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Plot MONECA Results as Dendrogram

Source: R/modern_plotting.R
plot_moneca_dendrogram.Rd

Creates a dendrogram-like visualization of the hierarchical clustering results from moneca analysis. This function shows how categories are progressively aggregated across segmentation levels, making the hierarchical structure clear.

Usage

plot_moneca_dendrogram(
  segments,
  height_method = "uniform",
  color_segments = TRUE,
  show_labels = TRUE,
  label_size = 3,
  branch_width = 1,
  title = "MONECA Hierarchical Clustering",
  subtitle = NULL,
  color_palette = "okabe-ito",
  theme_style = "minimal",
  vertical = TRUE
)

Arguments

segments

A moneca object returned by moneca.

height_method

Character string specifying how to calculate dendrogram heights:

  • "uniform" (default): Equal spacing between levels

  • "mobility": Height based on mobility reduction between levels

  • "segments": Height based on number of segments at each level

color_segments

Logical indicating whether to color branches by final segment membership. Default is TRUE.

show_labels

Logical indicating whether to show category labels at the bottom. Default is TRUE.

label_size

Numeric size for labels. Default is 3.

branch_width

Numeric width for dendrogram branches. Default is 1.

title

Character string for plot title. Default is "MONECA Hierarchical Clustering".

subtitle

Character string for plot subtitle. Default is NULL.

color_palette

Character string specifying the color palette for segment colors. Default is "okabe-ito" (CVD-safe). Also accepts RColorBrewer palette names (e.g., "Set3") or viridis options.

theme_style

Character string specifying the plot theme. Options are "minimal" (default), "classic", or "void".

vertical

Logical indicating whether to plot vertically (TRUE, default) or horizontally (FALSE).

Value

A ggplot2 object representing the dendrogram.

Details

This function creates a dendrogram visualization that clearly shows:

  • How individual categories (leaves) are grouped at each level

  • The hierarchical relationships between segments

  • The progressive aggregation from individual categories to larger segments

The dendrogram branches show merging points where categories or segments are combined based on the MONECA algorithm's clique detection. Unlike traditional hierarchical clustering, MONECA can create non-binary trees where multiple categories merge simultaneously.

Visual Features:

  • Curved branches: Uses smooth curves instead of angular segments for better aesthetics

  • Horizontal layout: Levels progress horizontally (left to right) with categories arranged vertically

  • No-Crossing Layout: Categories are automatically ordered using a hierarchical algorithm that completely eliminates line crossings between all levels

The algorithm processes segments from the most aggregated level down, ensuring that at each level, categories are grouped optimally to prevent any crossing lines. This creates the clearest possible visualization of the hierarchical structure.

See also

moneca for the main analysis function, plot_moneca_ggraph for network visualization, plot_stair_ggraph for multi-level visualization

Examples

if (FALSE) { # \dontrun{
# Generate synthetic data and run MONECA
mobility_data <- generate_mobility_data(n_classes = 8, seed = 123)
seg <- moneca(mobility_data, segment.levels = 3)

# Basic dendrogram
plot_moneca_dendrogram(seg)
} # }