affaan-m/ECC · error · ValueError

reference probe must contain finite in-duration times

Error message

reference probe {field} must contain finite in-duration times

What it means

_validate_probe requires the 'sample_times' and 'scene_changes' lists of the measured probe to contain only finite real timestamps in [0, duration]. A non-list value, a non-numeric/NaN/inf entry, or a timestamp outside the probe duration triggers this error. It prevents out-of-range times from corrupting style-sampling logic.

Solutions

1. Clamp/filter all entries to 0 <= t <= duration and drop non-numeric values before calling run_workflow
2. Fix the unit mismatch (e.g. divide ms values by 1000) in the probe-producing tool
3. Regenerate the probe so sample_times/scene_changes are plain lists of finite numbers
4. Pre-validate the lists with math.isfinite and bounds checks at load time

Example fix

# before
measured['scene_changes'] = [0, 4.2, 17.9]   # duration is 12.0 -> 17.9 out of range
run_workflow(measured)

# after
dur = measured['duration']
measured['scene_changes'] = [t for t in measured['scene_changes']
                             if isinstance(t, (int, float)) and math.isfinite(t) and 0 <= t <= dur]
run_workflow(measured)

import math
def validate_times(measured):
    dur = float(measured['duration'])
    for field in ('sample_times', 'scene_changes'):
        vals = measured.get(field, [])
        if not isinstance(vals, list):
            return False
        if any(not isinstance(v, (int, float)) or isinstance(v, bool)
               or not math.isfinite(v) or not (0 <= v <= dur) for v in vals):
            return False
    return True

def valid_time_list(vals, dur: float) -> bool:
    return isinstance(vals, list) and all(
        isinstance(v, (int, float)) and not isinstance(v, bool)
        and math.isfinite(v) and 0 <= float(v) <= dur for v in vals)

try:
    run_workflow(measured)
except ValueError as e:
    if 'in-duration times' in str(e):
        field = str(e).split()[2]
        print(f'Fix {field}: times must be numbers within [0, {measured["duration"]}]')
    else:
        raise

When it happens

Trigger: run_workflow receiving measured['sample_times'] or measured['scene_changes'] that is not a list, or contains a negative number, a value greater than 'duration', NaN/inf, or a non-numeric element.

Common situations: Scene-detection script emitting times in milliseconds while duration is in seconds; negative timestamps from misaligned offsets; nulls in the list where a detector failed to report; times captured before duration was finalized.

Understand the failure class

Background: "value must be between 0 and 1" / "out of range" / "must not be negative" errors: fixing range-validation failures across open-source libraries — this error's family across 42 libraries.

Related errors

• application bundle differs from its bound evidence
• At least one video is required
• cannot upload, file does not exist
• Draft name must be a plain file name
• Geometry, fps and duration must be finite and positive

AI-assisted analysis of affaan-m/ECC@8321021c54 (2026-09-16). Data as JSON: /api/errors/361034383fed0df5. Report an issue: GitHub.

Appendix: source

Thrown at skills/taste-application/scripts/tasteforge/workflow.py:155

                require_finite_evidence(nested)
        elif isinstance(value, list):
            for nested in value:
                require_finite_evidence(nested)

    require_finite_evidence(measured)
    duration = measured.get("duration")
    if not _finite_real(duration):
        raise ValueError("reference probe duration must be finite and positive")
    duration = cast(float, duration)
    if float(duration) <= 0:
        raise ValueError("reference probe duration must be finite and positive")
    for field in ("sample_times", "scene_changes"):
        values = measured.get(field, [])
        if not isinstance(values, list) or any(
            not _finite_real(value) or float(value) < 0 or float(value) > float(duration)
            for value in values
        ):
            raise ValueError(f"reference probe {field} must contain finite in-duration times")
    samples = measured.get("style_samples", [])
    if not isinstance(samples, list) or any(
        not isinstance(sample, dict)
        or not _finite_real(sample.get("time"))
        or float(cast(float, sample["time"])) < 0
        or float(cast(float, sample["time"])) > float(duration)
        for sample in samples
    ):
        raise ValueError("reference style evidence times must be finite and within duration")
    return float(duration)


class _SafeOutput:
    """Descriptor-bound output tree with no-follow traversal and atomic writes."""

    def __init__(self, root: Path) -> None:
        self._root_fd = -1
        if not hasattr(os, "O_NOFOLLOW") or not hasattr(os, "O_DIRECTORY"):

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