From 515d4297e7209d0a8b49cab8b5fbc7cac90e1bb3 Mon Sep 17 00:00:00 2001 From: Kevin Johnson Date: Wed, 11 Nov 2020 11:13:01 -0800 Subject: [PATCH] DOC ssf documentation update --- pandas_ta/overlap/ssf.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/pandas_ta/overlap/ssf.py b/pandas_ta/overlap/ssf.py index b72988b..f3ed7ed 100644 --- a/pandas_ta/overlap/ssf.py +++ b/pandas_ta/overlap/ssf.py @@ -18,7 +18,6 @@ def ssf(close, length=None, poles=None, offset=None, **kwargs): # Calculate Result m = close.size ssf = close.copy() - ssf[poles:] = 0 if poles == 3: x = npPi / length # x = PI / n @@ -56,10 +55,15 @@ def ssf(close, length=None, poles=None, offset=None, **kwargs): ssf.__doc__ = \ -"""Ehler's Super Smoother Filter (SSF) +"""Ehler's Super Smoother Filter (SSF) © 2013 -Ehler's solution to reduce lag and remove aliasing noise with his research in -aerospace analog filter design. © 2013 John F. Ehlers +John F. Ehlers's solution to reduce lag and remove aliasing noise with his +research in aerospace analog filter design. This indicator comes with two +versions determined by the keyword poles. By default, it uses two poles but +there is an option for three poles. Since SSF is a (Resursive) Digital Filter, +the number of poles determine how many prior recursive SSF bars to include in +the design of the filter. So two poles uses two prior SSF bars and three poles +uses three prior SSF bars for their filter calculations. Sources: http://www.stockspotter.com/files/PredictiveIndicators.pdf