plot_net_group: Plot two networks side by side with R2 progress rings

In InterconectaR: Psychological Network Analysis and Psychometric Insights

Plot two networks side by side with R2 progress rings

Description

Creates a faceted ggplot comparing two group networks (e.g., female vs male) with nodes colored by domain, R2 progress rings, gradient-colored edges, and optional abbreviated labels with a legend mapping.

Usage

plot_net_group(
  mat1,
  mat2,
  r2_1,
  r2_2,
  group_names = c("Femenino", "Masculino"),
  labels = colnames(mat1),
  short_labels = NULL,
  full_labels = NULL,
  groups_list = NULL,
  group_cols = NULL,
  palette = "Darjeeling1",
  node_radius = 0.2,
  node_label_size = NULL,
  ring_offset = 0.045,
  ring_stroke = 2.4,
  ring_progress_col = "black",
  edge_min = 0,
  lwd_range = c(0.4, 4.5),
  alpha_range = c(0.15, 1),
  edge_color_pos = NULL,
  edge_color_neg = NULL,
  edge_curvature = 0,
  show_edge_values = TRUE,
  edge_label_digits = 2,
  edge_label_size = 3.2,
  edge_label_offset = 0.05,
  edge_label_bg = TRUE,
  edge_label_bg_fill = "white",
  edge_label_bg_alpha = 0.9,
  show_R2_text = TRUE,
  R2_text_size = NULL,
  R2_text_color = "grey30",
  R2_digits = 2,
  R2_position = "below",
  title = NULL,
  subtitle = NULL,
  caption = "default"
)

Arguments

mat1	Adjacency matrix for the first group.
mat2	Adjacency matrix for the second group.
r2_1	Numeric vector of R2 values for the first group.
r2_2	Numeric vector of R2 values for the second group.
group_names	Character vector of length 2 with facet labels (default: c("Femenino","Masculino")).
labels	Character vector of node labels (default: colnames of mat1).
short_labels	Optional character vector of abbreviations displayed inside nodes.
full_labels	Optional character vector of full names for the caption legend.
groups_list	Named list mapping domain names to node indices.
group_cols	Named character vector of colors per domain.
palette	Wes Anderson palette used when group_cols or edge colors are not supplied.
node_radius	Numeric radius of node circles.
node_label_size	Text size for node labels (NULL = auto).
ring_offset	Gap between node circle and R2 ring.
ring_stroke	Line width of the R2 ring.
ring_progress_col	Color of the R2 progress arc.
edge_min	Minimum absolute edge weight to display.
lwd_range	Numeric vector of length 2: min and max line widths.
alpha_range	Numeric vector of length 2: min and max alpha for edges.
edge_color_pos	Color for the strongest positive edge.
edge_color_neg	Color for the strongest negative edge.
edge_curvature	Curvature of edges (0 = straight).
show_edge_values	Logical; show edge weight labels?
edge_label_digits	Number of decimal digits for edge labels.
edge_label_size	Text size for edge labels.
edge_label_offset	Perpendicular offset for edge labels.
edge_label_bg	Logical; use background box for edge labels?
edge_label_bg_fill	Fill color of the edge label background.
edge_label_bg_alpha	Alpha of the edge label background.
show_R2_text	Logical; show R2 numeric text near nodes?
R2_text_size	Text size for R2 labels (NULL = auto).
R2_text_color	Color for R2 labels.
R2_digits	Decimal digits for R2 labels.
R2_position	Position of R2 text: "below", "above", "right", "left".
title	Optional plot title.
subtitle	Optional plot subtitle.
caption	Caption text. '"default"' explains the R2 ring; 'NULL' removes the caption.

Value

A ggplot object.

Examples

set.seed(123)
n <- 300
f1 <- rnorm(n)
f2 <- 0.3 * f1 + rnorm(n)
items <- data.frame(
  sapply(1:4, function(i) 0.7 * f1 + rnorm(n, 0, 0.7)),
  sapply(1:4, function(i) 0.7 * f2 + rnorm(n, 0, 0.7))
)
names(items) <- c(paste0("A", 1:4), paste0("B", 1:4))
sex <- rep(c("Female", "Male"), each = n / 2)

net_f <- bootnet::estimateNetwork(items[sex == "Female", ], default = "EBICglasso")
net_m <- bootnet::estimateNetwork(items[sex == "Male", ], default = "EBICglasso")
r2_f <- mgm_error_metrics(items[sex == "Female", ], type = rep("g", 8),
                          level = rep(1, 8))$R2
r2_m <- mgm_error_metrics(items[sex == "Male", ], type = rep("g", 8),
                          level = rep(1, 8))$R2
plot_net_group(
  mat1 = net_f$graph, mat2 = net_m$graph,
  r2_1 = r2_f, r2_2 = r2_m,
  group_names = c("Female", "Male"),
  groups_list = list(Anxiety = 1:4, Depression = 5:8)
)

InterconectaR documentation built on Oct. 16, 2026, 1:06 a.m.