dress-graph 0.7.0

DRESS: A deterministic, parameter-free framework for canonical graph fingerprinting via continuous structural edge refinement.

dress-graph (Python)

A Continuous Framework for Structural Graph Refinement

DRESS is a deterministic, parameter-free framework that iteratively refines the structural similarity of edges in a graph to produce a canonical fingerprint: a real-valued edge vector, obtained by converging a non-linear dynamical system to its unique fixed point. The fingerprint is self-contained, isomorphism-invariant by construction, guaranteed bitwise-equal across any vertex labeling, numerically stable (no overflow, no error amplification, no undefined behavior), fast and embarrassingly parallel to compute: DRESS total runtime is O(I * m * d_max) for I iterations to convergence, and convergence is guaranteed by Birkhoff contraction.

Install

pip install dress-graph

Quick start

from dress import dress_fit

result = dress_fit(
    n_vertices=4,
    sources=[0, 1, 2, 0],
    targets=[1, 2, 3, 3],
)
print(result.edge_dress)  # DRESS value for each edge

For the full API and documentation, see the main repository.