2_values

List of values for inner donut ring (for double donut).

donut2_colors

List of color vectors for inner donut ring segments.

donut2_inner_ratio

Inner radius ratio for inner donut ring. Default 0.4.

edge_color

Edge color(s). If NULL, uses edge_positive_color/edge_negative_color based on weight.

edge_width

Edge width(s). If NULL, scales by weight using edge_size and edge_width_range.

edge_size

Maximum edge size for weight scaling. NULL (default) uses the upper bound of edge_width_range. Larger values = thicker edges overall.

esize

Deprecated. Use edge_size instead.

edge_width_range

Output width range as c(min, max) for weight-based scaling. Default c(0.1, 4). Edges are scaled to fit within this range unless edge_size supplies the maximum.

edge_scale_mode

Scaling mode for edge weights: "linear" (default, qgraph-style), "log" (logarithmic for wide weight ranges), "sqrt" (moderate compression), or "rank" (equal visual spacing regardless of weight distribution).

edge_cutoff

Optional cutoff for edge emphasis. NULL (default) or 0 disables cutoff fading. Positive values fade edges whose absolute weights are below the cutoff; width scaling remains continuous.

cut

Deprecated. Use edge_cutoff instead.

edge_alpha

Edge transparency (0-1). Default 0.8.

edge_labels

Edge labels: TRUE (show weights), FALSE (none), or character vector.

edge_label_size

Edge label size.

edge_label_color

Edge label text color.

edge_label_bg

Edge label background color.

edge_label_position

Position along edge (0-1).

edge_label_offset

Perpendicular offset for edge labels (0 = on line, positive = above).

edge_label_fontface

Font face: "plain", "bold", "italic", "bold.italic".

edge_label_shadow

Logical: enable drop shadow for edge labels? Default FALSE.

edge_label_shadow_color

Color for edge label shadow. Default "gray40".

edge_label_shadow_offset

Offset distance for shadow in points. Default 0.5.

edge_label_shadow_alpha

Transparency for shadow (0-1). Default 0.5.

edge_label_halo

Logical: enable white halo/outline around edge labels for readability over dark edges? Default TRUE. When TRUE, overrides shadow settings.

edge_style

Line type(s): 1=solid, 2=dashed, 3=dotted, etc.

curvature

Edge curvature. 0 for straight, positive/negative for curves.

curve_scale

Not used.

curve_shape

Spline tension (-1 to 1). Default 0.

curve_pivot

Position along edge for curve control point (0-1).

curves

Curve mode: TRUE (default) = single edges straight, reciprocal edges curve as ellipse (two opposing curves); FALSE = all straight; "force" = all curved.

arrow_size

Arrow head size.

arrow_angle

Arrow head angle in radians. Default pi/6 (30 degrees).

show_arrows

Logical or vector: show arrows on directed edges?

bidirectional

Logical or vector: show arrows at both ends?

loop_rotation

Angle(s) in radians for self-loop direction.

show

Dispatch-only placeholder used by method dispatch (e.g., splot.tna_disparity). Not intended for direct use.

edge_start_style

Style for the start segment of edges: "solid" (default), "dashed", or "dotted". Use dashed/dotted to indicate edge direction (source node).

edge_start_length

Fraction of edge length for the styled start segment (0-0.5). Default 0.15 (15% of edge). Only applies when edge_start_style is not "solid".

edge_start_dot_density

Pattern for dotted start segments. A two-character string where the first digit is dot length and second is gap length (in line width units). Default "12" (1 unit dot, 2 units gap). Use "11" for tighter dots, "13" for more spacing. Only applies when edge_start_style = "dotted".

edge_ci

Numeric vector of CI widths (0-1 scale). Larger values = more uncertainty.

edge_ci_scale

Width multiplier for underlay thickness. Default 2.

edge_ci_alpha

Transparency for underlay (0-1). Default 0.15.

edge_ci_color

Underlay color. NA (default) uses main edge color.

edge_ci_style

Line type for underlay: 1=solid, 2=dashed, 3=dotted. Default 2.

