"""Tables 2-3 of article/sim_numerics.md regenerated from sweep_full.json.

The published tables predate Chandrupatla's own method as a baseline (it is first on
Alefeld-Potra-Shi) and name the projection variant as proposed, while the code and
the proposed method is the scheduled projection with its multiplier declared (Valeri,
2026-09-21, variant a), the earned projection the constant-free variant.  Baselines are
the library alone (Chandrupatla = scipy elementwise.find_root, Brent = brentq).  This
prints the rows and head-to-head counts from the data, with the SAME ranking function the
verifier uses, so nothing in the new tables is transcribed by hand.

    python -u tables_for_md.py
"""
from __future__ import annotations

from report_sweep import CREDIT, PROPOSED, TUNED, head_to_head, load, place

NONE = "pure.ratio.derived3.none"
NAMES = {PROPOSED: "**proposed: tent, 3-point, projection ($c=2$)**",
         CREDIT: "constant-free variant: earned projection",
         NONE: "the same rule with no safeguard at all",
         "chandrupatla": "Chandrupatla", "toms748": "TOMS 748", "brent": "Brent",
         "dekker": "Dekker", "itp_oracle": "ITP, per-problem oracle",
         "ridders": "Ridders", "itp": "ITP, recommended constants",
         "illinois": "Illinois", "bisection": "bisection",
         "regula_falsi": "false position",
         "pure.sqrt.bracket.project": "similarity, $1-\\sqrt{|z|}$, bracket scale, projection",
         "pure.exp_abs.bracket.both": "similarity, $e^{-|z|}$, bracket scale, both guards"}
APS_ROWS = ("chandrupatla", CREDIT, NONE, "toms748", "brent", "dekker", "itp_oracle",
            "ridders", PROPOSED, "itp", "illinois", "bisection", "regula_falsi")
CHA_ROWS = ("pure.sqrt.bracket.project", "chandrupatla", "itp_oracle",
            "pure.exp_abs.bracket.both", "itp", PROPOSED, "bisection", CREDIT, NONE,
            "toms748", "brent")
OPPONENTS = ("chandrupatla", "toms748", "brent", "itp", "itp_oracle", "bisection")


def main():
    rows = load()
    by = {r["label"]: r for r in rows}
    print(f"configurations in the sweep: {len(rows)}")
    for setname, keys in (("APS", APS_ROWS), ("CHA", CHA_ROWS)):
        n = by[PROPOSED][setname]["n"]
        print(f"\n{setname}, {n} problems")
        print("| # | configuration | tuned | solved | total evals | $>2\\times$ |")
        print("|---|---|---|---|---|---|")
        for k in sorted(keys, key=lambda k: place(rows, setname, k)):
            d = by[k][setname]
            tuned = "yes" if k in TUNED else "no"
            over = "—" if k in ("regula_falsi",) else str(d["over"])
            print(f"| {place(rows, setname, k)} | {NAMES[k]} | {tuned} | "
                  f"{d['solved']}/{n} | {d['total']} | {over} |")
    for lbl in (PROPOSED, CREDIT):
        print(f"\nhead to head, {lbl} (wins/ties/losses on problems both solve)")
        for setname in ("APS", "CHA"):
            cells = []
            for opp in OPPONENTS:
                w, t, l, _ = head_to_head(rows, lbl, opp, setname)
                cells.append(f"{opp} {w}/{t}/{l}")
            print(f"  {setname}: " + ", ".join(cells))
    for lbl in (PROPOSED, CREDIT, "chandrupatla", "toms748", "brent", "itp_oracle"):
        d = by[lbl]
        print(f"  both sets {lbl:34s} {d['APS']['total'] + d['CHA']['total']}")


if __name__ == "__main__":
    main()