"""Summarise bench.py rows: per (target, frame), the median of the 3 run p50s with the
min-max of those run p50s (the A-vs-A spread, i.e. the noise floor), the median run p90,
and the median server-side probe mean.
    python summarize.py rows-2026-09-27.json
"""
import json, statistics, sys
from collections import defaultdict

rows = json.load(open(sys.argv[1]))
g = defaultdict(list)
for r in rows:
    g[(r["target"], r["frame"])].append(r)
targets = list(dict.fromkeys(r["target"] for r in rows))
frames = list(dict.fromkeys(r["frame"] for r in rows))
print(f"{'target':<14} {'frame':<17} {'p50 med':>8} {'p50 run min-max':>16} {'p90 med':>8} {'server med':>10} bad")
for t in targets:
    for f in frames:
        rs = g[(t, f)]
        p50s = [r["p50"] for r in rs]
        srv = [r["server_probe_mean"] for r in rs if r["server_probe_mean"] is not None]
        print(f"{t:<14} {f:<17} {statistics.median(p50s):8.1f} {min(p50s):7.1f}-{max(p50s):<8.1f}"
              f" {statistics.median(r['p90'] for r in rs):8.1f}"
              f" {(statistics.median(srv) if srv else float('nan')):10.1f} {sum(r['bad'] for r in rs)}")