"""§12 teacher-bias check: re-run published echoes and compare."""
import asyncio, json, sys, glob, os, statistics as st
sys.path.insert(0, '/workspace/af-eval')
from tclient import score_action

SCR = '/tmp/claude-0/-workspace/6f4c3d56-0e4f-49c0-aa06-affb765ae406/scratchpad'
pref = json.load(open('prefixes300.json'))
sel = json.load(open(SCR + '/sample300.json'))[:12]

async def main():
    deltas_own, deltas_empty, deltas_za = [], [], []
    sem = asyncio.Semaphore(4)
    async def one(tid):
        d = json.load(open(SCR + '/turns/' + tid.replace('/', '_') + '.json'))
        P = pref[tid]['prefix']
        out = []
        for r in d['teacher_refs']:
            async with sem:
                own = await score_action(P, r['thought'], r['action'])
                emp = await score_action(P, "", r['action'])
            out.append((own['lp_per_byte'] - r['lp_own'], emp['lp_per_byte'] - r['lp_empty']))
        # also a king pair: lpC(y_i | z_king)
        kp = d['king']['pairs']
        zk = kp[0]['thought']
        za = []
        for i, r in enumerate(d['teacher_refs']):
            if i >= len(kp): break
            async with sem:
                s = await score_action(P, zk, r['action'])
            za.append(s['lp_per_byte'] - kp[i]['lpC_yc_za'])
        return out, za
    res = await asyncio.gather(*[one(t) for t in sel])
    for out, za in res:
        for a, b in out:
            deltas_own.append(a); deltas_empty.append(b)
        deltas_za += za
    def rep(name, v):
        if not v: print(name, 'no data'); return
        m = st.mean(v); sd = st.pstdev(v) if len(v) > 1 else 0.0
        se = sd / (len(v) ** 0.5) if v else 0
        print(f"{name:14s} n={len(v):3d} mean {m:+.3e}  sd {sd:.3e}  SE {se:.3e}  max|d| {max(abs(x) for x in v):.3e}")
    rep('lpC(y|z_own)', deltas_own)
    rep('lpC(y|empty)', deltas_empty)
    rep('lpC(y_i|z_K)', deltas_za)

asyncio.run(main())