"""Render PNG figures for Window 1 results (B1', B2, B3).

Inputs (all expected under <results-dir>):
- b3_policy_comparison.json        (per-policy table)
- b2_sweep_summary.json            (per-cell B2 sweep)
- apc_upper_w600.json              (theoretical bounds)
- lmetric_reuse.json               (intra/cross/shared decomp)
- kv_footprint_summary.json        (full trace KV stats)

Outputs (under <out-dir>):
- fig_b3_apc_vs_hotspot.png
- fig_b3_latency_bars.png
- fig_b3_apc_vs_upper.png
- fig_b3_failure_breakdown.png
- fig_b3_per_worker_ttft_p90.png
- fig_b2_tpot_vs_prefill.png
- fig_b2_ttft_vs_prefill.png
- fig_reuse_decomposition.png
- fig_kv_footprint_cdf.png
"""

from __future__ import annotations

import argparse
import json
from pathlib import Path

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

POLICY_ORDER = ["lmetric", "load_only", "sticky", "unified", "capped"]
POLICY_COLOR = {
    "lmetric":   "#1f77b4",
    "load_only": "#ff7f0e",
    "sticky":    "#d62728",
    "unified":   "#2ca02c",
    "capped":    "#9467bd",
}


def _load(results_dir: Path, name: str) -> dict:
    return json.loads((results_dir / name).read_text())


def fig_b3_apc_vs_hotspot(comp: dict, upper: dict, out: Path) -> None:
    upper_intra = upper["apc_upper_intra_session"]
    fig, ax = plt.subplots(figsize=(6, 4.5))
    for r in comp["rows"]:
        pol = r["policy"]
        if pol not in POLICY_ORDER:
            continue
        ax.scatter(r["apc_ratio"] * 100, r["hotspot_index_ttft_p90"],
                    s=180, color=POLICY_COLOR.get(pol, "gray"), label=pol,
                    edgecolors="black", linewidths=0.5)
        ax.annotate(pol, (r["apc_ratio"] * 100, r["hotspot_index_ttft_p90"]),
                     xytext=(7, 7), textcoords="offset points",
                     fontsize=9)
    ax.axvline(upper_intra * 100, linestyle="--", color="gray", alpha=0.6,
                label=f"intra-session APC upper {upper_intra * 100:.1f}%")
    ax.set_xlabel("APC achieved (%)")
    ax.set_ylabel("hotspot_index = max(worker TTFT p90) / median")
    ax.set_title("B3: APC vs hot-spot tradeoff across policies")
    ax.grid(alpha=0.3)
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def fig_b3_latency_bars(comp: dict, out: Path) -> None:
    by = {r["policy"]: r for r in comp["rows"]}
    pols = [p for p in POLICY_ORDER if p in by]
    metrics = [("TTFT p90 (s)", "ttft_p90_s"),
                ("TPOT p90 (ms)", "tpot_p90_s"),
                ("E2E p90 (s)", "e2e_p90_s")]
    fig, axes = plt.subplots(1, 3, figsize=(12, 4))
    for ax, (label, key) in zip(axes, metrics):
        vals = [by[p][key] * (1000 if "TPOT" in label else 1) for p in pols]
        ax.bar(pols, vals, color=[POLICY_COLOR.get(p, "gray") for p in pols],
                edgecolor="black", linewidth=0.5)
        ax.set_title(label)
        ax.tick_params(axis="x", rotation=20)
        for i, v in enumerate(vals):
            ax.text(i, v, f"{v:.1f}", ha="center", va="bottom", fontsize=9)
        ax.grid(alpha=0.3, axis="y")
    fig.suptitle("B3 headline latencies per policy")
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def fig_b3_apc_vs_upper(comp: dict, upper: dict, out: Path) -> None:
    by = {r["policy"]: r for r in comp["rows"]}
    pols = [p for p in POLICY_ORDER if p in by]
    achieved = [by[p]["apc_ratio"] * 100 for p in pols]
    fig, ax = plt.subplots(figsize=(6.5, 4))
    bars = ax.bar(pols, achieved,
                    color=[POLICY_COLOR.get(p, "gray") for p in pols],
                    edgecolor="black", linewidth=0.5)
    ax.axhline(upper["apc_upper_intra_session"] * 100, linestyle="--",
                color="black", alpha=0.7,
                label=f"intra-session ceiling {upper['apc_upper_intra_session'] * 100:.1f}%")
    ax.axhline(upper["apc_upper_any_session"] * 100, linestyle=":",
                color="darkgray", alpha=0.7,
                label=f"any-session ceiling {upper['apc_upper_any_session'] * 100:.1f}%")
    for b, v in zip(bars, achieved):
        ax.text(b.get_x() + b.get_width() / 2, v + 1, f"{v:.1f}%",
                 ha="center", fontsize=9)
    ax.set_ylim(0, 100)
    ax.set_ylabel("APC ratio (%)")
    ax.set_title("B3: APC achieved vs theoretical ceiling")
    ax.legend(loc="upper right", fontsize=9)
    ax.grid(alpha=0.3, axis="y")
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def fig_b3_failure_breakdown(comp: dict, out: Path) -> None:
    by = {r["policy"]: r for r in comp["rows"]}
    pols = [p for p in POLICY_ORDER if p in by]
    causes = ["same_worker_prefill_overlap", "hot_worker_queue",
               "cache_miss_large_append", "high_kv_occupancy", "unknown"]
    cause_color = {
        "same_worker_prefill_overlap": "#d62728",
        "hot_worker_queue":            "#ff7f0e",
        "cache_miss_large_append":     "#1f77b4",
        "high_kv_occupancy":           "#8c564b",
        "unknown":                     "#7f7f7f",
    }
    fig, ax = plt.subplots(figsize=(7, 4.5))
    bottom = [0.0] * len(pols)
    for c in causes:
        vals = [(by[p].get("failure_counts") or {}).get(c, 0) for p in pols]
        ax.bar(pols, vals, bottom=bottom, label=c.replace("_", " "),
                color=cause_color[c], edgecolor="black", linewidth=0.3)
        bottom = [a + b for a, b in zip(bottom, vals)]
    for i, total in enumerate(bottom):
        ax.text(i, total + 3, f"n={int(total)}", ha="center", fontsize=9)
    ax.set_ylabel("slow request count (TTFT > 2× p90 threshold)")
    ax.set_title("B3: slow-request cause breakdown per policy")
    ax.legend(fontsize=8, loc="upper right")
    ax.grid(alpha=0.3, axis="y")
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def fig_b3_per_worker_ttft(results_dir: Path, comp: dict, out: Path) -> None:
    """Per-worker TTFT p90 grouped bars; reads each policy's hotspot_index.json."""
    by = {r["policy"]: r for r in comp["rows"]}
    pols = [p for p in POLICY_ORDER if p in by]
    fig, axes = plt.subplots(1, len(pols), figsize=(3 * len(pols), 4),
                              sharey=True)
    if len(pols) == 1:
        axes = [axes]
    for ax, pol in zip(axes, pols):
        path = results_dir / f"per_worker_{pol}.json"
        if not path.exists():
            ax.text(0.5, 0.5, f"{pol}: no data", ha="center", va="center",
                     transform=ax.transAxes)
            continue
        per = json.loads(path.read_text()).get("per_worker_ttft_p90_s") or {}
        items = sorted(per.items(), key=lambda kv: int(kv[0].rsplit(":", 1)[1]))
        labels = [f"e{int(k.rsplit(':', 1)[1]) - 8000}" for k, _ in items]
        vals = [v for _, v in items]
        ax.bar(labels, vals, color=POLICY_COLOR.get(pol, "gray"),
                edgecolor="black", linewidth=0.5)
        for i, v in enumerate(vals):
            ax.text(i, v, f"{v:.1f}", ha="center", va="bottom", fontsize=8)
        ax.set_title(f"{pol}\nhotspot={by[pol]['hotspot_index_ttft_p90']:.2f}",
                      fontsize=10)
        ax.tick_params(axis="x", labelsize=8)
        ax.grid(alpha=0.3, axis="y")
    axes[0].set_ylabel("worker TTFT p90 (s)")
    fig.suptitle("B3 per-worker TTFT p90 distribution")
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def fig_b2_curves(b2: dict, out_tpot: Path, out_ttft: Path) -> None:
    sizes = sorted({r["prefill_size"] for r in b2["rows"]})
    by_var = {"same": {}, "different": {}}
    for r in b2["rows"]:
        by_var[r["variant"]][r["prefill_size"]] = r

