HKUDS/Vibe-Trading · error · ValueError

ts_min window must be >= 1, got {n}

Error message

ts_min window must be >= 1, got {n}

What it means

ts_min computes a rolling minimum per column with NaN warmup. Like ts_max it requires window n >= 1 since pandas rolling cannot accept zero/negative windows; the guard raises ValueError before pandas does.

Source

Thrown at agent/src/factors/base.py:203

def ts_std(df: pd.DataFrame, n: int) -> pd.DataFrame:
    """Rolling sample std (ddof=1) per column, warmup → NaN."""
    if n < 2:
        raise ValueError(f"ts_std window must be >= 2, got {n}")
    return df.rolling(window=n, min_periods=n).std(ddof=1)


def ts_max(df: pd.DataFrame, n: int) -> pd.DataFrame:
    """Rolling max per column, warmup → NaN."""
    if n < 1:
        raise ValueError(f"ts_max window must be >= 1, got {n}")
    return df.rolling(window=n, min_periods=n).max()


def ts_min(df: pd.DataFrame, n: int) -> pd.DataFrame:
    """Rolling min per column, warmup → NaN."""
    if n < 1:
        raise ValueError(f"ts_min window must be >= 1, got {n}")
    return df.rolling(window=n, min_periods=n).min()


def _argmax_last(arr: np.ndarray) -> float:
    if np.isnan(arr).all():
        return np.nan
    arr_filled = np.where(np.isnan(arr), -np.inf, arr)
    return float(np.argmax(arr_filled))


def _argmin_last(arr: np.ndarray) -> float:
    if np.isnan(arr).all():
        return np.nan
    arr_filled = np.where(np.isnan(arr), np.inf, arr)
    return float(np.argmin(arr_filled))


def ts_argmax(df: pd.DataFrame, n: int) -> pd.DataFrame:

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Use a window >= 1
2. Validate factor spec windows at load time
3. Clamp computed windows with max(1, n)

Example fix

// before
ts_min(df, n)
// after
if n < 1: raise ValueError('window must be >= 1')
ts_min(df, n)

if not isinstance(n, int) or n < 1: raise ValueError(f'window must be int >= 1, got {n!r}')

def is_valid_window(n: object) -> bool:
    return isinstance(n, int) and not isinstance(n, bool) and n >= 1

When it happens

Trigger: Calling ts_min(df, 0) or ts_min(df, -1), or a parameterized factor spec with a bad window value.

Common situations: YAML/JSON factor configs with window: 0, dynamically computed windows on tiny datasets, or copy-paste from a spec using a different convention (0-based windows).

Related errors

• ts_max window must be >= 1, got {n}
• decay_linear window must be >= 1, got {n}
• fit_ornstein_uhlenbeck needs a series that varies; this one
• __series__ needs a 'values' list
• __dataframe__ needs a 'data' list of rows

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/7fcc47e8e17b0fe5. Report an issue: GitHub.