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Multi-Level Segmentation Visualization (Stair Plot)

Source: R/modern_plotting.R
plot_stair_ggraph.Rd

Creates a series of network plots showing how segmentation evolves across hierarchical levels in a moneca analysis. This "stair plot" provides insight into the progressive clustering of social positions.

Usage

plot_stair_ggraph(
  segments,
  levels = seq_along(segments$segment.list),
  layout = NULL,
  ncol = 2,
  segment_naming = "auto",
  include_first_level = TRUE,
  ...
)

Arguments

segments

A moneca object returned by moneca.

levels

Integer vector specifying which hierarchical levels to visualize. Default includes all levels.

layout

Layout specification for consistency across plots. Can be:

  • NULL (default): Use layout.matrix() for consistent positioning

  • Character string: Layout algorithm name ("fr", "kk", "stress", etc.)

  • Matrix: Custom coordinate matrix for node positions

ncol

Integer specifying the number of columns in the plot grid. Default is 2. Set to 1 for vertical arrangement.

segment_naming

Specifies how to name segments across all visualization levels. Can be:

  • Character string: "auto" (default), "concat", "pattern", or "custom" - these are passed to segment.membership.enhanced for automatic naming

  • data.frame: Custom segment labels with columns "name" (node names from the mobility matrix) and "segment_label" (desired custom labels). This allows complete control over segment naming across all hierarchical levels

  • NULL: Uses default "auto" strategy

When a data.frame is provided, custom labels override automatically generated names consistently across all levels. The data.frame approach is particularly useful for stair plots as it maintains consistent naming across the hierarchical progression.

include_first_level

Logical indicating whether to include the first level (individual classes without segmentation). Default is TRUE.

...

Additional arguments passed to plot_moneca_ggraph.

Value

If combine_plots = TRUE, returns a combined plot grid object. If combine_plots = FALSE, returns a list of ggplot objects, one for each level.

Details

The stair plot helps visualize the hierarchical nature of MONECA segmentation by showing how larger segments at higher levels break down into smaller, more specific segments at lower levels. This is particularly useful for:

  • Understanding the segmentation process

  • Identifying optimal levels of analysis

  • Presenting results to different audiences

  • Comparing segmentation stability across levels

When using a consistent layout across all plots, the relative positions of nodes remain the same, making it easier to track how segments evolve.

See also

plot_moneca_ggraph for single-level visualization, plot_ego_ggraph for ego network analysis, layout.matrix for consistent layouts, moneca for the main analysis function

Examples

if (FALSE) { # \dontrun{
# Generate synthetic data and run MONECA
mobility_data <- generate_mobility_data(n_classes = 6, seed = 123)
seg <- moneca(mobility_data, segment.levels = 4)

# Basic stair plot
stair_plots <- plot_stair_ggraph(seg)

# Customized stair plot with specific levels
custom_stair <- plot_stair_ggraph(seg,
                                 levels = c(2, 3),
                                 layout = "stress",
                                 ncol = 1)
} # }