cograph: Modern Network Visualization

Description

A modern, extensible network visualization package that provides high-quality static and interactive network plots. cograph accepts adjacency matrices, edge lists, or igraph objects and offers customizable layouts, node shapes, edge styles, and themes.

Main Functions

• cograph: Main entry point for creating network visualizations

• sn_layout: Apply layout algorithms

• sn_nodes: Customize node aesthetics

• sn_edges: Customize edge aesthetics

• sn_theme: Apply visual themes

• sn_render: Render to device

• sn_ggplot: Convert to ggplot2 object

Layouts

cograph provides several built-in layouts:

• circle: Nodes arranged in a circle

• spring: Fruchterman-Reingold force-directed layout

• groups: Group-based circular layout

• custom: User-provided coordinates

Themes

Built-in themes include:

• classic: Traditional network visualization style

• colorblind: Accessible color scheme

• gray: Grayscale theme

• dark: Dark background theme

• minimal: Clean, minimal style

Author(s)

Maintainer: Sonsoles López-Pernas sonsoles.lopez@uef.fi

Authors:

• Mohammed Saqr

• Santtu Tikka

See Also

Useful links:

• https://sonsoles.me/cograph/

• Report bugs at https://github.com/sonsoleslp/cograph/issues

cograph Scaling Constants

Description

Central location for all scaling factors used in splot() and soplot(). These constants are calibrated to produce similar visual output to qgraph when using equivalent parameter values.

Usage

COGRAPH_SCALE

Format

A list with the following elements:

node_factor

Scale factor applied to node_size parameter

node_default

Default node size when not specified

label_default

Default label size (cex multiplier)

label_coupled

Whether label size is coupled to node size

edge_base

Base edge width

edge_scale

Edge width scale factor

edge_default

Default edge width

arrow_factor

Scale factor for arrow sizes

arrow_default

Default arrow size

Details

The default scaling mode uses values calibrated to match qgraph visual appearance:

• node_size = 6 in cograph should look similar to vsize = 6 in qgraph

• label_size = 1 uses cex-style multiplier (independent of node size)

• arrow_size = 1 produces consistent arrows between splot and soplot

Legacy mode preserves the original cograph v1.x behavior where:

• Node sizes used a 0.04 scale factor

• Label sizes were coupled to node size (vsize * 8)

• Arrow sizes differed between splot (0.03) and soplot (0.015)

Legacy Scaling Constants (Pre-v2.0 Behavior)

Description

Scaling constants that preserve the original cograph v1.x behavior. Use scaling = "legacy" to enable these values.

Usage

COGRAPH_SCALE_LEGACY

Format

A list with the same structure as COGRAPH_SCALE

CographLayout R6 Class

Description

Class for managing layout algorithms and computing node positions.

Methods

Public methods

• CographLayout$new()

• CographLayout$compute()

• CographLayout$normalize_coords()

• CographLayout$get_type()

• CographLayout$get_params()

• CographLayout$print()

• CographLayout$clone()

Method new()

Create a new CographLayout object.

Usage

CographLayout$new(type = "circle", ...)

Arguments

Returns

A new CographLayout object.

Method compute()

Compute layout coordinates for a network.

Usage

CographLayout$compute(network, ...)

Arguments

Returns

Data frame with x, y coordinates.

Method normalize_coords()

Normalize coordinates to 0-1 range with padding.

Usage

CographLayout$normalize_coords(coords, padding = 0.1)

Arguments

Returns

Normalized coordinates.

Method get_type()

Get layout type.

Usage

CographLayout$get_type()

Returns

Character string.

Method get_params()

Get layout parameters.

Usage

CographLayout$get_params()

Returns

List of parameters.

Method print()

Print layout summary.

Usage

CographLayout$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

CographLayout$clone(deep = FALSE)

Arguments

Examples

# Create a circular layout
layout <- CographLayout$new("circle")

# Apply to network
adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- CographNetwork$new(adj)
coords <- layout$compute(net)

CographNetwork R6 Class

Description

Core class representing a network for visualization. Stores nodes, edges, layout coordinates, and aesthetic mappings.

Active bindings

Methods

Public methods

• CographNetwork$new()

• CographNetwork$clone_network()

• CographNetwork$set_nodes()

• CographNetwork$set_edges()

• CographNetwork$set_directed()

• CographNetwork$set_weights()

• CographNetwork$set_layout_coords()

• CographNetwork$set_node_aes()

• CographNetwork$set_edge_aes()

• CographNetwork$set_theme()

• CographNetwork$get_nodes()

• CographNetwork$get_edges()

• CographNetwork$get_layout()

• CographNetwork$get_node_aes()

• CographNetwork$get_edge_aes()

• CographNetwork$get_theme()

• CographNetwork$set_layout_info()

• CographNetwork$get_layout_info()

• CographNetwork$set_plot_params()

• CographNetwork$get_plot_params()

• CographNetwork$print()

• CographNetwork$clone()

Method new()

Create a new CographNetwork object.

Usage

CographNetwork$new(input = NULL, directed = NULL, node_labels = NULL)

Arguments

Returns

A new CographNetwork object.

Method clone_network()

Clone the network with optional modifications.

Usage

CographNetwork$clone_network()

Returns

A new CographNetwork object.

Method set_nodes()

Set nodes data frame.

Usage

CographNetwork$set_nodes(nodes)

Arguments

Method set_edges()

Set edges data frame.

Usage

CographNetwork$set_edges(edges)

Arguments

Method set_directed()

Set directed flag.

Usage

CographNetwork$set_directed(directed)

Arguments

Method set_weights()

Set edge weights.

Usage

CographNetwork$set_weights(weights)

Arguments

Method set_layout_coords()

Set layout coordinates.

Usage

CographNetwork$set_layout_coords(coords)

Arguments

Method set_node_aes()

Set node aesthetics.

Usage

CographNetwork$set_node_aes(aes)

Arguments

Method set_edge_aes()

Set edge aesthetics.

Usage

CographNetwork$set_edge_aes(aes)

Arguments

Method set_theme()

Set theme.

Usage

CographNetwork$set_theme(theme)

Arguments

Method get_nodes()

Get nodes data frame.

Usage

CographNetwork$get_nodes()

Returns

Data frame with node information.

Method get_edges()

Get edges data frame.

Usage

CographNetwork$get_edges()

Returns

Data frame with edge information.

Method get_layout()

Get layout coordinates.

Usage

CographNetwork$get_layout()

Returns

Data frame with x, y coordinates.

Method get_node_aes()

Get node aesthetics.

Usage

CographNetwork$get_node_aes()

Returns

List of node aesthetic parameters.

Method get_edge_aes()

Get edge aesthetics.

Usage

CographNetwork$get_edge_aes()

Returns

List of edge aesthetic parameters.

Method get_theme()

Get theme.

Usage

CographNetwork$get_theme()

Returns

CographTheme object.

Method set_layout_info()

Set layout info.

Usage

CographNetwork$set_layout_info(info)

Arguments

Method get_layout_info()

Get layout info.

Usage

CographNetwork$get_layout_info()

Returns

List with layout information.

Method set_plot_params()

Set plot parameters.

Usage

CographNetwork$set_plot_params(params)

Arguments

Method get_plot_params()

Get plot parameters.

Usage

CographNetwork$get_plot_params()

Returns

List of plot parameters.

Method print()

Print network summary.

Usage

CographNetwork$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

CographNetwork$clone(deep = FALSE)

Arguments

Examples

# Create network from adjacency matrix
adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- CographNetwork$new(adj)

# Access properties
net$n_nodes
net$n_edges
net$is_directed

CographTheme R6 Class

Description

Class for managing visual themes for network plots.

Active bindings

Methods

Public methods

• CographTheme$new()

• CographTheme$get()

• CographTheme$set()

• CographTheme$get_all()

• CographTheme$merge()

• CographTheme$clone_theme()

• CographTheme$print()

• CographTheme$clone()

Method new()

Create a new CographTheme object.

Usage

CographTheme$new(
  name = "custom",
  background = "white",
  node_fill = "#4A90D9",
  node_border = "#2C5AA0",
  node_border_width = 1,
  edge_color = "gray50",
  edge_positive_color = "#2E7D32",
  edge_negative_color = "#C62828",
  edge_width = 1,
  label_color = "black",
  label_size = 10,
  title_color = "black",
  title_size = 14,
  legend_background = "white"
)

Arguments

Returns

A new CographTheme object.

Method get()

Get a theme parameter.

Usage

CographTheme$get(name)

Arguments

Returns

Parameter value.

Method set()

Set a theme parameter.

Usage

CographTheme$set(name, value)

Arguments

Method get_all()

Get all theme parameters.

Usage

CographTheme$get_all()

Returns

List of parameters.

Method merge()

Merge with another theme.

Usage

CographTheme$merge(other)

Arguments

Returns

A new merged CographTheme.

Method clone_theme()

Clone the theme.

Usage

CographTheme$clone_theme()

Returns

A new CographTheme.

Method print()

Print theme summary.

Usage

CographTheme$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

CographTheme$clone(deep = FALSE)

Arguments

Examples

# Create a custom theme
theme <- CographTheme$new(
  background = "white",
  node_fill = "steelblue",
  edge_color = "gray60"
)

qgraph Scaling Constants (Exact Values)

Description

Scaling constants that exactly replicate qgraph's visual formulas. Used by splot() for qgraph-compatible network visualization.

Usage

QGRAPH_SCALE

Format

A list with the following elements:

vsize_base

Base multiplier in vsize formula: 8

vsize_decay

Decay constant in vsize formula: 80

vsize_min

Minimum added to vsize: 1

vsize_factor

Scale factor to convert vsize to user coordinates: 0.015

esize_base

Base multiplier in esize formula: 15

esize_decay

Decay constant in esize formula: 90

esize_min

Minimum added to esize: 1

esize_unweighted

Default edge width for unweighted networks: 2

cent2edge_divisor

Divisor in cent2edge formula: 17.5

cent2edge_reference

Reference value in cent2edge: 2.16

cent2edge_plot_ref

Plot reference size: 7

curve_ref_diagonal

Diagonal reference for curve normalization: sqrt(98)

arrow_factor

Arrow size scale factor: 0.04

Edge Aesthetics

Description

Functions for setting edge aesthetic properties.

