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rsync of obra/drill@013fcb8b7d into superpowers/evals/, excluding .git/, .venv/, results/, .env/, __pycache__/, *.egg-info/, .private-journal/. The drill repo is unaffected by this commit; archival is a separate manual step after this PR merges. Source SHA recorded at evals/.drill-source-sha for divergence detection.
256 lines
8.5 KiB
Python
256 lines
8.5 KiB
Python
"""Compare: load and aggregate drill results across backends and runs."""
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from __future__ import annotations
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import json
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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from drill.stats import wilson_ci
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from drill.verifier import Verdict
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@dataclass
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class BackendResult:
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backend: str
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total_runs: int
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passed_runs: int
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errored_runs: int
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avg_turns: float
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criterion_counts: dict[str, tuple[int, int]] # criterion -> (passed, total)
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sweep_id: str | None
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timestamp: str | None
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partial: bool
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@property
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def pass_rate(self) -> float:
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if self.total_runs == 0:
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return 0.0
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return self.passed_runs / self.total_runs
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def load_scenario_results(
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scenario_dir: Path,
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*,
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sweep_id: str | None = None,
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) -> dict[str, BackendResult]:
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results: dict[str, BackendResult] = {}
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for backend_dir in sorted(scenario_dir.iterdir()):
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if not backend_dir.is_dir():
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continue
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timestamp_dirs = sorted(backend_dir.iterdir())
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if not timestamp_dirs:
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continue
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target_dir: Path | None = None
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if sweep_id:
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for d in timestamp_dirs:
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rg_path = d / "run-group.json"
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if rg_path.exists():
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rg = json.loads(rg_path.read_text())
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if rg.get("sweep_id") == sweep_id:
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target_dir = d
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break
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else:
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target_dir = timestamp_dirs[-1]
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if target_dir is None:
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continue
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result = _load_backend_result(backend_dir.name, target_dir)
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if result is not None:
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results[backend_dir.name] = result
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return results
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def _load_backend_result(backend_name: str, timestamp_dir: Path) -> BackendResult | None:
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rg_path = timestamp_dir / "run-group.json"
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if rg_path.exists():
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return _load_new_format(backend_name, timestamp_dir, rg_path)
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elif (timestamp_dir / "verdict.json").exists():
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return _load_old_format(backend_name, timestamp_dir)
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return None
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def _load_new_format(backend_name: str, timestamp_dir: Path, rg_path: Path) -> BackendResult:
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rg: dict[str, Any] = json.loads(rg_path.read_text())
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run_dirs = sorted(
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d for d in timestamp_dir.iterdir() if d.is_dir() and d.name.startswith("run-")
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)
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verdicts: list[Verdict] = []
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metas: list[dict[str, Any]] = []
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for run_dir in run_dirs:
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verdict_path = run_dir / "verdict.json"
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meta_path = run_dir / "meta.json"
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if verdict_path.exists():
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verdicts.append(Verdict.model_validate_json(verdict_path.read_text()))
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if meta_path.exists():
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metas.append(json.loads(meta_path.read_text()))
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passed_runs = sum(1 for v in verdicts if v.passed)
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errored_runs = sum(1 for r in rg.get("runs", []) if r.get("status") == "error")
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avg_turns = sum(m.get("actor_turns", 0) for m in metas) / len(metas) if metas else 0.0
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criterion_counts: dict[str, tuple[int, int]] = {}
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for v in verdicts:
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for c in v.criteria:
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prev_passed, prev_total = criterion_counts.get(c.criterion, (0, 0))
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criterion_counts[c.criterion] = (
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prev_passed + (1 if c.verdict == "pass" else 0),
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prev_total + 1,
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)
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return BackendResult(
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backend=backend_name,
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total_runs=len(verdicts),
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passed_runs=passed_runs,
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errored_runs=errored_runs,
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avg_turns=round(avg_turns, 1),
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criterion_counts=criterion_counts,
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sweep_id=rg.get("sweep_id"),
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timestamp=rg.get("timestamp"),
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partial=rg.get("partial", False),
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)
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def _load_old_format(backend_name: str, timestamp_dir: Path) -> BackendResult:
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verdict = Verdict.model_validate_json((timestamp_dir / "verdict.json").read_text())
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meta: dict[str, Any] = {}
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meta_path = timestamp_dir / "meta.json"
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if meta_path.exists():
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meta = json.loads(meta_path.read_text())
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criterion_counts: dict[str, tuple[int, int]] = {}
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for c in verdict.criteria:
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criterion_counts[c.criterion] = (1 if c.verdict == "pass" else 0, 1)
