from pathlib import Path
import json, html, csv, shutil
import matplotlib

matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from matplotlib.backends.backend_pdf import PdfPages
from .paths import paths

P, D = paths()
R = json.loads((D / "RESULT.json").read_text())
V = json.loads((D / "VALIDATION.json").read_text())
plt.rcParams.update(
    {
        "font.family": "DejaVu Sans",
        "font.size": 11,
        "axes.spines.top": False,
        "axes.spines.right": False,
        "pdf.fonttype": 42,
        "svg.fonttype": "none",
        "text.color": "#19324a",
    }
)
colors = ["#9BAABD", "#007F86", "#3178BD", "#9D5CBB"]
figs = []
joint = []
for pair, title, scope in [
    ("tmax", "TMax-27B (27B)", "Terminal-Bench 2.1 | 253 normal trials"),
    ("deepswe", "DeepSWE-Preview (32B)", "SWE-bench Verified | 1,998 generations"),
]:
    r = R[pair]
    entries = [
        {
            "objective": "fifo",
            "minutes": r["deadline_minutes"],
            "all_resource_hours": {
                k: r["baseline"][k]["hours"]
                for k in ["cpu", "memory", "gpu", "storage"]
            },
        }
    ] + [
        next(v for v in V if v["pair"] == pair and v["objective"] == o)
        for o in ["cpu", "gpu"] + (["storage"] if pair == "deepswe" else [])
    ]
    names = [
        "FIFO baseline",
        "CPU/RAM minimum: fastest found",
        "GPU-hours: best found",
        "Cache-hours: best found",
    ][: len(entries)]
    fig, axs = plt.subplots(2, 2, figsize=(13.5, 9.5), facecolor="white")
    fig.subplots_adjust(
        left=0.09, right=0.97, top=0.72, bottom=0.15, hspace=0.46, wspace=0.30
    )
    fig.text(
        0.09, 0.956, title + " — Resource-Hours by Schedule", fontsize=21, weight="bold"
    )
    fig.text(
        0.09,
        0.91,
        f"{scope} | Completion time ≤ FIFO ({r['deadline_minutes']:,.2f} min)",
        fontsize=12,
        color="#536577",
    )
    fig.legend(
        handles=[
            Patch(facecolor=colors[i], label=f"{name} · {e['minutes']:,.2f} min")
            for i, (name, e) in enumerate(zip(names, entries))
        ],
        loc="upper left",
        bbox_to_anchor=(0.08, 0.875),
        ncol=2,
        frameon=False,
        fontsize=10.5,
        columnspacing=2,
    )
    for ax, res, ttl, unit in zip(
        axs.flat,
        ["cpu", "memory", "gpu", "storage"],
        ["CPU", "Memory", "GPU", "Storage: compressed image cache"],
        ["core-hours", "GiB-hours", "GPU-hours", "GiB-hours"],
    ):
        vals = [e["all_resource_hours"][res] for e in entries]
        ax.set_title(ttl, loc="left", fontsize=13, weight="bold", pad=11)
        ax.set_ylabel(unit)
        ax.set_xticks([])
        ax.set_axisbelow(True)
        ax.grid(axis="y", alpha=0.16)
        if vals[0] is None:
            ax.set_yticks([])
            ax.text(
                0.5,
                0.45,
                "Not measured",
                transform=ax.transAxes,
                ha="center",
                color="#718293",
                fontsize=16,
            )
            continue
        mx = max(vals)
        ax.set_ylim(0, mx * 1.37)
        ax.set_xlim(-0.65, len(vals) - 0.35)
        for i, v in enumerate(vals):
            ax.bar(i, v, width=0.61, color=colors[i])
            ax.text(
                i,
                v + mx * 0.025,
                f"{v:,.2f}",
                ha="center",
                weight="bold",
                fontsize=10.5,
            )
            if i:
                ax.text(
                    i,
                    v + mx * 0.12,
                    f"−{100*(1-v/vals[0]):.1f}%",
                    ha="center",
                    weight="bold",
                    color=colors[i],
                    fontsize=11,
                )
    for name, e in zip(names, entries):
        joint.append(
            {
                "pair": pair,
                "schedule": name,
                "minutes": e["minutes"],
                **e["all_resource_hours"],
            }
        )
    fig.text(
        0.09,
        0.083,
        "Same color = the SAME complete schedule across all four panels. Scales are independent.",
        fontsize=11,
        weight="bold",
    )
    msg = (
        "CPU + RAM + best-found GPU-hours are attained together by the blue schedule."
        if pair == "tmax"
        else "CPU/RAM minima coexist with either objective; best-found GPU and cache values use different schedules."
    )
    fig.text(0.09, 0.055, msg, fontsize=10.5)
    fig.text(
        0.09,
        0.026,
        "Fixed trace timings; zero transition cost. CPU/RAM: quota-hours. GPU/cache optima are not globally proven.",
        fontsize=10,
        color="#536577",
    )
    for ext in ["png", "pdf", "svg"]:
        fig.savefig(D / f"{pair}_min_hours_schedules.{ext}", dpi=200, facecolor="white")
    figs.append(fig)
with PdfPages(D / "resource_hours_by_schedule.pdf") as pdf:
    for fig in figs:
        pdf.savefig(fig)
with (D / "joint_schedules.csv").open("w") as f:
    w = csv.DictWriter(f, fieldnames=list(joint[0]))
    w.writeheader()
    w.writerows(joint)
rows = [
    [
        "Workload / schedule",
        "CPU core-hours",
        "Memory GiB-hours",
        "GPU-hours",
        "Cache GiB-hours",
        "Completion (min)",
    ]
]
for r in joint:
    if r["schedule"] == "FIFO baseline":
        continue
    rows.append(
        [
            ("TMax" if r["pair"] == "tmax" else "DeepSWE") + " / " + r["schedule"],
            *[
                ("—" if r[k] is None else f"{r[k]:,.2f}")
                for k in ["cpu", "memory", "gpu", "storage"]
            ],
            f"{r['minutes']:,.2f}",
        ]
    )
text = """### Which minima can be attained together?

The values above were selected separately by objective. The table below instead reports complete schedules: every value within a row is attained simultaneously in the replay. CPU and memory totals are invariant across phase-reclaim schedules. TMax attains the reported CPU, memory and best-found GPU values together at 129.21 minutes (storage unavailable). For DeepSWE, both GPU-optimized and cache-optimized schedules attain the CPU/RAM minima, but the best-found GPU and cache values are not attained together by any selected schedule. This does not prove that a joint optimum is impossible.

"""
text += (
    '<table header-row="true" fit-page-width="true">\n'
    + "".join(
        "<tr>" + "".join("<td>" + html.escape(x) + "</td>" for x in row) + "</tr>\n"
        for row in rows
    )
    + "</table>\n\n"
)
(D / "JOINT_NOTION.txt").write_text(text)
print("Rendered two charts and joint-schedule table.")