# -*- coding: utf-8 -*-
from pandas import DataFrame
from pandas_ta import Imports
from pandas_ta.utils import get_offset, verify_series
from pandas_ta.utils import recent_maximum_index, recent_minimum_index
[docs]def aroon(high, low, length=None, scalar=None, talib=None, offset=None, **kwargs):
"""Indicator: Aroon & Aroon Oscillator"""
# Validate Arguments
length = length if length and length > 0 else 14
scalar = float(scalar) if scalar else 100
high = verify_series(high, length)
low = verify_series(low, length)
offset = get_offset(offset)
mode_tal = bool(talib) if isinstance(talib, bool) else True
if high is None or low is None: return
# Calculate Result
if Imports["talib"] and mode_tal:
from talib import AROON, AROONOSC
aroon_down, aroon_up = AROON(high, low, length)
aroon_osc = AROONOSC(high, low, length)
else:
periods_from_hh = high.rolling(length + 1).apply(recent_maximum_index, raw=True)
periods_from_ll = low.rolling(length + 1).apply(recent_minimum_index, raw=True)
aroon_up = aroon_down = scalar
aroon_up *= 1 - (periods_from_hh / length)
aroon_down *= 1 - (periods_from_ll / length)
aroon_osc = aroon_up - aroon_down
# Handle fills
if "fillna" in kwargs:
aroon_up.fillna(kwargs["fillna"], inplace=True)
aroon_down.fillna(kwargs["fillna"], inplace=True)
aroon_osc.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
aroon_up.fillna(method=kwargs["fill_method"], inplace=True)
aroon_down.fillna(method=kwargs["fill_method"], inplace=True)
aroon_osc.fillna(method=kwargs["fill_method"], inplace=True)
# Offset
if offset != 0:
aroon_up = aroon_up.shift(offset)
aroon_down = aroon_down.shift(offset)
aroon_osc = aroon_osc.shift(offset)
# Name and Categorize it
aroon_up.name = f"AROONU_{length}"
aroon_down.name = f"AROOND_{length}"
aroon_osc.name = f"AROONOSC_{length}"
aroon_down.category = aroon_up.category = aroon_osc.category = "trend"
# Prepare DataFrame to return
data = {
aroon_down.name: aroon_down,
aroon_up.name: aroon_up,
aroon_osc.name: aroon_osc,
}
aroondf = DataFrame(data)
aroondf.name = f"AROON_{length}"
aroondf.category = aroon_down.category
return aroondf
aroon.__doc__ = \
"""Aroon & Aroon Oscillator (AROON)
Aroon attempts to identify if a security is trending and how strong.
Sources:
https://www.tradingview.com/wiki/Aroon
https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/aroon-ar/
Calculation:
Default Inputs:
length=1, scalar=100
recent_maximum_index(x): return int(np.argmax(x[::-1]))
recent_minimum_index(x): return int(np.argmin(x[::-1]))
periods_from_hh = high.rolling(length + 1).apply(recent_maximum_index, raw=True)
AROON_UP = scalar * (1 - (periods_from_hh / length))
periods_from_ll = low.rolling(length + 1).apply(recent_minimum_index, raw=True)
AROON_DN = scalar * (1 - (periods_from_ll / length))
AROON_OSC = AROON_UP - AROON_DN
Args:
close (pd.Series): Series of 'close's
length (int): It's period. Default: 14
scalar (float): How much to magnify. Default: 100
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.DataFrame: aroon_up, aroon_down, aroon_osc columns.
"""