#!/usr/bin/env python3 """Procedure-fidelity gates for kcnuX4xEpL reproduction. Usage: python3 gates.py exp01 --toy # structural checks, relaxed params python3 gates.py exp01 --full # structural checks + exact full-scale params python3 gates.py exp01 --full --report Gates verify STRUCTURE / SHAPES / SCHEMA / RANGES / (synthetic) PROVENANCE only. They NEVER encode expected paper outcomes (no beta==1/(d+2) assertions). """ import json, os, sys, math RESULTS = os.path.join(os.path.dirname(os.path.abspath(__file__)), "results", "exp01.json") FULL = { "N": 2000, "M": 2000, "R": 10, "d_grid": [100, 200, 500, 1000], "eps_multipliers": [1e-8, 5e-8, 1e-7, 5e-7, 1e-6, 5e-6, 1e-5, 5e-5, 1e-4, 5e-4], "initTol": 0.01, "tau": 1e-12, "base": 1.00005, "a": 0, "solvers": ["nonlinear_gauss_seidel", "semismooth_newton"], } K = 10 def _num(x): return isinstance(x, (int, float)) and not isinstance(x, bool) def check(results, toy, report): C = [] # (name, ok, detail) def add(name, ok, detail=""): C.append((name, bool(ok), detail)) m = results.get("meta", {}) add("meta present", isinstance(m, dict) and len(m) > 0) # ---- synthetic provenance (this paper uses a SYNTHETIC family, no real dataset) ---- add("provenance: base==1.00005", m.get("base") == 1.00005, str(m.get("base"))) add("provenance: a==0", m.get("a") == 0) add("provenance: tau==1e-12", m.get("tau") == 1e-12) add("provenance: initTol==0.01", m.get("initTol") == 0.01) add("provenance: solvers set", m.get("solvers") == FULL["solvers"], str(m.get("solvers"))) em = m.get("eps_multipliers", []) add("eps_multipliers length 10", isinstance(em, list) and len(em) == K) if isinstance(em, list) and len(em) == K: okm = all(abs(a - b) <= 1e-9 * max(1, abs(b)) for a, b in zip(em, FULL["eps_multipliers"])) add("eps_multipliers match spec grid", okm, str(em)) if not toy: add("full: N==2000", m.get("N") == 2000) add("full: M==2000", m.get("M") == 2000) add("full: R==10", m.get("R") == 10) add("full: d_grid exact", m.get("d_grid") == FULL["d_grid"], str(m.get("d_grid"))) else: add("toy: N present int", _num(m.get("N"))) add("toy: d_grid nonempty", isinstance(m.get("d_grid"), list) and len(m.get("d_grid")) >= 1) d_grid = m.get("d_grid", []) if isinstance(m.get("d_grid"), list) else [] solvers = m.get("solvers", []) if isinstance(m.get("solvers"), list) else [] R = m.get("R", 0) # ---- records ---- recs = results.get("records", []) add("records is list nonempty", isinstance(recs, list) and len(recs) > 0) if not isinstance(recs, list): recs = [] if not toy and d_grid and solvers and _num(R): add("full: record count == len(d_grid)*R*len(solvers)", len(recs) == len(d_grid) * R * len(solvers), f"{len(recs)} vs {len(d_grid) * R * len(solvers)}") fields = ["d", "seed", "solver", "c_med", "eps_actual", "dbias", "converged", "n_active", "beta_hat", "alpha_hat", "rel_err"] all_shape_ok = True all_range_ok = True seen = set() for r in recs: if not isinstance(r, dict): all_shape_ok = False continue if not all(f in r for f in fields): all_shape_ok = False continue seen.add((r.get("d"), r.get("seed"), r.get("solver"))) for arr in ("eps_actual", "dbias", "converged", "n_active"): v = r.get(arr) if not (isinstance(v, list) and len(v) == K): all_shape_ok = False # ranges if not (_num(r.get("c_med")) and r["c_med"] > 0): all_range_ok = False ea = r.get("eps_actual", []) if isinstance(ea, list) and all(_num(x) and x > 0 for x in ea): pass else: all_range_ok = False db = r.get("dbias", []) if isinstance(db, list): for x in db: if x is None: continue if not (_num(x) and x >= 0 and math.isfinite(x)): all_range_ok = False if not (_num(r.get("beta_hat")) and math.isfinite(r["beta_hat"])): all_range_ok = False if r.get("solver") not in solvers: all_range_ok = False if r.get("d") not in d_grid: all_range_ok = False add("all records have required fields", all_shape_ok) add("all record arrays length 10", all_shape_ok) add("record ranges sane (c_med>0, eps>0, dbias>=0/null, beta finite)", all_range_ok) if not toy and d_grid and solvers and _num(R): expected = {(d, s, sv) for d in d_grid for s in range(R) for sv in solvers} add("full: (d,seed,solver) grid complete", seen == expected, f"missing {len(expected - seen)}") # ---- summary ---- summ = results.get("summary", []) add("summary is list nonempty", isinstance(summ, list) and len(summ) > 0) if isinstance(summ, list): sok = True for s in summ: if not isinstance(s, dict): sok = False continue for f in ("d", "solver", "theory", "beta_mean", "beta_std", "rel_err_mean", "rel_err_std"): if f not in s: sok = False if _num(s.get("d")) and _num(s.get("theory")): if abs(s["theory"] - 1.0 / (s["d"] + 2)) > 1e-9: sok = False # theory column must equal 1/(d+2) (definition, not outcome) add("summary rows well-formed; theory==1/(d+2)", sok) if not toy and d_grid and solvers: add("full: summary has len(d_grid)*len(solvers) rows", len(summ) == len(d_grid) * len(solvers), f"{len(summ)} vs {len(d_grid) * len(solvers)}") ok = all(c[1] for c in C) if report: print(f"=== gates report exp01 ({'toy' if toy else 'full'}) ===") for name, cok, detail in C: print(f" [{'PASS' if cok else 'FAIL'}] {name}" + (f" ({detail})" if detail and not cok else "")) print(f"=== {'ALL PASS' if ok else 'FAILURES PRESENT'} ({sum(c[1] for c in C)}/{len(C)}) ===") return ok def main(): args = sys.argv[1:] if not args or args[0] != "exp01": print("usage: python3 gates.py exp01 --toy|--full [--report]") sys.exit(2) toy = "--toy" in args full = "--full" in args if toy == full: print("specify exactly one of --toy / --full") sys.exit(2) report = "--report" in args if not os.path.exists(RESULTS): print(f"[FAIL] results file missing: {RESULTS}") sys.exit(1) try: with open(RESULTS) as f: results = json.load(f) except Exception as e: print(f"[FAIL] cannot parse {RESULTS}: {e}") sys.exit(1) ok = check(results, toy=toy, report=report or True) sys.exit(0 if ok else 1) if __name__ == "__main__": main()