Node Aesthetics

Description

Functions for setting node aesthetic properties.

Aesthetic Scale Functions

Description

Functions for creating aesthetic scales.

Aggregate Duplicate Edges

Description

Combines duplicate edges by aggregating their weights using a specified function (sum, mean, max, min, or first).

Usage

aggregate_duplicate_edges(edges, method = "mean")

Arguments

Details

Aggregation Methods

sum

Total weight of all duplicate edges. Useful for frequency counts or when edges represent additive quantities (e.g., number of emails).

mean

Average weight. Useful for averaging multiple measurements or when duplicates represent repeated observations.

max

Maximum weight. Useful for finding the strongest connection or most recent value.

min

Minimum weight. Useful for the most conservative estimate or earliest value.

first

Keep first occurrence. Useful for preserving original order or when duplicates are erroneous.

The output edge list uses canonical node ordering (lower index first for undirected networks), ensuring consistent from/to assignment.

Value

A deduplicated data frame with the same columns as the input, where each node pair appears only once with its aggregated weight.

See Also

detect_duplicate_edges for identifying duplicates before aggregation

Calculate Arrow Base Midpoint

Description

Returns the midpoint between the arrow wings (where the curve should end). This is used to connect the edge line to the back of the arrow head.

Usage

arrow_base_midpoint(x, y, angle, size, arrow_angle = pi/6)

Arguments

Value

List with x, y coordinates of the arrow base midpoint.

Calculate Arrow Head Points

Description

Returns the vertices for an arrow head polygon without drawing.

Usage

arrow_head_points(x, y, angle, size, arrow_angle = pi/6)

Arguments

Value

List with x, y vectors and midpoint coordinates.

Calculate Arrow Head Points

Description

Calculate Arrow Head Points

Usage

arrow_points(x, y, angle, size, width = 0.5, x_scale = 1, y_scale = 1)

Arguments

Value

List with arrow polygon coordinates and midpoint for line connection.

Calculate Arrow Radius

Description

Returns the distance from arrow tip to base midpoint. This is how far back from the tip the arrow extends.

Usage

arrow_radius(size, arrow_angle = pi/6)

Arguments

Value

The arrow radius (distance from tip to base).

Convert to Cograph Network

Description

Creates a lightweight cograph_network object from various network inputs. The resulting object is a named list with all data accessible via $.

Usage

as_cograph(x, directed = NULL, ...)

Arguments

Details

The cograph_network format is designed to be:

• Simple: All data accessible via net$from, net$to, net$weight, etc.

• Modern: Uses named list elements instead of attributes for clean $ access

• Compatible: Works seamlessly with splot() and other cograph functions

Use getter functions for programmatic access: get_nodes, get_edges, get_labels

Use setter functions to modify: set_nodes, set_edges, set_layout

Value

A cograph_network object: a named list with components:

from

Integer vector of source node indices

to

Integer vector of target node indices

weight

Numeric vector of edge weights

nodes

Data frame with id, label, (x, y if layout applied)

directed

Logical indicating if network is directed

n_nodes

Integer count of nodes

n_edges

Integer count of edges

labels

Character vector of node labels

source

Character indicating input type

layout

Layout coordinates (NULL until computed)

layout_info

Layout algorithm info (NULL until computed)

See Also

get_nodes to extract the nodes data frame, get_edges to extract edges as a data frame, n_nodes and n_edges for counts, is_directed to check directedness, splot for plotting

Examples

# From adjacency matrix
mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)

# Direct $ access to all data
net$from       # edge sources
net$to         # edge targets
net$weight     # edge weights
net$nodes      # nodes data frame
net$directed   # TRUE/FALSE
net$n_nodes    # 3
net$n_edges    # 3

# Getter functions (recommended for programmatic use)
get_nodes(net)   # nodes data frame
get_edges(net)   # edges data frame (from, to, weight)
get_labels(net)  # character vector of labels
n_nodes(net)     # 3
n_edges(net)     # 3
is_directed(net) # FALSE (symmetric matrix)

# Setter functions
net <- set_nodes(net, data.frame(id = 1:3, label = c("A", "B", "C")))
net <- set_edges(net, data.frame(from = c(1,2), to = c(2,3), weight = c(0.5, 0.8)))
net <- set_layout(net, data.frame(x = c(0, 1, 0.5), y = c(0, 0, 1)))

# Plot it
splot(net)

# From igraph (if installed)
if (requireNamespace("igraph", quietly = TRUE)) {
  library(igraph)
  g <- make_ring(10)
  net <- as_cograph(g)
  splot(net)
}

Create cograph_network S3 class wrapper

Description

Create cograph_network S3 class wrapper

Usage

as_cograph_network(network)

Arguments

Value

Object with cograph_network class.

Aspect-Corrected atan2

Description

Calculate angle accounting for aspect ratio differences.

Usage

atan2_usr(dy, dx)

Arguments

Value

Angle in radians.

Calculate Bezier Curve Points

Description

Calculate points along a quadratic Bezier curve.

Usage

bezier_points(x0, y0, x1, y1, x2, y2, n = 50)

Arguments

Value

Data frame with x, y coordinates.

Generate Brain Vertices

Description

Generate Brain Vertices

Usage

brain_vertices(x, y, r, n = 80)

Arguments

Value

List with x, y vectors of vertices.

Build Edge Labels from Template

Description

Generates edge labels for all edges using template formatting.

Usage

build_edge_labels_from_template(
  template = NULL,
  style = "none",
  weights = NULL,
  ci_lower = NULL,
  ci_upper = NULL,
  p_values = NULL,
  stars = NULL,
  digits = 2,
  p_digits = 3,
  p_prefix = "p=",
  ci_format = "bracket",
  oneline = TRUE,
  n
)

Arguments

Value

Character vector of formatted labels.

Calculate Point on Node Boundary

Description

Given a node center, size, and angle, calculates the point on the node boundary. Works with various shapes.

Usage

cent_to_edge(x, y, angle, cex, cex2 = NULL, shape = "circle")

Arguments

Value

List with x, y coordinates on boundary.

Generate Circle Vertices

Description

Generate Circle Vertices

Usage

circle_vertices(x, y, r, n = 50)

Arguments

Value

List with x, y vectors of vertices.

Generate Cloud Vertices

Description

Generate Cloud Vertices

Usage

cloud_vertices(x, y, r, n = 100)

Arguments

Value

List with x, y vectors of vertices.

Create a Network Visualization

Description

The main entry point for cograph. Accepts adjacency matrices, edge lists, igraph, statnet network, qgraph, or tna objects and creates a visualization-ready network object.

Usage

cograph(
  input,
  layout = "spring",
  directed = NULL,
  node_labels = NULL,
  seed = 42,
  ...
)

Arguments

Value

A cograph_network object that can be further customized and rendered.

See Also

splot for base R graphics rendering, soplot for grid graphics rendering, sn_nodes for node customization, sn_edges for edge customization, sn_layout for changing layouts, sn_theme for visual themes, sn_palette for color palettes, from_qgraph and from_tna for converting external objects

Examples

# From adjacency matrix
adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
cograph(adj)

# From edge list
edges <- data.frame(from = c(1, 1, 2), to = c(2, 3, 3))
cograph(edges)

# With customization (pipe-friendly workflow)
adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
cograph(adj, layout = "circle") |>
  sn_nodes(fill = "steelblue") |>
  sn_edges(color = "gray50") |>
  splot()

# Weighted network with automatic styling
w_adj <- matrix(c(0, 0.5, -0.3, 0.5, 0, 0.4, -0.3, 0.4, 0), nrow = 3)
cograph(w_adj) |>
  sn_edges(color = "weight", width = "weight") |>
  splot()

# With igraph (if installed)
if (requireNamespace("igraph", quietly = TRUE)) {
  library(igraph)
  g <- make_ring(10)
  cograph(g) |> splot()
}

Main Entry Point

Description

The primary function for creating network visualizations.

Compute Adaptive Base Edge Size

Description

Calculates the maximum edge width that decreases with more nodes. Inspired by qgraph but scaled for line widths (not pixels).

Usage

compute_adaptive_esize(n_nodes, directed = FALSE)

Arguments

Details

The formula produces reasonable line widths:

• 3 nodes: ~5

• 10 nodes: ~4.5

• 50 nodes: ~3

• 100 nodes: ~2

• 200 nodes: ~1.2

For directed networks, the size is reduced by 30% (minimum 1).

Value

Numeric maximum edge width (suitable for lwd parameter).

Compute Circular Layout

Description

Positions nodes along arcs of a circle, with each group occupying one arc. Groups are separated by gaps controlled by angle_spacing.

Usage

compute_circular_layout(
  node_list,
  lab,
  group_indices,
  n_groups,
  angle_spacing = 0.15
)

Arguments

Value

List with x and y position vectors.

Compute Connectivity-Based Jitter (Horizontal Layout)

Description

For horizontal layouts (left/right columns). Nodes with more cross-group connections are jittered horizontally toward center.

Usage

compute_connectivity_jitter_horizontal(
  weights,
  g1_idx,
  g2_idx,
  amount = 0.8,
  side = "group1"
)

Arguments

Value

Numeric vector of x-offsets for each node.

Compute Connectivity-Based Jitter (Vertical Layout)

Description

For vertical layouts (top/bottom rows). Nodes with more cross-group connections are jittered vertically toward center.

Usage

compute_connectivity_jitter_vertical(
  weights,
  g1_idx,
  g2_idx,
  amount = 0.8,
  side = "group1"
)

Arguments

Value

Numeric vector of y-offsets for each node.

