mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
107 lines
2.8 KiB
Python
107 lines
2.8 KiB
Python
# -*- coding: utf-8 -*-
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from pandas import DataFrame
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from ..utils import get_drift, get_offset, non_zero_range, verify_series
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def brar(open_,
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high,
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low,
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close,
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length=None,
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scalar=None,
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drift=None,
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offset=None,
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**kwargs):
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"""Indicator: BRAR (BRAR)"""
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# Validate Arguments
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open_ = verify_series(open_)
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high = verify_series(high)
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low = verify_series(low)
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close = verify_series(close)
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length = int(length) if length and length > 0 else 26
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scalar = float(scalar) if scalar else 100
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high_open_range = non_zero_range(high, open_)
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open_low_range = non_zero_range(open_, low)
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drift = get_drift(drift)
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offset = get_offset(offset)
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# Calculate Result
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hcy = non_zero_range(high, close.shift(drift))
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cyl = non_zero_range(close.shift(drift), low)
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hcy[hcy < 0] = 0 # Zero negative values
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cyl[cyl < 0] = 0 # ""
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ar = scalar * high_open_range.rolling(length).sum()
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ar /= open_low_range.rolling(length).sum()
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br = scalar * hcy.rolling(length).sum()
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br /= cyl.rolling(length).sum()
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# Offset
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if offset != 0:
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ar = ar.shift(offset)
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br = ar.shift(offset)
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# Handle fills
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if "fillna" in kwargs:
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ar.fillna(kwargs["fillna"], inplace=True)
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br.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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ar.fillna(method=kwargs["fill_method"], inplace=True)
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br.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Categorize it
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_props = f"_{length}"
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ar.name = f"AR{_props}"
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br.name = f"BR{_props}"
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ar.category = br.category = "momentum"
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# Prepare DataFrame to return
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brardf = DataFrame({ar.name: ar, br.name: br})
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brardf.name = f"BRAR{_props}"
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brardf.category = "momentum"
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return brardf
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brar.__doc__ = """BRAR (BRAR)
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BR and AR
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Sources:
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No internet resources on definitive definition.
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Request by Github user homily, issue #46
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Calculation:
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Default Inputs:
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length=26, scalar=100
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SUM = Sum
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HO_Diff = high - open
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OL_Diff = open - low
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HCY = high - close[-1]
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CYL = close[-1] - low
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HCY[HCY < 0] = 0
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CYL[CYL < 0] = 0
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AR = scalar * SUM(HO, length) / SUM(OL, length)
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BR = scalar * SUM(HCY, length) / SUM(CYL, length)
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Args:
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open_ (pd.Series): Series of 'open's
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high (pd.Series): Series of 'high's
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low (pd.Series): Series of 'low's
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close (pd.Series): Series of 'close's
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length (int): The period. Default: 26
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scalar (float): How much to magnify. Default: 100
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drift (int): The difference period. Default: 1
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offset (int): How many periods to offset the result. Default: 0
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Kwargs:
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fillna (value, optional): pd.DataFrame.fillna(value)
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fill_method (value, optional): Type of fill method
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Returns:
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pd.DataFrame: ar, br columns.
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"""
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