edge_ci_arrows

Logical: show arrows on underlay? Default FALSE.

edge_priority

Numeric vector of edge priorities. Higher values render on top. Useful for ensuring significant edges appear above non-significant ones.

edge_label_style

Preset style: "none", "estimate", "full", "range", "stars".

edge_label_template

Template with placeholders: {est}, {range}, {low}, {up}, {p}, {p_diff}, {stars}. Overrides edge_label_style if provided.

edge_label_digits

Decimal places for estimates. Default 2.

edge_label_oneline

Logical: single line format? Default TRUE.

edge_label_ci_format

CI format: "bracket" for [low, up] or "dash" for low-up.

edge_label_leading_zero

Logical: show leading zero for values < 1? Default TRUE. Set to FALSE to display ".5" instead of "0.5".

edge_ci_lower

Numeric vector of lower CI bounds for labels.

edge_ci_upper

Numeric vector of upper CI bounds for labels.

edge_label_p

Numeric vector of p-values for edges.

edge_label_p_diff

Probability-of-difference values for the {p_diff} template placeholder: a per-edge numeric vector, or a full node-by-node matrix, which is indexed at each plotted edge and so stays aligned when minimum or threshold remove edges. A matrix with dimnames is aligned to the plot's node names, so it may be supplied in any node order.

edge_label_p_digits

Decimal places for p-values. Default 3.

edge_label_p_prefix

Prefix for p-values. Default "p=".

edge_label_stars

Stars for labels: character vector, TRUE (compute from p), or numeric (treated as p-values).

weight_digits

Number of decimal places to which the weights of a matrix input are rounded before plotting, so edges that round to zero are removed. Default 2. NULL disables rounding.

threshold

Minimum absolute weight to display.

minimum

Alias for threshold (qgraph compatibility). Uses max of threshold and minimum.

maximum

Maximum weight for scaling. NULL for auto.

positive_color

Deprecated. Use edge_positive_color instead.

negative_color

Deprecated. Use edge_negative_color instead.

edge_duplicates

How to handle duplicate edges in undirected networks. NULL (default) = stop with error listing duplicates. Options: "sum", "mean", "first", "max", "min", or a custom aggregation function.

title

Plot title.

title_size

Title font size.

margins

Margins as c(bottom, left, top, right).

background

Background color.

rescale

Logical: rescale layout to -1 to 1 range?

layout_scale

Scale factor for layout. >1 expands (spreads nodes apart), <1 contracts (brings nodes closer). Use "auto" to automatically scale based on node count (compact for small networks, expanded for large). Default 1.

layout_margin

Margin around the layout as fraction of range. Default 0.15. Set to 0 for no extra margin (tighter fit). Affects white space around nodes.

aspect

Logical: maintain aspect ratio?

use_pch

Logical: use points() for simple circles (faster). Default FALSE.

usePCH

Deprecated. Use use_pch instead.

scaling

Scaling mode: "default" for qgraph-matched scaling where node_size=6 looks similar to qgraph vsize=6, or "legacy" to preserve pre-v2.0 behavior.

align_panels

Logical. If TRUE, forces a uniform symmetric plot box (c(-layout_scale, layout_scale) on each axis) so two networks plotted side-by-side in a par(mfrow) grid render at identical absolute scales, for example bootstrap panels or networks with different numbers of nodes. Default FALSE uses bounds computed from the layout, which fill the canvas more tightly. The fixed box is applied only when the layout is rescaled, so align_panels = TRUE has no effect with rescale = FALSE.

legend

Logical: show legend?

legend_position

Position: "topright", "topleft", "bottomright", "bottomleft".

legend_size

Legend text size.

legend_edge_colors

Logical: show positive/negative edge colors in legend?

legend_node_sizes

Logical: show node size scale in legend?

groups

Group assignments for node coloring/legend.

node_names

Alternative names for legend (separate from labels).