Wrapper for Gephi FR Layout (for layout registry)

Description

Wrapper for Gephi FR Layout (for layout registry)

Usage

compute_layout_gephi_fr(
  network,
  area = 10000,
  gravity = 10,
  speed = 1,
  niter = 100,
  ...
)

Arguments

Value

Data frame with x, y coordinates.

Compute Polygon Layout

Description

Positions nodes along edges of a regular n-sided polygon. Each group is placed along one edge. Edges are offset outward from vertices to create empty angles at corners.

Usage

compute_polygon_layout(
  node_list,
  lab,
  group_indices,
  n_sides,
  angle_spacing = 0.15
)

Arguments

Value

List with x and y position vectors.

Create Edge Data Frame

Description

Create Edge Data Frame

Usage

create_edges_df(from, to, weight = NULL, directed = FALSE)

Arguments

Value

Data frame with edge information.

Create Grid Grob Tree

Description

Create a complete grid grob tree for the network (without drawing).

Usage

create_grid_grob(network, title = NULL)

Arguments

Value

A grid gTree object.

Create Node Data Frame

Description

Create Node Data Frame

Usage

create_nodes_df(n, labels = NULL, names = NULL)

Arguments

Value

Data frame with node information.

Generate Cross/Plus Vertices

Description

Generate Cross/Plus Vertices

Usage

cross_vertices(x, y, r, thickness = 0.3)

Arguments

Value

List with x, y vectors of vertices.

Calculate Control Point for Curved Edge

Description

Calculate Control Point for Curved Edge

Usage

curve_control_point(x1, y1, x2, y2, curvature, pivot = 0.5, shape = 0)

Arguments

Value

List with x, y coordinates of control point.

Detect Duplicate Edges in Undirected Network

Description

Identifies edges that appear multiple times between the same pair of nodes. For undirected networks, edges A->B and B->A are considered duplicates. For directed networks, only identical from->to pairs are duplicates.

Usage

detect_duplicate_edges(edges)

Arguments

Details

This function is useful for cleaning network data before visualization. Duplicate edges can arise from:

• Data collection errors (same edge recorded twice)

• Combining multiple data sources

• Converting from formats that allow multi-edges

• Edge lists that include both A->B and B->A for undirected networks

The function creates canonical keys by sorting node pairs (lower index first), so edges 1->2 and 2->1 map to the same key "1-2" in undirected mode.

Value

A list with two components:

has_duplicates

Logical indicating whether any duplicates were found.

info

A list of duplicate details, where each element contains: nodes (the node pair), count (number of edges), and weights (vector of weights if available).

See Also

aggregate_duplicate_edges for combining duplicates into single edges

Generate Diamond Vertices

Description

Generate Diamond Vertices

Usage

diamond_vertices(x, y, r)

Arguments

Value

List with x, y vectors of vertices.

Draw Arrow Head

Description

Draws a filled triangular arrow head at the specified position.

Usage

draw_arrow_base(
  x,
  y,
  angle,
  size,
  arrow_angle = pi/6,
  col = "black",
  border = NULL,
  lwd = 1
)

Arguments

Draw Brain Node

Description

Simplified brain outline using overlapping curves.

Usage

draw_brain(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Chip Node

Description

Square with pins extending from all edges (processor/IC chip).

Usage

draw_chip(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  pins_per_side = 3,
  ...
)

Arguments

Draw Chip Node (Base R)

Description

Square with pins extending from all edges.

Usage

draw_chip_node_base(
  x,
  y,
  size,
  col,
  border.col,
  border.width,
  pins_per_side = 3
)

Draw Circle Node

Description

Draw Circle Node

Usage

draw_circle(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Circle Arrow (Dot)

Description

Draws a circular dot at the arrow position (alternative to triangular arrow).

Usage

draw_circle_arrow_base(x, y, size, col = "black", border = NULL)

Arguments

Draw Cloud Node

Description

Cloud shape (cloud computing).

Usage

draw_cloud(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Cross/Plus Node

Description

Draw Cross/Plus Node

Usage

draw_cross(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  thickness = 0.3,
  ...
)

Draw Curve with Optional Start Segment

Description

Draws a curve (as lines) with an optional differently-styled start segment. Used internally to support dashed/dotted start segments for edge direction clarity.

Usage

draw_curve_with_start_segment(
  x,
  y,
  col,
  lwd,
  lty,
  start_lty = 1,
  start_fraction = 0
)

Arguments

Draw Curved Arrow Head

Description

Draws an arrow head at the end of a curved edge, with angle following the curve direction.

Usage

draw_curved_arrow_base(
  spline_x,
  spline_y,
  size,
  arrow_angle = pi/6,
  col = "black",
  border = NULL
)

Arguments

Draw Curved Edge

Description

Draw Curved Edge

Usage

draw_curved_edge(
  x1,
  y1,
  x2,
  y2,
  curvature,
  color,
  width,
  lty,
  show_arrow,
  arrow_size,
  bidirectional = FALSE,
  curve_shape = 0,
  curve_pivot = 0.5,
  x_scale = 1,
  y_scale = 1
)

Draw Curved Edge with xspline (qgraph-style)

Description

Renders a curved edge using xspline() with optional arrow. Uses qgraph-style curve calculation for smooth, natural-looking curves. Curve direction is normalized so positive curve always bends the same visual direction regardless of edge orientation.

Usage

draw_curved_edge_base(
  x1,
  y1,
  x2,
  y2,
  curve = 0.2,
  curvePivot = 0.5,
  col = "gray50",
  lwd = 1,
  lty = 1,
  arrow = TRUE,
  asize = 0.02,
  bidirectional = FALSE,
  start_lty = 1,
  start_fraction = 0,
  arrow_angle = pi/6
)

Arguments

Draw Database Node

Description

Cylinder shape (data storage).

Usage

draw_database(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Database Node (Base R)

Description

Cylinder shape.

Usage

draw_database_node_base(x, y, size, col, border.col, border.width)

Draw Diamond Node

Description

Draw Diamond Node

Usage

draw_diamond(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Donut Node

Description

Draw a donut chart node showing a fill proportion (0-1) as an arc. The fill starts from 12 o'clock (top) and fills clockwise.

Usage

draw_donut(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  values = NULL,
  colors = NULL,
  inner_ratio = 0.5,
  bg_color = "gray90",
  show_value = TRUE,
  value_size = 8,
  value_color = "black",
  value_fontface = "bold",
  value_fontfamily = "sans",
  value_digits = 2,
  value_prefix = "",
  value_suffix = "",
  value_format = NULL,
  donut_border_width = NULL,
  ...
)

Arguments

Draw Donut Chart Node

Description

Renders a node as a donut chart with an inner hole. The donut shows a fill proportion (0-1) as an arc starting from 12 o'clock.

Usage

draw_donut_node_base(
  x,
  y,
  size,
  values,
  colors = NULL,
  default_color = NULL,
  inner_ratio = 0.5,
  bg_color = "gray90",
  center_color = "white",
  border.col = "black",
  border.width = 1,
  donut_border.width = NULL,
  outer_border.col = NULL,
  border.lty = 1,
  show_value = TRUE,
  value_cex = 0.8,
  value_col = "black",
  value_fontface = "bold",
  value_fontfamily = "sans",
  value_digits = 2,
  value_prefix = "",
  value_suffix = ""
)

Arguments

Draw Donut with Inner Pie Node

Description

Draw a node with an outer donut ring showing a proportion and an inner pie chart with multiple segments.

Usage

draw_donut_pie(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  donut_value = NULL,
  pie_values = NULL,
  pie_colors = NULL,
  inner_ratio = 0.5,
  bg_color = "gray90",
  pie_border_width = NULL,
  donut_border_width = NULL,
  ...
)

Arguments

Draw Donut with Inner Pie

Description

Renders a node with outer donut ring and inner pie chart.

Usage

draw_donut_pie_node_base(
  x,
  y,
  size,
  donut_value = 1,
  donut_color = "#4A90D9",
  pie_values = NULL,
  pie_colors = NULL,
  pie_default_color = NULL,
  inner_ratio = 0.5,
  bg_color = "gray90",
  border.col = "black",
  border.width = 1,
  pie_border.width = NULL,
  donut_border.width = NULL
)

Arguments

Draw Double Donut with Inner Pie Node

Description

Draw a node with two concentric donut rings and an optional inner pie chart. From outside to inside: outer donut ring, inner donut ring, center pie.

Usage

draw_double_donut_pie(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  donut_values = NULL,
  donut_colors = NULL,
  donut2_values = NULL,
  donut2_colors = NULL,
  pie_values = NULL,
  pie_colors = NULL,
  outer_inner_ratio = 0.7,
  inner_inner_ratio = 0.4,
  bg_color = "gray90",
  pie_border_width = NULL,
  donut_border_width = NULL,
  ...
)

Arguments

Draw Double Donut with Inner Pie

Description

Renders a node with two concentric donut rings and an optional inner pie chart. From outside to inside: outer donut ring, inner donut ring, center pie.

Usage

draw_double_donut_pie_node_base(
  x,
  y,
  size,
  donut_values = NULL,
  donut_colors = NULL,
  donut2_values = NULL,
  donut2_colors = NULL,
  pie_values = NULL,
  pie_colors = NULL,
  pie_default_color = NULL,
  outer_inner_ratio = 0.7,
  inner_inner_ratio = 0.4,
  bg_color = "gray90",
  border.col = "black",
  border.width = 1,
  pie_border.width = NULL,
  donut_border.width = NULL
)

Arguments

Draw Edge Label

Description

Renders a label on an edge.

Usage

draw_edge_label_base(
  x,
  y,
  label,
  cex = 0.8,
  col = "gray30",
  bg = "white",
  font = 1,
  shadow = FALSE,
  shadow_color = "gray40",
  shadow_offset = 0.5,
  shadow_alpha = 0.5
)

Arguments

Draw Ellipse Node

Description

Draw Ellipse Node

Usage

draw_ellipse(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  aspect = 0.6,
  ...
)

Draw Gear Node

Description

Gear/cog shape (processing/automation).

