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pandas-ta/pandas_ta/volume/eom.py
T
2019-05-20 13:25:33 -07:00

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2.6 KiB
Python

# -*- coding: utf-8 -*-
from ..overlap.hl2 import hl2
from ..utils import get_drift, get_offset, verify_series
def eom(high, low, close, volume, length=None, divisor=None, drift=None, offset=None, **kwargs):
"""Indicator: Ease of Movement (EOM)"""
# Validate arguments
high = verify_series(high)
low = verify_series(low)
close = verify_series(close)
volume = verify_series(volume)
length = int(length) if length and length > 0 else 14
min_periods = int(kwargs['min_periods']) if 'min_periods' in kwargs and kwargs['min_periods'] is not None else length
divisor = divisor if divisor and divisor > 0 else 100000000
drift = get_drift(drift)
offset = get_offset(offset)
# Calculate Result
hl_range = high - low
distance = hl2(high=high, low=low) - hl2(high=high.shift(drift), low=low.shift(drift))
box_ratio = (volume / divisor) / hl_range
eom = distance / box_ratio
eom = eom.rolling(length, min_periods=min_periods).mean()
# 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
eom.name = 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:
https://www.tradingview.com/wiki/Ease_of_Movement_(EOM)
https://www.motivewave.com/studies/ease_of_movement.htm
https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:ease_of_movement_emv
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.
"""