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pandas-ta/pandas_ta/overlap/midpoint.py
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Python

# -*- coding: utf-8 -*-
from pandas_ta import Imports
from pandas_ta.utils import get_offset, verify_series
def midpoint(close, length=None, talib=None, offset=None, **kwargs):
"""Midpoint
The Midpoint is the average of the rolling high and low of period length.
Args:
close (pd.Series): Series of 'close's
length (int): It's period. Default: 2
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.
"""
# Validate arguments
length = int(length) if length and length > 0 else 2
min_periods = int(kwargs["min_periods"]) if "min_periods" in kwargs and kwargs["min_periods"] is not None else length
close = verify_series(close, max(length, min_periods))
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 MIDPOINT
midpoint = MIDPOINT(close, length)
else:
lowest = close.rolling(length, min_periods=min_periods).min()
highest = close.rolling(length, min_periods=min_periods).max()
midpoint = 0.5 * (lowest + highest)
# Offset
if offset != 0:
midpoint = midpoint.shift(offset)
# Handle fills
if "fillna" in kwargs:
midpoint.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
midpoint.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
midpoint.name = f"MIDPOINT_{length}"
midpoint.category = "overlap"
return midpoint