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0ffbb74 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 | """Run evaluation v3 (change_lens) as pre-registered in docs/evaluation-plan-v3.md.
Cases L1-L8 from ``scripts/v3_cases.py`` on seeds 900-907 (L1 -> 900, ...).
Contenders: the agent (change_lens and view_frame on), the scripted operator
(lens rule) and the naive scan. Results go to ``runs/evaluation-v3/``; one
line per run in ``results.jsonl``; ``--summary`` prints the tables.
Usage (PowerShell)::
.venv\\Scripts\\python.exe scripts\\run_evaluation_v3.py --oracle
.venv\\Scripts\\python.exe scripts\\run_evaluation_v3.py --run
.venv\\Scripts\\python.exe scripts\\run_evaluation_v3.py --summary
"""
from __future__ import annotations
import argparse
import json
import sys
import traceback
from pathlib import Path
from typing import Any
sys.path.insert(0, str(Path(__file__).resolve().parent))
from v3_cases import LensCase, all_cases, oracle_verdict # noqa: E402
from beampilot.agent import AgentConfig, make_client, run_agent, save_run # noqa: E402
from beampilot.baselines import naive_uniform, scripted_iso # noqa: E402
from beampilot.session import ( # noqa: E402
MeasurementSession,
reveal_truth,
session_record,
)
OUT_DIR = Path("runs") / "evaluation-v3"
RESULTS = OUT_DIR / "results.jsonl"
FIRST_SEED = 900
BUDGET_USD = 3.0 # plan v3, deviation 1 (was 2.0)
# Agent limits for v3 (plan deviation 1): more model calls and tokens; the
# per-run cost cap stays at $0.50.
AGENT_CONFIG = {
"change_lens": True,
"max_model_calls": 80,
"max_total_tokens": 3_000_000,
"max_cost_usd": 0.50,
}
CONTENDERS = ("agent", "scripted", "naive")
# Measurement within tolerance (iso_compliant cases): design section 7, item 7.
M2_TOL = 0.03
D0_TOL = 0.05
Z0_TOL_ZR = 0.1
def seed_of(case: LensCase) -> int:
return FIRST_SEED + int(case.case_id[1:]) - 1
def within_tolerance(report: dict[str, Any], truth: dict[str, Any]) -> dict[str, Any]:
"""Errors of the back-calculated beam and M² against the truth, per axis."""
back = report.get("original_beam_back_calculated") or {}
m2 = report.get("m2") or {}
errors: dict[str, Any] = {}
ok = bool(back) and bool(m2)
for axis in ("x", "y"):
b, m = back.get(axis), (m2.get(axis) or {}).get("m2")
if b is None or m is None:
errors[axis] = None
ok = False
continue
d0 = b["d0_um"] / truth[f"d0_{axis}_um"] - 1
z0 = (b["z0_mm"] - truth[f"z0_{axis}_mm"]) / truth[f"z_r_{axis}_mm"]
m2e = m / truth[f"m2_{axis}"] - 1
errors[axis] = {
"d0_rel": d0,
"z0_zr": z0,
"m2_rel": m2e,
"dz0_mm_per_plus_1pct_f": b["dz0_mm_per_plus_1pct_f"],
}
ok &= abs(d0) <= D0_TOL and abs(z0) <= Z0_TOL_ZR and abs(m2e) <= M2_TOL
return {"within_tolerance": ok, "errors": errors}
def score(case, contender, session, report, extra) -> dict[str, Any]:
truth = reveal_truth(session)
expected = oracle_verdict(case.scenario(seed_of(case)))
lens = report.get("lens")
row = {
"case": case.case_id,
"seed": seed_of(case),
"contender": contender,
"expected": expected,
"verdict": report["verdict"],
"correct": report["verdict"] == expected,
"lens": None if lens is None else [lens["f_mm"], lens["lens_z_mm"]],
"lens_changes": len(session.lens_changes),
"positions": session.positions_used,
"explanation": report.get("explanation", ""),
"stopped_by_limit": report.get("stopped_by_limit"),
**extra,
}
if expected == "iso_compliant":
row.update(within_tolerance(report, truth))
return row
def record(row: dict[str, Any]) -> None:
with RESULTS.open("a", encoding="utf-8") as handle:
handle.write(json.dumps(row, ensure_ascii=False) + "\n")
print(