tna_styling

Logical or NULL. If TRUE, applies TNA visual defaults (oval layout, TNA color palette, edge labels as estimates, dotted edge starts, etc.) as a base layer. Any explicitly provided argument overrides the TNA default. If FALSE, no TNA styling is applied. If NULL (default), automatically set to TRUE when x is a tna object, FALSE otherwise. Can be used with any input type (matrix, igraph, cograph_network).

psych_styling

Logical or NULL. Undirected counterpart of tna_styling. If TRUE, applies psychometric-network defaults (spring layout, Okabe-Ito palette, no arrows, solid edge lines, and minimum = 0.01) as a base layer. If NULL (default), splot.netobject auto-enables it on correlation-family input (glasso, cor, pcor, ising) and on the undirected constituents of net_mlvar. Explicit user args always win.

predictability

Logical or NULL. Draws a per-node predictability ring (a donut fill) from a predictability column on the network's node table, the way qgraph/bootnet show node predictability. If TRUE, draws it when the column is present; if FALSE, never; if NULL (default), draws it when the object marks it as its default (network$meta$predictability_default, set e.g. by a psychnet glasso network). A caller's own pie_values / donut_fill takes precedence.

i

Group index or name when x is a group_tna object. If NULL (default), plots all groups in a grid. If specified (e.g., i = 1 or i = "Treatment"), plots only that group.

filetype

Output format: "default" (screen), "png", "pdf", "svg", "jpeg", "tiff".

filename

Output filename (without extension).

width

Output width in inches.

height

Output height in inches.

res

Resolution in DPI for raster outputs (PNG, JPEG, TIFF). Default 600.

Value

splot() returns the plotted cograph_network object invisibly. splot.net_bootstrap(), splot.netobject(), splot.boot_glasso(), splot.tna_communities() and splot.cograph_communities() return the cograph_network built by splot(), and splot.net_permutation() returns it or NULL when there is no edge to plot. splot.net_mlvar() and splot.wtna_mixed() return x. All are called for the side effect of plotting.

Details

splot.net_bootstrap() plots a net_bootstrap object from the Nestimate package. It shows the original network, whose weights are taken from $original$weights, with the edges styled by bootstrap significance.

splot.tna_communities() plots the tna model stored in attr(x, "tna") by tna::communities(), with nodes colored by community. The walktrap assignment is used when present, and the first algorithm column of x$assignments otherwise.

splot.cograph_communities() plots the network stored in attr(x, "network") by detect_communities(), with nodes colored by community.

splot.net_mlvar() plots one or all of the temporal, contemporaneous and between-subjects networks of a net_mlvar object from Nestimate::build_mlvar().

splot.netobject() plots a netobject from Nestimate. Networks estimated by a transition-type method ("relative", "frequency", "attention", "co_occurrence", "wtna", "wtna_cooccurrence", "entropy") get tna_styling = TRUE, and other methods, such as correlation and partial correlation networks, get psych_styling = TRUE. When the method is not recorded, directed networks get the TNA styling. Arguments supplied by the caller override these defaults.

splot.boot_glasso() plots the partial-correlation network of a boot_glasso object from Nestimate, with the bootstrap inclusion probability of each edge mapped to its opacity.

splot.wtna_mixed() plots a wtna_mixed object from Nestimate::wtna(..., method = "both"), either as one overlaid network or as two panels.

splot.net_permutation() plots the edge differences of a net_permutation object from Nestimate, with significant differences highlighted. The direction of the network is taken from x$x$directed.

Edge Curve Behavior

Edge curving is controlled by two interacting arguments:

curves: Mode for automatic curving. FALSE = all straight, TRUE (default) = curve only reciprocal edge pairs as an ellipse, "force" = curve all edges inward toward network center.
curvature: Manual curvature amount (0-1 typical). Sets the magnitude of curves. Default 0 uses automatic 0.175 for curved edges. Positive values curve edges; the direction is automatically determined.

For reciprocal edges (A->B and B->A both exist), the edges curve in opposite directions to form a visual ellipse, making bidirectional relationships clear.

