return (window - 1) / 6.0 if window > 1 else 0.5
-def zero_phase_gaussian(series: pd.Series, window: int, std: float):
+def zero_phase_gaussian(series: pd.Series, window: int, std: float) -> pd.Series:
kernel = gaussian(window, std=std)
kernel /= kernel.sum()
padding_length = window - 1
- padded_series = np.pad(series.values, (padding_length, padding_length), mode="edge")
+ padded_series_values = np.pad(
+ series.values, (padding_length, padding_length), mode="edge"
+ )
- forward = convolve(padded_series, kernel, mode="valid")
+ forward = convolve(padded_series_values, kernel, mode="valid")
backward = convolve(forward[::-1], kernel, mode="valid")[::-1]
return pd.Series(backward, index=series.index)