f"{row['case']} {row['contender']:<9} {row.get('verdict', row.get('not_run'))} "
f"correct={row.get('correct')} tol={row.get('within_tolerance')} "
f"pos={row.get('positions')} ${row.get('cost_usd', 0):.3f}",
flush=True,
)
def run_all() -> int:
OUT_DIR.mkdir(parents=True, exist_ok=True)
if RESULTS.exists():
print(f"{RESULTS} exists; move it away first", file=sys.stderr)
return 2
cases = all_cases()
for case in cases:
for contender, strategy in (
("scripted", scripted_iso),
("naive", naive_uniform),
):
session = MeasurementSession(case.scenario(seed_of(case)))
report = strategy(session)["report"]
record(score(case, contender, session, report, {"cost_usd": 0.0}))
client = make_client()
total = 0.0
for case in cases:
if total >= BUDGET_USD:
record({"case": case.case_id, "contender": "agent", "not_run": "budget"})
continue
session = MeasurementSession(case.scenario(seed_of(case)))
try:
run = run_agent(session, client, AgentConfig(**AGENT_CONFIG))
except Exception: # noqa: BLE001 - record and stop: no silent re-runs
record(
{
"case": case.case_id,
"contender": "agent",
"error": traceback.format_exc(limit=3),
}
)
return 1
total += run.cost_usd
save_run(
run,
OUT_DIR / f"{case.case_id}_agent.json",
{"case": case.case_id, "seed": seed_of(case), **session_record(session)},
)
extra = {
"cost_usd": round(run.cost_usd, 6),
"model_calls": len(run.steps),
"stop_reason": run.stop_reason,
"views_used": session.views_used,
}
record(score(case, "agent", session, run.report, extra))
print(f"agent cost total ${total:.4f}")
return 0
def summary() -> str:
rows = [json.loads(line) for line in RESULTS.read_text("utf-8").splitlines()]
lines = [
"| Case | Contender | Expected | Verdict | Correct | Within tolerance "
"| Lens | Positions | Model calls | Cost |",
"|---|---|---|---|---|---|---|---|---|---|",
]
for row in rows:
if "not_run" in row or "error" in row:
status = row.get("not_run") or "error"
lines.append(
f"| {row['case']} | {row['contender']} | {status} |" + " |" * 7
)
continue
lens = (
"–" if row["lens"] is None else f"{row['lens'][0]:g} @ {row['lens'][1]:g}"
)
tol = row.get("within_tolerance")
lines.append(
f"| {row['case']} | {row['contender']} | {row['expected']} | "
f"{row['verdict']} | {'yes' if row['correct'] else '**no**'} | "
f"{'–' if tol is None else ('yes' if tol else '**no**')} | {lens} | "
f"{row['positions']} | {row.get('model_calls', '–')} | "
f"${row.get('cost_usd', 0.0):.3f} |"
)
for contender in CONTENDERS:
own = [r for r in rows if r.get("contender") == contender and "correct" in r]
tol = [r for r in own if "within_tolerance" in r]
lines.append(
f"\n**{contender}:** {sum(r['correct'] for r in own)}/{len(own)} correct "
f"verdicts; {sum(r['within_tolerance'] for r in tol)}/{len(tol)} within "
f"tolerance; cost ${sum(r.get('cost_usd', 0.0) for r in own):.3f}."
)
return "\n".join(lines)
def main() -> int:
sys.stdout.reconfigure(encoding="utf-8", errors="replace", line_buffering=True)
parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
mode = parser.add_mutually_exclusive_group(required=True)
mode.add_argument("--oracle", action="store_true")
mode.add_argument("--run", action="store_true")
mode.add_argument("--summary", action="store_true")
args = parser.parse_args()
if args.oracle:
for case in all_cases():
verdict = oracle_verdict(case.scenario(seed_of(case)))
print(f"{case.case_id} seed {seed_of(case)}: {verdict}")
return 0
if args.summary:
print(summary())
return 0
return run_all()
if __name__ == "__main__":
sys.exit(main())
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