Usage

draw_gear(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  n_teeth = 8,
  ...
)

Arguments

Draw Heart Node

Description

Draw Heart Node

Usage

draw_heart(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Hexagon Node

Description

Draw Hexagon Node

Usage

draw_hexagon(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Network Node

Description

Interconnected nodes pattern (mini network inside).

Usage

draw_network(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Network Node (Base R)

Description

Interconnected nodes pattern.

Usage

draw_network_node_base(x, y, size, col, border.col, border.width)

Draw Neural Node

Description

Circle with small connection circles around the perimeter (neuron-like).

Usage

draw_neural(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  n_connections = 6,
  ...
)

Arguments

Draw Neural Node (Base R)

Description

Circle with small connection circles around perimeter.

Usage

draw_neural_node_base(
  x,
  y,
  size,
  col,
  border.col,
  border.width,
  n_connections = 6
)

Draw a Single Node

Description

Renders a node at the specified position with given aesthetics.

Usage

draw_node_base(
  x,
  y,
  size,
  size2 = NULL,
  shape = "circle",
  col = "#4A90D9",
  border.col = "#2C5AA0",
  border.width = 1,
  ...
)

Arguments

Draw Node Label

Description

Renders a text label at or near a node.

Usage

draw_node_label_base(
  x,
  y,
  label,
  cex = 1,
  col = "black",
  font = 1,
  family = "sans",
  hjust = 0.5,
  vjust = 0.5,
  srt = 0,
  pos = NULL,
  offset = 0.5
)

Arguments

Draw Open Arrow Head

Description

Draws an open (unfilled) V-shaped arrow head.

Usage

draw_open_arrow_base(
  x,
  y,
  angle,
  size,
  arrow_angle = pi/6,
  col = "black",
  lwd = 1
)

Arguments

Draw Pentagon Node

Description

Draw Pentagon Node

Usage

draw_pentagon(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Pie Node

Description

Draw a pie chart node with multiple segments.

Usage

draw_pie(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  values = NULL,
  colors = NULL,
  pie_border_width = NULL,
  default_color = NULL,
  ...
)

Arguments

Draw Pie Chart Node

Description

Renders a node as a pie chart with multiple colored segments. The pie is drawn slightly inside the node boundary to leave room for arrows.

Usage

draw_pie_node_base(
  x,
  y,
  size,
  values,
  colors = NULL,
  default_color = NULL,
  border.col = "black",
  border.width = 1,
  pie_border.width = NULL
)

Arguments

Draw Polygon Donut Node

Description

Draws a donut ring on a polygon shape where segments follow polygon edges. The fill shows a proportion (0-1) as filled segments starting from the top vertex.

Usage

draw_polygon_donut(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  values = NULL,
  colors = NULL,
  inner_ratio = 0.5,
  bg_color = "gray90",
  donut_shape = "square",
  show_value = TRUE,
  value_size = 8,
  value_color = "black",
  value_fontface = "bold",
  value_fontfamily = "sans",
  value_digits = 2,
  value_prefix = "",
  value_suffix = "",
  value_format = NULL,
  donut_border_width = NULL,
  ...
)

Arguments

Draw Polygon Donut Node (Base R)

Description

Renders a donut on a polygon shape where segments follow polygon edges. The donut shows a fill proportion (0-1) as filled segments starting from the top.

Usage

draw_polygon_donut_node_base(
  x,
  y,
  size,
  values,
  colors = NULL,
  default_color = NULL,
  inner_ratio = 0.5,
  bg_color = "gray90",
  center_color = "white",
  donut_shape = "square",
  border.col = "black",
  border.width = 1,
  donut_border.width = NULL,
  outer_border.col = NULL,
  border.lty = 1,
  show_value = TRUE,
  value_cex = 0.8,
  value_col = "black",
  value_fontface = "bold",
  value_fontfamily = "sans",
  value_digits = 2,
  value_prefix = "",
  value_suffix = ""
)

Arguments

Draw Robot Node

Description

Rounded square with antenna and eyes (robot head).

Usage

draw_robot(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Robot Node (Base R)

Description

Rounded square with antenna and eyes.

Usage

draw_robot_node_base(x, y, size, col, border.col, border.width)

Draw Self-Loop

Description

Draw Self-Loop

Usage

draw_self_loop(x, y, node_size, color, width, lty, rotation = pi/2)

Arguments

Draw Self-Loop Edge (qgraph-style)

Description

Renders a self-loop (edge from node to itself) using a teardrop/circular loop shape similar to qgraph.

Usage

draw_self_loop_base(
  x,
  y,
  node_size,
  col = "gray50",
  lwd = 1,
  lty = 1,
  rotation = pi/2,
  arrow = TRUE,
  asize = 0.02,
  arrow_angle = pi/6
)

Arguments

Draw Square Node

Description

Draw Square Node

Usage

draw_square(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Draw Star Node

Description

Draw Star Node

Usage

draw_star(
  x,
  y,
  size,
  fill,
  border_color,
  border_width,
  alpha = 1,
  n_points = 5,
  inner_ratio = 0.4,
  ...
)

Draw Straight Edge

Description

Draw Straight Edge

Usage

draw_straight_edge(
  x1,
  y1,
  x2,
  y2,
  color,
  width,
  lty,
  show_arrow,
  arrow_size,
  bidirectional = FALSE,
  x_scale = 1,
  y_scale = 1
)

Draw Straight Edge

Description

Renders a straight edge between two points with optional arrow.

Usage

draw_straight_edge_base(
  x1,
  y1,
  x2,
  y2,
  col = "gray50",
  lwd = 1,
  lty = 1,
  arrow = TRUE,
  asize = 0.02,
  bidirectional = FALSE,
  start_lty = 1,
  start_fraction = 0,
  arrow_angle = pi/6
)

Arguments

Draw SVG Shape (Grid)

Description

Render an SVG as a node shape using grid graphics.

Usage

draw_svg_shape(
  x,
  y,
  size,
  svg_data,
  fill,
  border_color,
  border_width,
  alpha = 1,
  preserve_aspect = TRUE
)

Arguments

Value

Grid grob or nullGrob if SVG unavailable.

Draw SVG Shape (Base R)

Description

Render an SVG as a node shape using base R graphics. Falls back to circle if rasterization fails.

Usage

draw_svg_shape_base(x, y, size, svg_data, fill, border_color, border_width)

Arguments

Draw Triangle Node

Description

Draw Triangle Node

Usage

draw_triangle(x, y, size, fill, border_color, border_width, alpha = 1, ...)

Calculate Edge Endpoint on Node Border

Description

Calculates the point where an edge should meet the node border. Uses plain NPC units to match circleGrob borders.

Usage

edge_endpoint(
  node_x,
  node_y,
  other_x,
  other_y,
  node_size,
  shape = "circle",
  x_scale = 1,
  y_scale = 1
)

Arguments

Value

List with x, y coordinates in npc.

Generate Ellipse Vertices

Description

Generate Ellipse Vertices

Usage

ellipse_vertices(x, y, rx, ry, n = 50)

Arguments

Value

List with x, y vectors of vertices.

Expand Parameter to Length (Strict)

Description

Expands a parameter to length n. Only accepts length 1 or length n. Throws error for any other length (no silent recycling).

Usage

expand_param(x, n, name = "parameter")

Arguments

Value

Vector of length n.

Filter Edges by Weight Threshold

Description

Removes edges below the minimum weight threshold.

Usage

filter_edges_by_weight(edges, minimum = 0)

Arguments

Value

Filtered edge data frame.

Find Split Index for Curve Based on Arc Length Fraction

Description

Calculates the index at which to split a curve's coordinate arrays so that the first segment covers a given fraction of the total arc length.

Usage

find_curve_split_index(x, y, fraction)

Arguments

Value

Index at which to split the arrays.

Convert Fontface String to Numeric

Description

Converts fontface string specification to numeric value used by R graphics. Handles both string ("plain", "bold", "italic", "bold.italic") and numeric (1, 2, 3, 4) inputs for backwards compatibility.

Usage

fontface_to_numeric(fontface)

Arguments

Value

Numeric fontface value (1=plain, 2=bold, 3=italic, 4=bold.italic).

Convert Numeric Fontface to String

Description

Converts numeric fontface value to string specification. Handles both numeric (1, 2, 3, 4) and string inputs.

Usage

fontface_to_string(fontface)

Arguments

Value

Character fontface value ("plain", "bold", "italic", "bold.italic").

Format CI Range

Description

Formats confidence interval bounds as a range string.

Usage

format_ci_range(lower, upper, digits = 2, format = "bracket")

Arguments

Value

Formatted CI range string.

Format Edge Label from Template

Description

Processes a template string with placeholders and substitutes values.

Usage

format_edge_label_template(
  template,
  weight = NA,
  ci_lower = NA,
  ci_upper = NA,
  p_value = NA,
  stars = "",
  digits = 2,
  p_digits = 3,
  p_prefix = "p=",
  ci_format = "bracket",
  oneline = TRUE
)

Arguments

Value

Formatted label string.

Format P-value

Description

Formats a p-value with specified decimal places and prefix.

Usage

format_pvalue(p, digits = 3, prefix = "p=")

Arguments

Value

Formatted p-value string.

Convert a qgraph object to cograph parameters

Description

Extracts the network, layout, and all relevant arguments from a qgraph object and passes them to a cograph plotting engine. Reads resolved values from graphAttributes rather than raw Arguments.

