Source code for pandas_ta.volume.eom

# -*- coding: utf-8 -*-
from pandas_ta.overlap import hl2, sma
from pandas_ta.utils import get_drift, get_offset, non_zero_range, verify_series

[docs]def eom(high, low, close, volume, length=None, divisor=None, drift=None, offset=None, **kwargs): """Indicator: Ease of Movement (EOM)""" # Validate arguments length = int(length) if length and length > 0 else 14 divisor = divisor if divisor and divisor > 0 else 100000000 high = verify_series(high, length) low = verify_series(low, length) close = verify_series(close, length) volume = verify_series(volume, length) drift = get_drift(drift) offset = get_offset(offset) if high is None or low is None or close is None or volume is None: return # Calculate Result high_low_range = non_zero_range(high, low) distance = hl2(high=high, low=low) distance -= hl2(high=high.shift(drift), low=low.shift(drift)) box_ratio = volume / divisor box_ratio /= high_low_range eom = distance / box_ratio eom = sma(eom, length=length) # Offset if offset != 0: eom = eom.shift(offset) # Handle fills if "fillna" in kwargs: eom.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: eom.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it = f"EOM_{length}_{divisor}" eom.category = "volume" return eom
eom.__doc__ = \ """Ease of Movement (EOM) Ease of Movement is a volume based oscillator that is designed to measure the relationship between price and volume flucuating across a zero line. Sources: Calculation: Default Inputs: length=14, divisor=100000000, drift=1 SMA = Simple Moving Average hl_range = high - low distance = 0.5 * (high - high.shift(drift) + low - low.shift(drift)) box_ratio = (volume / divisor) / hl_range eom = distance / box_ratio EOM = SMA(eom, length) Args: high (pd.Series): Series of 'high's low (pd.Series): Series of 'low's close (pd.Series): Series of 'close's volume (pd.Series): Series of 'volume's length (int): The short period. Default: 14 drift (int): The diff period. Default: 1 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. """