# -*- coding: utf-8 -*-
from pandas_ta.overlap import dema, ema, hma, rma, sma
from pandas_ta.utils import get_offset, non_zero_range, verify_series
[docs]def qstick(open_, close, length=None, offset=None, **kwargs):
"""Indicator: Q Stick"""
# Validate Arguments
length = int(length) if length and length > 0 else 10
ma = kwargs.pop("ma", "sma")
open_ = verify_series(open_, length)
close = verify_series(close, length)
offset = get_offset(offset)
if open_ is None or close is None: return
# Calculate Result
diff = non_zero_range(close, open_)
if ma == "dema":
qstick = dema(diff, length=length, **kwargs)
elif ma == "ema":
qstick = ema(diff, length=length, **kwargs)
elif ma == "hma":
qstick = hma(diff, length=length)
elif ma == "rma":
qstick = rma(diff, length=length)
else: # "sma"
qstick = sma(diff, length=length)
# Offset
if offset != 0:
qstick = qstick.shift(offset)
# Handle fills
if "fillna" in kwargs:
qstick.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
qstick.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
qstick.name = f"QS_{length}"
qstick.category = "trend"
return qstick
qstick.__doc__ = \
"""Q Stick
The Q Stick indicator, developed by Tushar Chande, attempts to quantify and
identify trends in candlestick charts.
Sources:
https://library.tradingtechnologies.com/trade/chrt-ti-qstick.html
Calculation:
Default Inputs:
length=10
xMA is one of: sma (default), dema, ema, hma, rma
qstick = xMA(close - open, length)
Args:
open (pd.Series): Series of 'open's
close (pd.Series): Series of 'close's
length (int): It's period. Default: 1
ma (str): The type of moving average to use. Default: None, which is 'sma'
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.
"""