"""Policy counterfactuals on measured worker evidence arrival times.
All crops enter together; these are not camera/UI end-to-end timings.
"""
from pathlib import Path
import json
from statistics import median
from analyze import POLICIES,decide,infer_groups,propagate,metrics

DIR=Path(__file__).resolve().parent;OUT=DIR/'evidence'


def main():
    frozen=json.loads((OUT/'observations.json').read_text())
    data=frozen['resolutions']['live'];sig=frozen['signatures']
    edges=json.loads((OUT/'analysis.json').read_text())['resolutions']['live']['guarded_edges']
    events=json.loads((OUT/'anytime-events.json').read_text())
    families=json.loads((DIR/'group-truth.json').read_text())['families']
    report={'clock':'Measured local/OCR completion; frozen appearance edges are precomputed, grouping and transport time excluded. Diagnostic counterfactual, not live deployment.','policies':{}}
    horizon=events['complete_ms']+1000
    for policy in POLICIES:
        for grouped in (False,True):
            rows={o['id']:{**o,'rank':[],'local':{},'text':{},'read':''} for o in data['observations']}
            history={i:[(0.,None)] for i in rows};snapshots={};current={i:None for i in rows}
            for event in sorted(events['events'],key=lambda e:e['ms']):
                for delay in (250,500,1000):
                    if delay<event['ms'] and str(delay) not in snapshots:snapshots[str(delay)]=metrics(list(rows.values()),current,families)
                o=rows[event['id']]
                if event['kind']=='local':o['rank']=event['rank']
                else:o['read']=event['read'];o['text']=event['text']
                obs=list(rows.values());base={i:decide(o,policy,sig) for i,o in rows.items()}
                groups=infer_groups(data,edges,{i:decide(o,'strict',sig) for i,o in rows.items()})
                current=propagate(obs,groups,base,sig,guarded=True)[0] if grouped else base
                for i,sku in current.items():
                    if sku!=history[i][-1][1]:history[i].append((event['ms'],sku))
            for delay in (250,500,1000):snapshots.setdefault(str(delay),metrics(list(rows.values()),current,families))
            first=[];stable=[];flips=0;corrections=0;blank_ms=wrong_ms=sibling_ms=0.
            for i,h in history.items():
                truth=rows[i]['truth'];named=[at for at,sku in h if sku]
                if named:first.append(min(named))
                if h[-1][1]==truth and truth!='unknown':stable.append(h[-1][0])
                previous=None
                for (_,sku),(end,_) in zip(h,h[1:]+[(horizon,None)]):
                    if sku and previous and sku!=previous:
                        flips+=1;corrections+=sku==truth
                    if sku:previous=sku
                for (at,sku),(end,_) in zip(h,h[1:]+[(horizon,None)]):
                    duration=end-at
                    if not sku:blank_ms+=duration
                    elif sku!=truth:
                        wrong_ms+=duration
                        if truth in families and families.get(sku)==families[truth]:sibling_ms+=duration
            final=metrics(list(rows.values()),current,families)
            assert final['correct']+final['wrong']==final['shown']<=109
            report['policies'][policy+('/grouped' if grouped else '/individual')]={'final':final,'timed':snapshots,'first_any_ms':min(first) if first else None,'first_per_facing_p50_ms':median(first) if first else None,'time_to_final_correct_p50_ms':median(stable) if stable else None,'identity_flips':flips,'wrong_to_correct_events':corrections,'blank_facing_ms':blank_ms,'wrong_facing_ms':wrong_ms,'wrong_sibling_facing_ms':sibling_ms,'loss_proxy':(blank_ms+1.5*sibling_ms+4*(wrong_ms-sibling_ms)+200*flips)/(109*horizon),'horizon_ms':horizon}
    (OUT/'anytime-policies.json').write_text(json.dumps(report,ensure_ascii=False,indent=2))
    for name,r in report['policies'].items():print(name,r['final']['shown'],r['final']['correct'],round(r['first_per_facing_p50_ms'],1),r['identity_flips'],round(r['loss_proxy'],3))

if __name__=='__main__':main()