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Feature Extraction
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csv
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Tags:
graph-theory
graph-isomorphism
color-refinement
weisfeiler-lehman
structural-invariants
graph-kernels
License:
Download codigo/wl.py from Jose-dev/graphkind-universos: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Jose-dev/graphkind-universos/resolve/main/codigo/wl.py
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hf download hf://datasets/Jose-dev/graphkind-universos/codigo/wl.py
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curl -L -o wl.py https://huggingface.co/datasets/Jose-dev/graphkind-universos/resolve/main/codigo/wl.py
5.53 kB
| """Color refinement (WL) y utilidades — autocontenido. | |
| - wl_sym: WL simétrico (in/out por color, grados crudos) — el del teorema. | |
| - wl_k_colors: k-FWL (folklore, correlacionada; ≡ (k+1)-WL) — la jerarquía | |
| de observadores. El nombre "k-WL" a secas designa la variante estándar | |
| (multiséts separados por posición), que es estrictamente más débil. | |
| - helpers de grafos (bitmasks), complemento, digrafos. | |
| """ | |
| import hashlib | |
| from collections import Counter | |
| from itertools import product | |
| def h(s): | |
| return hashlib.sha256(s.encode()).hexdigest()[:12] | |
| def wl_sym(n, adj, f, h_fn=None, info=False, rondas_fijas=None): | |
| """Perfil del WL simétrico: multiset de tamaños de clase. | |
| Por defecto corre hasta que la partición se estabiliza (tope n+2). | |
| `h_fn` permite cambiar la función de hash (certificado de colisión); | |
| `rondas_fijas` fuerza un número exacto de rondas (certificado de | |
| convergencia); `info=True` devuelve (perfil, rondas_usadas). | |
| """ | |
| hh = h_fn or h | |
| in_adj = transp(n, adj) | |
| colors = [hh(f"g|{adj[v].bit_count()}|{in_adj[v].bit_count()}") | |
| for v in range(n)] | |
| prev = None | |
| usadas = 0 | |
| tope = rondas_fijas if rondas_fijas is not None else (n + 2) | |
| for r in range(tope): | |
| new = [] | |
| for v in range(n): | |
| cnt = Counter() | |
| m = adj[v] | |
| while m: | |
| u = (m & -m).bit_length() - 1 | |
| m &= m - 1 | |
| cnt[colors[u]] += 1 | |
| ci = Counter() | |
| m = in_adj[v] | |
| while m: | |
| u = (m & -m).bit_length() - 1 | |
| m &= m - 1 | |
| ci[colors[u]] += 1 | |
| keys = set(cnt) | set(ci) | |
| prof = tuple(sorted((c, f(ci.get(c, 0)), f(cnt.get(c, 0))) | |
| for c in keys)) | |
| new.append(hh(f"{colors[v]}|{prof}")) | |
| colors = new | |
| usadas = r + 1 | |
| if rondas_fijas is None: | |
| part = tuple(sorted(Counter(colors).values())) | |
| if part == prev: | |
| break | |
| prev = part | |
| perfil = tuple(sorted(Counter(colors).values())) | |
| return (perfil, usadas) if info else perfil | |
| def transp(n, adj): | |
| out = [0] * n | |
| for v in range(n): | |
| m = adj[v] | |
| while m: | |
| u = (m & -m).bit_length() - 1 | |
| m &= m - 1 | |
| out[u] |= 1 << v | |
| return out | |
| def wl_k_colors(n, adj, k, rounds=None): | |
| """k-FWL (folklore, correlacionada; ≡ (k+1)-WL): colores de k-tuplas. | |
| La actualización usa pares de posiciones (i,j) con el MISMO w; por la | |
| equivalencia conocida es tan fuerte como (k+1)-WL. La variante estándar | |
| ("k-WL", multiséts separados) es más débil y NO separa Rook de | |
| Shrikhande en k=3 (ver EXP-159 del laboratorio).""" | |
| if rounds is None: | |
| rounds = n + 2 | |
| tuplas = list(product(range(n), repeat=k)) | |
| def init(t): | |
| grados = [str(adj[a].bit_count()) for a in t] | |
| est = [] | |
| for i in range(k): | |
| for j in range(i + 1, k): | |
| a, b = t[i], t[j] | |
| est.append("=" if a == b else | |
| ("1" if (adj[a] >> b) & 1 else "0")) | |
| return h("|".join(grados) + ":" + "".join(est)) | |
| colors = {t: init(t) for t in tuplas} | |
| prev = None | |
| for _ in range(rounds): | |
| new = {} | |
| for t in tuplas: | |
| vecinos = [] | |
| for i in range(k): | |
| for j in range(i + 1, k): | |
| for w in range(n): | |
| t2 = t[:i] + (w,) + t[i + 1:] | |
| t3 = t[:j] + (w,) + t[j + 1:] | |
| vecinos.append((i, j, colors[t2], colors[t3])) | |
| vecinos.sort() | |
| new[t] = h(colors[t] + "|" + ",".join( | |
| f"{i}{j}:{a}:{b}" for i, j, a, b in vecinos)) | |
| colors = new | |
| firma = tuple(sorted(colors.values())) | |
| if firma == prev: | |
| break | |
| prev = firma | |
| return colors | |
| def wl_k_union(adj1, adj2, k): | |
| n1, n2 = len(adj1), len(adj2) | |
| n = n1 + n2 | |
| adj_u = [0] * n | |
| for v in range(n1): | |
| adj_u[v] = adj1[v] | |
| for v in range(n2): | |
| adj_u[n1 + v] = adj2[v] << n1 | |
| return wl_k_colors(n, adj_u, k, rounds=n + 2) | |
| def separados(adj1, adj2, k): | |
| """¿k-FWL separa los dos grafos? (colores compartidos en la unión).""" | |
| n1 = len(adj1) | |
| colors = wl_k_union(adj1, adj2, k) | |
| c1 = Counter(colors[t] for t in product(range(n1), repeat=k)) | |
| c2 = Counter(colors[t] for t in product(range(n1, n1 + len(adj2)), | |
| repeat=k)) | |
| return set(c1) != set(c2) or sorted(c1.values()) != sorted(c2.values()) | |
| def build_adj(n, mask): | |
| adj = [0] * n | |
| bit = 0 | |
| for i in range(n): | |
| for j in range(i + 1, n): | |
| if (mask >> bit) & 1: | |
| adj[i] |= 1 << j | |
| adj[j] |= 1 << i | |
| bit += 1 | |
| return adj | |
| def comp_adj(n, adj): | |
| out = [0] * n | |
| for i in range(n): | |
| for j in range(i + 1, n): | |
| if not (adj[i] >> j) & 1: | |
| out[i] |= 1 << j | |
| out[j] |= 1 << i | |
| return out | |
| def all_digraphs(n): | |
| pos = [(u, v) for u in range(n) for v in range(n) if u != v] | |
| for mask in range(1 << len(pos)): | |
| adj = [0] * n | |
| for k, (u, v) in enumerate(pos): | |
| if (mask >> k) & 1: | |
| adj[u] |= 1 << v | |
| yield mask, adj | |
| def all_graphs(n): | |
| for mask in range(1 << (n * (n - 1) // 2)): | |
| yield mask, build_adj(n, mask) | |