    for name, key, ylabel, ymax_log, out in [
        ("TPOT", "tpot_p90", "TPOT p90 (ms)", True, out_tpot),
        ("TTFT", "ttft_p90", "TTFT p90 (s)", True, out_ttft),
    ]:
        fig, axes = plt.subplots(1, 2, figsize=(11, 4))
        ax_abs, ax_idx = axes
        for variant in ("different", "same"):
            xs, ys_o, ys_c, idxs = [], [], [], []
            for sz in sizes:
                r = by_var[variant].get(sz)
                if not r: continue
                ov = r.get(f"{key}_overlap_s")
                cl = r.get(f"{key}_clean_s")
                if ov is None or cl is None: continue
                xs.append(sz)
                scale = 1000 if name == "TPOT" else 1.0
                ys_o.append(ov * scale)
                ys_c.append(cl * scale)
                idxs.append(ov / cl)
            color = "#d62728" if variant == "same" else "#1f77b4"
            ax_abs.plot(xs, ys_o, "o-", color=color,
                         label=f"{variant} (overlap)")
            ax_abs.plot(xs, ys_c, "s--", color=color, alpha=0.5,
                         label=f"{variant} (clean)")
            ax_idx.plot(xs, idxs, "o-", color=color, label=variant,
                         linewidth=2)
        ax_abs.set_xscale("log", base=2)
        ax_abs.set_yscale("log")
        ax_abs.set_xlabel("prefill injection size (tokens)")
        ax_abs.set_ylabel(ylabel + " (log)")
        ax_abs.set_title(f"B2 {name} absolute (overlap vs clean)")
        ax_abs.legend(fontsize=8)
        ax_abs.grid(alpha=0.3, which="both")

