HKUDS/Vibe-Trading · error · ValueError

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

Error message

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

What it means

ts_mean requires n >= 1; a rolling mean over zero or negative observations is undefined, so the guard raises immediately. Warmup rows (first n-1) are NaN because min_periods=n.

Source

Thrown at agent/src/factors/base.py:182

def ts_cov(x: pd.DataFrame, y: pd.DataFrame, n: int) -> pd.DataFrame:
    """Rolling sample covariance per column, min_periods=n."""
    if n < 2:
        raise ValueError(f"ts_cov window must be >= 2, got {n}")
    x = _as_float(x)
    y = _as_float(y)
    cols = x.columns.union(y.columns)
    xa = x.reindex(columns=cols)
    ya = y.reindex(columns=cols)
    cov = xa.rolling(window=n, min_periods=n).cov(ya)
    return cov.replace([np.inf, -np.inf], np.nan)


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


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:

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Pass a positive integer window
2. Validate window parameters at config load time
3. When deriving windows from data length, assert n >= 1 before calling

Example fix

# before
m = ts_mean(df, n=0)

# after
m = ts_mean(df, n=20)

if not isinstance(n, int) or n < 1:
    raise ValueError(f'invalid ts_mean window: {n!r}')
m = ts_mean(df, n)

def is_valid_ts_mean_window(n) -> bool:
    return isinstance(n, int) and n >= 1

When it happens

Trigger: ts_mean(df, 0), ts_mean(df, -3), or a window computed as len(df) - offset that hits 0. Called from compute() in the factor pipeline.

Common situations: Missing config values defaulting to 0; percentage windows (0.5) instead of counts; dynamic windows on very short dataframes.

Related errors

• ts_rank window must be >= 1, got {n}
• ts_corr window must be >= 2, got {n}
• ts_cov window must be >= 2, got {n}
• ts_std window must be >= 2, got {n}
• granger_test needs max_lag >= 1, got {max_lag}

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/79f5ec433ac0957b. Report an issue: GitHub.