#!/usr/bin/env python3
"""Plot fixed-holdout validation for the ten selected calendar RL candidates."""

from pathlib import Path

import matplotlib.pyplot as plt
import pandas as pd


ARTIFACTS = Path(__file__).resolve().parent
INPUT = ARTIFACTS / "top-ten-checkpoint-fixed-validation.csv"
OUTPUT_PNG = ARTIFACTS / "top-ten-checkpoint-fixed-validation.png"
OUTPUT_SVG = ARTIFACTS / "top-ten-checkpoint-fixed-validation.svg"

LABELS = {
    "q3c-rl-calendar-if-v47-r6": "Historical R6 (v2 train verifier)",
    "q3c-rl-calendar-if-v49-nodapo-lr2-r1": "RLOO, LR 2e-6",
    "q3c-rl-calendar-if-v49-nodapo-lr4-r1": "RLOO, LR 4e-6",
    "q3c-rl-calendar-if-v49-dapo-b32-r1": "DAPO, batch 32",
    "q3c-rl-calendar-if-v49-rloo-entropy3e3-stale0-lr1-r1": "RLOO, entropy 0.003, LR 1e-6",
    "q3c-rl-calendar-if-v49-rloo-entropy3e5-lr2-g16-constdenom-warmup4-r1": (
        "RLOO, constant denominator, group 16"
    ),
    "q3c-rl-calendar-agent-v49-sync-r5": "Synchronous RLOO",
    "q3c-rl-calendar-agent-v49-shaped-nodapo-lr2-r1": "Shaped RLOO, LR 2e-6",
    "q3c-rl-calendar-agent-v49-shaped-nodapo-lr4-r1": "Shaped RLOO, LR 4e-6",
    "q3c-rl-calendar-agent-v49-shaped-rloo-entropy3e3-stale0-lr1-r1": (
        "Shaped RLOO, entropy 0.003, LR 1e-6"
    ),
    "q3c-rl-calendar-agent-v49-shaped-rloo-entropy3e5-lr2-g16-constdenom-warmup4-r1": (
        "Shaped RLOO, constant denominator, group 16"
    ),
}


def main() -> None:
    frame = pd.read_csv(INPUT)
    figure, axes = plt.subplots(1, 2, figsize=(18, 11), sharey=True)
    colors = plt.get_cmap("tab10").colors

    for axis, dataset, title in zip(
        axes,
        ("instruction-following", "agent"),
        ("Instruction-following calendar", "Agent calendar"),
        strict=True,
    ):
        subset = frame[frame["dataset"] == dataset]
        base = subset[subset["source_job"] == "Qwen/Qwen3-Coder-30B-A3B-Instruct"].iloc[0]
        axis.axhline(
            base["val_avg_score"],
            color="#5f6368",
            linestyle=(0, (5, 3)),
            linewidth=2,
            label=f"Base model ({base['val_avg_score']:.3f})",
        )

        jobs = [job for job in subset["source_job"].drop_duplicates() if job != base["source_job"]]
        for index, job in enumerate(jobs):
            series = subset[subset["source_job"] == job].sort_values("checkpoint_step")
            historical = job == "q3c-rl-calendar-if-v47-r6"
            color = "#8a8a8a" if historical else colors[index % len(colors)]
            line_style = ":" if historical else "-"
            axis.plot(
                series["checkpoint_step"],
                series["val_avg_score"],
                marker="o",
                markersize=6,
                linewidth=2.5,
                linestyle=line_style,
                color=color,
                label=LABELS[job],
            )
            peak = series.loc[series["val_avg_score"].idxmax()]
            axis.scatter(
                [peak["checkpoint_step"]],
                [peak["val_avg_score"]],
                marker="D",
                s=90,
                color=color,
                edgecolor="white",
                linewidth=1.2,
                zorder=4,
            )

        axis.set_title(title, fontsize=20, fontweight="bold", pad=14)
        axis.set_xlabel("Checkpoint step", fontsize=15)
        axis.set_xticks(sorted(subset["checkpoint_step"].unique()))
        axis.set_xlim(-0.6, subset["checkpoint_step"].max() + 0.8)
        axis.set_ylim(0, 0.52)
        axis.grid(True, alpha=0.25)
        axis.legend(loc="upper center", bbox_to_anchor=(0.5, -0.15), frameon=False, fontsize=11, ncol=2)

    axes[0].set_ylabel("Fixed-holdout mean reward", fontsize=15)
    figure.suptitle("Qwen3-Coder calendar RL checkpoint validation", fontsize=25, fontweight="bold", y=0.98)
    figure.text(
        0.5,
        0.935,
        "Seed-42, 128-task holdouts, temperature 0. All RL candidates trained on sources containing the later holdout; R6 also used the older v2 verifier.",
        ha="center",
        fontsize=14,
        color="#4f4f4f",
    )
    figure.text(0.5, 0.055, "Diamonds mark each curve's peak.", ha="center", fontsize=12, color="#4f4f4f")
    figure.subplots_adjust(top=0.86, bottom=0.27, left=0.08, right=0.98, wspace=0.10)
    figure.savefig(OUTPUT_PNG, dpi=180)
    figure.savefig(OUTPUT_SVG)


if __name__ == "__main__":
    main()