"""Part C — gamma-wall policies on the forward GEX archive (pre-reg 2026-09-09)."""
import gzip, json, glob, os, numpy as np, pandas as pd, warnings
warnings.filterwarnings("ignore")
src=open("crown_policies.py").read().split("\ndf=run()")[0]; cp={}; exec(src, cp)
FP=cp["FP"]; d=cp["load_nq"](); QUAD=cp["QUAD"]
def f(x):
    try: return float(x)
    except: return 0.0
def compute_gamma(rows, spot, window=0.06):
    sks=sorted([(f(r["strike"]),f(r["call_gex"]),f(r["put_gex"])) for r in rows if f(r["strike"])>0])
    if not sks: return None
    net=[c+p for _,c,p in sks]; gross=sum(abs(c)+abs(p) for _,c,p in sks); tilt=sum(net)/gross if gross>0 else 0
    regime="neutral" if abs(tilt)<0.08 else ("long" if tilt>0 else "short")
    lo,hi=spot*(1-window),spot*(1+window); near=[s for s in sks if lo<=s[0]<=hi]; win=near or sks
    above=[s for s in win if s[0]>=spot]; below=[s for s in win if s[0]<=spot]; buf=spot*0.003
    def nearest_sig(c, gex, min_gap=0):
        pool=[s for s in c if abs(s[0]-spot)>=min_gap] if min_gap else c; use=pool or c
        if not use: return None
        peak=max(gex(s) for s in use)
        if peak<=0: return max(use,key=gex)[0]
        sig=[s for s in use if gex(s)>=0.5*peak]
        return min(sig,key=lambda s:abs(s[0]-spot))[0] if sig else max(use,key=gex)[0]
    cw=nearest_sig(above or win, lambda s:s[1], buf) or spot; pw=nearest_sig(below or win, lambda s:-s[2], buf) or spot
    run=0; flip=win[0][0]; mn=float("inf")
    for s in win:
        run+=s[1]+s[2]
        if run<mn: mn=run; flip=s[0]
    return dict(spot=spot, call=cw, put=pw, flip=flip, tilt=tilt, regime=regime)
snaps={}
for path in sorted(glob.glob(f"{FP}/gex/2026/QQQ_*T0910.json.gz")):
    j=json.load(gzip.open(path)); dd=j["data"]; st=dd.get("stock_state") or {}; spot=f(st.get("close")) or f(st.get("prev_close"))
    g=compute_gamma(dd.get("greek_exposure_strike") or [], spot) if spot else None
    if g: snaps[pd.Timestamp(j["et_date"]).date()]=g
print("gamma snapshots usable:",len(snaps), min(snaps) if snaps else "", "→", max(snaps) if snaps else "")
rows=[]
for sday,g in d.groupby("sday"):
    if sday not in snaps: continue
    rth=g[(g["min"]>=570)&(g["min"]<960)].reset_index(drop=True)
    if len(rth)<300 or sday in QUAD: continue
    gm=snaps[sday]; o=rth.iloc[0]["open"]; k=o/gm["spot"]; cw=gm["call"]*k; pw=gm["put"]*k; flip=gm["flip"]*k
    f5=cp["five_min"](rth); c=f5.c.values
    def fade(i):
        if i==0: return 0
        if c[i-1]>cw and c[i]<=cw: return -1
        if c[i-1]<pw and c[i]>=pw: return 1
        return 0
    brk=lambda i: (1 if c[i]>cw else (-1 if c[i]<pw else 0))
    sigs={}
    sigs["P8_longg_fade"]=cp["first_signal"](f5,fade) if gm["regime"]=="long" else (None,0)
    sigs["P9_shortg_break"]=cp["first_signal"](f5,brk) if gm["regime"]=="short" else (None,0)
    close=rth.iloc[-1]["close"]; caged = pw<=close<=cw
    for pol,(i5,side) in sigs.items():
        elig = (pol=="P8_longg_fade" and gm["regime"]=="long") or (pol=="P9_shortg_break" and gm["regime"]=="short")
        w=cp["walk"](rth,int(f5.endmin[i5]),side,f5,i5) if (i5 is not None and side) else None
        rows.append(dict(date=sday,pol=pol,elig=elig,trig=w is not None,side=side,regime=gm["regime"],tilt=round(gm["tilt"],3),cw=round(cw),pw=round(pw),caged=caged,**(w or {})))
    rows.append(dict(date=sday,pol="P10_cage",elig=True,trig=False,side=0,regime=gm["regime"],tilt=round(gm["tilt"],3),cw=round(cw),pw=round(pw),caged=caged))
df=pd.DataFrame(rows); os.makedirs("data",exist_ok=True); df.to_parquet("data/gamma_policy.parquet")
L=[f"# Gamma-wall policies — forward ledger · {pd.Timestamp.now():%Y-%m-%d %H:%M}\n\nSessions with a 09:10 QQQ snapshot: {df.date.nunique()} ({df.date.min()} → {df.date.max()}). Regimes: "+", ".join(f"{k} {v}" for k,v in df[df.pol=='P10_cage'].regime.value_counts().items())+".\n"]
for pol,g in df.groupby("pol"):
    if pol=="P10_cage": L.append(f"- **P10 cage held** (close inside [put wall, call wall]): {g.caged.mean()*100:.0f}% of {len(g)} sessions (live grader: 35%)."); continue
    e=g[g.elig]; t=g[g.trig]
    if not len(t): L.append(f"- **{pol}**: eligible {len(e)}, triggers 0 — n too small."); continue
    L.append(f"- **{pol}**: eligible {len(e)}, triggers {len(t)}, W/L/T {(t.res=='win').sum()}/{(t.res=='loss').sum()}/{(t.res=='timeout').sum()}, R/trigger {t.r.mean():+.3f}, $ at 1 NQ {t.pts.sum()*20:+,.0f} — **n too small (rule needs ≥100)**; ledger accrues.")
L.append("\nPer-session detail:\n"); 
for _,r in df[df.pol!="P10_cage"].sort_values(["date","pol"]).iterrows(): L.append(f"  {r.date} {r.pol:16s} {r.regime:7s} tilt {r.tilt:+.2f} walls {r.pw}–{r.cw} → {('%s %+.2fR' % (r.res, r.r)) if r.trig else 'no trigger'}")
res="\n".join(L); open(f"{FP}/studies/2026-09-09-gamma-policies-ledger.md","w").write(res); print(res)