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Classical-MDS baseline layout for GMDS experiments

Source: R/export_examples.R, R/gmds_layout_interface.R
classical.mds.Rd

classical.mds() computes the classical-MDS baseline using stats::cmdscale() on the graph shortest-path distance matrix and returns a common "grip_gmds_layout" result.

Usage

classical.mds(
  prepared = NULL,
  edges = NULL,
  n = NULL,
  adj.list = NULL,
  weight.list = NULL,
  edge.weights = NULL,
  dim = 2L,
  add = FALSE,
  eig = TRUE,
  diagnostics = TRUE,
  scale.mode = c("profiled", "identity", "user"),
  distance.floor = 1e-08,
  edge.length.epsilon = 1e-08,
  band.quantiles = c(1/3, 2/3)
)

Arguments

prepared

Optional all-pairs prepared object returned by prepare.graph.geodesic.mds() or prepare.geodesic.kk(). Edge-only objects from prepare.edge.kk() are intentionally rejected because classical MDS requires a graph distance matrix.

edges

Two-column integer edge matrix used when prepared is omitted. Supply either edges/edge.weights or adj.list/weight.list, not both. Raw graph inputs cannot be combined with a prepared object.

n

Finite positive integer vertex count. When supplied with a prepared object, it must match the stored graph size.

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.

dim

Target embedding dimension. Values greater than 3 are supported for GMDS and edge-KK workflows.

add, eig

Passed to stats::cmdscale().

diagnostics

If TRUE, attach the common GMDS diagnostic panel. If FALSE and raw graph inputs are supplied, classical.mds() uses a distance-matrix-only preparation path and does not build the full all-pairs path cache.

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.

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.

Value

A "grip_gmds_layout" object.

Workflow guides

Start with vignette("function-guide", package = "grip") to choose a layout, diagnostic, or reference comparison. List installed guides with vignette(package = "grip").

Examples

cycle_edges <- edges.cycle(6)
prepared <- prepare.graph.geodesic.mds(cycle_edges, n = 6)
fit <- classical.mds(prepared = prepared, dim = 2)