Usage

from_qgraph(
  qgraph_object,
  engine = c("splot", "soplot"),
  plot = TRUE,
  weight_digits = 2,
  show_zero_edges = FALSE,
  ...
)

Arguments

Details

Parameter Mapping

The following qgraph parameters are automatically extracted and mapped to cograph equivalents:

Node properties:

• labels/names -> labels

• color -> node_fill

• width -> node_size (scaled by 1.3x)

• shape -> node_shape (mapped to cograph equivalents)

• border.color -> node_border_color

• border.width -> node_border_width

• label.cex -> label_size

• label.color -> label_color

Edge properties:

• labels -> edge_labels

• label.cex -> edge_label_size (scaled by 0.5x)

• lty -> edge_style (numeric to name conversion)

• curve -> curvature

• asize -> arrow_size (scaled by 0.3x)

Graph properties:

• minimum -> threshold

• maximum -> maximum

• groups -> groups

• directed -> directed

• posCol/negCol -> edge_positive_color/edge_negative_color

Pie/Donut:

• pie values -> donut_fill with donut_inner_ratio=0.8

• pieColor -> donut_color

Important Notes

• edge_color and edge_width are NOT extracted because qgraph bakes its cut-based fading into these vectors, producing near-invisible edges. cograph applies its own weight-based styling instead.

• The cut parameter is also not passed because it causes faint edges with hanging labels.

• Layout coordinates from qgraph are preserved with rescale=FALSE.

• If you override layout, rescale is automatically re-enabled.

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_tna for tna object conversion

Examples

# Convert and plot a qgraph object
if (requireNamespace("qgraph", quietly = TRUE)) {
  library(qgraph)
  adj <- matrix(c(0, .5, .3, .5, 0, .4, .3, .4, 0), 3, 3)
  q <- qgraph(adj)
  from_qgraph(q)  # Plots with splot

  # Use soplot engine instead
  from_qgraph(q, engine = "soplot")

  # Override extracted parameters
  from_qgraph(q, node_fill = "steelblue", layout = "circle")

  # Extract parameters without plotting
  params <- from_qgraph(q, plot = FALSE)
  names(params)  # See what was extracted

  # Works with themed qgraph objects
  q_themed <- qgraph(adj, theme = "colorblind", posCol = "blue")
  from_qgraph(q_themed)
}

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 = 2,
  show_zero_edges = FALSE,
  ...
)

Arguments

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

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
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)
}

Generate Gear Vertices

Description

Generate Gear Vertices

Usage

gear_vertices(x, y, r, n_teeth = 8)

Arguments

Value

List with x, y vectors of vertices.

Get Polygon Vertices by Shape Name

Description

Returns outer polygon vertices for donut ring shapes.

Usage

get_donut_base_vertices(shape, x, y, r)

Arguments

Value

List with x, y vectors of vertices.

Get Label Position on Edge

Description

Calculates the position for an edge label (matches qgraph-style curves). For curved edges, the label is offset perpendicular to the edge to avoid overlapping with the edge line.

Usage

get_edge_label_position(
  x1,
  y1,
  x2,
  y2,
  position = 0.5,
  curve = 0,
  curvePivot = 0.5,
  label_offset = 0
)

Arguments

Value

List with x, y coordinates.

Get Edge Rendering Order

Description

Returns indices for rendering edges from weakest to strongest.

Usage

get_edge_order(edges)

Arguments

Value

Integer vector of indices.

Get Edges from Cograph Network

Description

Extracts the edges data frame from a cograph_network object. For the new format, builds a data frame from the from/to/weight vectors.

Usage

get_edges(x)

Arguments

Value

A data frame with columns: from, to, weight.

See Also

as_cograph, n_edges, get_nodes

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
get_edges(net)

Get Labels from Cograph Network

Description

Extracts the node labels vector from a cograph_network object.

Usage

get_labels(x)

Arguments

Value

A character vector of node labels.

See Also

as_cograph, get_nodes

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
get_labels(net)

Get a Registered Layout

Description

Get a Registered Layout

Usage

get_layout(name)

Arguments

Value

The layout function, or NULL if not found.

Examples

get_layout("circle")

Get Node Rendering Order

Description

Returns indices for rendering nodes from largest to smallest.

Usage

get_node_order(sizes)

Arguments

Value

Integer vector of indices.

Get Nodes from Cograph Network

Description

Extracts the nodes data frame from a cograph_network object.

Usage

get_nodes(x)

Arguments

Value

A data frame with columns: id, label, name, x, y (and possibly others).

See Also

as_cograph, n_nodes, get_edges

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
get_nodes(net)

Get Scaling Constants

Description

Returns the appropriate scaling constants based on the scaling mode.

Usage

get_scale_constants(scaling = "default")

Arguments

Value

A list of scaling constants.

Get a Registered Shape

Description

Get a Registered Shape

Usage

get_shape(name)

Arguments

Value

The shape drawing function, or NULL if not found.

Examples

get_shape("circle")

Get Shape Vertices

Description

Dispatch function to get vertices for any supported shape.

Usage

get_shape_vertices(shape, x, y, r, r2 = NULL, ...)

Arguments

Value

List with x, y vectors of vertices.

Get Significance Stars from P-values

Description

Converts p-values to significance stars following conventional thresholds.

Usage

get_significance_stars(p)

Arguments

Value

Character vector of stars.

Get Registered SVG Shape

Description

Retrieve SVG shape data by name.

Usage

get_svg_shape(name)

Arguments

Value

SVG data list or NULL if not found.

Get Template from Style Preset

Description

Converts a style preset name to its corresponding template string.

Usage

get_template_from_style(style)

Arguments

Value

Template string or NULL for "none".

Get a Registered Theme

Description

Get a Registered Theme

Usage

get_theme(name)

Arguments

Value

The theme object, or NULL if not found.

Examples

get_theme("classic")

Get X-axis Scale Factor (inches per user unit)

Description

Get X-axis Scale Factor (inches per user unit)

Usage

get_x_scale()

Value

Scale factor.

Get Y-axis Scale Factor (inches per user unit)

Description

Get Y-axis Scale Factor (inches per user unit)

Usage

get_y_scale()

Value

Scale factor.

Global Registries for cograph

Description

Internal registries for shapes, layouts, and themes.

Handle Deprecated Parameter

Description

Handles backwards compatibility for renamed parameters. If the old parameter name is used (not NULL), issues a deprecation warning and returns the old value. Otherwise returns the new parameter value.

Usage

handle_deprecated_param(
  new_val,
  old_val,
  new_name,
  old_name,
  new_val_was_set = NULL
)

Arguments

Details

For parameters with defaults, use new_val_was_set to indicate whether the user explicitly provided the new value. If FALSE (user didn't set it) and old_val is provided, the old value takes precedence.

Value

The effective parameter value.

Check if a package is available

Description

Internal wrapper around requireNamespace that can be mocked in tests.

Usage

has_package(pkg)

Arguments

Value

Logical.

Generate Heart Vertices

Description

Generate Heart Vertices

Usage

heart_vertices(x, y, r, n = 100)

Arguments

Value

List with x, y vectors of vertices.

Generate Hexagon Vertices

Description

Generate Hexagon Vertices

Usage

hexagon_vertices(x, y, r)

Arguments

Value

List with x, y vectors of vertices.

Convert Inches to User Coordinates (X-axis)

Description

Convert Inches to User Coordinates (X-axis)

Usage

in_to_usr_x(x)

Arguments

Value

Value in user coordinates.

Convert Inches to User Coordinates (Y-axis)

Description

Convert Inches to User Coordinates (Y-axis)

Usage

in_to_usr_y(y)

Arguments

Value

Value in user coordinates.

Initialize Global Registries

Description

Initialize Global Registries

Usage

init_registries()

Edge List Input Parsing

Description

Functions for parsing edge list data frames.

igraph Input Parsing

Description

Functions for parsing igraph objects.

Matrix Input Parsing

Description

Functions for parsing adjacency/weight matrices.

Input Parsing Functions

Description

Functions for parsing network input into internal format.

qgraph Input Parsing

Description

Functions for parsing qgraph objects.

Statnet Network Input Parsing

Description

Functions for parsing statnet network objects.

tna Input Parsing

Description

Functions for parsing tna objects.

Inset Polygon Vertices

Description

Creates an inner polygon by scaling vertices toward the centroid.

Usage

inset_polygon_vertices(outer, inner_ratio)

Arguments

Value

List with x, y vectors of inner polygon vertices.

Check if object is a CographNetwork

Description

Check if object is a CographNetwork

Usage

is_cograph_network(x)

Arguments

Value

Logical.

Check if object is a CographTheme

Description

Check if object is a CographTheme

Usage

is_cograph_theme(x)

Arguments

Value

Logical.

Check if Network is Directed

Description

Checks whether a cograph_network is directed.

Usage

is_directed(x)

Arguments

Value

Logical: TRUE if directed, FALSE if undirected.

See Also

as_cograph

Examples

# Symmetric matrix -> undirected
mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
is_directed(net)  # FALSE

# Asymmetric matrix -> directed
mat2 <- matrix(c(0, 1, 0, 0, 0, 1, 0, 0, 0), nrow = 3)
net2 <- as_cograph(mat2)
is_directed(net2)  # TRUE

Detect if Matrix is Symmetric

Description

Detect if Matrix is Symmetric

Usage

is_symmetric_matrix(m, tol = .Machine$double.eps^0.5)

Arguments

Value

Logical.

Circular Layout

Description

Arrange nodes in a circle.

Group-based Layout

Description

Arrange nodes in groups, with each group in a circular arrangement.

Oval/Ellipse Layout

Description

Arrange nodes in an oval (ellipse) shape.

Layout Registry Functions

Description

Functions for registering built-in layouts.

Fruchterman-Reingold Spring Layout

Description

Force-directed layout using the Fruchterman-Reingold algorithm.

Bipartite Layout

Description

Arrange nodes in two columns by type.

Usage

layout_bipartite_fn(network, types = NULL, ...)

Arguments

Value

Data frame with x, y coordinates.

Circular Layout

Description

Arrange nodes evenly spaced around a circle.

Usage

layout_circle(network, order = NULL, start_angle = pi/2, clockwise = TRUE)

Arguments

Value

Data frame with x, y coordinates.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- CographNetwork$new(adj)
coords <- layout_circle(net)

Custom Layout (passthrough)

Description

Pass user-provided coordinates through to the layout.

Usage

layout_custom_fn(network, coords, ...)

Arguments

Value

Data frame with x, y coordinates.

