grip (version 0.2.0)

score.gmds: Score a layout with the common GMDS diagnostic panel

Description

`score.gmds()` provides a common diagnostic panel for GMDS-oriented layouts. It summarizes edge-length fidelity, fixed-path geodesic stress, short/mid/long geodesic bands, ordinary metric-MDS chord stress, and simple spread/shortcut diagnostics for any coordinate matrix on a prepared graph.

Usage

score.gmds(
  coords,
  prepared = NULL,
  edges = NULL,
  n = NULL,
  adj_list = NULL,
  weight_list = NULL,
  edge_weights = NULL,
  scale_mode = c("profiled", "identity", "user"),
  edge_scale = NULL,
  path_scale = NULL,
  chord_scale = NULL,
  distance_floor = 1e-08,
  edge_length_epsilon = 1e-08,
  band_quantiles = c(1/3, 2/3)
)

Value

A one-row data frame with the common diagnostic columns.

Arguments

coords

Numeric coordinate matrix.

prepared

Optional object returned by [prepare.edge.kk()], [prepare.graph.geodesic.mds()] or [prepare.geodesic.kk()]. Edge-only objects from [prepare.edge.kk()] report only edge diagnostics; all-pairs GMDS path and chord diagnostics are unavailable.

edges

Two-column edge matrix used when `prepared` is omitted.

n

Number of vertices used when `prepared` is omitted.

adj_list

Optional adjacency list used when `prepared` is omitted.

weight_list

Optional edge-weight list parallel to `adj_list`.

edge_weights

Optional positive edge weights parallel to `edges`.

scale_mode

Scale policy for edge, path, and chord targets: `"profiled"` fits one scalar for each diagnostic family, `"identity"` uses scale one, and `"user"` uses the corresponding supplied scale.

edge_scale, path_scale, chord_scale

Optional user scales used when `scale_mode = "user"`.

distance_floor

Positive floor for relative residuals.

edge_length_epsilon

Small stabilizer for fixed-path embedded lengths.

band_quantiles

Two quantiles splitting graph distances into short, mid, and long bands.

Examples

cycle_edges <- edges.cycle(6)
theta <- seq(0, 2 * pi, length.out = 7)[-7]
coords <- cbind(cos(theta), sin(theta))
prepared <- prepare.graph.geodesic.mds(cycle_edges, n = 6)
score <- score.gmds(coords, prepared = prepared)