Weight Scaling Modes (edge_scale_mode)

Controls how edge weights are mapped to visual widths:

"linear" (default): Width proportional to weight. Best when weights are similar in magnitude.
"log": Logarithmic scaling. Best when weights span multiple orders of magnitude (e.g., 0.01 to 100).
"sqrt": Square root scaling. Moderate compression, good for moderately skewed distributions.
"rank": Rank-based scaling. Ignores actual values; uses relative ordering. All edges get equal visual spacing regardless of weight distribution.

Donut vs Pie vs Double Donut

Three ways to show additional data on nodes:

Donut (donut_fill): Single ring showing a proportion (0-1). Ideal for completion rates, probabilities, or any single metric per node. Use donut_color for fill color and donut_bg_color for unfilled portion.
Pie (pie_values): Multiple colored segments showing category breakdown. Ideal for composition data. Values are normalized to sum to 1. Use pie_colors for segment colors.
Double donut (donut2_values): Two concentric rings for comparing two metrics per node. Outer ring uses donut_fill/donut_color, inner ring uses donut2_values/donut2_colors.

CI Underlay System

Confidence interval underlays draw a wider, semi-transparent edge behind the main edge to visualize uncertainty:

edge_ci: Vector of CI widths (0-1 scale). Larger = more uncertainty.
edge_ci_scale: Multiplier for underlay width relative to main edge. Default 2 means underlay is twice as wide as main edge at CI=1.
edge_ci_alpha: Transparency of underlay (0-1). Default 0.15.
edge_ci_style: Line type: 1=solid, 2=dashed (default), 3=dotted.

Edge Label Templates

For statistical output, use templates to format complex labels:

edge_label_template: Template string with placeholders: {est} for estimate/weight, {low}/{up} for CI bounds, {range} for formatted range, {p} for p-value, {p_diff} for the probability of the difference (Bayesian comparisons), {stars} for significance stars.
edge_label_style: Preset styles: "estimate" (weight only), "full" (estimate + CI), "range" (CI only), "stars" (significance).

Producer-Supplied splot Metadata

Packages that create cograph_network-compatible objects can attach a small plotting contract at x$meta$splot. This lets producer packages such as Nestimate, lagdynamics, or other modeling packages describe their preferred cograph rendering without adding a new cograph-side class branch for every object type.

The contract is optional. Objects without meta$splot follow the normal splot() path and all existing class-specific dispatch remains in place. When present, the supported fields are:

renderer: Character scalar naming the cograph renderer to use. "network" (also "splot", "default", or "base") means the object follows the normal splot() path, including any class-specific method, with the metadata defaults applied. Other values are resolved through a cograph-maintained whitelist of existing renderers, for example "difference", "bootstrap", "permutation", "stability", "mlvar", "netobject", "netobject_group", "netobject_ml", "boot_glasso", and "wtna_mixed". Arbitrary function names are never evaluated.
weight: Optional character scalar naming the default edge weight to render. If it names an edge column, that column is copied to edges$weight for the plot (the producer's edge set is kept, and the weights matrix is rebuilt to match). If it names a matrix stored on the object, that matrix becomes the rendered network: it is copied to weights and the drawn edge set is rebuilt from its nonzero cells (aligned to the object's node order via dimnames when present). This is useful when the analytical object stores several edge quantities (for example counts, probabilities, residuals, effects) but has one preferred plot view. When the name matches both an edge column and a stored matrix, the matrix form wins.
defaults: Named list of splot() or renderer arguments. These are defaults only: any argument explicitly supplied by the user wins. Defaults can include regular splot() arguments such as layout, node_fill, edge_labels, weight_digits, or renderer-specific arguments such as display for bootstrap renderers.

The precedence rule is always:


user arguments > x$meta$splot$defaults > cograph defaults

Example producer-side metadata:


x$meta$splot <- list(
  renderer = "network",
  weight = "adj_res",
  defaults = list(
    node_fill = "white",
    edge_labels = TRUE,
    weight_digits = 1
  )
)

Examples

splot(regulation_net)