Gephi Fruchterman-Reingold Layout

Description

Force-directed layout that replicates Gephi's Fruchterman-Reingold algorithm. This is a strict port of the Java implementation from Gephi's source code.

Usage

layout_gephi_fr(g, area = 10000, gravity = 10, speed = 1, niter = 100)

Arguments

Details

This layout is a direct port of Gephi's ForceAtlas algorithm variant of Fruchterman-Reingold. Key differences from igraph's layout_with_fr:

• Uses Gephi's specific constants (SPEED_DIVISOR=800, AREA_MULTIPLICATOR=10000)

• Includes configurable gravity toward center

• Different cooling/speed mechanism

Value

A matrix with x,y coordinates for each node.

Grid Layout

Description

Arrange nodes in a grid pattern.

Usage

layout_grid_fn(network, ncol = NULL, ...)

Arguments

Value

Data frame with x, y coordinates.

Group-based Layout

Description

Arrange nodes based on group membership. Groups are positioned in a circular arrangement around the center, with nodes within each group also arranged in a circle.

Usage

layout_groups(
  network,
  groups,
  group_positions = NULL,
  inner_radius = 0.15,
  outer_radius = 0.35
)

Arguments

Value

Data frame with x, y coordinates.

Examples

# Create a network with groups
adj <- matrix(0, 9, 9)
adj[1, 2:3] <- 1; adj[2:3, 1] <- 1  # Group 1
adj[4, 5:6] <- 1; adj[5:6, 4] <- 1  # Group 2
adj[7, 8:9] <- 1; adj[8:9, 7] <- 1  # Group 3
net <- CographNetwork$new(adj)
groups <- c(1, 1, 1, 2, 2, 2, 3, 3, 3)
coords <- layout_groups(net, groups)

Oval Layout

Description

Arrange nodes evenly spaced around an ellipse. This creates an oval-shaped network layout that is wider than it is tall (or vice versa depending on ratio).

Usage

layout_oval(
  network,
  ratio = 1.5,
  order = NULL,
  start_angle = pi/2,
  clockwise = TRUE,
  rotation = 0
)

Arguments

Value

Data frame with x, y coordinates.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- CographNetwork$new(adj)
coords <- layout_oval(net, ratio = 1.5)

Random Layout

Description

Place nodes at random positions.

Usage

layout_random_fn(network, seed = NULL, ...)

Arguments

Value

Data frame with x, y coordinates.

Fruchterman-Reingold Spring Layout

Description

Compute node positions using the Fruchterman-Reingold force-directed algorithm. Nodes connected by edges are attracted to each other while all nodes repel each other.

Usage

layout_spring(
  network,
  iterations = 500,
  cooling = 0.95,
  repulsion = 1,
  attraction = 1,
  seed = NULL,
  initial = NULL
)

Arguments

Value

Data frame with x, y coordinates.

Examples

adj <- matrix(c(0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0), nrow = 4)
net <- CographNetwork$new(adj)
coords <- layout_spring(net, seed = 42)

Star Layout

Description

Place one node at center, rest in a circle.

Usage

layout_star_fn(network, center = 1, ...)

Arguments

Value

Data frame with x, y coordinates.

List Available Layouts

Description

List Available Layouts

Usage

list_layouts()

Value

Character vector of registered layout names.

Examples

list_layouts()

List Available Color Palettes

Description

Returns the names of all registered color palettes.

Usage

list_palettes()

Value

Character vector of palette names.

Examples

list_palettes()

List Available Shapes

Description

List Available Shapes

Usage

list_shapes()

Value

Character vector of registered shape names.

Examples

list_shapes()

List Registered SVG Shapes

Description

Get names of all registered custom SVG shapes.

Usage

list_svg_shapes()

Value

Character vector of registered shape names.

Examples

list_svg_shapes()

List Available Themes

Description

List Available Themes

Usage

list_themes()

Value

Character vector of registered theme names.

Examples

list_themes()

Map Edge Colors by Weight

Description

Map edge colors based on weight values.

Usage

map_edge_colors(
  weights,
  positive_color = "#2E7D32",
  negative_color = "#C62828",
  zero_color = "gray50"
)

Arguments

Value

Character vector of colors.

Map Node Colors by Group

Description

Helper function to map node colors based on group membership.

Usage

map_node_colors(groups, palette = NULL)

Arguments

Value

Character vector of colors.

Map qgraph lty codes to cograph edge style names

Description

Map qgraph lty codes to cograph edge style names

Usage

map_qgraph_lty(lty)

Arguments

Value

Character vector of cograph style names

Map qgraph shape names to cograph equivalents

Description

Map qgraph shape names to cograph equivalents

Usage

map_qgraph_shape(shapes)

Arguments

Value

Character vector of cograph shape names

Plot Methods

Description

S3 plot methods for Cograph objects.

Print Methods

Description

S3 print methods for Cograph objects.

Get Number of Edges

Description

Returns the number of edges in a cograph_network.

Usage

n_edges(x)

Arguments

Value

Integer: number of edges.

See Also

as_cograph, n_nodes

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
n_edges(net)  # 3

Get Number of Nodes

Description

Returns the number of nodes in a cograph_network.

Usage

n_nodes(x)

Arguments

Value

Integer: number of nodes.

See Also

as_cograph, n_edges, get_nodes

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
n_nodes(net)  # 3

Get Nodes from Cograph Network (Deprecated)

Description

Extracts the nodes data frame from a cograph_network object. Deprecated: Use get_nodes instead.

Usage

nodes(x)

Arguments

Value

A data frame with columns: id, label, name, x, y (and possibly others).

See Also

get_nodes, as_cograph, n_nodes

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
nodes(net)  # Deprecated, use get_nodes(net) instead

Offset Point from Center

Description

Calculate a point offset from another point by a given distance.

Usage

offset_point(x, y, toward_x, toward_y, offset)

Arguments

Value

List with x, y coordinates.

Output and Saving

Description

Functions for saving network visualizations to files.

Blues Palette

Description

Generate a blue sequential palette.

Usage

palette_blues(n, alpha = 1)

Arguments

Value

Character vector of colors.

Examples

palette_blues(5)

Colorblind-friendly Palette

Description

Generate a colorblind-friendly palette using Wong's colors.

Usage

palette_colorblind(n, alpha = 1)

Arguments

Value

Character vector of colors.

Examples

palette_colorblind(5)

Diverging Palette

Description

Generate a diverging color palette (blue-white-red).

Usage

palette_diverging(n, alpha = 1, midpoint = "white")

Arguments

Value

Character vector of colors.

Examples

palette_diverging(5)

Pastel Palette

Description

Generate a soft pastel color palette.

Usage

palette_pastel(n, alpha = 1)

Arguments

Value

Character vector of colors.

Examples

palette_pastel(5)

Rainbow Palette

Description

Generate a rainbow color palette.

Usage

palette_rainbow(n, alpha = 1)

Arguments

Value

Character vector of colors.

Examples

palette_rainbow(5)

Reds Palette

Description

Generate a red sequential palette.

Usage

palette_reds(n, alpha = 1)

Arguments

Value

Character vector of colors.

Examples

palette_reds(5)

Viridis Palette

Description

Generate colors from the viridis palette.

Usage

palette_viridis(n, alpha = 1, option = "viridis")

Arguments

Value

Character vector of colors.

Examples

palette_viridis(5)

Color Palettes

Description

Built-in color palettes for network visualization.

Parse Network Input

Description

Automatically detects input type and converts to internal format.

Usage

parse_input(input, directed = NULL)

Arguments

Value

List with nodes, edges, directed, and weights components.

Parse SVG Content

Description

Parse SVG from string or file.

Usage

parse_svg(svg_data)

Arguments

Value

Parsed SVG object (grImport2 Picture or NULL).

Generate Pentagon Vertices

Description

Generate Pentagon Vertices

Usage

pentagon_vertices(x, y, r)

Arguments

Value

List with x, y vectors of vertices.

Calculate Perpendicular Midpoint for Curved Edges

Description

Computes a control point perpendicular to the line between two nodes, used for xspline() curve generation.

Usage

perp_mid(x0, y0, x1, y1, cex, q = 0.5)

Arguments

Value

List with x, y coordinates of control point.

Plot cograph_network Object

Description

Plot cograph_network Object

Usage

## S3 method for class 'cograph_network'
plot(x, ...)

Arguments

Value

Invisible x.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- cograph(adj)
plot(net)

Plot Heterogeneous TNA Network (Multi-Group Layout)

Description

Plots a TNA model with nodes arranged in multiple groups using geometric layouts:

• 2 groups: Bipartite (two vertical columns or horizontal rows)

• 3+ groups: Polygon (nodes along edges of a regular polygon)

Supports triangle (3), rectangle (4), pentagon (5), hexagon (6), and beyond.

Usage

plot_htna(
  x,
  node_list,
  layout = "auto",
  use_list_order = TRUE,
  jitter = TRUE,
  jitter_amount = 0.8,
  jitter_side = "first",
  orientation = "vertical",
  group1_pos = -1.2,
  group2_pos = 1.2,
  curvature = 0.4,
  group1_color = "#ffd89d",
  group2_color = "#a68ba5",
  group1_shape = "circle",
  group2_shape = "square",
  group_colors = NULL,
  group_shapes = NULL,
  angle_spacing = 0.15,
  edge_colors = NULL,
  legend = TRUE,
  legend_position = "topright",
  extend_lines = FALSE,
  scale = 1,
  ...
)

Arguments

Value

Invisibly returns the result from tplot().

