#!/usr/bin/env python3
"""Five interleaved L80 readiness pairs comparing L109 and L112 at W8 and W12."""
from __future__ import annotations

import json
import re
import statistics
import subprocess
import time
from pathlib import Path

ROOT = Path(__file__).resolve().parents[4]
OUT = ROOT / "Saved/Linux/l112/timing"
DATA = ROOT / "Standalone/data/owner_world.json"
BINARIES = {
    "base": ROOT / "Saved/Linux/l109/bin-final/VoxelForgeCoreHeadless-l109-clang",
    "candidate": ROOT / "Saved/Linux/l112/bin-clang/VoxelForgeCoreHeadless-l112-clang",
}
CAMERAS = {
    0: (8.0, 16.0, -372.2626953125),
    1: (25.8369140625, 3.19921875, -737.0),
    2: (19.166015625, -14.2001953125, -753.3740234375),
    3: (-20.0625, -5.068359375, -900.353515625),
}
PIPELINE = re.compile(r"^\[StreamPipeline\] (.*)$", re.M)
FIELDS = re.compile(r"([a-zA-Z0-9_]+)=([^ ]+)")
NEAR = re.compile(
    r"^\[WorldAssemblerNearLODReady\] lods=0-2 tiles=(\d+)/(\d+) cold_ready_s=([0-9.]+)$",
    re.M,
)


def run(strate: int, workers: int, variant: str, phase: str, replicate: int) -> dict:
    OUT.mkdir(parents=True, exist_ok=True)
    label = f"s{strate}-w{workers}-{variant}-{phase}{replicate}"
    log = OUT / f"{label}.log"
    camera = ",".join(f"{v:.12f}" for v in CAMERAS[strate]) + ",0,0"
    command = [
        "taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--",
        "timeout", "1740s", str(BINARIES[variant]), str(DATA),
        "--world-assembler-prototype", "--stream-benchmark", "--stream-pipeline",
        f"--workers={workers}", "--clip-radius=3", "--max-clip-level=8", "--max-level=8",
        f"--camera={camera}", "--profile-lod-work", "--stream-scheduler-policy=3",
    ]
    start = time.monotonic()
    with log.open("w", encoding="utf-8") as output:
        result = subprocess.run(command, cwd=ROOT, stdout=output,
                                stderr=subprocess.STDOUT, check=False, timeout=1740)
    content = log.read_text(encoding="utf-8", errors="replace")
    pipeline_match = PIPELINE.search(content)
    near_match = NEAR.search(content)
    if result.returncode or pipeline_match is None or near_match is None:
        raise SystemExit(f"readiness run failed or trace missing: {log}; exit={result.returncode}")
    pipeline = dict(FIELDS.findall(pipeline_match.group(1)))
    row = {
        "strate": strate, "workers": workers, "variant": variant,
        "phase": phase, "replicate": replicate, "exit_code": result.returncode,
        "wall_s": round(time.monotonic() - start, 3),
        "lod02_ready_s": float(near_match.group(3)),
        "whole_view_ready_s": float(pipeline["whole_view_ready"].removesuffix("s")),
        "whole_tiles": int(pipeline["whole_tiles"].split("/")[0]),
        "log": str(log.relative_to(ROOT)),
    }
    print("[L112TimingRun] " + json.dumps(row, sort_keys=True), flush=True)
    return row


def main() -> int:
    if not DATA.is_file() or any(not binary.is_file() for binary in BINARIES.values()):
        raise SystemExit("missing L109/L112 data or timing binary")
    rows = []
    for strate in range(4):
        for workers in (8, 12):
            run(strate, workers, "base", "warmup", 0)
            run(strate, workers, "candidate", "warmup", 0)
            for replicate in range(1, 6):
                order = ("base", "candidate") if replicate % 2 else ("candidate", "base")
                for variant in order:
                    rows.append(run(strate, workers, variant, "measured", replicate))
                    (OUT / "runs-partial.json").write_text(
                        json.dumps(rows, indent=2) + "\n", encoding="utf-8")
    summary = []
    for strate in range(4):
        for workers in (8, 12):
            item = {"strate": strate, "workers": workers, "pairs": 5}
            for variant in ("base", "candidate"):
                group = [row for row in rows if row["strate"] == strate
                         and row["workers"] == workers and row["variant"] == variant]
                for key in ("lod02_ready_s", "whole_view_ready_s"):
                    values = [row[key] for row in group]
                    item[f"{variant}_{key}"] = values
                    item[f"{variant}_{key}_median"] = statistics.median(values)
            for key in ("lod02_ready_s", "whole_view_ready_s"):
                base = item[f"base_{key}_median"]
                candidate = item[f"candidate_{key}_median"]
                item[f"{key}_delta_pct"] = round(100 * (candidate / base - 1), 2)
            summary.append(item)
    (OUT / "summary.json").write_text(
        json.dumps({"runs": rows, "summary": summary}, indent=2) + "\n",
        encoding="utf-8")
    return 0


if __name__ == "__main__":
    raise SystemExit(main())