Source code for pandas_ta.trend.vhf

# -*- coding: utf-8 -*-
from numpy import fabs as npFabs
from pandas_ta.utils import get_drift, get_offset, non_zero_range, verify_series

[docs]def vhf(close, length=None, drift=None, offset=None, **kwargs): """Indicator: Vertical Horizontal Filter (VHF)""" # Validate arguments length = int(length) if length and length > 0 else 28 close = verify_series(close, length) drift = get_drift(drift) offset = get_offset(offset) if close is None: return # Calculate Result hcp = close.rolling(length).max() lcp = close.rolling(length).min() diff = npFabs(close.diff(drift)) vhf = npFabs(non_zero_range(hcp, lcp)) / diff.rolling(length).sum() # Offset if offset != 0: vhf = vhf.shift(offset) # Handle fills if "fillna" in kwargs: vhf.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: vhf.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it = f"VHF_{length}" vhf.category = "trend" return vhf
vhf.__doc__ = \ """Vertical Horizontal Filter (VHF) VHF was created by Adam White to identify trending and ranging markets. Sources: Calculation: Default Inputs: length = 28 HCP = Highest Close Price in Period LCP = Lowest Close Price in Period Change = abs(Ct - Ct-1) VHF = (HCP - LCP) / RollingSum[length] of Change Args: source (pd.Series): Series of prices (usually close). length (int): The period length. Default: 28 offset (int): How many periods to offset the result. Default: 0 Kwargs: fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method Returns: pd.Series: New feature generated. """