"""Single-run routing figure: training-time hack vs SHIPPED-model hack.

The routing story in one plot. During training the model keeps hacking (it runs
with the quarantine knob ON, so the per-step hack_s curve climbs like vanilla).
But the model we'd actually SHIP has the knob deleted -- its hack rate (the
ship-eval, measured every --eval-ablate-every steps) is what matters. If routing
works, the ship curve sits well BELOW the training curve at preserved solve.

    uv run python scripts/plot_route_evidence.py LOG.log --out out/route_evidence.png

Reads either old (hack_abl/solve_abl) or new (hack_ship/solve_ship) ship columns.
"""
from __future__ import annotations

import sys
from pathlib import Path

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import tyro


def _frac(tok: str) -> float | None:
    if "/" in tok:
        a, b = tok.split("/")
        return int(a) / int(b) if int(b) else None
    try:
        v = float(tok)
        return None if v != v else v          # NaN -> None
    except ValueError:
        return None


def parse(log: Path):
    txt = log.read_text(errors="replace")
    hdr = next(l.split("| INFO |", 1)[1].split() for l in txt.splitlines()
               if "| INFO |" in l and "hack_s" in l and "refr" in l)
    idx = {n: i for i, n in enumerate(hdr)}
    i_step, i_train = idx["step"], idx["hack_s?"]
    i_solve = idx["gt_s↑"]
    i_hship = idx.get("hack_ship", idx.get("hack_abl"))
    i_sship = idx.get("solve_ship", idx.get("solve_abl"))
    steps, train_hack, solve_train = [], [], []
    ship_step, ship_hack, ship_solve = [], [], []
    for l in txt.splitlines():
        if "| INFO |" not in l:
            continue
        r = l.split("| INFO |", 1)[1].split()
        if not r or not r[0].isdigit() or len(r) <= i_sship:
            continue
        s = int(r[i_step])
        steps.append(s)
        train_hack.append(_frac(r[i_train]))
        solve_train.append(_frac(r[i_solve]))
        h = _frac(r[i_hship])
        if h is not None:                       # ship-eval only fires every N steps
            ship_step.append(s); ship_hack.append(h); ship_solve.append(_frac(r[i_sship]))
    return dict(steps=steps, train_hack=train_hack, solve_train=solve_train,
                ship_step=ship_step, ship_hack=ship_hack, ship_solve=ship_solve)


def main(log: str, out: str = "out/route_evidence.png") -> None:
    d = parse(Path(log))
    fig, ax = plt.subplots(figsize=(7, 4.2))
    ax.plot(d["steps"], d["train_hack"], color="#c0392b", lw=2,
            label="hack — training (quarantine knob ON)")
    ax.plot(d["ship_step"], d["ship_hack"], color="#c0392b", lw=2, ls="--",
            marker="o", label="hack — SHIPPED (knob deleted)")
    ax.plot(d["ship_step"], d["ship_solve"], color="#2f7d4f", lw=2,
            marker="s", label="solve — shipped")
    if d["ship_hack"]:
        ax.annotate(f"ship {d['ship_hack'][-1]:.0%}", (d["ship_step"][-1], d["ship_hack"][-1]),
                    textcoords="offset points", xytext=(6, 0), color="#c0392b", fontsize=9)
        ax.annotate(f"train {d['train_hack'][-1]:.0%}", (d["steps"][-1], d["train_hack"][-1]),
                    textcoords="offset points", xytext=(6, 0), color="#c0392b", fontsize=9)
    ax.set_xlabel("GRPO step"); ax.set_ylabel("rate")
    ax.set_ylim(-0.03, 1.03)
    ax.set_title("Gradient routing: model hacks while training, but the\n"
                 "shipped model (cheat-knob deleted) does not", fontsize=11)
    ax.legend(loc="center left", fontsize=8, framealpha=0.9)
    ax.grid(alpha=0.25)
    fig.tight_layout()
    Path(out).parent.mkdir(parents=True, exist_ok=True)
    fig.savefig(out, dpi=130)
    print(f"wrote {out}  (train_hack_final={d['train_hack'][-1]:.3f}, "
          f"ship_hack_final={d['ship_hack'][-1]:.3f}, ship_solve_final={d['ship_solve'][-1]:.3f})")


if __name__ == "__main__":
    tyro.cli(main)