extrema_smoothing = self.freqai_info.get("extrema_smoothing", "gaussian")
if std is None:
std = derive_gaussian_std_from_window(window)
+ gaussian_window = get_gaussian_window(std, True)
+ odd_window = get_odd_window(window)
smoothing_methods: dict = {
"gaussian": series.rolling(
- window=get_gaussian_window(std, True),
+ window=gaussian_window,
win_type="gaussian",
center=True,
).mean(std=std),
"zero_phase_gaussian": zero_phase_gaussian(series=series, std=std),
"boxcar": series.rolling(
- window=get_odd_window(window), win_type="boxcar", center=True
+ window=odd_window, win_type="boxcar", center=True
).mean(),
"triang": series.rolling(
- window=get_odd_window(window), win_type="triang", center=True
+ window=odd_window, win_type="triang", center=True
).mean(),
- "smm": series.rolling(window=get_odd_window(window), center=True).median(),
- "sma": series.rolling(window=get_odd_window(window), center=True).mean(),
+ "smm": series.rolling(window=odd_window, center=True).median(),
+ "sma": series.rolling(window=odd_window, center=True).mean(),
"ewma": series.ewm(span=window).mean(),
"zlewma": pta.zlma(series, length=window, mamode="ema"),
}