"""RTT per (experiment, solution): mean, SD, quantiles, spread.

Also emits tso-pacing's variance-reduction ratios vs the other solutions.
"""
from pathlib import Path

import numpy as np
import pandas as pd


def _stats(x: np.ndarray) -> dict[str, str]:
    q05, q25, q50, q75, q95 = np.percentile(x, [5, 25, 50, 75, 95])
    return {
        "mean-ms":        f"{x.mean():.2f}",
        "sd-ms":          f"{x.std(ddof=1):.2f}",
        "median-ms":      f"{q50:.2f}",
        "iqr-ms":         f"{q75 - q25:.2f}",
        "p05-ms":         f"{q05:.2f}",
        "p95-ms":         f"{q95:.2f}",
        "spread-5-95-ms": f"{q95 - q05:.2f}",
        "n-samples":      str(x.size),
    }


def compute(derived: Path) -> tuple[dict[str, str], list[Path]]:
    out: dict[str, str] = {}
    sources: list[Path] = []
    for exp_dir in sorted(p for p in derived.iterdir() if p.is_dir()):
        rtts = exp_dir / "rtts.csv"
        if not rtts.exists():
            continue
        sources.append(rtts)
        df = pd.read_csv(rtts)
        per_sol: dict[str, dict[str, str]] = {}
        for sol, sub in df.groupby("solution", sort=True):
            x = sub["rtt_us"].to_numpy() / 1000.0
            stats = _stats(x)
            per_sol[sol] = stats
            for k, v in stats.items():
                out[f"{exp_dir.name}/rtt/{sol}/{k}"] = v

        if "tso-pacing" in per_sol:
            pac_sd     = float(per_sol["tso-pacing"]["sd-ms"])
            pac_spread = float(per_sol["tso-pacing"]["spread-5-95-ms"])
            pac_iqr    = float(per_sol["tso-pacing"]["iqr-ms"])
            for other in ("no-tso", "tso", "cake"):
                if other not in per_sol:
                    continue
                o = per_sol[other]
                o_sd     = float(o["sd-ms"])
                o_spread = float(o["spread-5-95-ms"])
                o_iqr    = float(o["iqr-ms"])
                base = f"{exp_dir.name}/rtt/tso-pacing-vs-{other}"
                out[f"{base}/sd-ratio-pct"]         = f"{100 * pac_sd / o_sd:.1f}"
                out[f"{base}/spread-ratio-pct"]     = f"{100 * pac_spread / o_spread:.1f}"
                out[f"{base}/iqr-ratio-pct"]        = f"{100 * pac_iqr / o_iqr:.1f}"
                out[f"{base}/sd-reduction-pct"]     = f"{100 * (1 - pac_sd / o_sd):.1f}"
                out[f"{base}/spread-reduction-pct"] = f"{100 * (1 - pac_spread / o_spread):.1f}"
                out[f"{base}/iqr-reduction-pct"]    = f"{100 * (1 - pac_iqr / o_iqr):.1f}"
    return out, sources