# -*- coding: utf-8 -*-
from .true_range import true_range
from pandas_ta import Imports
from pandas_ta.overlap import ma
from pandas_ta.utils import get_drift, get_offset, verify_series
[docs]def atr(high, low, close, length=None, mamode=None, talib=None, drift=None, offset=None, **kwargs):
"""Indicator: Average True Range (ATR)"""
# Validate arguments
length = int(length) if length and length > 0 else 14
mamode = mamode.lower() if mamode and isinstance(mamode, str) else "rma"
high = verify_series(high, length)
low = verify_series(low, length)
close = verify_series(close, length)
drift = get_drift(drift)
offset = get_offset(offset)
mode_tal = bool(talib) if isinstance(talib, bool) else True
if high is None or low is None or close is None: return
# Calculate Result
if Imports["talib"] and mode_tal:
from talib import ATR
atr = ATR(high, low, close, length)
else:
tr = true_range(high=high, low=low, close=close, drift=drift)
atr = ma(mamode, tr, length=length)
percentage = kwargs.pop("percent", False)
if percentage:
atr *= 100 / close
# Offset
if offset != 0:
atr = atr.shift(offset)
# Handle fills
if "fillna" in kwargs:
atr.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
atr.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
atr.name = f"ATR{mamode[0]}_{length}{'p' if percentage else ''}"
atr.category = "volatility"
return atr
atr.__doc__ = \
"""Average True Range (ATR)
Averge True Range is used to measure volatility, especially volatility caused by
gaps or limit moves.
Sources:
https://www.tradingview.com/wiki/Average_True_Range_(ATR)
Calculation:
Default Inputs:
length=14, drift=1, percent=False
EMA = Exponential Moving Average
SMA = Simple Moving Average
WMA = Weighted Moving Average
RMA = WildeR's Moving Average
TR = True Range
tr = TR(high, low, close, drift)
if 'ema':
ATR = EMA(tr, length)
elif 'sma':
ATR = SMA(tr, length)
elif 'wma':
ATR = WMA(tr, length)
else:
ATR = RMA(tr, length)
if percent:
ATR *= 100 / close
Args:
high (pd.Series): Series of 'high's
low (pd.Series): Series of 'low's
close (pd.Series): Series of 'close's
length (int): It's period. Default: 14
mamode (str): See ```help(ta.ma)```. Default: 'rma'
talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib
version. Default: True
drift (int): The difference period. Default: 1
offset (int): How many periods to offset the result. Default: 0
Kwargs:
percent (bool, optional): Return as percentage. Default: False
fillna (value, optional): pd.DataFrame.fillna(value)
fill_method (value, optional): Type of fill method
Returns:
pd.Series: New feature generated.
"""