rohitg00/ai-engineering-from-scratch · error · ValueError

log scale metric must be positive, got {v}

Error message

log scale metric must be positive, got {v}

What it means

Error "log scale metric must be positive, got {v}" thrown in rohitg00/ai-engineering-from-scratch.

Source

Thrown at phases/19-capstone-projects/53-result-evaluator/code/main.py:215

        raise PairingError("no shared seeds between candidate and baseline")
    return [cand_map[s] for s in shared], [base_map[s] for s in shared]


def _improvement(candidate_mean: float, baseline_mean: float, direction: str) -> float:
    denom = abs(baseline_mean) if baseline_mean != 0.0 else 1.0
    raw = (candidate_mean - baseline_mean) / denom
    if direction == LOWER:
        return -raw
    return raw


def _log_transform(values: list[float], scale: str) -> list[float]:
    if scale != LOG:
        return list(values)
    out = []
    for v in values:
        if v <= 0.0:
            raise ValueError(f"log scale metric must be positive, got {v}")
        out.append(math.log(v))
    return out


@dataclass
class EvaluatorConfig:
    improvement_threshold: float = 0.02
    significance_threshold: float = 0.05


class Evaluator:
    """Pure function over (candidate, baseline) result lists; returns a Verdict."""

    def __init__(self, config: EvaluatorConfig | None = None) -> None:
        self._cfg = config or EvaluatorConfig()

    def evaluate(
        self,

View on GitHub (pinned to 39ea8a1c6d)

When it happens

Trigger: Thrown at phases/19-capstone-projects/53-result-evaluator/code/main.py:215 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of rohitg00/ai-engineering-from-scratch@39ea8a1c6d (2026-08-26). Data as JSON: /api/errors/b5b314f4b68a48e8. Report an issue: GitHub.