"""Phase 3 gate — computational performance and stylized facts at N = 100, 1,000, 10,000 traders (no API)."""
from __future__ import annotations

import json
import sys
import time
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
from market_agents.experiments.config import RunConfig  # noqa: E402
from market_agents.experiments.runner import run_config  # noqa: E402
from market_agents.metrics.outcomes import run_outcomes  # noqa: E402

ROOT = Path(__file__).resolve().parents[1]
rows = []
for n, seeds in ((100, [1, 2, 3]), (1000, [1, 2, 3]), (10000, [1])):
    for s in seeds:
        act = {k: v * 100.0 / n for k, v in RunConfig().population.activity.items()}   # constant order flow per tick
        cfg = RunConfig.from_yaml(ROOT / "configs/baseline.yaml", **{"name": f"scale_{n}", "seed": s, "population.n_traders": n,
                                                                      "population.activity": act})
        t0 = time.perf_counter()
        res = run_config(cfg)
        oc = run_outcomes(res)
        oc["wall_s"] = time.perf_counter() - t0
        oc["n_orders"] = int(res.agents["n_orders"].sum())
        rows.append(oc)
        print(f"N={n} seed={s}: {oc['wall_s']:.1f}s, {oc['n_trades']} trades, {oc['n_orders']} orders, mad={oc['mad_pct']:.2f}% "
              f"acf1={oc['acf_r_1']:.2f} kurt={oc['kurtosis']:.1f} spread={oc['spread_bp']:.1f}bp", flush=True)
out = ROOT / "results/calibration"
out.mkdir(parents=True, exist_ok=True)
with open(out / "scale_benchmark.json", "w") as f:
    json.dump(rows, f, indent=1, default=float)