Plot Centrality Heatmap — plot_centrality

Heatmap of nodes (rows) by centrality measures (columns), z-standardized within measure so the diverging palette is meaningful. Optional row clustering groups nodes with similar centrality profiles.

Usage

plot_centrality_heatmap(
  x,
  measures = NULL,
  cluster_rows = TRUE,
  order_by = NULL,
  show_values = FALSE,
  value_digits = 1L,
  low = "#2171B5",
  mid = "white",
  high = "#CB181D",
  limits = c(-2.5, 2.5),
  title = NULL,
  subtitle = "z-scored within measure",
  ...
)

Arguments

x: Centrality data frame (from centrality) or a network input.
measures: Character vector of measure names.
cluster_rows: Logical. Hierarchically cluster rows so nodes with similar profiles are adjacent. Default TRUE.
order_by: If cluster_rows = FALSE, optionally the name of a measure to sort rows by (descending). Default: first measure.
show_values: Logical. Print z-scores in cells. Default FALSE.
value_digits: Decimal places for cell values. Default 1.
low, mid, high: Color stops for the diverging scale. Defaults to blue -> white -> red.
limits: Numeric c(min, max) z-score range. Values outside are squished to the endpoints. Default c(-2.5, 2.5).
title, subtitle: Plot title and subtitle.
...: Passed to centrality when x is a network.

Value

A ggplot object.

Examples

adj <- matrix(c(0,1,1,0,0, 1,0,1,1,0, 1,1,0,1,1, 0,1,1,0,1, 0,0,1,1,0),
              5, 5)
rownames(adj) <- colnames(adj) <- LETTERS[1:5]
plot_centrality_heatmap(adj)