        ax_idx.set_xscale("log", base=2)
        if ymax_log:
            ax_idx.set_yscale("log")
        ax_idx.axhline(1.0, color="black", linestyle=":", alpha=0.5)
        ax_idx.set_xlabel("prefill injection size (tokens)")
        ax_idx.set_ylabel(f"{name} idx = overlap / clean")
        ax_idx.set_title(f"B2 {name} interference index (same vs different worker)")
        ax_idx.legend()
        ax_idx.grid(alpha=0.3, which="both")
        fig.tight_layout()
        fig.savefig(out, dpi=120)
        plt.close(fig)


def fig_reuse_decomposition(reuse: dict, out: Path) -> None:
    fr = reuse.get("fractions") or {}
    labels = ["intra-session", "cross-session", "shared-prefix", "unclassified"]
    vals = [fr.get("intra", 0), fr.get("cross", 0),
             fr.get("shared", 0), fr.get("unclassified", 0)]
    colors = ["#2ca02c", "#ff7f0e", "#9467bd", "#7f7f7f"]
    fig, ax = plt.subplots(figsize=(6, 3))
    bottom = 0.0
    for label, v, c in zip(labels, vals, colors):
        ax.barh(["lmetric run"], [v], left=[bottom], color=c, edgecolor="black",
                 linewidth=0.5, label=f"{label} ({v * 100:.1f}%)")
        bottom += v
    ax.set_xlabel("fraction of cached_tokens")
    ax.set_xlim(0, 1)
    ax.set_title("Real reuse decomposition (w600 lmetric run)")
    ax.legend(fontsize=9, loc="lower right")
    ax.grid(alpha=0.3, axis="x")
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def fig_kv_footprint_cdf(kv: dict, out: Path) -> None:
    s = kv.get("kv_mib_per_request") or {}
    vals = [s.get(k) for k in ("p50", "p90", "p95", "p99")]
    labels = ["p50", "p90", "p95", "p99"]
    fig, ax = plt.subplots(figsize=(6, 3.5))
    ax.bar(labels, vals, color="#1f77b4", edgecolor="black", linewidth=0.5)
    for i, v in enumerate(vals):
        ax.text(i, v, f"{v:.0f} MiB", ha="center", va="bottom", fontsize=9)
    ax.axhline(95 * 1024, color="red", linestyle="--", alpha=0.5,
                label="H20 ~95 GiB usable")
    ax.set_ylabel("KV bytes per request (MiB)")
    ax.set_title("B1' Per-request KV footprint (Qwen3-Coder-30B-A3B, 98304 B/token)")
    ax.legend()
    ax.grid(alpha=0.3, axis="y")
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)


def main() -> None:
    p = argparse.ArgumentParser()
    p.add_argument("--results-dir", type=Path, required=True)
    p.add_argument("--out-dir", type=Path, required=True)
    p.add_argument("--exclude-policies", default="",
                   help="Comma-separated policies to drop from per-policy figures")
    args = p.parse_args()
    args.out_dir.mkdir(parents=True, exist_ok=True)

    excluded = {s.strip() for s in args.exclude_policies.split(",") if s.strip()}
    if excluded:
        global POLICY_ORDER
        POLICY_ORDER = [p for p in POLICY_ORDER if p not in excluded]
        print(f"excluding policies: {sorted(excluded)} -> kept {POLICY_ORDER}")

    comp = _load(args.results_dir, "b3_policy_comparison.json")
    upper = _load(args.results_dir, "apc_upper_w600.json")
    b2 = _load(args.results_dir, "b2_sweep_summary.json")
    reuse = _load(args.results_dir, "lmetric_reuse.json")
    kv = _load(args.results_dir, "kv_footprint_summary.json")

    fig_b3_apc_vs_hotspot(comp, upper, args.out_dir / "fig_b3_apc_vs_hotspot.png")
    fig_b3_latency_bars(comp, args.out_dir / "fig_b3_latency_bars.png")
    fig_b3_apc_vs_upper(comp, upper, args.out_dir / "fig_b3_apc_vs_upper.png")
    fig_b3_failure_breakdown(comp, args.out_dir / "fig_b3_failure_breakdown.png")
    fig_b3_per_worker_ttft(args.results_dir, comp,
                            args.out_dir / "fig_b3_per_worker_ttft_p90.png")
    fig_b2_curves(b2,
                   args.out_dir / "fig_b2_tpot_vs_prefill.png",
                   args.out_dir / "fig_b2_ttft_vs_prefill.png")
    fig_reuse_decomposition(reuse, args.out_dir / "fig_reuse_decomposition.png")
    fig_kv_footprint_cdf(kv, args.out_dir / "fig_kv_footprint_cdf.png")
    print(f"wrote 8 figures to {args.out_dir}")


if __name__ == "__main__":
    main()