File size: 2,280 Bytes
dd138ec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | """Recompute four-way H stats over all COMPLETE tetratic runs (no checkpoint file).
Persistent: re-run anytime. Prints per-model incoming H + per-seed H->gpt-oss + counts."""
import sqlite3, json
from collections import defaultdict
from pathlib import Path
import numpy as np
HERE = Path(__file__).parent
SHORT = {"Qwen/Qwen3-32B":"Qwen","openai/gpt-oss-20b":"gpt-oss",
"mistralai/Magistral-Small-2509":"Mag","zai-org/GLM-4-32B-0414":"GLM-4"}
perH = defaultdict(list); byseed = defaultdict(list); runs = []
for db in sorted(HERE.glob("tetra_s*_r*.db")):
base = db.stem
if (HERE / f"{base}_checkpoint.json").exists():
continue # incomplete
mp = str(db).replace(".db", ".metadata.json")
if not Path(mp).exists():
continue
seed = base.split("_")[1]
fam = {int(k)+1: SHORT.get(v["model"]) for k, v in json.load(open(mp))["agent_model_map"].items()}
try:
c = sqlite3.connect(db)
posts = c.execute("SELECT post_id,user_id FROM post").fetchall()
coms = c.execute("SELECT post_id,user_id FROM comment").fetchall(); c.close()
except Exception:
continue
owner = {p: u for p, u in posts}; F = sorted(set(fam.values()))
nf = {f: sum(1 for v in fam.values() if v == f) for f in F}; ntot = sum(nf.values())
edges = [(fam[cu], fam[owner[p]]) for p, cu in coms
if owner.get(p) and owner[p] != cu and cu in fam and owner[p] in fam]
tot = len(edges)
if tot < 100:
continue
obs = defaultdict(int)
for x, y in edges: obs[(x, y)] += 1
runs.append(base)
for Y in F:
h = np.mean([obs.get((X, Y), 0)/tot/((nf[X]/ntot)*((nf[Y])/(ntot-1)))-1 for X in F if X != Y])
perH[Y].append(h)
if Y == "gpt-oss": byseed[seed].append(h)
print(f"=== tetratic H over {len(runs)} complete four-way runs ===")
print(f"runs: {sorted(runs)}")
print(f"{'model':8s} {'meanH':>7} {'sd':>6} {'min':>7} {'max':>7} n")
for m in ["gpt-oss", "Qwen", "GLM-4", "Mag"]:
v = np.array(perH[m]) if perH[m] else np.array([np.nan])
print(f"{m:8s} {v.mean():+7.2f} {v.std():6.2f} {v.min():+7.2f} {v.max():+7.2f} {len(perH[m])}")
print("H->gpt-oss by seed:")
for s in sorted(byseed):
v = byseed[s]; print(f" seed {s:5s}: {np.mean(v):+.2f} (n={len(v)})")
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