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return BackendResult(
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backend=backend_name,
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total_runs=1,
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passed_runs=1 if verdict.passed else 0,
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errored_runs=0,
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avg_turns=float(meta.get("actor_turns", 0)),
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criterion_counts=criterion_counts,
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sweep_id=None,
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timestamp=None,
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partial=False,
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)
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def format_compare_output(
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scenario: str,
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results: dict[str, BackendResult],
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) -> str:
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if not results:
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return f"No results found for: {scenario}"
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lines: list[str] = []
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is_multi_run = any(r.total_runs > 1 for r in results.values())
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if is_multi_run:
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first = next(iter(results.values()))
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lines.append(f"Scenario: {scenario}")
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if first.sweep_id:
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sweep_label = f"Sweep: {first.sweep_id}"
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if first.timestamp:
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date_str = first.timestamp.split("T")[0]
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sweep_label += f" | {date_str}"
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lines.append(sweep_label)
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lines.append("")
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header = f"{'':40s}"
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sub_header = f"{'':40s}"
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for name, r in results.items():
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header += f" {name:>12s}"
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sub_header += f" {'(n=' + str(r.total_runs) + ')':>12s}"
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lines.append(header)
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lines.append(sub_header)
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lines.append("-" * len(header))
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rate_line = f"{'Overall pass rate':40s}"
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ci_line = f"{' 95% CI':40s}"
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for r in results.values():
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pct = f"{r.pass_rate * 100:.1f}%"
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rate_line += f" {pct:>12s}"
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lo, hi = wilson_ci(r.passed_runs, r.total_runs)
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ci_str = f"[{lo * 100:.0f}, {hi * 100:.0f}]"
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ci_line += f" {ci_str:>12s}"
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lines.append(rate_line)
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lines.append(ci_line)
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lines.append("")
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all_criteria: list[str] = []
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seen: set[str] = set()
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for r in results.values():
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for crit in r.criterion_counts:
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if crit not in seen:
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all_criteria.append(crit)
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seen.add(crit)
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for crit in all_criteria:
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crit_line = f"{crit[:40]:40s}"
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for r in results.values():
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passed, total = r.criterion_counts.get(crit, (0, 0))
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crit_line += f" {str(passed) + '/' + str(total):>12s}"
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lines.append(crit_line)
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lines.append("")
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avg_line = f"{'Avg turns':40s}"
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err_line = f"{'Errors':40s}"
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for r in results.values():
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avg_line += f" {str(r.avg_turns):>12s}"
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err_line += f" {str(r.errored_runs):>12s}"
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lines.append(avg_line)
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lines.append(err_line)
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if any(r.total_runs < 10 for r in results.values()):
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lines.append("")
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lines.append("Note: CI is wide due to small sample size; consider --n 10+")
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if any(r.partial for r in results.values()):
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lines.append("")
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lines.append("Warning: Sweep was interrupted — results are incomplete.")
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else:
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lines.append(f"Scenario: {scenario}")
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lines.append("")
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lines.append(f"{'Backend':20s} {'Result':8s} {'Score':7s} {'Turns':5s}")
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lines.append("-" * 42)
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for name, r in results.items():
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result_str = "PASS" if r.passed_runs == r.total_runs else "FAIL"
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total_criteria = sum(t for _, t in r.criterion_counts.values())
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passed_criteria = sum(p for p, _ in r.criterion_counts.values())
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score = f"{passed_criteria}/{total_criteria}"
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turns_str = (
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str(int(r.avg_turns)) if r.avg_turns == int(r.avg_turns) else str(r.avg_turns)
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)
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lines.append(f"{name:20s} {result_str:8s} {score:7s} {turns_str:5s}")
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all_criteria = []
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seen = set()
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for r in results.values():
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for crit in r.criterion_counts:
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if crit not in seen:
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all_criteria.append(crit)
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seen.add(crit)
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lines.append("")
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header = f"{'':40s}"
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for name in results:
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header += f" {name:>12s}"
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lines.append(header)
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lines.append("-" * len(header))
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for crit in all_criteria:
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crit_line = f"{crit[:40]:40s}"
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for r in results.values():
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p, t = r.criterion_counts.get(crit, (0, 0))
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icon = "PASS" if p == t and t > 0 else "FAIL"
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crit_line += f" {icon:>12s}"
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lines.append(crit_line)
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return "\n".join(lines)
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