| Type: | Package |
| Title: | Diffusive Recursive Structural Similarity on Graphs |
| Version: | 0.1.2 |
| Description: | Compute per-edge similarity values on graphs using the DRESS (Diffusive Recursive Structural Similarity) algorithm. Supports weighted/unweighted and directed/undirected graphs. Iterative fixed-point fitting converges to stable edge scores that capture neighbourhood overlap structure. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| NeedsCompilation: | yes |
| SystemRequirements: | OpenMP |
| Packaged: | 2026-02-21 00:21:19 UTC; velic |
| Author: | Eduar Castrillo Velilla [aut, cre] |
| Maintainer: | Eduar Castrillo Velilla <velicast@outlook.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-02-25 19:00:08 UTC |
Compute DRESS Edge Similarity on Graphs
Description
Build a DRESS graph from an edge list and run iterative fitting to compute per-edge structural similarity values.
Usage
dress_fit(n_vertices, sources, targets, weights = NULL,
variant = DRESS_UNDIRECTED, max_iterations = 100L,
epsilon = 1e-6, precompute_intercepts = FALSE)
dress_version()
DRESS_UNDIRECTED
DRESS_DIRECTED
DRESS_FORWARD
DRESS_BACKWARD
Arguments
n_vertices |
Integer. Number of vertices (vertex ids must be in
|
sources |
Integer vector of length E – edge source endpoints (0-based). |
targets |
Integer vector of length E – edge target endpoints (0-based). |
weights |
Optional numeric vector of length E – per-edge weights.
|
variant |
Graph variant (default |
max_iterations |
Maximum number of fitting iterations (default 100). |
epsilon |
Convergence threshold – stop when the max per-edge change falls below this value (default 1e-6). |
precompute_intercepts |
Logical. Pre-compute common-neighbor index
for faster iteration at the cost of more memory (default |
Value
A list with components:
sources |
Integer vector [E] – edge source endpoints (0-based). |
targets |
Integer vector [E] – edge target endpoints (0-based). |
edge_dress |
Numeric vector [E] – DRESS similarity per edge. |
edge_weight |
Numeric vector [E] – variant-specific weight. |
node_dress |
Numeric vector [N] – per-node norm. |
iterations |
Integer – number of iterations performed. |
delta |
Numeric – final max per-edge change. |
References
E. Castrillo, E. Leon, J. Gomez. Dynamic Structural Similarity on Graphs. arXiv:1805.01419, 2018.
Examples
# Triangle + pendant: 0-1, 1-2, 2-0, 2-3
res <- dress_fit(4L, c(0L,1L,2L,2L), c(1L,2L,0L,3L))
res$edge_dress