"""WHERE the remaining gap to Chandrupatla on the wide-bracket set actually is.

Measure before proposing: our best guaranteed configuration reaches CHA 2683 against
Chandrupatla's 2423. Rather than invent a mechanism, this locates the loss per problem and
per family, and reports for each problem what the two methods spend, so the next
pre-registration can name a mechanism that addresses the measured loss.

    python -u diag_cha_gap.py
"""

from __future__ import annotations

import math
from collections import defaultdict

from simroot.baselines import CHANDRUPATLA_BASELINE
from simroot.baselines import best_of, chandrupatla, chandrupatla_scipy
from simroot.pure import pure_root
from sweep_full import ACC, MAXFEV, XTOL, load_problems

CHA_BASE = CHANDRUPATLA_BASELINE   # the library alone (2026-09-21)


def ours(f, a, b):
    st = {}
    x, n, ok = pure_root(f, a, b, XTOL, MAXFEV, similarity="ratio", scale="derived3",
                         guard="safe", prestep="slope", direction="dissimilar", stats=st)
    return x, n, ok, st


def main():
    rows = []
    fam_loss = defaultdict(lambda: [0, 0, 0])      # family -> [ours, theirs, count]
    tot_o = tot_c = 0
    print(f"{'problem':<12} {'ours':>6} {'CH':>6} {'diff':>6} {'w0/xtol decades':>16} "
          f"{'refused%':>9} {'forced%':>8} {'ok':>4}")
    for s, pid, f, a, b, root in load_problems():
        if s != "CHA":
            continue
        x_o, n_o, ok_o, st = ours(f, a, b)
        x_c, n_c, ok_c = CHA_BASE(f, a, b, XTOL, MAXFEV)
        ok_o = bool(ok_o and math.isfinite(x_o) and abs(x_o - root) <= ACC)
        ok_c = bool(ok_c and math.isfinite(float(x_c)) and abs(float(x_c) - root) <= ACC)
        c_o = n_o if ok_o else MAXFEV
        c_c = n_c if ok_c else MAXFEV
        tot_o += c_o
        tot_c += c_c
        fam = pid.split(".")[0]
        fam_loss[fam][0] += c_o
        fam_loss[fam][1] += c_c
        fam_loss[fam][2] += 1
        rows.append((c_o - c_c, pid, c_o, c_c))
        print(f"{pid:<12} {c_o:6d} {c_c:6d} {c_o - c_c:+6d} "
              f"{math.log2(abs(b - a) / XTOL):16.1f} "
              f"{100.0 * st.get('pre_refused', 0) / max(n_o, 1):8.1f}% "
              f"{100.0 * st.get('forced', 0) / max(n_o, 1):7.1f}% "
              f"{'' if ok_o else 'OURS FAIL':>4}")

    print(f"\ntotals: ours {tot_o}, Chandrupatla {tot_c}, gap {tot_o - tot_c:+d}")
    print("\nper family (ours / theirs / gap):")
    for fam in sorted(fam_loss, key=lambda k: -(fam_loss[k][0] - fam_loss[k][1])):
        o, c, n = fam_loss[fam]
        print(f"   {fam:<8} n={n}  {o:6d} / {c:6d}  gap {o - c:+6d}")
    print("\nthe five problems that cost us most:")
    for d, pid, o, c in sorted(rows, reverse=True)[:5]:
        print(f"   {pid:<10} ours {o:4d}  CH {c:4d}  gap {d:+5d}")
    print("\nthe five where we are ahead:")
    for d, pid, o, c in sorted(rows)[:5]:
        print(f"   {pid:<10} ours {o:4d}  CH {c:4d}  gap {d:+5d}")


if __name__ == "__main__":
    main()