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"""
Plot latest Spider benchmark results.
Outputs in the latest folder under benchmarks/results_pro/:
- metrics_overview.png: EM/SM/ExecAcc + latency (avg, p50, p95)
- latency_per_stage.png: bar of average per-stage latency
- latency_histogram.png: latency distribution across samples
"""
from __future__ import annotations
import json
from pathlib import Path
import matplotlib.pyplot as plt
ROOT = Path("benchmarks/results_pro")
def _latest_run_dir() -> Path:
summaries = sorted(
ROOT.glob("*/summary.json"), key=lambda p: p.stat().st_mtime, reverse=True
)
if not summaries:
raise SystemExit("❌ No benchmark results found under benchmarks/results_pro/")
return summaries[0].parent
def _load_summary(run: Path) -> dict:
return json.loads((run / "summary.json").read_text(encoding="utf-8"))
def _load_eval_rows(run: Path) -> list[dict]:
lines = (run / "eval.jsonl").read_text(encoding="utf-8").splitlines()
return [json.loads(x) for x in lines]
def plot_metrics_overview(run: Path, summary: dict) -> None:
# EM/SM/ExecAcc on [0,1]; latency in ms (show as seconds for scale)
labels = ["EM", "SM", "ExecAcc", "avg(s)", "p50(s)", "p95(s)"]
values = [
summary.get("EM", 0.0),
summary.get("SM", 0.0),
summary.get("ExecAcc", 0.0),
summary.get("avg_latency_ms", 0.0) / 1000.0,
summary.get("p50_latency_ms", 0.0) / 1000.0,
summary.get("p95_latency_ms", 0.0) / 1000.0,
]
plt.figure(figsize=(9, 5))
bars = plt.bar(labels, values)
for b, v in zip(bars, values):
plt.text(b.get_x() + b.get_width() / 2, v, f"{v:.2f}", ha="center", va="bottom")
plt.title("Metrics Overview (Spider)")
plt.ylim(0, max(1.0, max(values) * 1.15 if values else 1.0))
plt.tight_layout()
plt.savefig(run / "metrics_overview.png")
plt.close()
def plot_latency_hist(run: Path, rows: list[dict]) -> None:
latencies = [
r.get("latency_ms", 0)
for r in rows
if isinstance(r.get("latency_ms"), (int, float))
]
if not latencies:
return
plt.figure(figsize=(9, 4))
plt.hist(latencies, bins=min(20, max(5, int(len(latencies) ** 0.5))))
plt.title("Latency Distribution (ms)")
plt.xlabel("Latency (ms)")
plt.ylabel("Count")
plt.tight_layout()
plt.savefig(run / "latency_histogram.png")
plt.close()
def plot_latency_per_stage(run: Path, summary: dict, rows: list[dict]) -> None:
stages = [
"detector",
"planner",
"generator",
"safety",
"executor",
"verifier",
"repair",
]
# prefer summary keys if available; else derive from traces
raw_values = [summary.get(f"{s}_avg_ms") for s in stages]
# convert Nones to 0.0
values: list[float] = [float(v or 0.0) for v in raw_values]
if not any(values):
totals = {s: 0.0 for s in stages}
counts = {s: 0 for s in stages}
for r in rows:
trace = r.get("trace") or r.get("traces") or []
for t in trace:
s = t.get("stage")
if s in totals:
ms = t.get("ms", t.get("duration_ms", 0.0))
try:
totals[s] += float(ms)
counts[s] += 1
except Exception:
pass
values = [round(totals[s] / counts[s], 2) if counts[s] else 0.0 for s in stages]
plt.figure(figsize=(10, 5))
bars = plt.bar(stages, values)
for b, v in zip(bars, values):
plt.text(
b.get_x() + b.get_width() / 2,
float(v),
f"{v:.1f}",
ha="center",
va="bottom",
)
plt.title("Average Latency per Stage (ms)")
plt.xlabel("Stage")
plt.ylabel("Latency (ms)")
plt.tight_layout()
plt.savefig(run / "latency_per_stage.png")
plt.close()
def plot_errors_overview(run: Path) -> None:
p = run / "trace.jsonl"
if not p.exists():
return
from collections import Counter
counts: Counter[str] = Counter()
with p.open("r", encoding="utf-8") as f:
for line in f:
try:
obj = json.loads(line)
except Exception:
continue
for t in obj.get("trace", []):
et = t.get("error_type")
if et:
counts[et] += 1
if not counts:
return
labels, values = zip(*sorted(counts.items(), key=lambda x: x[1], reverse=True))
plt.figure(figsize=(9, 4))
plt.bar(labels, values)
plt.title("Errors by Type")
plt.ylabel("Count")
plt.tight_layout()
plt.savefig(run / "errors_overview.png")
plt.close()
def main() -> None:
run = _latest_run_dir()
print(f"📂 Using latest run: {run.name}")
summary = _load_summary(run)
rows = _load_eval_rows(run)
plot_metrics_overview(run, summary)
plot_latency_hist(run, rows)
plot_latency_per_stage(run, summary, rows)
plot_errors_overview(run)
print(
"✅ Saved: metrics_overview.png, latency_histogram.png, latency_per_stage.png, errors_overview.png"
)
if __name__ == "__main__":
main()
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