Examples

# --- 2-group bipartite example ---
nodes_2 <- c("Wrong", "Retry", "Right", "Attempt", "Instruction", "Skip",
              "Order", "Correct", "Hint", "Quit", "Clarify", "Question", "Praise")
set.seed(1)
m2 <- matrix(runif(length(nodes_2)^2, 0, 0.3), length(nodes_2), length(nodes_2))
diag(m2) <- 0
dimnames(m2) <- list(nodes_2, nodes_2)

node_types <- list(
  Student = c("Wrong", "Retry", "Right", "Attempt", "Instruction", "Skip"),
  AI = c("Order", "Correct", "Hint", "Quit", "Clarify", "Question", "Praise")
)
plot_htna(m2, node_types)
plot_htna(m2, node_types, jitter_amount = 0.5)

# --- Triangle layout (3 groups) ---
nodes_3 <- c("Explain", "Question", "Feedback",
              "Answer", "Ask", "Attempt",
              "Hint", "Score", "Progress")
m3 <- matrix(runif(81, 0, 0.3), 9, 9)
diag(m3) <- 0
dimnames(m3) <- list(nodes_3, nodes_3)

node_types_3 <- list(
  Teacher = c("Explain", "Question", "Feedback"),
  Student = c("Answer", "Ask", "Attempt"),
  System  = c("Hint", "Score", "Progress")
)
plot_htna(m3, node_types_3)
plot_htna(m3, node_types_3, layout = "triangle")

# --- Rectangle layout (4 groups) ---
nodes_4 <- c("Click", "Type", "Scroll",
              "Validate", "Transform",
              "Display", "Alert",
              "Save", "Load", "Cache")
m4 <- matrix(runif(100, 0, 0.3), 10, 10)
diag(m4) <- 0
dimnames(m4) <- list(nodes_4, nodes_4)

node_types_4 <- list(
  Input   = c("Click", "Type", "Scroll"),
  Process = c("Validate", "Transform"),
  Output  = c("Display", "Alert"),
  Storage = c("Save", "Load", "Cache")
)
plot_htna(m4, node_types_4)

Multilevel Network Visualization

Description

Visualizes multilevel/multiplex networks where multiple layers are stacked in a 3D perspective view. Each layer contains nodes connected by solid edges (within-layer), while dashed lines connect nodes between adjacent layers (inter-layer edges). Each layer is enclosed in a parallelogram shell giving a pseudo-3D appearance.

Usage

plot_mlna(
  model,
  layer_list,
  layout = "horizontal",
  layer_spacing = 2.2,
  layer_width = 4.5,
  layer_depth = 2.2,
  skew_angle = 25,
  node_spacing = 0.7,
  colors = NULL,
  shapes = NULL,
  edge_colors = NULL,
  within_edges = TRUE,
  between_edges = TRUE,
  between_style = 2,
  show_border = TRUE,
  legend = TRUE,
  legend_position = "topright",
  curvature = 0.15,
  node_size = 3,
  minimum = 0,
  scale = 1,
  ...
)

mlna(
  model,
  layer_list,
  layout = "horizontal",
  layer_spacing = 2.2,
  layer_width = 4.5,
  layer_depth = 2.2,
  skew_angle = 25,
  node_spacing = 0.7,
  colors = NULL,
  shapes = NULL,
  edge_colors = NULL,
  within_edges = TRUE,
  between_edges = TRUE,
  between_style = 2,
  show_border = TRUE,
  legend = TRUE,
  legend_position = "topright",
  curvature = 0.15,
  node_size = 3,
  minimum = 0,
  scale = 1,
  ...
)

Arguments

Details

Value

Invisibly returns NULL.

Examples

# Create multilevel network
set.seed(42)
nodes <- paste0("N", 1:15)
m <- matrix(runif(225, 0, 0.3), 15, 15)
diag(m) <- 0
colnames(m) <- rownames(m) <- nodes

# Define 3 layers
layers <- list(
  Macro = paste0("N", 1:5),
  Meso = paste0("N", 6:10),
  Micro = paste0("N", 11:15)
)

# Basic usage
plot_mlna(m, layers)

# Customized
plot_mlna(m, layers,
     layer_spacing = 2.5,
     layer_width = 5,
     between_style = 2,  # dashed
     minimum = 0.1)

# Circle layout within layers
plot_mlna(m, layers, layout = "circle")

Multi-Cluster TNA Network Plot

Description

Visualizes multiple network clusters with summary edges between clusters and individual edges within clusters. Each cluster is displayed as a shape (circle, square, diamond, triangle) containing its nodes.

Usage

plot_mtna(
  x,
  cluster_list,
  layout = "circle",
  spacing = 3,
  shape_size = 1.2,
  node_spacing = 0.5,
  colors = NULL,
  shapes = NULL,
  edge_colors = NULL,
  bundle_edges = TRUE,
  bundle_strength = 0.8,
  summary_edges = TRUE,
  within_edges = TRUE,
  show_border = TRUE,
  legend = TRUE,
  legend_position = "topright",
  curvature = 0.3,
  node_size = 2,
  scale = 1,
  ...
)

mtna(
  x,
  cluster_list,
  layout = "circle",
  spacing = 3,
  shape_size = 1.2,
  node_spacing = 0.5,
  colors = NULL,
  shapes = NULL,
  edge_colors = NULL,
  bundle_edges = TRUE,
  bundle_strength = 0.8,
  summary_edges = TRUE,
  within_edges = TRUE,
  show_border = TRUE,
  legend = TRUE,
  legend_position = "topright",
  curvature = 0.3,
  node_size = 2,
  scale = 1,
  ...
)

Arguments

Value

Invisibly returns NULL for summary mode, or the plot_tna result.

Examples

# Create network with 4 clusters
nodes <- paste0("N", 1:20)
m <- matrix(runif(400, 0, 0.3), 20, 20)
diag(m) <- 0
colnames(m) <- rownames(m) <- nodes

clusters <- list(
  North = paste0("N", 1:5),
  East = paste0("N", 6:10),
  South = paste0("N", 11:15),
  West = paste0("N", 16:20)
)

# Summary edges between clusters + individual edges within
plot_mtna(m, clusters, summary_edges = TRUE)

# Control spacing and sizes
plot_mtna(m, clusters, spacing = 4, shape_size = 1.5, node_spacing = 0.6)

TNA-Style Network Plot (qgraph Compatible)

Description

A drop-in replacement for qgraph::qgraph() that uses cograph's splot engine. Accepts qgraph parameter names for seamless migration from qgraph to cograph.

Usage

plot_tna(
  x,
  color = NULL,
  labels = NULL,
  layout = "oval",
  theme = "colorblind",
  mar = c(0.1, 0.1, 0.1, 0.1),
  cut = NULL,
  edge.labels = TRUE,
  edge.label.position = 0.7,
  edge.label.cex = 0.6,
  edge.color = "#003355",
  vsize = 7,
  pie = NULL,
  pieColor = NULL,
  lty = NULL,
  directed = NULL,
  minimum = NULL,
  posCol = NULL,
  negCol = NULL,
  arrowAngle = NULL,
  title = NULL,
  ...
)

tplot(
  x,
  color = NULL,
  labels = NULL,
  layout = "oval",
  theme = "colorblind",
  mar = c(0.1, 0.1, 0.1, 0.1),
  cut = NULL,
  edge.labels = TRUE,
  edge.label.position = 0.7,
  edge.label.cex = 0.6,
  edge.color = "#003355",
  vsize = 7,
  pie = NULL,
  pieColor = NULL,
  lty = NULL,
  directed = NULL,
  minimum = NULL,
  posCol = NULL,
  negCol = NULL,
  arrowAngle = NULL,
  title = NULL,
  ...
)

Arguments

Value

Invisibly returns the cograph_network object from splot().

Examples

# Simple usage
m <- matrix(runif(25), 5, 5)
plot_tna(m)

# With qgraph-style parameters
plot_tna(m, vsize = 15, edge.label.cex = 2, layout = "circle")

# With custom colors
plot_tna(m, color = rainbow(5), vsize = 10)

Calculate Angle Between Two Points

Description

Calculate Angle Between Two Points

Usage

point_angle(x1, y1, x2, y2)

Arguments

Value

Angle in radians.

Calculate Distance Between Two Points

Description

Calculate Distance Between Two Points

Usage

point_distance(x1, y1, x2, y2)

Arguments

Value

Euclidean distance.

Calculate Point on Circle

Description

Calculate Point on Circle

Usage

point_on_circle(cx, cy, r, angle)

Arguments

Value

List with x, y coordinates.

Print cograph_network Object

Description

Print cograph_network Object

Usage

## S3 method for class 'cograph_network'
print(x, ...)

Arguments

Value

Invisible x.

qgraph-style Arrow Size Calculation

Description

Calculates arrow size based on edge width, matching qgraph behavior.

Usage

qgraph_arrow_size(edge_width, base_asize = 1)

Arguments

Value

Arrow size in user coordinates.

qgraph Cent2Edge (EXACT - critical formula)

Description

Calculates the point on node boundary where an edge should connect. This is qgraph's exact formula for positioning arrows and edge endpoints.

Usage

qgraph_cent2edge(x, y, cex, offset = 0, angle, plot_info = NULL)

Arguments

Value

List with x, y coordinates on node boundary.

qgraph Point on Node Boundary

Description

Simplified boundary calculation for splot that approximates qgraph behavior while working with cograph's coordinate system.

Usage

qgraph_cent_to_edge_simple(x, y, angle, node_size, shape = "circle")

Arguments

Value

List with x, y coordinates on boundary.

qgraph Default Edge Size

Description

Calculates the default maximum edge width using qgraph's exact formula. Formula: 15 * exp(-n/90) + 1 (halved for directed networks, minimum 1)

Usage

qgraph_default_esize(n_nodes, weighted = TRUE, directed = FALSE)

Arguments

Value

Default esize value.

qgraph Default Node Size

Description

Calculates the default node size using qgraph's exact formula. Formula: 8 * exp(-n/80) + 1

Usage

qgraph_default_vsize(n_nodes)

Arguments

Value

Default vsize value (before scale factor conversion).

qgraph Curve Normalization Factor

Description

Calculates the normalization factor for edge curvature to maintain consistent visual appearance across different plot sizes. Formula: sqrt(sum(pin^2)) / sqrt(7^2 + 7^2)

Usage

qgraph_norm_curve()

Value

Numeric normalization factor.

Get Plot Dimension Info

Description

Retrieves current plot device information needed for qgraph-style calculations.

