geometry.diagnostics: Geometry-aware diagnostics against a canonical target

Description

geometry.diagnostics() augments the graph-aware quality measures in score.layout() with target-aware geometric diagnostics. The function aligns coords to target.coords using an orthogonal Procrustes fit, then reports global symmetry, local angle preservation, edge-axis concentration, and, for Sierpinski carpet layouts, boundary, corridor, and hole-center diagnostics.

Usage

geometry.diagnostics(
  coords,
  target.coords,
  edges,
  family = NULL,
  sample.size.symmetry = 512L,
  sample.size.wedges = 4000L,
  rng.seed = 1L
)

Value

A one-row data frame of geometric diagnostics.

Arguments

coords: Numeric layout matrix with 2 or 3 columns.
target.coords: Canonical target coordinates with the same shape as coords.
edges: Two-column integer edge matrix.
family: Optional graph-family label. Use "sierpinski.carpet" to enable carpet-specific diagnostics.
sample.size.symmetry: Number of vertices sampled when evaluating global symmetry.
sample.size.wedges: Number of wedges sampled when evaluating local angle deviation.
rng.seed: Integer seed used for the symmetry and wedge sampling.

Details

Metrics are reported so that larger global.symmetry.score and edge.axis.concentration are better, while smaller procrustes.rmse, local.angle.deviation, boundary.waviness, corridor.waviness, hole.center.error, central.hole.skew, central.hole.aspect.error, and central.hole.center.error are better.