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Compare multiple layout candidates across seeds

Source: R/grip_quality.R
compare.layouts.Rd

compare.layouts() computes layouts for several candidate presets or parameter lists, optionally expands a local parameter search, scores each run with score.layout(), and summarizes both quality metrics and seed-to-seed stability. This is the main real-data workflow for graphs where no canonical embedding is known.

Usage

compare.layouts(
  edges = NULL,
  n = NULL,
  adj_list = NULL,
  weight_list = NULL,
  edge_weights = NULL,
  dim = 2,
  candidates = c("default"),
  search = NULL,
  clusters = NULL,
  seeds = 1:3,
  sample.size.stress = 2000L,
  sample.size.nonedge = 5000L,
  edge.crossings = c("auto", "always", "never"),
  edge.crossings.max.edges = 1000L,
  score.weights = grip.default.compare.score.weights(),
  return.layouts = FALSE,
  disconnected = c("components", "error")
)

Arguments

edges

Two-column integer matrix of edges (1-based vertex ids).

n

Number of vertices.

adj_list

Adjacency list (1-based) for undirected graphs.

weight_list

Optional parallel list of positive edge weights.

edge_weights

Optional positive edge-weight vector parallel to edges.

dim

Layout dimension (2 or 3).

candidates

Either a character vector such as c("default", "mesh", "tree") or a named list of candidate layout specifications. Each list element may be NULL (use defaults), a single preset name, or a named list of grip() tuning arguments such as preset, placement, rounds, or repulsion_factor.

Optional named list describing a grid search over layout settings. Any of preset, placement, rounds, final_rounds, num_init, num_nbrs, r, s, repulsion_factor, and tinit_factor may be supplied as vectors. All combinations are expanded into candidates. Special fields candidate.prefix and include.base control candidate naming and whether the all-first-values setting is guaranteed to appear.

clusters

Optional cluster or community labels used to compute cluster.separation.

seeds

Integer seeds used for repeated runs.

sample.size.stress

Number of sampled pairs used for sampled.stress.

sample.size.nonedge

Number of sampled non-edge pairs used for sampled.nonedge.sep.ratio.

edge.crossings

How to compute edge.crossings for 2D layouts.

edge.crossings.max.edges

Edge-count threshold for edge.crossings = "auto".

score.weights

Optional named numeric vector used to compute score.composite. Set to NULL to omit the composite score.

return.layouts

If TRUE, include the realized coordinate matrices in the return value.

disconnected

Passed through to grip().

Value

A list with runs and summary data frames and, optionally, realized layouts.

Examples

edges <- edges.path(5)
cmp <- compare.layouts(
  edges = edges,
  n = 5,
  dim = 2,
  candidates = c("default", "tree"),
  seeds = 1L
)
cmp$summary[, c("candidate", "rounds", "final.rounds")]
#>   candidate rounds final.rounds
#> 1   default     20           25
#> 2      tree     64          160

search.cmp <- compare.layouts(
  edges = edges,
  n = 5,
  dim = 2,
  search = list(
    candidate.prefix = "path.search",
    rounds = c(4L, 6L),
    final_rounds = c(4L, 6L)
  ),
  seeds = 1L
)
search.cmp$summary[, c("candidate", "rounds", "final.rounds")]
#>                             candidate rounds final.rounds
#> 1 path.search.rounds.6.final_rounds.4      6            4
#> 2 path.search.rounds.6.final_rounds.6      6            6
#> 3 path.search.rounds.4.final_rounds.4      4            4
#> 4 path.search.rounds.4.final_rounds.6      4            6