Usage

qgraph_plot_info()

Value

List with usr, pin, mai, csi, and dev_name components.

qgraph Edge Width Scaling (EXACT)

Description

Scales edge weights to widths using qgraph's exact formula. Output range is 1 to esize for continuous scaling (cut = 0).

Usage

qgraph_scale_edge_widths(
  weights,
  minimum = 0,
  maximum = NULL,
  cut = 0,
  esize = NULL
)

Arguments

Value

Numeric vector of scaled edge widths.

qgraph Node Size to User Coordinates

Description

Converts qgraph vsize to user coordinate radius using qgraph's exact logic.

Usage

qgraph_vsize_to_user(vsize, plot_info = NULL)

Arguments

Value

Node radius in user coordinates.

Generate Rectangle Vertices

Description

Generate Rectangle Vertices

Usage

rectangle_vertices(x, y, w, h)

Arguments

Value

List with x, y vectors of vertices.

Recycle Value to Length

Description

Recycle Value to Length

Usage

recycle_to_length(x, n)

Arguments

Value

Recycled vector.

Register Built-in Layouts

Description

Register all built-in layout algorithms.

Usage

register_builtin_layouts()

Register Built-in Palettes

Description

Register Built-in Palettes

Usage

register_builtin_palettes()

Register Built-in Shapes

Description

Register all built-in node shapes.

Usage

register_builtin_shapes()

Register Built-in Themes

Description

Register all built-in themes.

Usage

register_builtin_themes()

Register a Custom Layout

Description

Register a new layout algorithm that can be used for network visualization.

Usage

register_layout(name, layout_fn)

Arguments

Value

Invisible NULL.

Examples

# Register a simple random layout
register_layout("random", function(network, ...) {
  n <- network$n_nodes
  cbind(x = runif(n), y = runif(n))
})

Register a Custom Shape

Description

Register a new shape that can be used for node rendering.

Usage

register_shape(name, draw_fn)

Arguments

Value

Invisible NULL.

Examples

# Register a custom hexagon shape
register_shape("hexagon", function(x, y, size, fill, border_color, border_width, ...) {
  angles <- seq(0, 2 * pi, length.out = 7)
  grid::polygonGrob(
    x = x + size * cos(angles),
    y = y + size * sin(angles),
    gp = grid::gpar(fill = fill, col = border_color, lwd = border_width)
  )
})

Register Custom SVG Shape

Description

Register an SVG file or string as a custom node shape.

Usage

register_svg_shape(name, svg_source)

Arguments

Value

Invisible NULL. The shape is registered for use with sn_nodes().

Examples

# Register a custom SVG shape from an inline SVG string
register_svg_shape("simple_star",
  '<svg viewBox="0 0 100 100">
    <polygon points="50,5 20,99 95,39 5,39 80,99" fill="currentColor"/>
  </svg>')

# Create a small adjacency matrix
adj <- matrix(c(0, 1, 1, 0, 0, 1, 1, 0, 0), nrow = 3,
              dimnames = list(c("A", "B", "C"), c("A", "B", "C")))

# Use in network (requires grImport2 for SVG rendering; falls back to circle)
cograph(adj) |> sn_nodes(shape = "simple_star")

Register a Custom Theme

Description

Register a new theme for network visualization.

Usage

register_theme(name, theme)

Arguments

Value

Invisible NULL.

Examples

# Register a custom theme
register_theme("custom", list(
  background = "white",
  node_fill = "steelblue",
  node_border = "navy",
  edge_color = "gray50"
))

Generate Regular Polygon Vertices

Description

Generate Regular Polygon Vertices

Usage

regular_polygon_vertices(x, y, r, n, rotation = pi/2)

Arguments

Value

List with x, y vectors of vertices.

Edge Rendering

Description

Functions for rendering edges using grid graphics.

ggplot2 Conversion

Description

Convert Cograph network to ggplot2 object.

Grid Rendering

Description

Main grid-based rendering functions.

Node Rendering

Description

Functions for rendering nodes using grid graphics.

Render Edge Labels

Description

Create grid grobs for edge labels with background, borders, and styling.

Usage

render_edge_labels_grid(network)

Arguments

Value

A grid gList of label grobs.

Render All Edges

Description

Create grid grobs for all edges in the network.

Usage

render_edges_grid(network)

Arguments

Value

A grid gList of edge grobs.

Render Edges for splot

Description

Render Edges for splot

Usage

render_edges_splot(
  edges,
  layout,
  node_sizes,
  shapes,
  edge_color,
  edge_width,
  edge_style,
  curvature,
  curve_shape,
  curve_pivot,
  show_arrows,
  arrow_size,
  arrow_angle = pi/6,
  bidirectional,
  loop_rotation,
  edge_labels,
  edge_label_size,
  edge_label_color,
  edge_label_bg,
  edge_label_position,
  edge_label_offset = 0,
  edge_label_fontface,
  edge_label_shadow = FALSE,
  edge_label_shadow_color = "gray40",
  edge_label_shadow_offset = 0.5,
  edge_label_shadow_alpha = 0.5,
  edge_ci = NULL,
  edge_ci_scale = 2,
  edge_ci_alpha = 0.15,
  edge_ci_color = NULL,
  edge_ci_style = 2,
  edge_ci_arrows = FALSE,
  is_reciprocal = NULL,
  edge_start_style = "solid",
  edge_start_length = 0.15,
  edge_start_dot_density = "12"
)

Render Legend

Description

Create grid grobs for the network legend.

Usage

render_legend_grid(network, position = "topright")

Arguments

Value

A grid gList of legend grobs.

Render Legend for splot

Description

Renders a comprehensive legend showing node groups, edge weight colors, and optionally node sizes.

Usage

render_legend_splot(
  groups,
  node_names,
  nodes,
  node_colors,
  position = "topright",
  cex = 0.8,
  show_edge_colors = FALSE,
  positive_color = "#2E7D32",
  negative_color = "#C62828",
  has_pos_edges = FALSE,
  has_neg_edges = FALSE,
  show_node_sizes = FALSE,
  node_size = NULL
)

Arguments

Render Node Labels

Description

Create grid grobs for node labels.

Usage

render_node_labels_grid(network)

Arguments

Value

A grid gList of label grobs.

Render All Nodes

Description

Renders all nodes in the network.

Usage

render_nodes_base(
  layout,
  vsize,
  vsize2 = NULL,
  shape = "circle",
  color = "#4A90D9",
  border.color = "#2C5AA0",
  border.width = 1,
  pie = NULL,
  pieColor = NULL,
  donut = NULL,
  donutColor = NULL,
  labels = NULL,
  label.cex = 1,
  label.color = "black"
)

Arguments

Render All Nodes

Description

Create grid grobs for all nodes in the network.

Usage

render_nodes_grid(network)

Arguments

Value

A grid gList of node grobs.

Render Nodes for splot

Description

Render Nodes for splot

Usage

render_nodes_splot(
  layout,
  node_size,
  node_size2,
  node_shape,
  node_fill,
  node_border_color,
  node_border_width,
  pie_values,
  pie_colors,
  pie_border_width,
  donut_values,
  donut_colors,
  donut_border_color,
  donut_border_width,
  donut_outer_border_color = NULL,
  donut_line_type = "solid",
  donut_inner_ratio,
  donut_bg_color,
  donut_shape,
  donut_show_value,
  donut_value_size,
  donut_value_color,
  donut_value_fontface = "bold",
  donut_value_fontfamily = "sans",
  donut_value_digits = 2,
  donut_value_prefix = "",
  donut_value_suffix = "",
  donut2_values,
  donut2_colors,
  donut2_inner_ratio,
  labels,
  label_size,
  label_color,
  label_position,
  label_fontface = "plain",
  label_fontfamily = "sans",
  label_hjust = 0.5,
  label_vjust = 0.5,
  label_angle = 0,
  use_pch = FALSE
)

Arguments

Rescale Layout to -1 to 1 Range

Description

Rescale Layout to -1 to 1 Range

Usage

rescale_layout(layout, mar = 0.1)

Arguments

Value

Rescaled layout.

Resolve Aesthetic Value

Description

Resolve an aesthetic value that could be a constant, vector, or column name.

Usage

resolve_aesthetic(value, data = NULL, n = NULL, default = NULL)

Arguments

Value

Resolved vector of values.

Resolve Curvature Parameter

Description

Determines edge curvatures, handling reciprocal edges.

Usage

resolve_curvatures(curve, edges, curveScale = TRUE, default_curve = 0.2)

Arguments

Value

Vector of curvatures.

Resolve Edge Colors

Description

Determines edge colors based on weights, explicit colors, or defaults.

Usage

resolve_edge_colors(
  edges,
  edge.color = NULL,
  posCol = "#2E7D32",
  negCol = "#C62828",
  default_col = "gray50"
)

Arguments

Value

Vector of colors for each edge.

Resolve Edge Labels

Description

Determines edge labels from various inputs.

Usage

resolve_edge_labels(edge.labels, edges, m)

Arguments

Value

Character vector of labels (or NULL for no labels).

Resolve Edge Widths

Description

Determines edge widths based on weights or explicit values. Supports multiple scaling modes, two-tier cutoff, and output range specification.

Usage

resolve_edge_widths(
  edges,
  edge.width = NULL,
  esize = NULL,
  n_nodes = NULL,
  directed = FALSE,
  maximum = NULL,
  minimum = 0,
  cut = NULL,
  edge_width_range = NULL,
  edge_scale_mode = NULL,
  scaling = "default",
  base_width = NULL,
  scale_factor = NULL
)

Arguments

Value

Vector of widths for each edge.

Resolve Label Sizes

Description

Determines label sizes, either independent (new default) or coupled to node size (legacy).

Usage

resolve_label_sizes(label_size, node_size_usr, n, scaling = "default")

Arguments

Value

Vector of label sizes (cex values).

Resolve Labels

Description

Determines node labels from various inputs.

Usage

resolve_labels(labels, nodes, n)

Arguments