mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
# -*- coding: utf-8 -*-
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from ..utils import get_offset, symmetric_triangle, verify_series, weights
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def swma(close, length=None, asc=None, offset=None, **kwargs):
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"""Indicator: Symmetric Weighted Moving Average (SWMA)"""
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# Validate Arguments
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close = verify_series(close)
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length = int(length) if length and length > 0 else 10
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min_periods = (int(kwargs["min_periods"]) if "min_periods" in kwargs and
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kwargs["min_periods"] is not None else length)
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asc = asc if asc else True
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offset = get_offset(offset)
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# Calculate Result
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triangle = symmetric_triangle(length, weighted=True)
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swma = close.rolling(length, min_periods=length).apply(weights(triangle),
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raw=True)
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# Offset
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if offset != 0:
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swma = swma.shift(offset)
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# Name & Category
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swma.name = f"SWMA_{length}"
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swma.category = "overlap"
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return swma
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swma.__doc__ = """Symmetric Weighted Moving Average (SWMA)
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Symmetric Weighted Moving Average where weights are based on a symmetric
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triangle. For example: n=3 -> [1, 2, 1], n=4 -> [1, 2, 2, 1], etc... This moving
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average has variable length in contrast to TradingView's fixed length of 4.
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Source:
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https://www.tradingview.com/study-script-reference/#fun_swma
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Calculation:
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Default Inputs:
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length=10
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def weights(w):
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def _compute(x):
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return np.dot(w * x)
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return _compute
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triangle = utils.symmetric_triangle(length - 1)
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SWMA = close.rolling(length)_.apply(weights(triangle), raw=True)
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Args:
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close (pd.Series): Series of 'close's
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length (int): It's period. Default: 10
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asc (bool): Recent values weigh more. Default: True
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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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