# -*- coding: utf-8 -*-
from pandas import DataFrame
from pandas_ta import Imports
from pandas_ta.overlap import ma
from pandas_ta.utils import get_offset, tal_ma, verify_series
[docs]def ppo(close, fast=None, slow=None, signal=None, scalar=None, mamode=None, talib=None, offset=None, **kwargs):
"""Indicator: Percentage Price Oscillator (PPO)"""
# Validate Arguments
fast = int(fast) if fast and fast > 0 else 12
slow = int(slow) if slow and slow > 0 else 26
signal = int(signal) if signal and signal > 0 else 9
scalar = float(scalar) if scalar else 100
mamode = mamode if isinstance(mamode, str) else "sma"
if slow < fast:
fast, slow = slow, fast
close = verify_series(close, max(fast, slow, signal))
offset = get_offset(offset)
mode_tal = bool(talib) if isinstance(talib, bool) else True
if close is None: return
# Calculate Result
if Imports["talib"] and mode_tal:
from talib import PPO
ppo = PPO(close, fast, slow, tal_ma(mamode))
else:
fastma = ma(mamode, close, length=fast)
slowma = ma(mamode, close, length=slow)
ppo = scalar * (fastma - slowma)
ppo /= slowma
signalma = ma("ema", ppo, length=signal)
histogram = ppo - signalma
# Offset
if offset != 0:
ppo = ppo.shift(offset)
histogram = histogram.shift(offset)
signalma = signalma.shift(offset)
# Handle fills
if "fillna" in kwargs:
ppo.fillna(kwargs["fillna"], inplace=True)
histogram.fillna(kwargs["fillna"], inplace=True)
signalma.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
ppo.fillna(method=kwargs["fill_method"], inplace=True)
histogram.fillna(method=kwargs["fill_method"], inplace=True)
signalma.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
_props = f"_{fast}_{slow}_{signal}"
ppo.name = f"PPO{_props}"
histogram.name = f"PPOh{_props}"
signalma.name = f"PPOs{_props}"
ppo.category = histogram.category = signalma.category = "momentum"
# Prepare DataFrame to return
data = {ppo.name: ppo, histogram.name: histogram, signalma.name: signalma}
df = DataFrame(data)
df.name = f"PPO{_props}"
df.category = ppo.category
return df
ppo.__doc__ = \
"""Percentage Price Oscillator (PPO)
The Percentage Price Oscillator is similar to MACD in measuring momentum.
Sources:
https://www.tradingview.com/wiki/MACD_(Moving_Average_Convergence/Divergence)
Calculation:
Default Inputs:
fast=12, slow=26
SMA = Simple Moving Average
EMA = Exponential Moving Average
fast_sma = SMA(close, fast)
slow_sma = SMA(close, slow)
PPO = 100 * (fast_sma - slow_sma) / slow_sma
Signal = EMA(PPO, signal)
Histogram = PPO - Signal
Args:
close(pandas.Series): Series of 'close's
fast(int): The short period. Default: 12
slow(int): The long period. Default: 26
signal(int): The signal period. Default: 9
scalar (float): How much to magnify. Default: 100
mamode (str): See ```help(ta.ma)```. Default: 'sma'
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: ppo, histogram, signal columns
"""