Source code for pandas_ta.volume.adosc

# -*- coding: utf-8 -*-
from .ad import ad
from pandas_ta import Imports
from pandas_ta.overlap import ema
from pandas_ta.utils import get_offset, verify_series

[docs]def adosc(high, low, close, volume, open_=None, fast=None, slow=None, talib=None, offset=None, **kwargs): """Indicator: Accumulation/Distribution Oscillator""" # Validate Arguments fast = int(fast) if fast and fast > 0 else 3 slow = int(slow) if slow and slow > 0 else 10 _length = max(fast, slow) high = verify_series(high, _length) low = verify_series(low, _length) close = verify_series(close, _length) volume = verify_series(volume, _length) offset = get_offset(offset) if "length" in kwargs: kwargs.pop("length") mode_tal = bool(talib) if isinstance(talib, bool) else True if high is None or low is None or close is None or volume is None: return # Calculate Result if Imports["talib"] and mode_tal: from talib import ADOSC adosc = ADOSC(high, low, close, volume, fast, slow) else: ad_ = ad(high=high, low=low, close=close, volume=volume, open_=open_) fast_ad = ema(close=ad_, length=fast, **kwargs) slow_ad = ema(close=ad_, length=slow, **kwargs) adosc = fast_ad - slow_ad # Offset if offset != 0: adosc = adosc.shift(offset) # Handle fills if "fillna" in kwargs: adosc.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: adosc.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it = f"ADOSC_{fast}_{slow}" adosc.category = "volume" return adosc
adosc.__doc__ = \ """Accumulation/Distribution Oscillator or Chaikin Oscillator Accumulation/Distribution Oscillator indicator utilizes Accumulation/Distribution and treats it similarily to MACD or APO. Sources: Calculation: Default Inputs: fast=12, slow=26 AD = Accum/Dist ad = AD(high, low, close, open) fast_ad = EMA(ad, fast) slow_ad = EMA(ad, slow) ADOSC = fast_ad - slow_ad Args: high (pd.Series): Series of 'high's low (pd.Series): Series of 'low's close (pd.Series): Series of 'close's open (pd.Series): Series of 'open's volume (pd.Series): Series of 'volume's fast (int): The short period. Default: 12 slow (int): The long period. Default: 26 talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib version. Default: True 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. """