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Compare multiple cluster4d results

Source: R/cluster4d_methods.R
compare_cluster4d.Rd

Compares clustering results over exactly the same included mask voxels and physical coordinate system. Ambiguous center-based scores are not used.

Usage

compare_cluster4d(
  ...,
  metrics = c("summary", "spatial_dispersion"),
  feature_mat = NULL
)

Arguments

...

cluster4d_result objects to compare

metrics

Character vector selecting explicit estimands:

  • "summary": cluster-count and cluster-size summaries.

  • "spatial_dispersion": root mean squared physical distance in millimetres from voxels to their final cluster centroid (lower is more compact).

  • "temporal_coherence": mean Pearson correlation across all unordered within-cluster voxel pairs, requiring feature_mat.

  • "partition_agreement": adjusted Rand index, variation of information in bits, and pairwise Dice for exactly two results.

feature_mat

A shared finite numeric matrix with voxels in rows and at least two time/features in columns. Required only for "temporal_coherence". Rows must be non-constant.

Value

A data frame with one row per result and explicitly named metrics.

Details

Every result must carry canonical mask and affine provenance. The exact included voxel indices and physical geometry are checked before any cross-result comparison. Partition metrics use only observed contingency cells and never construct an N-by-N co-membership matrix. Pairwise agreement columns are repeated on the two result rows so the return value remains a data frame.