"""Summarize accuracy, contact phases and repeated cost for isolated variants."""
import argparse
import json
from pathlib import Path
import statistics

import numpy as np


def read(path):return json.loads(path.read_bytes())


def main():
    parser=argparse.ArgumentParser(description=__doc__)
    parser.add_argument('directory',type=Path)
    args=parser.parse_args();out=args.directory
    runs=read(out/'summary.json');rows=[];branches=[];groups=[]
    for profile,variants in runs.items():
        baseline=variants['off']
        base_force=baseline['groups']['force']['worstAbsolute']['maxAbsoluteError']
        base_time=baseline['timing']['medianSeconds']
        base_curves=np.load(out/profile/'off/curves.npz')
        for mode,r in variants.items():
            data=np.load(out/profile/mode/'curves.npz')
            contacts=[]
            for key in data.files:
                if key.startswith('platform|') and key.endswith('.gap'):
                    expected='amesim|'+key.split('|',1)[1]
                    mismatch=data['phaseMatched'] & ((data[key]<0)!=(data[expected]<0))
                    contacts.extend(dict(key=key.split('|',1)[1],time=float(data['time'][i])) for i in np.flatnonzero(mismatch))
            equal=all(np.array_equal(data[k],base_curves[k],equal_nan=True)
                      for k in data.files if k.startswith('platform|'))
            worst=r['groups']['force']['worstAbsolute'];timing=r['timing'];native=r['nativeRun']
            report=read(out/profile/mode/'comparison.json')
            branches.extend(dict(profile=profile,mode=mode,**c) for c in report['curves'] if c['quantity']=='force')
            groups.extend(dict(profile=profile,mode=mode,quantity=q,**g) for q,g in r['groups'].items())
            counter_keys=('nfev','acceptedSteps','rejectedSteps','solverStarts','stateTransitions','njev','nlu','experimentalEvents')
            counters=[{k:t.get(k) for k in counter_keys} for t in timing['runs']]
            row=dict(profile=profile,mode=mode,medianSolveSeconds=timing['medianSeconds'],
                minimumSolveSeconds=timing['minimumSeconds'],maximumSolveSeconds=timing['maximumSeconds'],
                timingRepeats=timing['repeats'],repeatCountersStable=all(c==counters[0] for c in counters),
                medianCpuSeconds=statistics.median(t['solveCpuSeconds'] for t in timing['runs']),
                solveChangePercent=100*(timing['medianSeconds']/base_time-1),
                forceMaxError=worst['maxAbsoluteError'],forceWorstTime=worst['worstTime'],forceWorstKey=worst['key'],
                forceErrorChangePercent=100*(worst['maxAbsoluteError']/base_force-1),
                forceQuietMax=max(c['quietMaxAbsolute'] for c in report['curves'] if c['quantity']=='force'),
                pressureMaxError=r['groups']['pressure']['worstAbsolute']['maxAbsoluteError'],
                temperatureMaxError=r['groups']['temperature']['worstAbsolute']['maxAbsoluteError'],
                above5PercentCount=r['above5PercentCount'],phaseUnpairedCount=r['phaseUnpairedGridCount'],
                contactPhaseMismatches=contacts,gridTrajectoryEqualsOff=equal,
                rawPeakContactForce=r['extraEventPointMaxContactForce'],
                acceptedSteps=native['acceptedSteps'],rejectedSteps=native['rejectedSteps'],
                nfev=native['nfev'],solverStarts=native['solverStarts'],njev=native['njev'],nlu=native['nlu'],
                stateTransitions=native['stateTransitions'],
                experimentalEvents=native.get('experimentalEvents',{}),jacobianMode=native['jacobianMode'])
            rows.append(row)
            print(json.dumps(row,ensure_ascii=False))
    (out/'effect-summary.json').write_text(json.dumps(rows,ensure_ascii=False,indent=2)+'\n',encoding='utf-8')
    (out/'branch-force-summary.json').write_text(json.dumps(branches,ensure_ascii=False,indent=2)+'\n',encoding='utf-8')
    (out/'group-summary.json').write_text(json.dumps(groups,ensure_ascii=False,indent=2)+'\n',encoding='utf-8')


if __name__=='__main__':main()