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78 lines
2.2 KiB
Python
78 lines
2.2 KiB
Python
# -*- coding: utf-8 -*-
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from .true_range import true_range
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from ..utils import get_drift, get_offset, verify_series
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def atr(high, low, close, length=None, mamode=None, drift=None, offset=None, **kwargs):
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"""Indicator: Average True Range (ATR)"""
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# Validate arguments
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high = verify_series(high)
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low = verify_series(low)
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close = verify_series(close)
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length = int(length) if length and length > 0 else 14
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min_periods = int(kwargs['min_periods']) if 'min_periods' in kwargs and kwargs['min_periods'] is not None else length
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mamode = mamode.lower() if mamode else 'ema'
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drift = get_drift(drift)
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offset = get_offset(offset)
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# Calculate Result
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tr = true_range(high=high, low=low, close=close, drift=drift)
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if mamode == 'ema':
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atr = tr.ewm(span=length, min_periods=min_periods).mean()
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else:
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atr = tr.rolling(length, min_periods=min_periods).mean()
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# Offset
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if offset != 0:
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atr = atr.shift(offset)
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# Handle fills
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if 'fillna' in kwargs:
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atr.fillna(kwargs['fillna'], inplace=True)
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if 'fill_method' in kwargs:
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atr.fillna(method=kwargs['fill_method'], inplace=True)
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# Name and Categorize it
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atr.name = f"ATR_{length}"
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atr.category = 'volatility'
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return atr
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atr.__doc__ = \
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"""Average True Range (ATR)
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Averge True Range is used to measure volatility, especially
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volatility caused by gaps or limit moves.
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Sources:
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https://www.tradingview.com/wiki/Average_True_Range_(ATR)
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Calculation:
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Default Inputs:
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length=14, drift=1
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SMA = Simple Moving Average
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EMA = Exponential Moving Average
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TR = True Range
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tr = TR(high, low, close, drift)
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if 'ema':
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ATR = EMA(tr, length)
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else:
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ATR = SMA(tr, length)
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Args:
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high (pd.Series): Series of 'high's
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low (pd.Series): Series of 'low's
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close (pd.Series): Series of 'close's
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length (int): It's period. Default: 14
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mamode (str): Two options: None or 'ema'. Default: 'ema'
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drift (int): The difference period. Default: 1
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offset (int): How many periods to offset the result. Default: 0
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Kwargs:
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fillna (value, optional): pd.DataFrame.fillna(value)
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fill_method (value, optional): Type of fill method
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Returns:
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pd.Series: New feature generated.
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""" |