mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
62 lines
1.7 KiB
Python
62 lines
1.7 KiB
Python
# -*- coding: utf-8 -*-
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from ..utils import get_offset, non_zero_range, verify_series
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def bop(open_, high, low, close, scalar=None, offset=None, **kwargs):
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"""Indicator: Balance of Power (BOP)"""
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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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scalar = float(scalar) if scalar else 1
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high_low_range = non_zero_range(high, low)
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close_open_range = non_zero_range(close, open_)
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offset = get_offset(offset)
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# Calculate Result
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bop = scalar * close_open_range / high_low_range
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# Offset
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if offset != 0:
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bop = bop.shift(offset)
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# Handle fills
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if "fillna" in kwargs:
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bop.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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bop.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Categorize it
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bop.name = f"BOP"
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bop.category = "momentum"
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return bop
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bop.__doc__ = """Balance of Power (BOP)
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Balance of Power measure the market strength of buyers against sellers.
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Sources:
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http://www.worden.com/TeleChartHelp/Content/Indicators/Balance_of_Power.htm
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Calculation:
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BOP = scalar * (close - open) / (high - low)
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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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scalar (float): How much to magnify. 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.Series: New feature generated.
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"""
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