# Detect wall crosses (calls: up through heaviest CE strike; puts: down through heaviest PE strike) + outcomes + random same-minute base.
import numpy as np,pandas as pd,sys,os,warnings; warnings.filterwarnings('ignore')
sys.path.insert(0,os.path.dirname(__file__)); from cwlib import *
DD=load(); rows=[]
def wall(D,j,sgn,lo,hi):
    c=D['c'][j]
    if c!=c: return None
    K=D['K']; oi=D['oi_CE' if sgn>0 else 'oi_PE'][j]
    m=((K>=c)&(K<=c+hi)) if sgn>0 else ((K<=c)&(K>=c-hi)); m&=np.isfinite(oi)
    if lo=='strict': m&=(K>c) if sgn>0 else (K<c)
    if not m.any(): return None
    return K[m][np.argmax(oi[m])]
for d,D in sorted(DD.items()):
    c=D['c']; K=D['K']; basis=D['fut']-c
    for sgn in (1,-1):
        own='oi_CE' if sgn>0 else 'oi_PE'; opp='oi_PE' if sgn>0 else 'oi_CE'
        fixedW=wall(D,5,sgn,'strict',1000)
        seen=set(); fixed_done=False
        for i in range(1,LASTX+1):
            if c[i]!=c[i] or c[i-1]!=c[i-1]: continue
            for wd in ('dyn','fixed'):
                if wd=='dyn': W=wall(D,i-1,sgn,'ge',300)
                else:
                    if i<=5 or fixed_done: continue
                    W=fixedW
                if W is None: continue
                crossed=(c[i-1]<W<=c[i]) if sgn>0 else (c[i-1]>W>=c[i])
                if not crossed or (wd=='dyn' and W in seen): continue
                if wd=='dyn': seen.add(W)
                else: fixed_done=True
                k=np.where(K==W)[0][0]; oo=D[own][:,k]; op=D[opp][:,k]
                r=dict(date=d,exp=D['exp'],dte=(D['exp']-d).days,wd=d.dayofweek,side='call' if sgn>0 else 'put',wall=wd,K=W,i=i,hm=HM[i],spot=c[i],
                       own_oi_ref=oo[i-1],opp_oi_chg30=(op[i]/op[max(0,i-30)]-1)*100 if op[max(0,i-30)]>0 else np.nan,
                       own_oi_chg30_before=(oo[i-1]/oo[max(0,i-31)]-1)*100 if oo[max(0,i-31)]>0 else np.nan)
                for kk in (1,2,3):
                    r[f'own_drop{kk}']=(oo[i+kk]/oo[i-1]-1)*100 if oo[i-1]>0 and i+kk<375 else np.nan
                for X in (1,2,3):
                    s=next((i+kk for kk in (1,2,3) if r[f'own_drop{kk}']==r[f'own_drop{kk}'] and r[f'own_drop{kk}']<=-X),None)
                    r[f's_X{X}']=s if s is not None else -1
                    r[f'basis_chg5_X{X}']=(basis[s]-basis[s-5]) if s is not None else np.nan
                r['basis_chg5_X0']=basis[i]-basis[i-5] if i>=5 else np.nan
                rows.append(r)
E=pd.DataFrame(rows)
# outcomes at every needed signal minute (cross minute for (a), first OI-drop minute for X)
for X in (0,1,2,3):
    col='i' if X==0 else f's_X{X}'; res=[]
    for r in E.itertuples():
        s=getattr(r,col); o=outcome(DD[r.date],s,1 if r.side=='call' else -1) if s>=0 else None
        res.append({f'{k}_X{X}':v for k,v in (o or {}).items()})
    E=pd.concat([E,pd.DataFrame(res,index=E.index)],axis=1)
E.to_pickle(f'{C}/results/events.pkl'); E.to_csv(f'{C}/results/events.csv',index=False)
print(E.groupby(['side','wall']).size()); print(E.groupby(['side','wall']).date.nunique())
# random same-minute base: outcome for every day x minute 0..LASTX+3, both sides
base={}
for d,D in sorted(DD.items()):
    for sgn in (1,-1):
        for s in range(0,LASTX+4):
            o=outcome(D,s,sgn)
            if o: base[(d,sgn,s)]=o
B=pd.DataFrame.from_dict(base,orient='index'); B.index.names=['date','sgn','s']; B.to_pickle(f'{C}/results/base_outcomes.pkl'); print('base rows',len(B))